This next edition of the HP Discover Performance Discussion Series welcomes Colin Mahony, General Manager at HP Vertica, on this first day of the inaugural HP Vertica Big Data Conference in Boston.

It's been well over two years since HP acquired Vertica, and the analytics platform has become a pillar of HP's recently announced HAVEn Initiative. Now Vertica is poised to advance beyond its MPP column store database origins into a next generation anywhere analytics platform. New Vertica benefits include ease in cloud deployments and appliance delivery, as well as new features coming later this year for improved speed, lower-cost and greater ease in data input and access.

Learn how Mahony is guiding the future of the HP Vertica Analytics Platform, and how users are finding new ways to leverage its unique speed and attributes. The interview is conducted by Dana Gardner, Principal Analyst at Interarbor Solutions. [Follow Colin on Twitter.] [Disclosure: HP is a sponsor of BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: One of the things that strikes me about the market nowadays is that there seems to be a sense of tradeoffs going on when organizations are trying to pick their big data engine or platform. They have a set of value on one side, but it’s opposed by value on the other. They can’t have everything. One size does not fit all.

So how are you at Vertica able to help people deal with these tradeoffs that they're facing when it comes to a next-generation data platform?

Mahony: Vertica was founded on the premise that one size does not fit all. Using a single OLTP transactional database to do everything, including analytics, just doesn't make a lot of sense.

If you think about the areas that the people have to trade off, usually it’s scale for performance or analytics functionality for performance. One of things that I've spent a lot of time looking at is, especially over the last couple of years, is just some of the alternative platforms, not just for analytics, but for all of the different data needs.

You can take something like Hadoop as an example. Hadoop really is a distributed file system and has capabilities to run rudimentary analytics and transform processed data. But I think what people love about Hadoop is that it's really easy to load data into Hadoop. You don't have to define the schema or anything.

Instead of schema on write or load time, it’s schema on read time. People like that. They also like at least the perception that it is free and the scalability of it. On the database side, what people love about the database is that you're going to get really good performance, because the data is structured. If you're using a NexGen MPP platform like Vertica, you'll get the performance of the scalability.

Hadoop-like

We've been doing a lot of work in areas like making it easier to get the data into the platform, doing more with it, making it seem much more like a Hadoop-like environment. You can look at our past releases and see that there's been a lot of work done on that and we continue to make those investments.

One thing has been consistent at Vertica since the beginning. What we focus on is to make it really easy for people to get information onto the platform. Then, we make sure we continue to deliver new capabilities, performance, and functionality within the platform.

We make sure we’re enabling our customers and partners to deploy Vertica anywhere and everywhere, whether it’s cloud appliances, software, or the like. Those are the three tenets of the company. It’s all around this notion of making data matter and help people make better decisions that lead to better outcomes with superior information.

There's so much that can be done in this space, but I think the key for us is to focus on the things that we know we do really well. The good news is that it's such a large space with so many demands that we know we can make a huge impact without trying to take on the world. We know we can make a huge impact in what we’re doing.

I think you'll continue to see some interesting developments along the lines of what I'm describing, and it's very much in line with where we've been.

Gardner: Do more and more IT functions and business functions begin and end with big data? It seems to be at the center of so many things.

Exponential growth

Mahony: It is. To go back to the founding of Vertica [in 2005], I remember when Mike Stonebraker was giving the early presentations on the need for it. He talked a lot about the exponential growth of data and how that was outpacing any laws like Moore’s law or other hardware laws. So much information was being created, there was no way that just using more paralyzed hardware was going to be able to address the issue.

The state of the union back then was there was no such thing as "big data." But I think Mike, as a visionary, knew what was going to happen in the industry. And it has happened.

It wasn’t a long time ago, but I remember that I was trying to find our first sample dataset that was over a terabyte and we had a difficult time finding it. When we would talk to the early customers, they looked at us like we were crazy when we were asking about a terabyte.

We have an easy time now finding terabytes of data. The state of the union today is that what's driving so much around big data is that you have obviously the volume, variety, and velocity that we talk about often, but what's really driving those three things is human information, whether it's social media, tweets, or expressive content that’s just so prevalent right now, as well machine information.

If you look at the traditional structured database market by any number, it’s a small percentage of the amount of data that’s out there. The strength of Vertica, and really the strength of HP overall, is that we have the best assets for the unstructured human information in Autonomy, as well as the best assets when it comes to machine information and large data.

That has some structure. It’s semi-structured information, but it’s not your traditional transaction system. The power of all of that data comes together when you can have an engine that applies some structure to it and then is able to deliver the analytics that the organization needs. It's both IT as well as line of business, and even this new category we often talk about, which is the data scientist.

One of the great things about this show here is that we’ve got Billy Beane of Moneyball fame as our keynote speaker. The reason that we wanted Billy to come speak here is that Moneyball is exactly what’s happening right now in the world when it comes to big data.

You have the data scientist or the statistician, you have the line of business folks, and you have IT. They all have a part to play in the success of how information is used in companies. By bringing them together and by making the software that much easier for them to come together and solve these problems, you can create very real and differentiated value within organization.

So Moneyball is exactly what’s happening, certainly in corporate America, but also in government and in many other institutions that want to leverage information to be more efficient and create a competitive advantage.

Gardner: Colin, what about the notion of big data as agent for business transformation. We've been hearing about this for 30 years. It's been big part of the academic work in business schools. Process re-engineering has evolved into balanced scorecards. Getting more detailed information in real time about the customers and the marketplace probably has as much or more of a opportunity to transform businesses than just about anything else that's happened over the past 20 years.

More than technology

Mahony: It's an enormous opportunity for business transformation, and definitely the whole is greater than the sum of the parts. What makes companies really successful with information is not trying to boil the ocean, not trying to do a traditional enterprise data warehouse project that's going to take 24 months, if you're lucky, 36 most likely.

They’ll end up with some monolithic inflexible platform that will probably be outdated by the time it gets deployed. What is making a lot of companies successful is they find a particular use, they find a problem area that they want to drill down on, and they mobilize to do it.

For that, they need a solution that is quickly deployed, but also has that capability to become something much larger. Whether it's Vertica, Talend, or any of the other portfolios that we offer, we strive to make sure that somebody can get up and running quickly, whether it's Autonomy and human information analytics, Vertica and machine data or other types of transactional structured data.

The most important thing is that you find that business case, you focus on it, and prove very quickly. There's something we refer to as “Time to Terabyte,” which is less than a month, typically for Vertica. You get a return on investment (ROI) in less than a month for the investments that you made. If you prove that out, then everybody in the organization is happy, the line of business, the technology folks in IT, even the statisticians, data scientists.

From there, you start expanding the project, and that's exactly how we win most of our customers. We very rarely go in and say, "Buy an enterprise license for our product across the company." We certainly do those, but more typically we get into a business unit, we find the acute pain, and we solve that problem.

What they're betting on is the ability for us to expand and for them to expand in this platform. That's why we are, on the one hand, all about the platform and the integration, but on the other hand, not about to lose the flexibility and the modularity of what we do, because that's also a huge differentiator for HP's portfolio

I think that this is a wonderful time in the world of business transformation, and I think, unlike what has been talked about for the last 30 years, you now have the data that can back it up and prove it in real-time to the organization.

That's the big difference. You gave the balanced scorecard as an example. If you look at the balance scorecard methodology, you can take that methodology and drill down into a thousand fields of detail and be able to get that information in real time. That's the opportunity here, and that's I think why this market is so huge.

It's not just about faster speeds and feeds. It's about fundamentally stepping back and asking how we're running this business. What assets, especially information assets, do we have that could dramatically boost the productivity to the same extent that computers, when they were first introduced, boosted productivity. That's the goal that everybody is looking for when it comes to information.

Gardner: Tell our listeners and readers a bit more about yourself and your background.

Mahony: I've been with Vertica since the beginning. In fact, long before Vertica, my background has always been databases. I've always loved computer science, and had a minor in computer science in my undergraduate degree. In my first job out of school, I was taking databases and working with civilian US Government clients, and getting a lot of information published up to the web in the earliest days of the web.

I had a couple of other roles, but they were always very technology focused. Then I got my MBA on the business side and went into venture capital for seven years. That's where I met Mike Stonebraker, the founder of Vertica.

I just loved the idea, everything I knew about databases and the challenges of traditional database and everything I knew about the new world order of information -- at the time we didn’t even talk about the term big data -- it just seemed to align really well.

So I decided to leave the dark side of venture capital and I jumped into something that I have been incredibly passionate about. If you look at that lifecycle even my own background with Vertica and where we’ve come, it’s just been a great. The timing was great and as always it takes a lot more than just great technology and great people.

Gardner: It's been well over two years since HP acquired Vertica and, as we begin the inaugural 2013 Big Data Conference, how would you best characterize how Vertica has evolved since its founding back in 2005?

Mahony: Yes, this is our first user conference. It’s ironic that we've never had one before, but I think also this is a testament to that scale that HP can bring. We have wanted a user conference since the beginning. Obviously, it takes some critical mass to get there which we now have, but also it takes the support of an organization that knows how to do these conferences and understand the value of them.

And we’ve evolved quite a bit. It’s been a busy couple of years here, certainly post the HP acquisition. But I think at a high level, we’ve really shifted and expanded from being an MPP column store, very narrowly-focused database company, really into an analytic platform company.

With that comes several developments, obviously on the product side, but also as an organization, going through that maturation in terms of being able to operate at a global scale across the spectrum of what you would expect an analytics provider to offer.

Gardner: And how do you characterize the difference between a store and a platform? Are there many ecosystem players or is this an organic evolution of your capabilities or both?

Mahony: It’s both, the ecosystem and the tools that you interact with. And of course, we support a very rich and vibrant ecosystem of business-intelligencve (BI) tools, extract, transform and load (ETL) tools, and other types of management tools. Not just the ecosystem around it, but also looking within our own products.

So it's adding a lot of the capabilities like backup and recovery, additional analytics capabilities beyond just standard SQL with the SDKs that Vertica supports, the ability to run both the procedural and the other types of code within the product, being able to express things like MapReduce beyond what a traditional database system would do.

Since the founding of the company, we've tried to take the best part of the database world and the best parts of the SQL world, but address the most challenging issues that traditional databases have had. So whether it is scalability or it’s being able to run things beyond SQL or it’s just the performance, those are all the things that we have taken into account while we built Vertica, and I think we have always been on the fast track to a platform.

We knew it would be a journey and we knew that building a product and a platform from the bottom up is not an easy thing, but we also knew that once we got there, once we sort of crossed that chasm, if you will, then all those decisions that made in the beginning about this product and building an engine from the bottom up would pay off.

Platform modularity

For probably the last year, that's where we’ve been. Right now, we're seeing that it’s easy to add functionality to the platform because of the modularity of the platform, and we can add that functionality without giving up any of the performance.

make it a lot easier to become a platform, not only on the development side, but a much greater ecosystem, a global scale, being able to support customers globally 24/7.

Gardner: It’s only been a few months since the HP Discover 2013 Conference in Las Vegas where the HAVEn Initiative was announced. This puts Vertica in a very prominent place among other HP properties, technologies, platforms and approaches to solving this big data issue. Recap for us, if you would, what HAVEn is and why Vertica formed such an important pillar for this larger HP initiative?

Big-data lake

Mahony: What companies are looking for is this notion of the big-data lake. To me, it can mean many different things, but at the end of the day, companies want to take all the information assets that they have and they want to put them into a safe place, but a place where access to that information can be used by many different constituencies, whether it's IT, line of business, or data scientist.

So the notion of having a safe place, a harbor, or a port is what we announced as HP HAVEn, which is HP’s big data platform. It is primarily for analytics, but it can be used for just about anything when it comes to information and data.

What's so important about information right now is that there are different constituencies in the companies that want to take the information. First of all they want to capture all the information, not just structured, not just unstructured, but 100 percent of their information.

They want to get it to a place where they can leverage it and use it for a lot of different use cases, but the first part is get that information into the right place. For us, that is one of three components of HAVEn, which is the connectors.

We have over 700 connectors as part of HAVEn coming from Autonomy, coming from our Enterprise Security Group, the ArcSight core Logger and those connectors. That can be human information, extreme log information, or traditional database structured information.

Step one is the connectors to get these components. Step two is to put that data into the best engine for that data. Vertica obviously is one component, but you also have the Autonomy IDOL Engine, you have the ArcSight Logger engine, and also open-source technologies like Hadoop, which is actually the HP HAVEn. So we’ve got a place to put the information.

Step three is any N number of applications. What I'm seeing happening in the industry right now is just like we went from mainframe to client-server, and client-server to LAN, we're in a period now where applications are being developed. They're certainly web-based and distributed, but they're also analytical in nature.

They're driven by vast volumes of information and they close the loop, meaning that the experiences that are happening with an application, if you're driving a car, or whatever it might be, information is being passed, closed loop, back to a system that can then optimize the experience. That is creating a new class of applications.

For that new class of applications, you need the platform to be able to drive those. What we're bringing together in HAVEn is Hadoop, Autonomy, Vertica, Enterprise Security, core assets, and the N number of applications.

At Discover, we announced some of our own internal applications, which are powered by the HAVEn platforms. We announced our HP Analytics offering, which is built using Hadoop, Vertica, Enterprise Security, and Autonomy assets.

About community

We're making some of our own applications, but this is about the community and getting people to be able to build new set of applications that can use these components to really change how people are interacting with their data.

That’s HAVEn, and I am always careful to point out to people that HAVEn itself is not a product, but it's a platform and it’s a broader platform than the one that is just Vertica, Autonomy, or Enterprise Security. It’s a platform where 1+1+1+1+1, instead of equaling 5, should equal 8 or 10 or 12, and that's the goal. Of course, it's also a roadmap into areas that each of these components are working on to bring those closer together. So it’s exciting.

One thing I've certainly noticed over the years with our customers is that the shiny object of why a customer chooses Vertica may look very different across our customers. For some, it's the price. For some, it's the performance and the scale, massive volumes. For some it's a particular analytic function or several pattern matching capabilities. And for others, it's something entirely different.

But what's so exciting, especially about this conference, is that no matter what on-ramp they take, they tend to find a lot of the other capabilities once they get on. Hopefully, here at the conference, we're going to accelerate some of that just by getting our customers and our partners together in an environment where they can share stories.

Cloud and hybrid

Gardner: For our last item today, I wonder if we could take out our crystal ball apparatus and try to do a little blue-sky thinking. One of the other big trends these days of course is cloud computing and hybrid models for the distribution of workloads for applications, but also for data. I'm wondering, as we go down this journey over the next year or two, how do big data and cloud computing come together?

Mahony: As I mentioned in terms of the three things that we are focused on, number one is make it easy to get data into the platform. Number two is do a lot more with the platform, so that there is better analytic capabilities, better pattern matching, and better analytics packs on top of it.

Number three is make sure you can deploy Vertica everywhere, and in the everywhere and anywhere categories, the cloud is certainly the first name that comes to mind. That is absolutely the future of computing. In some ways, I guess, it's the past, but it's interesting how the past repeats itself.

We do run Vertica on hosted environments like Amazon cloud. We're in a private beta on the HP Cloud Service. So there are definitely offerings and developments that that has been underway here at Vertica for a while.

We embrace that, and to us, it's not mutually exclusive. What you described in the hybrid environment where you can run certain things locally. You can burst up to the cloud to do other workloads, especially if you're looking to pull some quick processing power and storage. That's going to be the future and that's the way, just like any other utilities, that we're going to consume some of these capabilities.

This is one of the strengths of a company the size and scale of HP. We have these offerings, whether it's software only, appliance, or cloud. We have the ability to deliver however the customer wants it, and we can also provide not only the flexible technologies, but the flexible business capabilities to make that happen with a lot of ease.

It's an exciting time. If you look at the pillars of the HP, we have cloud, mobility, big data, and security. All four of those pillars tie well into one another, because they're all related. Of course, all these activities that are happening up on the cloud are generating a lot of information, information that will be analyzed, I'm sure, in many different ways.

So it's something that kind of feeds on itself, the same way the mobility does. All of that is a good thing for the analytic space, wherever it is. The final thing I would say is that  the most important thing about analytics is that you do want it embedded into the various applications, just like when you are driving a car, you just want the GPS system to tell you where you are going.

Analytics is the same. You want it within the context of whatever it is that you are doing. Given that so many things are going to be served off the cloud, it's natural that that's the place that will host some of the analytics as well.

So it's an incredibly exciting time, and we're looking forward to having many more of these user conferences and are certainly going to enjoy the rest of the show this week. [Follow Colin on Twitter.]

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.

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This latest BriefingsDirect discussion from The Open Group Conference earlier this month in Philadelphia explores the essential role of standards in an increasingly complex and unpredictable world.

From risks around cybersecurity to supply chain concerns to fast-changing trends around cloud computing, the pace of change and pressures on businesses to adjust well have never been higher. To gain a fuller grip on such risk and complexity, The Open Group is shepherding a series of standards and initiatives to provide better tools for understanding and managing true operational dependability.

BriefingsDirect sat down with the President and CEO of The Open Group, Allen Brown, at the July conference to gather an update on the efforts. The interview was conducted by Dana Gardner, Principal Analyst at Interarbor Solutions. [Disclosure: The Open Group is a sponsor of BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: What are the environmental variables that many companies are facing now as they try to improve their businesses and assess the level of risk and difficulty?

Brown: There are a lot of moving targets. We're looking at a situation where organizations are having to put in increasingly complex systems. They're expected to make them highly available, highly safe, highly secure, and to do so faster and cheaper. That’s kind of tough.

Gardner: One of the ways that organizations have been working toward a solution is to have a standardized approach, perhaps some methodologies, because if all the different elements of their business approach this in a different way, we don’t get too far too quickly, and it can actually be more expensive.

Perhaps you could paint for us the vision of an organization like The Open Group in terms of helping organizations standardize and be a little bit more thoughtful and proactive toward these changed elements?

Brown

Brown: With the vision of The Open Group, the headline is "Boundaryless Information Flow." That was established back in 2002, at a time when organizations were breaking down the stovepipes or the silos within and between organizations and getting people to work together across functioning. They found, having done that, or having made some progress toward that, that the applications and systems were built for those silos. So how can we provide integrated information for all those people?

As we have moved forward, those boundaryless systems have become bigger and much more complex. Now, boundarylessness and complexity are giving everyone different types of challenges. Many of the forums or consortia that make up The Open Group are all tackling it from their own perspective, and it’s all coming together very well.

We have got something like the Future Airborne Capability Environment (FACE) Consortium, which is a managed consortium of The Open Group focused on federal aviation. In the federal aviation world they're dealing with issues like weapons systems.

New weapons

Over time, building similar weapons is going to be more expensive, inflation happens. But the changing nature of warfare is such that you've then got a situation where you’ve got to produce new weapons. You have to produce them quickly and you have to produce them inexpensively.

avionics within a cockpit of whatever airborne vehicle be more interchangeable, so that they can be adapted more quickly and do things faster and at lower cost. After all, cost is a major pressure on government departments right now.

We've also got the challenges of the supply chain. Because of the pressure on costs, it’s critical that large, complex systems are developed using a global supply chain. It’s impossible to do it all domestically at a cost. Given that, countries around the world, including the US and China, are all concerned about what they're putting into their complex systems that may have tainted or malicious code or counterfeit products.

The Open Group Trusted Technology Forum (OTTF) provides a standard that ensures that, at each stage along the supply chain, we know that what’s going into the products is clean, the process is clean, and what goes to the next link in the chain is clean. And we're working on an accreditation program all along the way.

We're also in a world, which when we mention security, everyone is concerned about being attacked, whether it’s cybersecurity or other areas of security, and we've got to concern ourselves with all of those as we go along the way.

Our Security Forum is looking at how we build those things out. The big thing about large, complex systems is that they're large and complex. If something goes wrong, how can you fix it in a prescribed time scale? How can you establish what went wrong quickly and how can you address it quickly?

If you've got large, complex systems that fail, it can mean human life, as it did with the BP oil disaster at Deepwater Horizon or with Space Shuttle Challenger. Or it could be financial. In many organizations, when something goes wrong, you end up giving away service.

An example that we might use is at a railway station where, if the barriers don’t work, the only solution may be to open them up and give free access. That could be expensive. And you can use that analogy for many other industries, but how can we avoid that human or financial cost in any of those things?

A couple of years after the Space Shuttle Challenger disaster, a number of criteria were laid down for making sure you had dependable systems, you could assess risk, and you could know that you would mitigate against it.

What The Open Group members are doing is looking at how you can get dependability and assuredness through different systems. Our Security Forum has done a couple of standards that have got a real bearing on this. One is called Dependency Modeling, and you can model out all of the dependencies that you have in any system.

Simple analogy

A very simple analogy is that if you are going on a road trip in a car, you’ve got to have a competent driver, have enough gas in the tank, know where you're going, have a map, all of those things.

What can go wrong? You can assess the risks. You may run out of gas or you may not know where you're going, but you can mitigate those risks, and you can also assign accountability. If the gas gauge is going down, it's the driver's accountability to check the gauge and make sure that more gas is put in.

We're trying to get that same sort of thinking through to these large complex systems. What you're looking at doing, as you develop or evolve large, complex systems, is to build in this accountability and build in understanding of the dependencies, understanding of the assurance cases that you need, and having these ways of identifying anomalies early, preventing anything from failing. If it does fail, you want to minimize the stoppage and, at the same time, minimize the cost and the impact, and more importantly, making sure that that failure never happens again in that system.

The Security Forum has done the Dependency Modeling standard. They have also provided us with the Risk Taxonomy. That's a separate standard that helps us analyze risk and go through all of the different areas of risk.

Now, the Real-time and Embedded Systems Forum  has produced the Dependability through Assuredness, a standard of The Open Group, that brings all of these things together. We've had a wonderful international endeavor on this, bringing a lot of work from Japan, working with the folks in the US and other parts of the world. It's been a unique activity.

Dependability through Assuredness depends upon having two interlocked cycles. The first is a Change Management Cycle that says that, as you look at requirements, you build out the dependencies, you build out the assurance cases for those dependencies, and you update the architecture. Everything has to start with architecture now.

You build in accountability, and accountability, importantly, has to be accepted. You can't just dictate that someone is accountable. You have to have a negotiation. Then, through ordinary operation, you assess whether there are anomalies that can be detected and fix those anomalies by new requirements that lead to new dependabilities, new assurance cases, new architecture and so on.

The other cycle that’s critical in this, though, is the Failure Response Cycle. If there is a perceived failure or an actual failure, there is understanding of the cause, prevention of it ever happening again, and repair. That goes through the Change Accommodation Cycle as well, to make sure that we update the requirements, the assurance cases, the dependability, the architecture, and the accountability.

So the plan is that with a dependable system through that assuredness, we can manage these large, complex systems much more easily.

Gardner: Many of The Open Group activities have been focused at the enterprise architect or business architect levels. Also with these risk and security issues, you're focusing at chief information security officers or governance, risk, and compliance (GRC), officials or administrators. It sounds as if the Dependability through Assuredness standard shoots a little higher. Is this something a board-level mentality or leadership should be thinking about, and is this something that reports to them?

Board-level issue

Brown: In an organization, risk is a board-level issue, security has become a board-level issue, and so has organization design and architecture. They're all up at that level. It's a matter of the fiscal responsibility of the board to make sure that the organization is sustainable, and to make sure that they've taken the right actions to protect their organization in the future, in the event of an attack or a failure in their activities.

The risks to an organization are financial and reputation, and those risks can be very real. So, yes, they should be up there. Interestingly, when we're looking at areas like business architecture, sometimes that might be part of the IT function, but very often now we're seeing as reporting through the business lines. Even in governments around the world, the business architects are very often reporting up to business heads.

Gardner: Here in Philadelphia, you're focused on some industry verticals, finance, government, health. We had a very interesting presentation this morning by Dr. David Nash, who is the Dean of the Jefferson School of Population Health, and he had some very interesting insights about what's going on in the United States vis-à-vis public policy and healthcare.

One of the things that jumped out at me was, at the end of his presentation, he was saying how important it was to have behavior modification as an element of not only individuals taking better care of themselves, but also how hospitals, providers, and even payers relate across those boundaries of their organization.

That brings me back to this notion that these standards are very powerful and useful, but without getting people to change, they don't have the impact that they should. So is there an element that you've learned and that perhaps we can borrow from Dr. Nash in terms of applying methods that actually provoke change, rather than react to change?

Brown: Yes, change is a challenge for many people. Getting people to change is like taking a horse to water, but will it drink? We've got to find methods of doing that.

One of the things about The Open Group standards is that they're pragmatic and practical standards. We've seen' in many of our standards' that where they apply to product or service, there is a procurement pull through. So the FACE Consortium, for example, a $30 billion procurement means that this is real and true.

In the case of healthcare, Dr. Nash was talking about the need for boundaryless information sharing across the organizations. This is a major change and it's a change to the culture of the organizations that are involved. It's also a change to the consumer, the patient, and the patient advocates.

All of those will change over time. Some of that will be social change, where the change is expected and it's a social norm. Some of that change will change as people, generations develop. The younger generations are more comfortable with authority that they perceive with the healthcare professionals, and also of modifying the behavior of the professionals.

The great thing about the healthcare service very often is that we have professionals who want to do a number of things. They want to improve the lives of their patients, and they also want to be able to do more with less.

Already a need

There's already a need. If you want to make any change, you have to create a need, but in the healthcare, there is already a pent-up need that people see that they want to change. We can provide them with the tools and the standards that enable it to do that, and standards are critically important, because you are using the same language across everyone.

It's much easier for people to apply the same standards if they are using the same language, and you get a multiplier effect on the rate of change that you can achieve by using those standards. But I believe that there is this pent-up demand. The need for change is there. If we can provide them with the appropriate usable standards, they will benefit more rapidly.

Good folks

The focus of The Open Group for the last couple of decades or so has always been on horizontal standards, standards that are applicable to any industry. Our focus is always about pragmatic standards that can be implemented and touched and felt by end-user consumer organizations.

Now, we're seeing how we can make those even more pragmatic and relevant by addressing the verticals, but we're not going to lose the horizontal focus. We'll be looking at what lessons can be learned and what we can build on. Big data is a great example of the fact that the same kind of approach of gathering the data from different sources, whatever that is, and for mixing it up and being able to analyze it, can be applied anywhere.

The challenge with that, of course, is being able to capture it, store it, analyze it, and make some sense of it. You need the resources, the storage, and the capability of actually doing that. It's not just a case of, "I'll go and get some big data today."

I do believe that there are lessons learned that we can move from one industry to another. I also believe that, since some geographic areas and some countries are ahead of others, there's also a cascading of knowledge and capability around the world in a given time scale as well.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: The Open Group.

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The next edition of the HP Discover Performance Podcast Series highlights how Infinity Insurance Companies in Birmingham, Alabama has been deploying a new data architecture -- native column store databases -- to improve productivity for their analysis and business intelligence (BI) queries.

To learn more about how Infinity has improved their performance and their results for their business analytics, BriefingsDirect interviewed Barry Ralston, Assistant Vice President for Data Management at Infinity Insurance Companies. The discussion, which took place at the recent HP Discover 2013 Conference in Las Vegas, is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions. [Learn more about the upcoming Vertica conference in Boston Aug. 5.]

Among other findings, Ralston and his team has seen a 100 times improvement in their top 12 worst-performing queries or longest-running queries when moving from a row-store-based Oracle Exadata implementation to a column store-based HP Vertica deployment. [Disclosure: HP is a sponsor of BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: What was it that you've been doing with your BI and data warehousing that prompted you to seek an alternative?

Ralston: Like many companies, we have constructed an enterprise data warehouse deployed to a row-store technology. In our case, it was initially Oracle RAC and then, eventually, the Oracle Exadata engineered hardware/software appliance.

Ralston

We were noticing that analysis that typically occurs in our space wasn’t really optimized for execution via that row store. Based on my experience with Vertica, we did a proof of concept with a couple of other alternative and analytic store-type databases. We specifically chose Vertica to achieve higher productivity and to allow us to focus on optimizing queries and extracting value out of the data.

Gardner: What does Infinity Insurance Companies do? How big are you, and how important is data and analysis to you?

Ralston: We are billion-dollar property and casualty company, headquartered in Birmingham, Alabama. Like any insurance carrier, data is key to what we do. But one of the things that drew me to Infinity, after years of being in a consulting role, was the idea of their determination to use data as a strategic weapon, not just IT as a whole, but data specifically within that larger IT as a strategic or competitive advantage.

Vertica environment

Gardner: You have quite a bit of internal and structured data. Tell me a bit what happened when you moved into a Vertica environment, first in the proof of concept phase and then into production?

Ralston: For the proof of concept, we took the most difficult or worst-performing queries from our Exadata implementation and moved that entire enterprise data warehouse set into a Vertica deployment on three Dual Hex Core, DL380 type machines. We're running at the same scale, with the same data, with the same queries.

We took the top 12 worst-performing queries or longest-running queries from the Exadata implementation, and not one of the proof of concept queries ran less than 100 times faster. It was an easy decision to make in terms of the analytic workload, versus trying to use the Oracle row-store technology.

Gardner: Let’s dig into that a bit. I'm not a computer scientist and I don’t claim to fully understand the difference between row store, relational, and the column-based approach for Vertica. Give us the quick "Data Architecture 101" explanation of why this improvement is so impressive? [Learn more about the upcoming Vertica conference in Boston Aug. 5.]

Ralston: The original family of relational databases -- the current big three are  Oracle, SQL Server and DB2 -- are based on what we call row-storage technologies. They store information in blocks on disks, writing an entire row at a time.

If you had a record for an insured, you might have the insured's name, the date the policy went into effect, the date the policy next shows a payment, etc. All those attributes were written all at the same time in series to a row, which is combined into a block.

So storage has to be allocated in a particular fashion, to facilitate things like updates. It’s an optimal way of storing data for transaction processing. For now, it’s probably the state-of-the-art for that. If I am running an accounting system or a quote system, that’s the way to go.

Analytic queries are fundamentally different than transaction-processing queries. Think of the transaction processing as a cash register. You ring up a sale with a series of line items. Those get written to that row store database and that works well.

But when I want to know the top 10 products sold to my most profitable 20 percent of customers in a certain set of regions in the country, those set-based queries don’t perform well without major indexing. Often, that relates back to additional physical storage in a row-storage architecture.

Column store databases -- Vertica is a native column store database -- store data fundamentally differently than those row stores. We might break down a record into an entire set of columns or store distinctly. This allows me to do a couple of different things from an architectural level.

Sort, compress, organize

First and foremost, I can sort, compress, and organize the data on disk much more efficiently. Compression has been recently added to row-storage architectures, but in a row-storage database, you largely have to compress at the entirety of a row.

I can’t choose an optimal compression algorithm for just a date, because in that row, I will have text, numbers, and dates. In a column store, I can apply specific compression algorithm to the data that's in that column. So date gets one algorithm, a monotone increasing key like a surrogate key you might have in a dimensional data warehouse, has a different encoding algorithm, etc.

This is sorting. How data gets retrieved is fundamentally different, another big point for row-storage databases at query time. I could say, "Tell me all the customers that bought a product in California, but I only want to know their last name."

If I have 20 different attributes, a row-storage database actually has to read all the attributes off of disk. The query engine eliminates the ones I didn’t ask for in the eventual results, but I've already incurred the penalty of the input-output (I/O). This has a huge impact when you think of things like call detail records in telecom which have a 144-some odd columns.

If I'm only asking against a column store database, "Give me all the people who have last names, who bought a product in California," I'm essentially asking the database to read two columns off disk, and that’s all that’s happening. My I/O factors are improved by an order of 10 or in the case of the CDR, 1 in 144.

Gardner: You can’t just go back and increase your I/O improvements in those relational environments by making it in-memory or cutting down on the distance between the data and the processing? That only gets you so far, and you can only throw hardware at it so much. So fundamentally, it’s all about the architecture.

Ralston: Absolutely correct. You've seen a lot of these -- I think one of the fun terms around this is "unnatural acts with data," as to how data gets either scattered or put into a cache or other things. Every time you introduce one of these mechanisms, you're putting another bottleneck between near real-time analytics and getting the data from a source system into a user’s hands for analytics. Think of a cache. If you’re going to cache, you’ve got to warm that cache up to get an effect.

If I'm streaming data in from a sensor, real-time location servers, or something like that, I don’t get a whole lot of value out of the cache to start until it gets warmed up. I totally agree with your point there, Dana, that it’s all about the architecture.

In short, in leveraging Vertica, the underlying architecture allows me to create a playfield, if you will, for business analysts. They don’t necessarily have to be data scientists to enjoy it and be able to relate things that have a business relationship between each other, but not necessarily one that’s reflected in the data model, for whatever reason.

Performance suffers

Obviously in a row storage architecture, and specifically within dimensional data warehouses, if there is no index between a pair of columns, your performance begins to suffer. Vertica creates no indexes and it’s self-indexing the data via sorting and encoding.

So if I have an end user who wants to analyze something that’s never been analyzed before, but has a semantic relationship between those items, I don’t have to re-architect the data storage for them to get information back at the speed of their decision.

Gardner: What about opening this up to some new types of data and/or giving your users the folks in the insurance company the opportunity to look to external types of queries and learn more about markets, where they can apply new insurance products and grow the top line?

Ralston: That's definitely part of our strategic plan. Right now, 100 percent of the data being leveraged at Infinity is structured. We're leveraging Vertica to manage all that structured data, but we have a plan to leverage Hadoop and the Vertica Hadoop connectors, based on what I'm seeing around HAVEn, the idea of being able to seamlessly structured, non-structured data from one point.

Insurance is an interesting business in that, as my product and pricing people look for the next great indicator of risk, we essentially get to ride a wave of that competitive advantage for as long a period of time as it takes us to report that new rate to a state. The state shares that with our competitors, and then our competitors have to see if they want to bake into their systems what we’ve just found.

So we can use Vertica as a competitive hammer, Vertica plus Hadoop to do things that our competitors aren’t able to do. Then, I’ve delivered what my CIO is asking me in terms of data as a competitive advantage.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.

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This latest BriefingsDirect podcast, from the recent 2013 Ariba LIVE Conference in Washington, D.C., explores the rapid adoption of better means for companies to conduct so-called spot buying -- a more ad-hoc and agile, yet managed, approach to buying products and services.

We'll examine new spot-buying research from The Hackett Group on the latest and greatest around agile procurement of low-volume purchases, and we'll learn how two companies are benefiting from making spot buying a new competency.

The panel consists of Kurt Albertson, Associate Principal Advisor at The Hackett Group in Atlanta; Ian Thomson, Koozoo’s Head of Business Development, based in San Francisco, and Cal Miller, Vice President of Business Development for Blue Marble Media in Atlanta. The interview is conducted Dana Gardner, Principal Analyst at Interarbor Solutions. [Disclosure: Ariba, an SAP company, is a sponsor of BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: How did we get to the need for tactical sourcing, and how did we actually begin dividing tactical and strategic sourcing at all?

Albertson: When you look at enterprises out there, our Key Issues Study for 2013 identified the top priorities area as profitability. So companies are continuing to focus on the profitability objective.

Customer satisfaction

The second slot was customer satisfaction, and you can view customer satisfaction as external customers, but also internal customers and the satisfaction around that.

With that as the overlay in terms of the two most important objectives for the enterprise --  the third, by the way, is revenue growth -- let’s cascade down to why tactical sourcing or spot buying is important.

The importance comes from those two topics. Companies are continuing to drive profitability, which means continuing take out cost. Most mature organizations have very robust and mature strategic-sourcing processes in place. They've hired very seasoned category managers to run those processes and they want them focused on the most valuable categories of spend, where you want to align your most strategic assets.

On the other side of that equation, you have this transactional stuff. Someone puts through a purchase order, where procurement has very little involvement. The requisitioners make the decision on what to buy and they go out and get pricing. Purchasing’s role is to issue a purchase order, and there is no kind of category management or expense management practice in place.

That’s been the traditional approach by organizations, this two-tiered approach to procurement. The issue, however, comes when you have your category managers trying to get involved in spend where it’s not necessarily strategic, but you still want some level of spend management applied to it. So you've got these very seasoned resources focused on categories of spend that aren’t necessarily where they can add the biggest bang for the buck.

That’s what caused this phenomenon around spot buy, or tactical buy, taking this middle ground of spend, which our research shows is about 43 percent of spend on average. More importantly, more than sometimes half the transactional activity comes through it. So it's putting in place a better model to support that type of spend, so your category managers can go off and do what you hired them to do.

Gardner: And that 43 percent, does that cut across large companies as well as smaller ones?

Albertson: The 43 percent is an average, and there are going to be variances in that, depending on the industry, spend profile, and scale of the company, as you noted. Companies need to look at their spend, get the spend analytics in place to understand what they're buying to nail down the value proposition around this.

Smaller companies generally aren't going to have the maturity in place in terms of managing their spend. They're not going to have the category-manager capabilities in place. In all likelihood, they could be handling a much higher percentage of their spend through a more transactional nature. So for them, the opportunity might even be greater.

Cycle time

When we think about the reasons for doing spot buying, profitability was one reason, but customer service was the other, and customer service translates into cycle time.

That’s usually the issue with this type of spend. You can’t afford to have a category manager take it through a strategic sourcing process, which can take anywhere from six to 30 weeks.

People need this tomorrow. They need it in a week, and so you need a mechanism in place to focus on shorter cycle times and meet the needs of the customers. If you can’t do that, they're just going to bypass procurement, go do their own thing, and apply no rigor of spend management against that.

It's a common misperception that of that 43 percent of influence spend that we would consider tactical, it's all emergency buys. A lot of it isn’t necessarily emergency buys. It’s just that a large percentage of that is more category-specific types of purchases, but companies just don’t have the preferred suppliers or the category expertise in place to go out, identify suppliers, and manage that spend. It falls under the standard levels that companies might have for sending something through strategic sourcing.

Gardner: Let’s go to some organizations that are grappling with these issues. First, Koozoo. Ian, tell us a little bit about Koozoo and how spot buying plays a role in your life.

Thomson: Koozoo is a technology startup based in San Francisco. We're venture-backed and we've made it very easy to share your view using an existing device. You take an old mobile phone, and we can convert that, using our software application, into a live-stream webcam.

In terms of efficiency, we're like many organizations, but as a start-up, in particular, we're resource constrained. I'm also the procurement manager, as it turns out. It’s not in my job title, but we needed to find something fast. We were launching a product and we needed something to support it.

It wasn’t a catalog item, and it wasn’t something I could find on Amazon. So looked for some suppliers online and found somebody that could meet our need within two weeks, which was super important, as we were looking at a launch date.

More developed need

I had gone to Alibaba and I looked at what Alibaba’s competitors were. Ariba Discovery came up as one of them. So that’s pretty much how I ran into it.

I think I "spot buyed" Ariba in order to spot buy. I tested Alibaba, and to be fair, it was not a very clean approach. I got a lot of messy inbound input and responses when I asked for what I thought was a relatively simple request.

There were things that weren’t meeting my needs. The communication wasn’t very easy on Alibaba, maybe because of the international nature of the would-be suppliers.

Gardner: Let’s go to Cal Miller at Blue Marble Media. First, Cal, tell us a bit about Blue Marble and why this nature of buying is important for you?

Miller: Blue Marble is a very small company, but we develop high profile video, film, motion graphics, and animation. We came to be involved with Ariba about three years ago. We were selected as a supplier to help them with a marketing project. The relationship grew, and as we learned more about Ariba, someone said, "You guys need to be on the Discovery Network program." We did, and it was a very wise decision, very fortunate.

Gardner: Are you using the spot buying and Discovery as a way of buying goods or allowing others to buy your goods in that spot-buying mode or both?

Miller: Our involvement is almost totally as a seller. In our business, at least half of our clients are in a spot-buy scenario. It’s not something they do every month or even every year. We have even Fortune 500 companies that will say they need to do this series of videos and haven’t done it for three years. So whoever gets assigned to start that project it is a spot buy, and we're hopeful that they'll find us and then we get that opportunity. So spot buying is a real strategy for us and for developing our revenue.

Gardner: You found therefore a channel in Ariba through which people who are in this ad-hoc need to execute quickly, but not with a lot of organization and history to it, can find you. How did that compare to other methods that you would typically use to be found?

Miller: Actually, there is very little comparison. The batting average, if you will, is excellent. The quality of people who are coming out to say, "We would like to meet you" is outstanding. Most generally, it’s a C-level contact. What we find is the interaction allows for a real relationship-development process. So even if we don’t get that particular opportunity, we're secure as one of their shortlisted go-to people, and that’s worth everything.

Gardner: Kurt Albertson, when you listen to both a buyer and a seller, it seems to me that there is a huge untapped potential for organizing and managing spot buying in the market.

Finding new customers

Albertson: Listen to Cal talk about Blue Marble’s experience. Certainly from a business development perspective, it’s another tool that I'm sure Cal appreciates in terms of going out and finding new customers.

Listening to Ian talk about it from the buy side is interesting. You have users like Ian who don’t have a mature procurement organization in place, and this is a tool they're using to go out and drive their procurement process.

But then, on the other end of that scale, you do have large global companies as well. As I talked about, these large global companies who haven’t done a good job of managing what we would consider tactical spend, which again is about 43 percent of what’s influenced.

For them, while they have built out very robust procurement organizations to manage the more strategic spend, it’s this 43 percent of influence spend that’s sub-optimized. So it’s more of an evolution of their procurement strategy to start putting in place the capabilities to address that chunk of spend that’s been sub-optimized.

Gardner: Tell us a bit more about your research. Were there any other findings that would benefit us, as we try to understand what spot buying is and why it should be important to more buyers and sellers?

Albertson: The first question that everyone generally tends to ask when trying to build out a new type of capability is what’s the return on that. Why would we do this? We have already talked about the issue of longer cycle times that occur, if you try to manage the spend through a traditional kind of procurement process and the dissatisfaction that causes. But the other option is to just let the requesters do what they want, and you don’t drive any kind of spend management practices around it.

When we look at the numbers, Dana, typically going through a traditional strategic sourcing process with highly skilled category managers, on average you'll drive just over 6 percent savings on that spend. Whereas, if you put in place more of a tactical spot-buy type process, the savings you will drive is less,  4.3 percent on average, according to our research.

So there's a little bit of a delta there by putting it through a more formal process. But the important thing is that if you look at the return, you're obviously not spending as much time and you're not having as mature resources and as experienced resources having to support that spend. So the investment is less. The return on investment that you get from a tactical process, as opposed to the more strategic process, is actually higher.

There is a very strong business case for going out and putting in place the capabilities to address the spend. That’s the question that most organizations will ask -- what is the return on the investment?

Gardner: Are all the procurement providers, service providers jumping on this? Is Ariba in front of the game in any way?

Process challenges

Albertson: There are some challenges with this process, and if you look at Ariba, they evolved from the front end of the sourcing process,  built out capabilities to support that, and have a lot of maturity in that space.

The other thing that they have built out is the networked community. If you look at tactical buying and spot buying, both of those are extremely important. First of all, you want a front-end ERFx process that you can quickly enable, can quickly go out in a standard methodology, and go to the market with standard requirements.

But the other component of that is that you need to have this network of a whole bunch of suppliers out there that you can then send that to. That’s where Ariba’s strength is in the fact that they have built out a very large network, the largest network out there for suppliers and buyers to interact.

And that’s really the most significant advantage that Ariba has in this space -- that network of buyers and suppliers, so they can very quickly go out and implement a supplier discovery type of execution and identify particular suppliers.

We may call this tactical spend, but it’s still important to the people who are going out within the companies and looking for what they're trying to get, a product or service. There needs to be a level of due diligence against these suppliers. There needs to be a level of trust. Compare that to doing a Google search and going out there and just finding suppliers. The Ariba Network provides that additional level of comfort and trust and prequalification of suppliers to participate in this process.

You're going to find companies coming at it from both ends. The smaller, less mature organizations from a procurement perspective are going to come at it from a primary buying and sourcing channel, whereas for the larger organizations, the bigger bang for the buck for them is going after and getting control over the strategic spend.

Again, we're in an environment right now, particularly for the larger organizations, where everyone is trying to continue to evolve the value proposition. Strategic category managers are moving into supply-relationship management, innovation, and how do they collaborate with suppliers to drive innovation.

We all know that across the G&A function, including procurement, there are not the significant investments of resources being made. So the only way they are going to be able to do that is extract themselves out of this kind of tactical activity and build out a different type of capability internally, including leveraging solutions like Ariba and the Supplier Discovery capability to go out and help facilitate that buy so that those category managers can continue to evolve the value that they provide to the business.

Cloud model

Gardner: It seems that the cloud model really suits this spot-buying and tactical-buying approach very well. You log on, the network can grow rapidly, and buyers and sellers can participate in this networked economy. Is this something that wouldn’t have happened 5 or 10 years ago, when we only looked at on-premise systems? Is the cloud a factor in why spot buying works now?

Albertson: Obviously, one of the drivers of this is how quickly can you get up to speed and start leveraging the technology and enabling the spot-buy tactical sourcing capabilities that you're building.

Then on the supply end, one of the driving forces is to enable as many suppliers and as many participants into this environment. That is going to be one of the key factors that determines success in this area, and certainly a software-as-a-service (SaaS) model works better for accomplishing that than an on-premise model does.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: Ariba, an SAP Company.

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This latest BriefingsDirect discussion, leading into The Open Group Conference on July 15 in Philadelphia, brings together a panel of experts to explore how new IT trends are empowering improvements, specifically in the area of healthcare. We'll learn how healthcare industry organizations are seeking large-scale transformation and what are some of the paths they're taking to realize that.

We'll see how improved cross-organizational collaboration and such trends as big data and cloud computing are helping to make healthcare more responsive and efficient.

The panel: Jason Uppal, Chief Architect and Acting CEO at clinicalMessage; Larry Schmidt, Chief Technologist at HP for the Health and Life Sciences Industries, and Jim Hietala, Vice President of Security at The Open Group. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

This special BriefingsDirect thought leadership interview comes in conjunction with The Open Group Conference, which is focused on enterprise transformation in the finance, government, and healthcare sectors. Registration to the conference remains open. Follow the conference on Twitter at #ogPHL. [Disclosure: The Open Group and HP are sponsors of BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: Let’s take a look at this very interesting and dynamic healthcare sector. What, in particular, is so special about healthcare and why do things like enterprise architecture and allowing for better interoperability and communication across organizational boundaries seem to be so relevant here?

Hietala: There’s general acknowledgement in the industry that, inside of healthcare and inside the healthcare ecosystem, information either doesn’t flow well or it only flows at a great cost in terms of custom integration projects and things like that.

Fertile ground

From The Open Group’s perspective, it seems that the healthcare industry and the ecosystem really is fertile ground for bringing to bear some of the enterprise architecture concepts that we work with at The Open Group in order to improve, not only how information flows, but ultimately, how patient care occurs.

Gardner: Larry Schmidt, similar question to you. What are some of the unique challenges that are facing the healthcare community as they try to improve on responsiveness, efficiency, and greater capabilities?

Schmidt: There are several things that have not really kept up with what technology is able to do today.

mobile technologies and want to be able to leverage that to provide additional observation of an individual, so that the doctor can make a more complete diagnosis of some sickness or possibly some medication that a person is on.

We want to be able to see that observation in real life, as opposed to having to take that in at the office, which typically winds up happening. I don’t know about everybody else, but every time I go see my doctor, oftentimes I get what’s called white coat syndrome. My blood pressure will go up. But that’s not giving the doctor an accurate reading from the standpoint of providing great observations.

Technology has advanced to the point where we can do that in real time using mobile and other technologies, yet the communication flow, that information flow, doesn't exist today, or is at best, not easily communicated between doctor and patient.

If you look at the ecosystem, as Jim offered, there are plenty of places that additional collaboration and communication can improve the whole healthcare delivery model.

That’s what we're about. We want to be able to find the places where the technology has advanced, where standards don’t exist today, and just fuel the idea of building common communication methods between those stakeholders and entities, allowing us to then further the flow of good information across the healthcare delivery model.

Gardner: Jason Uppal, let’s think about what, in addition to technology, architecture, and methodologies can bring to bear here? Is there also a lag in terms of process thinking in healthcare, as well as perhaps technology adoption?

Uppal: I'm going to refer to a presentation that I watched from a very well-known surgeon from Harvard, Dr. Atul Gawande. His point was is that, in the last 50 years, the medical industry has made great strides in identifying diseases, drugs, procedures, and therapies, but one thing that he was alluding to was that medicine forgot the cost, that everything is cost.

At what price?

Today, in his view, we can cure a lot of diseases and lot of issues, but at what price? Can anybody actually afford it?

Uppal

His view is that if healthcare is going to change and improve, it has to be outside of the medical industry. The tools that we have are better today, like collaborative tools that are available for us to use, and those are the ones that he was recommending that we need to explore further.

That is where enterprise architecture is a powerful methodology to use and say, "Let’s take a look at it from a holistic point of view of all the stakeholders. See what their information needs are. Get that information to them in real time and let them make the right decisions."

Therefore, there is no reason for the health information to be stuck in organizations. It could go with where the patient and providers are, and let them make the best decision, based on the best practices that are available to them, as opposed to having siloed information.

So enterprise-architecture methods are most suited for developing a very collaborative environment. Dr. Gawande was pointing out that, if healthcare is going to improve, it has to think about it not as medicine, but as healthcare delivery.

Gardner: And it seems that not only are there challenges in terms of technology adoption and even operating more like an efficient business in some ways. We also have very different climates from country to country, jurisdiction to jurisdiction. There are regulations, compliance, and so forth.

Going back to you, Larry, how important of an issue is that? How complex does it get because we have such different approaches to healthcare and insurance from country to country?

Schmidt: There are definitely complexities that occur based on the different insurance models and how healthcare is delivered across and between countries, but some of the basic and fundamental activities in the past that happened as a result of delivering healthcare are consistent across countries.

As Jason has offered, enterprise architecture can provide us the means to explore what the art of the possible might be today. It could allow us the opportunity to see how innovation can occur if we enable better communication flow between the stakeholders that exist with any healthcare delivery model in order to give us the opportunity to improve the overall population.

After all, that’s what this is all about. We want to be able to enable a collaborative model throughout the stakeholders to improve the overall health of the population. I think that’s pretty consistent across any country that we might work in.

Ongoing work

Gardner: Jim Hietala, maybe you could help us better understand what’s going on within The Open Group and, even more specifically, at the conference in Philadelphia. There is the Population Health Working Group and there is work towards a vision of enabling the boundaryless information flow between the stakeholders. Any other information and detail you could offer would be great. [Registration to the conference remains open. Follow the conference on Twitter at #ogPHL.]

Hietala: On Tuesday of the conference, we have a healthcare focus day. The keynote that morning will be given by Dr. David Nash, Dean of the Jefferson School of Population Health. He'll give what’s sure to be a pretty interesting presentation, followed by a reactors' panel, where we've invited folks from different stakeholder constituencies.

Hietala

We're are going to have clinicians there. We're going to have some IT folks and some actual patients to give their reaction to Dr. Nash’s presentation. We think that will be an interesting and entertaining panel discussion.

The balance of the day, in terms of the healthcare content, we have a workshop. Larry Schmidt is giving one of the presentations there, and Jason and myself and some other folks from our working group are involved in helping to facilitate and carry out the workshop.

The goal of it is to look into healthcare challenges, desired outcomes, the extended healthcare enterprise, and the extended healthcare IT enterprise and really gather those pain points that are out there around things like interoperability to surface those and develop a work program coming out of this.

So we expect it to be an interesting day if you are in the healthcare IT field or just the healthcare field generally, it would definitely be a day well spent to check it out.

Gardner: Larry, you're going to be talking on Tuesday. Without giving too much away, maybe you can help us understand the emphasis that you're taking, the area that you're going to be exploring.

Schmidt: I've titled the presentation "Remixing Healthcare through Enterprise Architecture." Jason offered some thoughts as to why we want to leverage enterprise architecture to discipline healthcare. My thoughts are that we want to be able to make sure we understand how the collaborative model would work in healthcare, taking into consideration all the constituents and stakeholders that exist within the complete ecosystem of healthcare.

This is not just collaboration across the doctors, patients, and maybe the payers in a healthcare delivery model. This could be out as far as the drug companies and being able to get drug companies to a point where they can reorder their raw materials to produce new drugs in the case of an epidemic that might be occurring.

Real-time model

It would be a real-time model that allows us the opportunity to understand what's truly happening, both to an individual from a healthcare standpoint, as well as to a country or a region within a country and so on from healthcare. This remixing of enterprise architecture is the introduction to that concept of leveraging enterprise architecture into this collaborative model.

Then, I would like to talk about some of the technologies that I've had the opportunity to explore around what is available today in technology. I believe we need to have some type of standardized messaging or collaboration models to allow us to further facilitate the ability of that technology to provide the value of healthcare delivery or betterment of healthcare to individuals. I'll talk about that a little bit within my presentation and give some good examples.

It’s really interesting. I just traveled from my company’s home base back to my home base and I thought about something like a body scanner that you get into in the airport. I know we're in the process of eliminating some of those scanners now within the security model from the airports, but could that possibly be something that becomes an element within healthcare delivery? Every time your body is scanned, there's a possibility you can gather information about that, and allow that to become a part of your electronic medical record.

Hopefully, that was forward thinking, but that kind of thinking is going to play into the art of the possible, with what we are going to be doing, both in this presentation and talking about that as part of the workshop.

Gardner: Larry, we've been having some other discussions with The Open Group around what they call Open Platform 3.0, which is the confluence of big data, mobile, cloud computing, and social.

One of the big issues today is this avalanche of data, the Internet of things, but also the Internet of people. It seems that the more work that's done to bring Open Platform 3.0 benefits to bear on business decisions, it could very well be impactful for centers and other data that comes from patients, regardless of where they are, to a medical establishment, regardless of where it is.

So do you think we're really on the cusp of a significant shift in how medicine is actually conducted?

Schmidt: I absolutely believe that. There is a lot of information available today that could be used in helping our population to be healthier. And it really isn't only the challenge of the communication model that we've been speaking about so far. It's also understanding the information that's available to us to take that and make that into knowledge to be applied in order to help improve the health of the population.

As we explore this from an as-is model in enterprise architecture to something that we believe we can first enable through a great collaboration model, through standardized messaging and things like that, I believe we're going to get into even deeper detail around how information can truly provide empowered decisions to physicians and individuals around their healthcare.

So it will carry forward into the big data and analytics challenges that we have talked about and currently are talking about with The Open Group.

Healthcare framework

Gardner: Jason Uppal, we've also seen how in other business sectors, industries have faced transformation and have needed to rely on something like enterprise architecture and a framework like TOGAF in order to manage that process and make it something that's standardized, understood, and repeatable.

It seems to me that healthcare can certainly use that, given the pace of change, but that the impact on healthcare could be quite a bit larger in terms of actual dollars. This is such a large part of the economy that even small incremental improvements can have dramatic effects when it comes to dollars and cents.

So is there a benefit to bringing enterprise architect to healthcare that is larger and greater than other sectors because of these economics and issues of scale?

Uppal: That's a great way to think about this thing. In other industries, applying enterprise architecture to do banking and insurance may be easily measured in terms of dollars and cents, but healthcare is a fundamentally different economy and industry.

It's not about dollars and cents. It's about people’s lives, and loved ones who are sick, who could very easily be treated, if they're caught in time and the right people are around the table at the right time. So this is more about human cost than dollars and cents. Dollars and cents are critical, but human cost is the larger play here.

Secondly, when we think about applying enterprise architecture to healthcare, we're not talking about just the U.S. population. We're talking about global population here. So whatever systems and methods are developed, they have to work for everybody in the world. If the U.S. economy can afford an expensive healthcare delivery, what about the countries that don't have the same kind of resources? Whatever methods and delivery mechanisms you develop have to work for everybody globally.

That's one of the thing that a methodology like TOGAF brings out and says to look at it from every stakeholder’s point of view, and unless you have dealt with every stakeholder’s concerns, you don't have an architecture, you have a system that's designed for that specific set of audience.

The cost is not this 18 percent of the gross domestic product in the U.S. that is representing healthcare. It's the human cost, which is many multitudes of that. That's is one of the areas where we could really start to think about how do we affect that part of the economy, not the 18 percent of it, but the larger part of the economy, to improve the health of the population, not only in the North America, but globally.

If that's the case, then what really will be the impact on our greater world economy is improving population health, and population health is probably becoming our biggest problem in our economy.

We'll be testing these methods at a greater international level, as opposed to just at an organization and industry level. This is a much larger challenge. A methodology like TOGAF is a proven and it could be stressed and tested to that level. This is a great opportunity for us to apply our tools and science to a problem that is larger than just dollars. It's about humans.

All "experts"

Gardner: Jim Hietala, in some ways, we're all experts on healthcare. When we're sick, we go for help and interact with a variety of different services to maintain our health and to improve our lifestyle. But in being experts, I guess that also means we are witnesses to some of the downside of an unconnected ecosystem of healthcare providers and payers.

One of the things I've noticed in that vein is that I have to deal with different organizations that don't seem to communicate well. If there's no central process organizer, it's really up to me as the patient to pull the lines together between the different services -- tests, clinical observations, diagnosis, back for results from tests, sharing the information, and so forth.

Have you done any studies or have anecdotal information about how that boundaryless information flow would be still relevant, even having more of a centralized repository that all the players could draw on, sort of a collaboration team resource of some sort? I know that’s worked in other industries. Is this not a perfect opportunity for that boundarylessness to be managed?

Hietala: I would say it is. We all have experiences with going to see a primary physician, maybe getting sent to a specialist, getting some tests done, and the boundaryless information that’s flowing tends to be on paper delivered by us as patients in all the cases.

So the opportunity to improve that situation is pretty obvious to anybody who's been in the healthcare system as a patient. I think it’s a great place to be doing work. There's a lot of money flowing to try and address this problem, at least here in the U.S. with the HITECH Act and some of the government spending around trying to improve healthcare.

You've got healthcare information exchanges that are starting to develop, and you have got lots of pain points for organizations in terms of trying to share information and not having standards that enable them to do it. It seems like an area that’s really a great opportunity area to bring lots of improvement.

Gardner: Let’s look for some examples of where this has been attempted and what the success brings about. I'll throw this out to anyone on the panel. Do you have any examples that you can point to, either named organizations or anecdotal use case scenarios, of a better organization, an architectural approach, leveraging IT efficiently and effectively, allowing data to flow, putting in processes that are repeatable, centralized, organized, and understood. How does that work out?

Uppal: I'll give you an example. One of the things that happens when a patient is admitted to hospital and in hospital is that hey get what's called a high-voltage care. There is staff around them 24x7. There are lots of people around, and every specialty that you can think of is available to them. So the patient, in about two or three days, starts to feel much better.

When that patient gets discharged, they get discharged to home most of the time. They go from very high-voltage care to next to no care. This is one of the areas where in one of the organizations we work with is able to discharge the patient and, instead of discharging them to the primary care doc, who may not receive any records from the hospital for several days, they get discharged to into a virtual team. So if the patient is at home, the virtual team is available to them through their mobile phone 24x7.

Connect with provider

If, at 3 o’clock in the morning, the patient doesn't feel right, instead of having to call an ambulance to go to hospital once again and get readmitted, they have a chance to connect with their care provider at that time and say, "This is what the issue is. What do you want me to do next? Is this normal for the medication that I am on, or this is something abnormal that is happening?"

When that information is available to that care provider who may not necessarily have been part of the care team when the patient was in the hospital, that quick readily available information is key for keeping that person at home, as opposed to being readmitted to the hospital.

We all know that the cost of being in a hospital is 10 times more than it is being at home. But there's also inconvenience and human suffering associated with being in a hospital, as opposed to being at home.

Those are some of the examples that we have, but they are very limited, because our current health ecosystem is a very organization specific, not  patient and provider specific. This is the area there is a huge room for opportunities for healthcare delivery, thinking about health information, not in the context of the organization where the patient is, as opposed to in a cloud, where it’s an association between the patient and provider and health information that’s there.

In the past, we used to have emails that were within our four walls. All of a sudden, with Gmail and Yahoo Mail, we have email available to us anywhere. A similar thing could be happening for the healthcare record. This could be somewhere in the cloud’s eco setting, where it’s securely protected and used by only people who have granted access to it.

Those are some of the examples where extending that model will bring infinite value to not only reducing the cost, but improving the cost and quality of care.

Schmidt: Jason touched upon the home healthcare scenario and being able to provide touch points at home. Another place that we see evolving right now in the industry is the whole concept of mobile office space. Both countries, as well as rural places within countries that are developed, are actually getting rural hospitals and rural healthcare offices dropped in by helicopter to allow the people who live in those communities to have the opportunity to talk to a doctor via satellite technologies and so on.

The whole concept of a architecture around and being able to deal with an extension of what truly lines up being telemedicine is something that we're seeing today. It would be wonderful if we could point to things like standards that allow us to be able to facilitate both the communication protocols as well as the information flows in that type of setting.

Many corporations can jump on the bandwagon to help the rural communities get the healthcare information and capabilities that they need via the whole concept of telemedicine.

That’s another area where enterprise architecture has come into play. Now that we see examples of that working in the industry today, I am hoping that as part of this working group, we'll get to the point where we're able to facilitate that much better, enabling innovation to occur for multiple companies via some of the architecture or the architecture work we are planning on producing.

Single view

Gardner: It seems that we've come a long way on the business side in many industries of getting a single view of the customer, as it’s called, the customer relationship management, big data, spreading the analysis around among different data sources and types. This sounds like a perfect fit for a single view of the patient across their life, across their care spectrum, and then of course involving many different types of organizations. But the government also needs to have a role here.

Jim Hietala, at The Open Group Conference in Philadelphia, you're focusing on not only healthcare, but finance and government. Regarding the government and some of the agencies that you all have as members on some of your panels, how well do they perceive this need for enterprise architecture level abilities to be brought to this healthcare issue?

Hietala: We've seen encouraging signs from folks in government that are encouraging to us in bringing this work to the forefront. There is a recognition that there needs to be better data flowing throughout the extended healthcare IT ecosystem, and I think generally they are supportive of initiatives like this to make that happen.

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The next edition of the HP Discover Performance Podcast Series examines how McKesson Corp. accomplished a multi-year, pan-IT management transformation. We’ll learn how McKesson's performance journey, from 2005 to the present, has enabled it to better leverage an agile, hybrid cloud model.

The discussion comes from the recent HP Discover 2013 Conference in Las Vegas.

Andy Smith, Vice President of Applications Hosting Services at McKesson, joins host Dana Gardner, Principal Analyst at Interarbor Solutions, to explore how McKesson gained a standardized services orientation to gain agility in deploying its many active applications. [Disclosure: HP is a sponsor of BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: It's hard to believe it's been a full year since we last spoke. What's changed in the last year in how McKesson had been progressing and maturing its applications delivery capabilities?

Smith: Probably one of the things that have changed in the last year is that our performance metrics have continued to improve. We're continuing to see a drop in the number of outages from the standardization and automation. The reliability of the systems has increased, the utilization of the systems has increased, and our system admin ratios have increased. So everything, all the key performance indicators (KPIs) are going in the right direction.

That allowed us to make the next shift, which was to focus on how can we do better at providing capabilities to our customers. How do we do it faster and better through provisioning, because now it's taking less time to do the support side of it.

Gardner: It's really interesting to me that a big part of all this is the provisioning aspect going from fewer manual processes and multiple points of touch to more self-provisioning. How has that worked out?

Smith: It's been very well received. We've been in production now roughly two-and-a-half months. Rather than delivering requests via business requests to add some compute capacity in an average of six months, we’re down to less than four days. I think we can get it down to less than 10 minutes by the time we hit the end of summer.

Well received

It's been a challenge to get people to think differently about their processes internal to IT that would allow us to do the automation, but it's been very well received.

Gardner: What were some of the hurdles in terms of trying to get standardized and creating that operating procedure that people could rally behind, self provision, and automate?

Smith: The first piece is just a change in culture. We believe we were customer-centric providers of services. What that really translated to was that we were customer-centric customized providers of services. So every request was a custom request. That resulted in slow delivery, but it also resulted in non-standardized solutions.

One of the most difficult things was getting the architects and engineers to think differently and to understand that standardization would actually be better for the customer. We could get it to them faster, more consistently, and more reliably, and on the back end, provide the support much more cheaply to get that mind shift.

But we were successful. I think everybody still likes to customize, but we haven't had to do that.

Gardner: Just for the edification of our listeners, tell us a bit about McKesson. You’re not just a small mom-and-pop shop.

Smith: No, I think we’re Fortune 14 now, with more than $122 billion in revenue and more than 43,500 employees. We focus specifically on healthcare, how to ensure that whatever is needed by  healthcare organizations is there when they need it.

Smith

That might be software systems that we write for providers. That could be claims processing that we do for providers. But, the biggest chunk of our business is supply chain, ensuring that the supplies, whether they be medical, surgical, or pharmaceutical, are in the hospital's and providers' hands as soon as they need them.

If a line of business needs to make an improvement in order to capture a need of a customer, with the old way of doing business, it would take me six months to get the computer on the floor. Then they could start their development. Now, you're down to less than a week and days. So they can start their development six months earlier, which really helps us be in a position to capture that new market faster. In turn, this also helps McKesson customers deliver critical healthcare solutions more rapidly to meet today's emerging healthcare needs and enable better health.

Gardner: And there are also some other factors in the market. There's even more talk now about cloud than last year, focusing on hybrid capabilities, where you can pick and choose how to deploy your apps. Then, there's the mobile factor.

Smith: We are recognizing that we have to build that next generation of applications. Part of that is the mobility piece of it, because we have to separate the physical application, the software-as-a-service (SaaS) application from the display device that the customer is going to use. It might be an Android, an iPhone,  or something else, a tablet.

So we're recognizing the fact that for next-generation of product, we really have to separate that mobile portion from it, because that display device could be almost anything.

Gardner: We’re here at HP Discover. How have the HP products and services come together to help you not only tackle these technical issues, but to foster the right culture?

Smith: When we talked last year, we had a lot of the support tools in place from HP -- operations orchestration, server automation, monitoring tools -- but we were using them to do support better. What we're able to do from the provisioning side is leverage that capability and leverage those existing tools.

All we had to do is purchase one additional tool which is a Cloud Service Automation (CSA) that sits on top of our existing tools. So it was a very minor investment, and we were able to leverage all the support tools to do the provisioning side of the business. It was very practical for us and relatively quick.

Gardner: Of course, a big emphasis here at HP Discover is HP Converged Cloud and talking about these different hybrid models. How has the automation provisioning services orientation, and standardization put you in a place to be able to avail yourselves of some of these hybrid models and the efficiencies and speed that come with that? How do they tie together -- what you’ve done with applications now and what you can perhaps do with cloud?

Smith: We’ll be the first to admit that providing the services internally is not necessarily always the best. We may not be the cheapest and we may not be the most capable. By getting better at how we do provisioning and how we do our own internal cloud frees up resources, and those resources now can start thinking about how we work with an external provider.

That's a lot of concern for us right now, because there is that risk factor. Do you put your intellectual property (IP) out there? Do you put your patients’ medical records out there? How do you protect it? And so there are a lot of business rules and contracting issues that we have to get through.

From a technology standpoint, we know we can do it. We’ve done it in the labs. We’ve provisioned out to third-party providers. It all works from a technology standpoint with the tools we have. Now we have to get through the business issues.

On the same journey

It's fortunate, in some ways, that HP is on the same journey. We partner on a lot of these things. When we brought CSA in, it was one of the earlier releases, and now we’ve partnered with them through the Customer Advisory Boards (CABs) and other methods. They continue to enhance this to meet our needs, but also to meet their needs.

Gardner: Now that you've been on this journey from 2005, where do you see yourselves in a couple of years?

Smith: Because we’re in healthcare, very similar to banking, we've hit a point where we don't believe we can afford to be down anymore.

Instead of talking about three nines, four nines, or five nines, we're starting to talk about, how we ensure the machines are never down, even for planned maintenance. That's taking a different kind of infrastructure, but that’s also taking a different kind of application that can tolerate machines being taken offline, but continue to run.

That's where our eye is, trying to figure out how to change the environment to be constantly on.

If the application isn't smart enough to tolerate a piece of machine going down, then you have to redesign the application architecture. Our applications are going to have to scale out horizontally across the equipment as the peaks and valleys of the customer demands change through the day or through the week.

The current architecture doesn't scale horizontally. It scales up and down. So you end up with a really big box that’s not needed some times of the day. It would be better if we could spread the load out horizontally.

Gardner: So just to close out, we have to think about applications now in the context of where they are deployed, in a cloud spectrum or continuum of hybrid types of models. We also have to think about them being delivered out to a variety of different endpoints.

Different end points

What do you think you’ll need to be doing differently from an application-development, deployment, and standardization perspective in order to accomplish both that ability to deploy anywhere and be high performance, as well as also be out on a variety of different end points?

Smith: The reality is that part of our journey over the last several years has been to consolidate the environment, consolidate the data centers, and consolidate and virtualize the servers. That's been great from a customer cost standpoint and standardization standpoint.

But now, when you're starting to deliver that SaaS mobile kind of application, speed of response to the customer, the keystroke, the screen refresh, are really important. You can't do that from a central data center. You've got to be able to push some of the applications and data out to regional locations. We’re not going to build those regional locations. It's just not practical.

That's where we see bringing in these hybrid clouds. We’ll host the primary app, let's say, back in our corporate data center, but then the mobile piece, the customer experience piece, is going to be have to be hosted in data centers that are scattered throughout the country and are much physically much closer to where the customer is.

Gardner: Of course, that’s going to require a different level of performance monitoring and management.

Smith: Exactly, because then you really have to monitor the application, not just the server at the back-end. You’ve got to be watching that performance to know whether you have a local ISP that’s come down, if you have got a local cloud that’s come down. You’re going to really have to be watching the endpoints so you can see that customer experience. So it is a different kind of application monitoring.

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This next edition of the HP Discover Performance Podcast Series targets on how IT leaders are improving security and reducing risks as they adapt to new and often harsh realities of doing business online.

We’re going to learn from a panel how professional services provider CSC, in a strategic partnership with HP, is helping companies and governments better understand and adapt to the tough cybersecurity landscape. 

Our panel consists of co-host Paul Muller, Chief Software Evangelist at HP Software; Dean Weber, Chief Technology Officer, CSC Global Cybersecurity, and Sam Visner, Vice President and General Manager, CSC Global Cybersecurity. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions. [Disclosure: HP is a sponsor of BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: What is the real scale of the threat here? Are we only just catching up in terms of the public perception of the reality of cyber-insecurity? How different is the reality from the public perception?

Weber: The difference is night and day. The reality is that we are under attack, and have been for quite some time. We are, as Sam likes to put it, facing a weapons-grade threat.

Visner: When I think about the threat, I think about several things happening at once. The first thing is that we’re asking IT, on which we depend, to do more. It's not just emails, collaboration, documents, and spreadsheets. It isn’t even just enterprise systems.

IT for manufacturing

It extends all the way down to the IT that we use for manufacturing, to control power plants, pipelines, airplanes, centrifuges, and medical devices. So, the first thing is that we’re asking IT to do more, and therefore there's more to defend. Secondly, the stakes are higher. It's not just up to us.

Visner

Government has said that the cybersecurity of the private sector is of public concern. If you're a regulated public utility for power, water, healthcare, finance, or transportation, your cybersecurity is an issue of public interest. So, this isn’t just the public cybersecurity, it's the cybers

Third is the point that Dean made, and I want to elaborate on it. The threat is very different.

Today, intellectual property, whether or not it's possessed by the public sector or the private sector, if it's valuable, if it's worth something. It's worth something to a bad guy who wants to steal it. And if you have critical infrastructure that you’re trying to manage, and a bad guy may want to disrupt it, because their government may want to be able to exercise power.

And the threats are different. The threats are not just technically sophisticated. That's something a hacker, a teenager, can do. In addition to being technically sophisticated, they’re operationally sophisticated.

That means this is foreign governments, or in some cases, foreign intelligence services that have the resources and the patience to study a target, a company, or a government agency over a long period of time, use social networking to figure out who has administrative privileges inside of that organization, and use that social networking to identify people whom they may want to subvert and who may help them in introducing malware.

Then, once they have decided what information they want, who safeguards it, they use their technical sophistication to follow up on it to exploit their operational knowledge. This is what differentiates a group of hackers, who maybe technically very bright, from an actual nation-state government that has the resources, the discipline, the time, and the patience to stick with the target and to exploit it over a long, long period of time.

So, when we use the term "weapons grade," what we mean is a cyber threat that's hard to detect, that's been wielded by a foreign government, a foreign armed force, or a foreign intelligence service -- the way a foreign government wields a weapon. That's what we’re really facing today in the way of cybersecurity threats.

Muller

Muller: You asked if the headlines are simply reflecting what has always been going on, and I think the answer is, yes. Definitely, there is an increased willingness of organizations to share the fact that they have been breached and to share what some of those vulnerabilities have been.

That's actually a healthy thing for society as a whole, rather than pretending that nothing is going on. Reporting the broken window is good for everybody. But, the reality is the sophistication and the scale of attacks as we have just heard, have gone up and have gone up quite measurably.

Cost of cybercrime

Every year we conduct a Cost of Cyber Crime Study with the Ponemon Institute. If we look just at the numbers between 2010 and 2012, from the most recent study in October, the cost impact of cyber crime has gone up 50 percent over that period of time. The number of successful attacks has gone up by two times. And the time to resolve attack is almost doubled as well. So it has become more expensive, greater scale, and it's becoming more difficult to solve.

Gardner: What strikes me as being quite different from the past, too, is when businesses encountered risks, even collective risks, they often had a law enforcement or other regulatory agency that would come to their rescue.

But, in reading the most recent The New Yorker, the May 20 issue, in an article titled Network Insecurity by John Seabrook, Richard McFeely, the Executive Assistant Director of the F.B.I, says quite straightforwardly, "We simply don't have the resources to monitor the mammoth quantity of intrusions that are going on out there."

So, enterprises, corporations, governments even can't really wait for the cavalry to come riding in. We’re sort of left to our own devices, or have I got that a little off-base, Dean?

Weber: The government can provide support in talking about threats and providing information about best practices, but overall, the private sector has a responsibility to manage its own infrastructures. The private sector may have to manage those infrastructures consistent with the public interest. That's what regulation means.

Weber

But the government is not going to provide cybersecurity for power companies’ power grid or for pharmaceutical companies’ research program. It can insist that there be good cybersecurity, but those organizations have always had to manage their own infrastructures.

Today, however, the threat to those infrastructures and the stakes of losing control of those infrastructures are much higher than they have ever been. That's what's amplified now.

There is also a tradeoff that can be done there in terms of how the government shares its threat intelligence. Today, threat intelligence shared at the highest levels generally requires a very, very high level of security, and that puts it out of reach of some organizations to be able to effectively utilize, even if they were so desirous.

So as we migrate ourselves into dealing with this enhanced threat environment, we need to also deal with the issues of enhancing the threat intelligence that we use as the basis of decision.

Gardner: Well, we've defined the fact that the means are there and that the incidences are increasing in scale, complexity, and severity. There is profit motive, the state secrets, and intellectual-property motives. Given all of that, what's wrong with the old methods?

Current threat

Weber: Against the current state-of-the-art threat, our ability to detect them, as they are coming in or while they are in has almost diminished to the point of non-existence. If we're catching them at all, we're catching them on the way out.

We've got to change the paradigm here. We've got to get better at threat intelligence. We've got to get better at event correlation. We've got to get better at the business of cybersecurity. And it has to be a public-private partnership that actually gets us there, because the public has an interest in the private infrastructure to operate its countries. That’s not just US; that’s global.

Visner: Let me add a point to that that’s germane to the relationship between CSC and HP Software. It's no longer an issue of finding a magic bullet. If I could just keep my antivirus up to fully updated, I would have the best signatures and I would be protected from the threat. Or if my firewall were adequately updated, I will be well protected.

Today, the threat is changing and the IT environment that we're trying to protect is changing. The threat, in many cases, doesn’t have a known signature and is being crafted by nations/states not to have it. Organizations ought to think twice about trying to do these themselves.

Our approach is to use a managed cybersecurity service that uses an infrastructure, a set of security operation centers, and an architecture of tools. That’s the approach we're using. What we're doing with HP Software is using some key pieces of HP Software technology to act as the glue that assembles the cybersecurity information management architecture that we use to manage the cybersecurity for Global 1000 companies and for key government agencies.

Our security operations centers have set of tools, some of which we've developed, and some of which we've sourced from partners, bound together with HP’s ArcSight Security Information and Event Management System. This allows us to add new tools, as we need to retire old tools, when they are no longer useful.

They do a better job of threat correlation and analysis, so that we can help organizations manage that cybersecurity in a dynamic environment, rather than leave them to the game of playing Whac-A-Mole. I've got a new threat. Let me add a new tool. Oh, I've got another new threat. Let me add another new tool. That's opposed to managing the total environment with total visibility.

So that managed cybersecurity approach is the approach that we're using, and the role of HP Software here is to provide a key technology that is the sort of binder, that is the backbone for much of that architecture that allows us to manage organically, as opposed to a piece at a time.

Customers, who try to manage a piece at a time, invariably get into trouble, because they can't do it. They're always playing catch up with the latest threat and they are always at least one or two steps behind that threat by trying to figure out what is the latest band-aid to stick over the wound.

Increased sophistication

Muller: The sophistication of the adversary has risen, especially if you're in that awkward position -- you're big enough to be interesting to an attacker, especially when it’s motivated by money, but you are not large enough to have access to up-to-date threat information from some of the intelligence agencies of your national government.

You're not large enough to be able to afford the sort of sophisticated resources who are able to dedicate the time taken to build and maintain honey pots to understand and hang out in all of the deep dark corners of the internet that nobody wants to go to.

Those sort of things are the types of behaviors you need to exhibit to stay ahead, or at least to not get behind, of those threat landscape. By working with an organization that has that sort of capacities by opting for managed service, you're able to tap into a skill set that’s deeper and broader and that often has an international or global outlook, which is particularly important. When the threat is distributed around the planet, your ability to respond to that needs to be distributed likewise.

Gardner: I'm hearing two things. One that this is a team sport. I'm also hearing that this is a function of better analytics -- of really knowing your systems, knowing your organization, monitoring in real time, and then being able to exploit that. Maybe we could drill down on those. This new end-state of a managed holistic security approach, let's talk about it being a team sport and a function of better analytics. Sam?

Visner: There's no question about it. It is a team sport. Fortunately, in the United States and in a few other countries, people recognize that it's a team sport. More and more, the government has said that the cybersecurity of the private sector is an issue of public interest, either to regulation, standards regulation, or policy.

More and more in the private sector, people have realized that they need threat information from the government, but there are also accruing threat information they need to share with the government and proliferate around their industries.

That has happened, and you can see coming out of the original Comprehensive National Cybersecurity Initiative of 2006-2007, all the way to the current recent executive order from the President of the United States, that this is a team sport. There is no question about that.

At the same time, a lot of companies are now developing tools that have APIs, programming interfaces that allow them to work together. Tools like ArcSight provide an environment that allows you to integrate a lot of different tools.

What's really changing is that global companies like CSC have become a global cybersecurity provider based on the idea that we will do this as a partner. We're not going to just sell a tool to a customer. We're going to be their partner to manage this environment.

More and more, they have the discussion underway about improved information sharing from the government to the private sector, based on intelligence information that might be provided to the private sector, and the private sector being provided with more protected means to share information relating to incidents, events, and investigations with the public sector.

Team sport

At the same time, enterprises themselves know that this has to be a team sport within an enterprise. It used to be that the email system was discreet, or your SAP system was discreet, inside of an enterprise. That might have been 10 years ago. But today, these things are part of a common enterprise and tomorrow they're going to be part of a common enterprise, where these things are provided as a service.

And the day after that, they'll be provided as a common enterprise with these things as a service on a common infrastructure that we call a cloud. And the day after that, that cloud will extend all the way down to the manufacturing systems on the shop floor, or the SCADA systems that control a railway, a pipeline, or the industrial control systems that control a medical device or an elevator, all the way out to 3D manufacturing.

The entire enterprise has to work together. The enterprise has to work together with its cybersecurity partner. The cybersecurity partner and the enterprise have to work together with the public sector and with regulatory and policy authorities. Governments increasingly have to work together to build a secured international ecosystem, because there are bad actors out there who don’t regard the theft of intellectual property as cyber crime.

Now fortunately, people get this increasingly and we're working together. That’s why we're finding partners who do the manage cybersecurity, and finding partners who can provide key pieces of technology. CSC and HP is an example of two companies working together in differentiated roles, but for a common and desirable outcome.

Three-step process

Weber: So let me think about how we chop this up, Dana. It’s a three-step process. The first is see, understand, and act -- at the risk of trivializing the complexity of approaching the problem. Seeing, as Sam has already pointed out, is to just try to get visibility of intent to attack, attacks in progress, or worse case, attacks that have taken place, attacks in progress, and finally, how we manage the exfiltration process.

Understanding is all about trying to unpack the difference between "bragging rights attacks," what I call high-intensity but low-grade attacks in terms of cyber threat. This is stuff that’s being done to deface the corporate website. Don’t get me wrong, it’s important, but in this scheme of things, it’s a distraction from some of the other activities that’s taking place. Also understanding is in terms of shifting or changing your compliance posture for some sort of further action.

Then, the last part is acting. It’s not good enough to simply to understand what’s going on, but it’s shutting down attacks in progress. It’s being able to take proactive steps to address breaches that may exist and particularly to address breaches in the underlying software.

We have always been worried about protecting the perimeter of our organization through the technologies, but continue to ignore one of the great issues out there, which is that software itself, in many cases, is inherently insecure. People are not scanning for, identifying, and addressing those issues in source code and binary vulnerability.

Gardner: What do you have to do in terms of thinking differently in order to start really positioning yourself to be proactive and aggressive with cybersecurity?

Visner: The first thing is that you’ve got to make an adequate assessment of the kind of organization you are. The role information and information technology plays in your organization, what we use the information for, and what information is most valuable. Or conversely, what would cause you the great difficulty, if you were to either lose control of that information or confidence in its integrity.

That has to be done not just for one piece of an enterprise, but for all pieces of the enterprise. By the way, there is a tremendous benefit, because you can re-visualize your enterprise. You can sort of business-process reengineer your enterprise, if you know on and what information you rely, what information is most valuable, what information, if was to be damaged, would cause you the most difficulty.

That’s the first thing I would do. The second thing is, since as-a-service is the way organizations buy things today and the way organizations provide things today, consider taking a look at cybersecurity as a service.

Rather than trying to manage it yourself, get a confident managed cyber-security services provider, which is our business at CSC, to do this work and be sure that they are equipped with the right tools and technologies, such as ArcSight Security Information and Event Management and other key technologies that we are sourcing from HP Software.

Third, if you're not willing to have somebody else manage it for you, get a managed cybersecurity services provider to build up your own internal cybersecurity management capabilities, so that you are your own managed cybersecurity services provider.

Next, be sure you understand, if you are part of critical infrastructure -- and there are some 23 critical infrastructure sectors -- what it is that you are required to do, what standards the government believes are pertinent to your business.

What information you should have shared with you, what information you are obligated to share, what regulations are relevant to your business, and be sure you understand that those are things that you want to do.

Strategic investment

Next, rather than trying to play Whac-A-Mole, having made these decisions, determine that you're going to make a strategic investment and not think of security as being added on and what's the least you need to do, but realize that cybersecurity is as organic to your value proposition as R&D is. It's as organic to your value proposition as electricity is. It's as organic to your value proposition as the good people who do the work. It's not once the least you need to do, but what are the things that contribute value.

Cybersecurity doesn’t just protect value, but in many cases, it can be a discriminator that enhances the value of your business, particularly if your business either relies on information, or information is your principal product, as it is today for many businesses in a knowledge economy. Those are things that you can do.

Lastly, you can get comfortable with the fact that this is a septic environment. There will always be risks. There will always be malware. Your job is not to eliminate it. Your job is to function confidently in the midst of it. You can, in fact, get to the point, both intellectually and emotionally, where that’s a possibility.

The fact that you can have an accident doesn’t deter us from driving. The fact that you can have a cold doesn’t deter us from going out to dinner or sending our kids to school.

What it does is make sure that we're vaccinated, that we drive well, that we are competent in our dealings with the rest of the society, and that we're prudent, but not frightened. Acting as if we are prudent, but not frightened, is a step we need to take.

Our brand name is CSC Global Cybersecurity. The term we use is Cyber Confidence. We're not going to make you threat proof, but we will make you competent and confident enough to be able to operate in the presence of these threats, because they are the new norms. Those are the things you can do.

Weber: In addition to what Sam talked about, I'm a huge fan of data classification. Knowing what to protect, gives you the opportunity to decide how much protection is necessary by whatever data classification that is.

Whether that’s a risk management framework like FISMA, or it’s a risk management framework like the IL Series Controls of the UK Government or similar in Australia, these are risk management frameworks. They are deterministic about the appropriate level of security. Is this public information, in which case all you have to do is worry about whether it’s damaged and how to recover if and when it is? Or is this critical? Is this injurious to life, limb, or the pursuit of profits? And if it is, then you need to apply all the protections that you can to it.

And last but not least, again, as I pointed out earlier, our ability to detect every intrusion is almost nil today. The state of the threat is so far advanced. Basically, they can get in when they want to, where they want to.

They can be in for a very long period of time without detection. I would encourage organizations to beef up their perimeter controls for egress filtering and enclaving, so that they have the ability to manage the data that is being actually traded out of their networks.

Cultural shift

Muller: It’s important to be alert, but not alarmed. Do not let security send you into a sense of panic and inaction. Don’t hire an organization to help you write security policy that then just sits on the shelf. A policy is not going to give you security. It’s certainly not going to stop any of bad guys from exfiltrating any of that information that you have.

I'll say a couple of things. First, it’s not like buying an alarm and locks for your organization. Before, physical security was kind of a process you went through, where you started, it had a start and middle and an end. This is an ongoing process of continually identifying incoming threats and activities from an adversary that is monetized and has a lot to gain from their success.

It’s an ongoing process. As a result, as we said earlier today, security is a team sport. Find a friend who does it really well and is prepared to invest on an ongoing manner to make sure that they're able to stay here.

I'd concur with Dean's point as well. Ultimately, it's about the exfiltrating of your data. Put in place processes that help you understand the information that is leaving your organization and take steps to mitigate that as quickly as possible. Those are my highest priorities.

I'd also add that if you're having trouble identifying some of the benefits for your organization, and even having trouble trying to get a threat assessment prioritized in your organization, have a look at the Cost of Cyber Crime Study that we've conducted across the Globe, United Kingdom, Germany, Australia, Japan and of course the US, was the third in the series, now we do it annually. You can get to hpenterprisesecurity.com and get a copy of that report and hopefully shift a few of the, maybe more intransigent people in your organization to action.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.

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As the volume and purpose of data and business intelligence (BI) has dramatically shifted, older notions and misconceptions — what amount to myths about data infrastructure — need to be updated and corrected, too.

So we're here to pose some better questions about data, and provide up-to-date answers for running data-driven businesses that can efficiently and repeatedly predict dynamic market trends and customer wants in real time.

As the volume and types of data that are brought to bear on business analytics advance, the means to manage and exploit that sea of data needs to be none too costly nor too complex for mid-sized companies to master. There are better ways than traditional data architectures.

To help identify what works best around modern big data management, BriefingsDirect interviewed Darin Bartik, executive director of products in the Information Management Group at Dell Software. The discussion was conducted by Dana Gardner, principal analyst at Interarbor Solutions.

Below are some excerpts.

Are people losing sight of the business value by getting lost in speeds and feeds and technical jargon around big data? Is there some sort of a disconnect between the providers and consumers of big data?

You hit the nail on the head with the first question. We are experiencing a disconnect between the technical side of big data and the business value of big data, and that's happening because we're digging too deeply into the technology.

With a term like big data, or any one of the trends that the information technology industry talks about so much, we tend to think about the technical side of it. But with analytics, with the whole conversation around big data — what we've been stressing with many of our customers — is that it starts with a business discussion. It starts with the questions that you're trying to answer about the business; not the technology, the tools, or the architecture of solving those problems. It has to start with the business discussion.

That's a pretty big flip. The traditional approach to BI and reporting has been one of technology frameworks, and a lot of things that were owned more by the IT group. This is part of the reason why a lot of the BI projects of the past struggled, because there was a disconnect between the business goals and the IT methods.

So you're right. There has been a disconnect, and that's what I've been trying to talk a lot about with customers — how to refocus on the business issues you need to think about, especially in the mid-market, where you maybe don't have as many resources at hand. It can be pretty confusing.

I've been a part of Dell Software since the acquisition of Quest Software. I was a part of that organization for close to 10 years. I've been in technology coming up on 20 years now. I spent a lot of time in enterprise resource planning (ERP), supply chain, and monitoring, performance management, and infrastructure management, especially on the Microsoft side of the world.

Most recently, as part of Quest, I was running the database management area — a business very well known for its products around Oracle, especially Toad, as well as our SQL Server management capabilities. We leveraged that expertise when we started to evolve into BI and analytics.

I started working with Hadoop back in 2008 to 2009, when it was still very foreign to most people. When Dell acquired Quest, I came in and had the opportunity to take over the Products Group in the ever-expanding world of information management. We're part of the Dell Software Group, which is a big piece of the strategy for Dell over all, and I'm excited to be here.

Without disparaging the vendors like us, or anyone else, the current confusion is part of the problem of any hype cycle. Many people jumped on the bandwagon of big data. Just like everyone was talking cloud. Everyone was talking virtualization, bring your own device (BYOD), and so forth.

Everyone jumps on these big trends. So it's very confusing for customers, because there are many different ways to come at the problem. This is why I keep bringing people back to staying focused on what the real opportunity is. It's a business opportunity, not a technical problem or a technical challenge that we start with.

Big-data challenge

Even the name "big data" stirs up myths right from the get-go, with "big" being a very relative term. Should we only be concerned about this when we have more data than we can manage? What is the relative position of big data and what are some of the myths around the size issue?

That's the perfect one to start with. The first word in the definition is actually part of the problem. "Big." What does big mean? Is there a certain threshold of petabytes that you have to get to? Or, if you're dealing with petabytes, is it not a problem until you get to exabytes?

It's not a size issue. When I think about big data, it's really a trend that has happened as a result of digitizing so much more of the information that we all have already and that we all produce. Machine data, sensor data, all the social media activities, and mobile devices are all contributing to the proliferation of data.

It's added a lot more data to our universe, but the real opportunity is to look for small elements of small datasets and look for combinations and patterns within the data that help answer those business questions that I was referencing earlier.

It's not necessarily a scale issue. What is a scale issue is when you get into some of the more complicated analytical processes and you need a certain data volume to make it statistically relevant. But what customers first want to think about is the business problems that they have. Then, they have to think about the datasets that they need in order to address those problems.

That may not be huge data volumes. You mentioned mid-market earlier. When we think about some organizations moving from gigabytes to terabytes, or doubling data volumes, that's a big data challenge in and of itself.

Analyzing big data won't necessarily contribute to your solving your business problems if you're not starting with the right questions. If you're just trying to store more data, that's not really the problem that we have at hand. That's something that we can all do quite well with current storage architectures and the evolving landscape of hardware that we have.

We all know that we have growing data, but the exact size, the exact threshold that we may cross, that's not the relevant issue.

I suppose this requires prioritization, which has to come from the business side of the house. As you point out, some statistically relevant data might be enough. If you can extrapolate and you have enough to do that, fine, but there might be other areas where you actually want to get every little bit of possible data or information relevant, because you don't know what you're looking for. They are the unknown unknowns. Perhaps there's some mythology about all data. It seems to me that what's important is the right data to accomplish what it is the business wants.

Absolutely. If your business challenge is an operational efficiency or a cost problem, where you have too much cost in the business and you're trying to pull out operational expense and not spend as much on capital expense, you can look at your operational data.

Maybe manufacturers are able to do that and analyze all of the sensor, machine, manufacturing line, and operational data. That's a very different type of data and a very different type of approach than looking at it in terms of sales and marketing.

If you're a retailer looking for a new set of customers or new markets to enter in terms of geographies, you're going to want to look at maybe census data and buying-behavior data of the different geographies. Maybe you want datasets that are outside your organization entirely. You may not have the data in your hands today. You may have to pull it in from outside resources. So there's a lot of variability and prioritization that all starts with that business issue that you're trying to address.

Perhaps it's better for the business to identify the important data, rather than the IT people saying it's too big or that big means we need to do something different. It seems like a business term rather than a tech term at this point.

I agree with you. The more we can focus on bringing business and IT to the table together to tackle this challenge, the better. And it does start with the executive management in the organization trying to think about things from that business perspective, rather than starting with the IT infrastructure management team.

Data scientists rare

What's our second myth?

I'd think about the idea of people and the skills needed to address this concept of big data. There is the term "data scientist" that has been thrown out all over the place lately. There's a lot of discussion about how you need a data scientist to tackle big data. But "big data" isn't necessarily the way you should think about what you're trying to accomplish. Instead, think about things in terms of being more data driven, and in terms of getting the data you need to address the business challenges that you have. That's not always going to require the skills of a data scientist.

I suspect that a lot of organizations would be happy to hear something like that, because data scientists are very rare today, and they're very expensive, because they are rare. Only certain geographies and certain industries have groomed the true data scientist. That's a unique blend between a data engineer and someone like an applied scientist, who can think quite differently than just a traditional BI developer or BI programmer.

Don't get stuck on thinking that, in order to take on a data-driven approach, you have to go out and hire a data scientist. There are other ways to tackle it. That's where you're going to combine people who can do the programming around your information, around the data management principles, and the people who can ask and answer the open-minded business questions. It doesn't all have to be encapsulated into that one magical person that's known now as the data scientist.

There are varying degrees of tackling this problem. You can get into very sophisticated algorithms and computations for which a data scientist may be the one to do that heavy lifting. But for many organizations and customers that we talk to everyday, it's something where they're taking on their first project and they are just starting to figure out how to address this opportunity.

For that, you can use a lot of the people that you have inside your organization, as well potentially consultants that can just help you break through some of the old barriers, such as thinking about intelligence, based strictly on a report and a structured dashboard format.

That's not the type of approach we want to take nowadays. So often a combination of programming and some open-minded thinking, done with a team-oriented approach, rather than that single keyhole person, is more than enough to accomplish your objectives.

Better decisions

It seems also that you're identifying confusion on the part of some to equate big data with BI and BI with big data. The data is a resource that the BI can use to offer certain values, but big data can be applied to doing a variety of other things. Perhaps we need to have a sub-debunking within this myth, and that is that big data and BI are different. How would you define them and separate them?

That's a common myth. If you think about BI in its traditional, generic sense, it's about gaining more intelligence about the business, which is still the primary benefit of the opportunity this trend of big data presents to us. Today, I think they're distinct, but over time, they will come together and become synonymous.

I equate it back to one of the more recent trends that came right before big data, cloud. In the beginning, most people thought cloud was the public-cloud concept. What's turned out to be true is that it's more of a private cloud or a hybrid cloud, where not everything moved from an on-premise traditional model, to a highly scalable, highly elastic public cloud. It's very much a mix.

They've kind of come together. So while cloud and traditional datacenters are the new infrastructure, it's all still infrastructure. The same is true for big data and BI, where BI, in the general sense of how can we gain intelligence and make smarter decisions about our business, will include the concept of big data.

So while we'll be using new technologies, which would include Hadoop, predictive analytics, and other things that have been driven so much faster by the trend of big data, we'll still be working back to that general purpose of making better decisions.

One of the reasons they're still different today is because we're still breaking some of the traditional mythology and beliefs around BI — that BI is all about standard reports and standard dashboards, driven by IT. But over time, as people think about business questions first, instead of thinking about standard reports and standard dashboards first, you'll see that convergence.

We probably need to start thinking about BI in terms of a wider audience, because all the studies I've seen don't show all that much confidence and satisfaction in the way BI delivers the analytics or the insights that people are looking for. So I suppose it's a work in progress when it comes to BI as well.

Two points on that. There has been a lot of disappointment around BI projects in the past. They've taken too long, for one. They've never really been finished, which of course, is a problem. And for many of the business users who depend on the output of BI — their reports, their dashboard, their access to data — it hasn't answered the questions in the way that they may want it to.

One of the things in front of us today is a way of thinking about it differently. Not only is there so much data, and so much opportunity now to look at that data in different ways, but there is also a requirement to look at it faster and to make decisions faster. So it really does break the old way of thinking.

Slowness is unacceptable. Standard reports don't come close to addressing the opportunity in front us, which is to ask a business question and answer it with the new way of thinking supported by pulling together different datasets. That's fundamentally different from the way we used to do it.

People are trying to make decisions about moving the business forward, and they're being forced to do it faster. Historical reporting just doesn't cut it. It's not enough. They need something that's much closer to real time. It's more important to think about open-ended questions, rather than just say, "What revenue did I make last month, and what products made that up?" There are new opportunities to go beyond that.

When it comes to these technology issues, do you also find, Darin, that there is a lack of creativity as to where the data and information resides or exists and thinking not so much about being able to run it, but rather acquire it? Is there a dissonance between the data I have and the data I need. How are people addressing that?

There is and there isn't. When we look at the data that we have, that's oftentimes a great way to start a project like this, because you can get going faster and it's data that you understand. But if you think that you have to get data from outside the organization, or you have to get new datasets in order to answer the question that's in front of us, then, again, you're going in with a predisposition to a myth.

You can start with data that you already have. You just may not have been looking at the data that you already have in the way that's required to answer the question in front of you. Or you may not have been looking at it all. You may have just been storing it, but not doing anything with it.

Storing data doesn't help you answer questions. Analyzing it does. It seems kind of simple, but so many people think that big data is a storage problem. I would argue it's not about the storage. It's like backup and recovery. Backing up data is not that important, until you need to recover it. Recovery is really the game changing thing.

Data-driven organization

It's interesting that with these myths, people have tended, over the years, without having the resources at hand, to shoot from the hip and second-guess. People who are good at that and businesses that have been successful have depended on some luck and intuition. In order to take advantage of big data, which should lead you to not having to make educated guesses, but to have really clear evidence, you can apply the same principle. It's more how you get big data in place, than how you would use the fruits of big data.

It seems like a cultural shift we have to make. Let's not jump to conclusions. Let's get the right information and find out where the data takes us.

You've hit on one of the biggest things that's in front of us over the next three to five years — the cultural shift that the big data concept introduces.

We looked at traditional BI as more of an IT function, where we were reporting back to the business. The business told us exactly what they wanted, and we tried to give that to them from the IT side of the fence.

But being successful today is less about intuition and more about being a data-driven organization, and, for that to happen, I can't stress this one enough, you need executives who are ready to make decisions based on data, even if the data may be counter intuitive to what their gut says and what their 25 years of experience have told them.

They're in a position of being an executive primarily because they have a lot of experience and have had a lot of success. But many of our markets are changing so frequently and so fast, because of new customer patterns and behaviors, because of new ways of customers interacting with us via different devices. Just think of the different ways that the markets are changing. So much of that historical precedence no longer really matters. You have to look at the data that's in front of us.

Because things are moving so much faster now, new markets are being penetrated and new regions are open to us. We're so much more of a global economy. Things move so much faster than they used to. If you're depending on gut feeling, you'll be wrong more often than you'll be right. You do have to depend on as much of a data-driven decision as you can. The only way to do that is to rethink the way you're using data.

Historical reports that tell you what happened 30 days ago don't help you make a decision about what's coming out next month, given that your competition just introduced a new product today. It's just a different mindset. So that cultural shift of being data-driven and going out and using data to answer questions, rather than using data to support your gut feeling, is a very big shift that many organizations are going to have to adapt to.

Executives who get that and drive it down into the organization, those are the executives and the teams that will succeed with big data initiatives, as opposed to those that have to do it from the bottom up.

What business issue?

Listening to you Darin, I can tell one thing that isn't a product of hype is just how important this all is. Getting big data right, doing that cultural shift, recognizing trends based on the evidence and in real-time as much as possible is really fundamental to how well many businesses will succeed or not.

So it's not hype to say that big data is going to be a part of your future and it's important. Let's move towards how you would start to implement or change or rethink things, so that you can not fall prey to these myths, but actually take advantage of the technologies, the reduction in costs for many of the infrastructures, and perhaps extend and exploit BI and big data problems.

It's fair to say that big data is not just a trend; it's a reality. And it's an opportunity for most organizations that want to take advantage of it. It will be a part of your future. It's either going to be part of your future, or it's going to be a part of your competition's future, and you're going to be struggling as a result of not taking advantage of it.

The first step that I would recommend — I've said it a few times already, but I don't think it can't be said too often — is pick a project that's going to address a business issue that you've been unable to address in the past.

What are the questions that you need to ask and answer about your business that will really move you forward?" Not just, "What data do we want to look at?" That's not the question.

The question is what business issue do we have in front of us that will take us forward the fastest? Is it reducing costs? Is it penetrating a new regional market? Is it penetrating a new vertical industry, or evolving into a new customer set?

These are the kind of questions we need to ask and the dialogue that we need to have. Then let's take the next step, which is getting data and thinking about the team to analyze it and the technologies to deploy. But that's the first step – deciding what we want to do as a business.

That sets you up for that cultural shift as well. If you start at the technology layer, if you start at the level of let's deploy Hadoop or some type of new technology that may be relevant to the equation, you're starting backwards. Many people do it, because it's easier to do that than it is to start an executive conversation and to start down the path of changing some cultural behavior. But it doesn't necessarily set you up for success.

It sounds as if you know you're going on a road trip and you get yourself a Ferrari, but you haven't really decided where you're going to go yet, so you didn't know that you actually needed a Ferrari.

Yeah. And it's not easy to get a tent inside a Ferrari. So you have to decide where you're going first. It's a very good analogy.

Technical approaches

What are some of the other ways when it comes to the landscape out there? There are vendors who claim to have it all, everything you need for this sort of thing. It strikes me that this is more of an early period and that you would want to look at a best-of-breed approach or an ecosystem approach.

So are there any words of wisdom in terms of how to think about the assets, tools, approaches, platforms, what have you, or not to limit yourself in a certain way?

There are countless vendors that are talking about big data and offering different technology approaches today. Based on the type of questions that you're trying to answer, whether it's more of an operational issue, a sales market issue, HR, or something else, there are going to be different directions that you can go in, in terms of the approaches and the technologies used.

I encourage the executives, both on the line-of-business side as well as the IT side, to go to some of the events that are the "un-conferences", where we talk about the big-data approach and the technologies. Go to the other events in your industry where they're talking about this and learn what your peers are doing. Learn from some of the mistakes that they've been making or some of the successes that they've been having.

There's a lot of success happening around this trend. Some people certainly are falling into the pitfalls, but get smart by going to your peers and going to your industry influencer groups and learning more about how to approach this.

There are technical approaches that you can take. There are different ways of storing your data. There are different ways of computing and processing your data. Then, of course, there are different analytical approaches that get more to the open-ended investigation of data. There are many tools and many products out there that can help you do that.

Dell has certainly gone down this road and is investing quite heavily in this area, with both structured and unstructured data analysis, as well as the storage of that data. We're happy to engage in those conversations as well, but there are a lot of resources out there that really help companies understand and figure out how to attack this problem.

Finding indicators

In the past, with many of the technology shifts, we've seen a tension and a need for decision around best-of-breed versus black box, or open versus entirely turnkey, and I'm sure that's going to continue for some time.

But one of the easier ways or best ways to understand how to approach some of those issues is through some examples. Do we have any use cases or examples that you're aware of, of actual organizations that have had some of these problems? What have they put in place, and what has worked for them?

I'll give you a couple of examples from two very different types of organizations, neither of which are huge organizations. The first one is a retail organization, Guess Jeans. The business issue they were tackling was, "How do we get more sales in our retail stores? How do we get each individual that's coming into our store to purchase more?"

We sat down and started thinking about the problem. We asked what data would we need to understand what's happening? We needed data that helps us understand the buyer's behavior once they come into the store. We don't need data about what they are doing outside the store necessarily, so let's look specifically at behaviors that take place once they get into the store.

We helped them capture and analyze video monitoring information. Basically it followed each of the people in the store and geospatial locations inside the store, based on their behavior. We tracked that data and then we compared against questions like did they buy, what did they buy, and how much did they buy. We were able to help them determine that if you get the customer into a dressing room, you're going to be about 50 percent more likely to close transactions with them.

So rather than trying to give incentives to come into the store or give discounts once they get into the store, they moved towards helping the store clerks, the people who ran the store and interacted with the customers, focus on getting those customers into a dressing room. That itself is a very different answer than what they might have thought of at first. It seems easy after you think about it, but it really did make a significant business impact for them in rather short order.

Now, they're also thinking about other business challenges that they have and other ways of analyzing data and other datasets, based on different business challenges, but that's one example.

Another example is on the higher education side. In universities, one of the biggest challenges is having students drop out or reduce their class load. The fewer classes they take, or if they dropout entirely, it obviously goes right to the top and bottom line of the organization, because it reduces tuition, as well as the other extraneous expenses that students incur at the university.

The University of Kentucky went on an effort to reduce students dropping out of classes or dropping entirely out of school. They looked at a series of datasets, such as demographic data, class data, the grades that they were receiving, what their attendance rates were, and so forth. They analyzed many different data points to determine the indicators of a future drop out.

Now, just raising the student retention rate by one percent would in turn mean about $1 million of top-line revenue to the university. So this was pretty important. And in the end, they were able to narrow it down to a couple of variables that strongly indicated which students were at risk, such that they could then proactively intervene with those students to help them succeed.

The key is that they started with a very specific problem. They started it from the university's core mission: to make sure that the students stayed in school and got the best education, and that's what they are trying to do with their initiative. It turned out well for them.

These were very different organizations or business types, in two very different verticals, and again, neither are huge organizations that have seas of data. But what they did are much more manageable and much more tangible examples many of us can kind of apply to our own businesses.

Using new technologies

Those really demonstrate how asking the right questions is so important.

Darin, we're almost out of time, but I did want to see if we could develop a little bit more insight into the Dell Software road map. Are there some directions that you can discuss that would indicate how organizations can better approach these problems and develop some of these innovative insights in business?

A couple of things. We've been in the business of data management, database management, and managing the infrastructure around data for well over a decade. Dell has assembled a group of companies, as well as a lot of organic development, based on their expertise in the data center for years. What we have today is a set of capabilities that help customers take more of a data-type agnostic view and a vendor agnostic view to the way they're approaching data and managing data.

You may have 15 tools around BI. You may have tools to look at your Oracle data, maybe new sets of unstructured data, and so forth. And you have different infrastructure environments set up to house that data and manage it. But the problem is that it's not helping you bring the data together and cross boundaries across data types and vendor toolset types, and that's the challenge that we're trying to help address.

We've introduced tools to help bring data together from any database, regardless of where it may be sitting, whether it's a data warehouse, a traditional database, a new type of database such as Hadoop, or some other type of unstructured data store.

We want to bring that data together and then analyze it. Whether you're looking at more of a traditional structured-data approach and you're exploring data and visualizing datasets that many people may be working with, or doing some of the more advanced things around unstructured data and looking for patterns, we're focused on giving you the ability to pull data from anywhere.

We're investing very heavily, Dana, into the Hadoop framework to help customers do a couple of key things. One is helping the people that own data today, the database administrators, data analysts, the people that are the stewards of data inside of IT, advance their skills to start using some of these new technologies, including Hadoop.

It's been something that we have done for a very long time, making your C players B players, and your B players A players. We want to continue to do that, leverage their existing experience with structured data, and move them over into the unstructured data world as well.

The other thing is that we're helping customers manage data in a much more pragmatic way. So if they are starting to use data that is in the cloud, via Salesforce.com or Taleo, but they also have data on-prem sitting in traditional data stores, how do we integrate that data without completely changing their infrastructure requirements? With capabilities that Dell Software has today, we can help integrate data no matter where it sits and then analyze it based on that business problem.

We help customers approach it more from a pragmatic view, where you're taking a stepwise approach. We don't expect customers to pull out their entire BI and data-management infrastructure and rewrite it from scratch on day one. That's not practical. It's not something we would recommend. Take a stepwise approach. Maybe change the way you're integrating data. Change the way you're storing data. Change, in some perspective, the way you're analyzing data between IT and the business, and have those teams collaborate.

But you don't have to do it all at one time. Take that stepwise approach. Tackle it from the business problems that you're trying to address, not just the new technologies we have in front of us.

There's much more to come from Dell in the information management space. It will be very interesting for us and for our customers to tackle this problem together. We're excited to make it happen.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: Dell Software.

Disclosure: Dell is a sponsor of BriefingsDirect podcasts.

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Known as the new model through which big data, cloud, and mobile and social — in combination — allow for advanced intelligence and automation in business, Platform 3.0 has so far lacked standards or even clear definitions.

The Open Group and its community are poised to change that, and we're here now to learn more how to leverage Platform 3.0 as more than a IT shift — and as a business game changer. It will be a big topic at next week's conference.

The panel: Dave Lounsbury, chief technical officer at The Open Group; Chris Harding, director of Interoperability at The Open Group; and Mark Skilton, global director in the Strategy Office at Capgemini. The discussion was moderated by Dana Gardner, principal analyst at Interarbor Solutions.

This special BriefingsDirect thought leadership interview comes in conjunction with The Open Group Conference, which is focused on enterprise transformation in the finance, government, and healthcare sectors. Registration to the conference remains open. Follow the conference on Twitter at #ogPHL.

Below are some excerpts.

Fundamental changes

A lot of people are still wrapping their minds around this notion of Platform 3.0, something that is a whole greater than the sum of the parts. Why is this more than an IT conversation or a shift in how things are delivered? Why are the business implications momentous?

Lounsbury: Well, Dana, there are lot of IT changes or technical changes going on that are bringing together a lot of factors. They're turning into this sort of super-saturated solution of ideas and possibilities and this emerging idea that this represents a new platform. I think it's a pretty fundamental change.

If you look at history, not just the history of IT, but all of human history, you see that step changes in societies and organizations are frequently driven by communication or connectedness. Think about the evolution of speech or the invention of the alphabet or movable-type printing. These technical innovations that we're seeing are bringing together these vast sources of data about the world around us and doing it in real time.

Further, we're starting to see a lot of rapid evolution in how you turn data into information and presenting the information in a way such that people can make decisions on it. Given all that we're starting to realize, we're on the cusp of another step of connectedness and awareness.

This really is going to drive some fundamental changes in the way we organize ourselves. Part of what The Open Group is doing, trying to bring Platform 3.0 together, is to try to get ahead of this and make sure that we understand not just what technical standards are needed, but how businesses will need to adapt and evolve what business processes they need to put in place in order to take maximum advantage of this to see change in the way that we look at the information.

Harding: Enterprises have to keep up with the way that things are moving in order to keep their positions in their industries. Enterprises can't afford to be working with yesterday's technology. It's a case of being able to understand the information that they're presented, and make the best decisions.

We've always talked about computers being about input, process, and output. Years ago, the input might have been through a teletype, the processing on a computer in the back office, and the output on print-out paper.

Now, we're talking about the input being through a range of sensors and social media, the processing is done on the cloud, and the output goes to your mobile device, so you have it wherever you are when you need it. Enterprises that stick in the past are probably going to suffer.

Massive growth

Mark Skilton, the ability to manage data at greater speed and scale, the whole three "V"s — velocity, volume, and value — on its own could perhaps be a game-changing shift in the market. The drive of mobile devices into lives of both consumers and workers is also a very big deal.

Of course, cloud has been an ongoing evolution of emphasis towards agility and efficiency in how workloads are supported. But is there something about the combination of how these are coming together at this particular time that, in your opinion, substantiates The Open Group's emphasis on this as a literal platform shift?

Skilton: It is exactly that in terms of the workloads. The world we're now into is the multi-workload environment, where you have mobile workloads, storage and compute workloads, and social networking workloads. There are many different types of data and traffic today in different cloud platforms and devices.

It has to do with not just one solution, not one subscription model — because we're now into this subscription-model era ... the subscription economy, as one group tends to describe it. Now, we're looking for not only just providing the security, the infrastructure, to deliver this kind of capability to a mobile device, as Chris was saying. The question is, how can you do this horizontally across other platforms? How can you integrate these things? This is something that is critical to the new order.

So Platform 3.0 is addressing this point by bringing this together. Just look at the numbers. Look at the scale that we're dealing with — 1.7 billion mobile devices sold in 2012, and 6.8 billion subscriptions estimated, according to the International Telecommunications Union (ITU) equivalent to 96 percent of the world population.

We had massive growth in scale of mobile data traffic and internet data expansion. Mobile data is increasing 18 percent fold from 2011 to 2016 reaching 130 exabytes annually. We passed 1 zettabyte of global online data storage back in 2010 and IP data traffic predicted to pass 1.3 zettabytes by 2016, with internet video accounting for 61 percent of total internet data, according to Cisco studies.

These studies also predict datacenter traffic combining network and internet based storage will reach 6.6 zettabytes annually, and nearly two thirds of this will be cloud based by 2016. This is only going to grow as social networking is reaching nearly one in four people around the world with 1.7 billion using at least one form of social networking in 2013, rising to one in three people with 2.55 billion global audience by 2017 as another extraordinary figure from an eMarketing.com study.

It is not surprising that many industry analysts are seeing growth in technologies of mobility, social computing, big data and cloud convergence at 30 to 40 percent and the shift to B2C commerce passing $1 trillion in 2012 is just the start of a wider digital transformation.

These numbers speak volumes in terms of the integration, interoperability, and connection of the new types of business and social realities that we have today.

Shift in constituency

Why should IT be thinking about this as a fundamental shift, rather than a modest change?

Lounsbury: A lot depends on how you define your IT organization. It's useful to separate the plumbing from the water. If we think of the water as the information that's flowing, it's how we make sure that the water is pure and getting to the places where you need to have the taps, where you need to have the water, etc.

But the plumbing also has to be up to the job. It needs to have the capacity. It needs to have new tools to filter out the impurities from the water. There's no point giving someone data if it's not been properly managed or if there's incorrect information.

What's going to happen in IT is not only do we have to focus on the mechanics of the plumbing, where we see things like the big database that we've seen in the open-source role and things like that nature, but there's the analytics and the data stewardship aspects of it.

We need to bring in mechanisms, so the data is valid and kept up to date. We need to indicate its freshness to the decision makers. Furthermore, IT is going to be called upon, whether as part of the enterprise IP or where end users will drive the selection of what they're going to do with analytic tools and recommendation tools to take the data and turn it into information. One of the things you can't do with business decision makers is overwhelm them with big rafts of data and expect them to figure it out.

You really need to present the information in a way that they can use to quickly make business decisions. That is an addition to the role of IT that may not have been there traditionally — how you think about the data and the role of what, in the beginning, was called data scientist and things of that nature.

Skilton: I'd just like to add to Dave's excellent points about the shape of data has changed, but also about why should IT get involved. We're seeing that there's a shift in the constituency of who is using this data.

We have the chief marketing officer and the chief procurement officer and other key line of business managers taking more direct control over the uses of information technology that enable their channels and interactions through mobile, social, and data analytics. We've got processes that were previously managed just by IT and are now being consumed by significant stakeholders and investors in the organization.

We have to recognize in IT that we are the masters of our own destiny. The information needs to be sorted into new types of mobile devices, new types of data intelligence, and ways of delivering this kind of service.

I read recently in MIT Sloan Management Review an article that asked what is the role of the CIO. There is still the critical role of managing the security, compliance, and performance of these systems. But there's also a socialization of IT, and this is where the positioning architectures which are cross-platform is key to delivering real value to the business users in the IT community.

How do we prevent this from going off the rails?

Harding: This a very important point. And to add to the difficulties, it's not only that a whole set of different people are getting involved with different kinds of information, but there's also a step change in the speed with which all this is delivered. It's no longer the case that you can say, "Oh well, we need some kind of information system to manage this information. We'll procure it and get a program written" that a year later that would be in place in delivering reports to it.

Now, people are looking to make sense of this information on the fly if possible. It's really a case of having the platforms be the standard technology platform and also the systems for using it, the business processes, understood and in place.

Then, you can do all these things quickly and build on learning from what people have done in the past, and not go out into all sorts of new experimental things that might not lead anywhere. It's a case of building up the standard platform in the industry best practice. This is where The Open Group can really help things along by being a recipient and a reflector of best practice and standard.

Skilton: Capgemini has been doing work in this area. I break it down into four levels of scalability. It's the platform scalability of understanding what you can do with your current legacy systems in introducing cloud computing or big data, and the infrastructure that gives you this, what we call multiplexing of resources. We're very much seeing this idea of introducing scalable platform resource management, and you see that a lot with the heritage of virtualization.

Going into networking and the network scalability, a lot of the customers have who inherited their old telecommunications networks are looking to introduce new MPLS-type scalable networks. The reason for this is that it's all about connectivity in the field. I meet a number of clients who are saying, "We've got this cloud service", or "This service is in a certain area of my country. If I move to another parts of the country or I'm traveling, I can't get connectivity". That's the big issue of scaling.

Another one is application programming interfaces (APIs). What we're seeing now is an explosion of integration and application services using API connectivity, and these are creating huge opportunities of what Chris Anderson of Wired used to call the "long tail effect". It is now a reality in terms of building that kind of social connectivity and data exchange that Dave was talking about.

Finally, there are the marketplaces. Companies need to think about what online marketplaces they need for digital branding, social branding, social networks, and awareness of your customers, suppliers, and employees. Customers can see that these four levels are where they need to start thinking about for IT strategy, and Platform 3.0 is right on this target of trying to work out what are the strategies of each of these new levels of scalability.

First step

We're coming up on The Open Group Conference in Philadelphia very shortly. What should we expect from that? What is The Open Group doing vis--vis Platform 3, and how can organizations benefit from seeing a more methodological or standardized approach to some way of rationalizing all of this complexity? [Registration to the conference remains open. Follow the conference on Twitter at #ogPHL.]

Lounsbury: We're still in the formational stages of "third platform" or Platform 3.0 for The Open Group as an industry. To some extent, we're starting pretty much at the ground floor with that in the Platform 3.0 forum. We're leveraging a lot of the components that have been done previously by the work of the members of The Open Group in cloud, services-oriented architecture (SOA), and some of the work on the Internet of Things.

Our first step is to bring those things together to make sure that we've got a foundation to depart from. The next thing is that through our Platform 3.0 Forum and the Steering Committee, we can ask people to talk about what their scenarios are for adoption of Platform 3.0?

That can range from things like the technological aspects of it and what standards are needed, but also to take a clue from our previous cloud working group. What are the best business practices in order to understand and then adopt some of these Platform 3.0 concepts to get your business using them?

What we're really working toward in Philadelphia is to set up an exchange of ideas among the people who can, from the buy side, bring in their use cases from the supply side, bring in their ideas about what the technology possibilities are, and bring those together and start to shape a set of tracks where we can create business and technical artifacts that will help businesses adopt the Platform 3.0 concept.

Harding: We certainly also need to understand the business environment within which Platform 3.0 will be used. We've heard already about new players, new roles of various kinds that are appearing, and the fact that the technology is there and the business is adapting to this to use technology in new ways.

For example, we've heard about the data scientist. The data scientist is a new kind of role, a new kind of person, that is playing a particular part in all this within enterprises. We're also hearing about marketplaces for services, new ways in which services are being made available and combined.

We really need to understand the actors in this new kind of business scenario. What are the pain points that people are having? What are the problems that need to be resolved in order to understand what kind of shape the new platform will have? That is one of the key things that the Platform 3.0 Forum members will be getting their teeth into.

Looking to the future, when we think about the ability of the data to be so powerful when processed properly, when recommendations can be delivered to the right place at the right time, but we also recognize that there are limits to a manual or even human level approach to that, scientist by scientist, analysis by analysis.

When we think about the implications of automation, it seems like there were already some early examples of where bringing cloud, data, social, mobile, interactions, granularity of interactions together, that we've begun to see that how a recommendation engine could be brought to bear. I'm thinking about the Siri capability at Apple and even some of the examples of the Watson Technology at IBM.

So to our panel, are there unknown unknowns about where this will lead in terms of having extraordinary intelligence, a super computer or datacenter of super computers, brought to bear almost any problem instantly and then the result delivered directly to a center, a smartphone, any number of end points?

It seems that the potential here is mind boggling. Mark Skilton, any thoughts?

Skilton: What we're talking about is the next generation of the internet. The advent of IPv6 and the explosion in multimedia services will start to drive the next generation of the internet.

I think that in the future, we'll be talking about a multiplicity of information that is not just about services at your location or your personal lifestyle or your working preferences. We'll see a convergence of information and services across multiple devices and new types of "co-presence services" that interact with your needs and social networks to provide predictive augmented information value.

When you start to get much more information about the context of where you are, the insight into what's happening, and the predictive nature of these, it becomes something that becomes much more embedded into everyday life and in real time in context of what you are doing.

I expect to see much more intelligent applications coming forward on mobile devices in the next five to 10 years driven by this interconnected explosion of real time processing data, traffic, devices, and social networking we describe in the scope of platform 3.0. This will add augmented intelligence, and is something that's really exciting and a complete game changer. I would call it the next killer app.

First-mover benefits

There's this notion of intelligence brought to bear rapidly in context, at a manageable cost. This seems to me a big change for businesses. We could, of course, go into the social implications as well, but just for businesses, that alone to me would be an incentive to get thinking and acting on this. So any thoughts about where businesses that do this well would be able to have significant advantage and first mover benefits?

Harding: Businesses always are taking stock. They understand their environments. They understand how the world that they live in is changing and they understand what part they play in it. It will be down to individual businesses to look at this new technical possibility and say, "So now this is where we could make a change to our business." It's the vision moment where you see a combination of technical possibility and business advantage that will work for your organization.

It's going to be different for every business, and, I'm very happy to say this, it's something that computers aren't going to be able to do for a very long time yet. It's going to really be down to business people to do this as they have been doing for centuries and millennia, to understand how they can take advantage of these things.

So it's a very exciting time, and we'll see businesses understanding and developing their individual business visions as the starting point for a cycle of business transformation, which is what we'll be very much talking about in Philadelphia. So yes, there will be businesses that gain advantage, but I wouldn't point to any particular business, or any particular sector and say, "It's going to be them" or "It's going to be them."

Dave Lounsbury, a last word to you. In terms of some of the future implications and vision, where could this lead in the not too distant future?

Lounsbury: I'd disagree a bit with my colleagues on this, and this could probably be a podcast on its own, Dana. You mentioned Siri, and I believe IBM just announced the commercial version of its Watson recommendation and analysis engine for use in some customer-facing applications.

I definitely see these as the thin end of the wedge on filling that gap between the growth of data and the analysis of data. I can imagine in not in the next couple of years, but in the next couple of technology cycles, that we'll see the concept of recommendations and analysis as a service, to bring it full circle to cloud. And keep in mind that all of case law is data and all of the medical textbooks ever written are data. Pick your industry, and there is a huge amount of knowledge base that humans must currently keep on top of.

This approach and these advances in the recommendation engines driven by the availability of big data are going to produce profound changes in the way knowledge workers produce their job. That's something that businesses, including their IT functions, absolutely need to stay in front of to remain competitive in the next decade or so.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: The Open Group.

Disclosure: The Open Group is a sponsor of this and other BriefingsDirect podcasts.

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The goal: To help enterprises better deliver risk assessment and, one hopes, defenses, in the current climate of challenging cybersecurity and against other looming business threats. By predicting risks and potential losses accurately, IT organizations can gain agility via thoughtful priorities and thereby repeatedly reduce the odds of losses.

The panel consisted of Jack Freund, information security risk assessment manager at TIAA-CREF; Jack Jones, principal at CXOWARE and an inventor of the FAIR risk analysis framework, and Jim Hietala, vice president, Security, at The Open Group. The discussion was moderated by Dana Gardner, principal analyst at Interarbor Solutions.

This special BriefingsDirect thought leadership interview comes in conjunction with The Open Group Conference to be held held beginning July 15 in Philadelphia. The conference is focused on enterprise transformation in the finance, government, and healthcare sectors. Registration to the conference remains open. Follow the conference on Twitter at #ogPHL.

Below are some excerpts.

Freund: We're entering a phase where there is going to be increased regulatory oversight over very nearly everything. When that happens, all eyes are going to turn to IT and IT risk management functions to answer the question of whether we're handling the right things.

Without quantifying risk, you're going to have a very hard time saying to your board of directors that you're handling the right things the way a reasonable company should.

As those regulators start to see and compare among other companies, they'll find that these companies over "here" are doing risk quantification, and you're not. You're putting yourself at a competitive disadvantage by not being able to provide those same sorts of services.

So you're saying that the market itself hasn't been enough to drive this, and that regulation is required?

Freund: It's probably a stronger driver than market forces at this point. But especially in information security, if you're not experiencing primary losses as a result of these sorts of things, then you have to look to economic externalities, which are largely put in play by regulatory forces here in the United States.

Jones: To support Jack's statement that regulators are becoming more interested in this, too, just in the last 60 days, I've spent time training people at two regulatory agencies on FAIR. So they're becoming more aware of these quantitative methods, and their level of interest is rising.

Hietala: Certainly, in the cybersecurity world in the past six or nine months, we've seen more and more discussion of the threats that are out there. We've got nation-state types of threats that are very concerning, very serious, and that organizations have to consider.

With what's happening, you've seen that the US Administration and President Obama direct the National Institute of Standards and Technology (NIST) to develop a new cybersecurity framework. Certainly, on the government side of things, there is an increased focus on what can we do to increase the level of cybersecurity throughout the country in critical infrastructure. So my short answer would be, yes, there is more interest in coming up with ways to accurately measure and assess risk so that we can then deal with it.

Risk quantification

Please give us the high-level overview of FAIR, also know as Factor Analysis of Information Risk.

Jones: First and foremost, FAIR is a model for what risk is and how it works. It's a decomposition of the factors that make up risk. If you can measure or estimate the value of those factors, you can derive risk quantitatively in dollars and cents.

You see a lot of "risk quantification" based on ordinal scales — 1, 2, 3, 4, 5 scales, that sort of thing. But that's actually not quantitative. If you dig into it, there's no way you could defend a mathematical analysis based on those ordinal approaches. So, FAIR is this model for risk that enables true quantitative analysis in a very pragmatic way.

For example, one organization I worked with recently had certain deficiencies from the security perspective that they were aware of, but that were going to be very problematic to fix. They had identified technology and process solutions that they thought would take them a long way toward a better risk position. But it was a very expensive proposition, and they didn't have money in the IT or information security budget for it.

So, we did a current-state analysis using FAIR, how much loss exposure they had on annualized basis. Then, we said, "If you plug this solution into place, given how it affects the frequency and magnitude of loss that you'd expect to experience, here's what your new annualized loss exposure would be." It turned out to be a multimillion-dollar reduction in annualized loss exposure for a few hundred thousand dollars cost.

When they took that business case to management, it was a no-brainer, and management signed the check in a hurry. So they ended up being in a much better position.

If they had gone to executive management saying, "Well, we've got a high risk and if we buy this set of stuff, we'll have low or medium risk", it would've been a much less convincing and understandable business case for the executives. There's reason to expect that it would have been challenging to get that sort of funding given how tight their corporate budgets were and that sort of thing. It can be incredibly effective in those business cases.

There's lots going on in the IT world. Perhaps IT's very nature, the roles and responsibilities, are shifting. Is doing such risk assessment and management becoming part and parcel of core competency of IT, and is that a fairly big departure from the past?

Hietala: It's becoming kind of a standard practice within IT. When you look at outsourcing your IT operations to a cloud-service provider, you have to consider the security risks in that environment. What do they look like and how do we measure them?

It's the same thing for things like mobile computing. You really have to look at the risks of folks carrying tablets and smartphones, and understand the risks associated with those same things for big data. For any of these large-scale changes to our IT infrastructure, you've got to understand what it means from a security and risk standpoint.

Freund: We have to find a way to better embed risk assessment [into businesses], which is really just a way to inform decision making and how we adapt all of these technological changes to increase market position and to make ourselves more competitive. That's important.

Whether that's an embedded function within IT, or it's an overarching function that exists across multiple business units, there are different models that work for different-sized companies and companies of different cultural types. But it has to be there. It's absolutely critical.

Board-level interest

Jack Jones, how do you come down this role of IT shifting in the risk assessment issues, something that's their responsibility. Are they embracing that or maybe wishing it away?

Jones: Some of them would certainly like to wish it away. I don't think IT's role in this idea for risk assessment and such has really changed. What is changing is the level of visibility and interest within the organization, the business side of the organization, in the IT risk position.

Previously, they were more or less tucked away in a dark corner. People just threw money at it and hoped bad things didn't happen. Now, you're getting a lot more board-level interest in IT risk, and with that visibility comes a responsibility, but also a certain amount of danger. If they're doing it really badly, they're incredibly immature in how they approach risk.

They're going to look pretty foolish in front of the board. Unfortunately, I've seen that play out. It's never pretty and it's never good news for the IT folks. They're realizing that they need to come up to speed a little bit from a risk perspective, so that they won't look the fools when they're in front of these executives.

They're used to seeing quantitative measures of opportunities and operational issues of risk of various natures. If IT comes to the table with a red, yellow, green chart, the board is left to wonder, first how to interpret that, and second, whether these guys really get it. I'm not sure the role has changed, but I think the responsibilities and level of expectations are changing.

Is there a synergistic relationship between a lot of the big-data and analytics investments that are being made for a variety of reasons, and also this ability to bring more science and discipline to risk analysis?

Are we seeing the dots being connected in these large organizations; that they can take more of what they garner from big data and business intelligence (BI) and apply that to these risk assessment activities? Is that happening yet?

Jones: It's just beginning to. It's very embryonic, and there are only probably a couple of organizations out there that I would argue are doing that with any sort of effectiveness. Imagine that — they're both using FAIR.

But when you think about BI or any sort of analytics, there are really two halves to the equation. One is data and the other is models. You can have all the data in the world, but if your models stink, then you can't be effective. And, of course, vice versa. If you've got great model and zero data, then you've got challenges there as well.

Being able to combine the two — good data and effective models — puts you in much better place. As an industry, we aren't there yet. We've got some really interesting things going on, and so there's a lot of potential there, but people have to leverage that data effectively and make sure they're using a model that makes sense.

There are some models out there that frankly are just so badly broken that all the data in the world isn't going to help you. The models will grossly misinform you. So people have to be careful, because data is great, but if you're applying it to a bad model, then you're in trouble.

We're coming up very rapidly on The Open Group Conference, beginning July 15. What should we expect? [Registration to the conference remains open. Follow the conference on Twitter at #ogPHL.]

Jones: We're offering FAIR training as a part of a conference. It's a two-day session with an opportunity afterwards to take the certification exam.

If history is any indication, people will go through the training. We get a lot of very positive remarks about a number of different things. One, they never imagined that risk could be interesting. They're also surprised that it's not, as one friend of mine calls it "rocket surgery". It's relatively straightforward and intuitive stuff. It's just that as a profession, we haven't had this framework for reference, as well as some of the methods that we apply to make it practical and defensible before.

So we've gotten great feedback in the past, and I think people will be pleasantly surprised at what they experienced.

Freund: One of the things I always say about FAIR training is it's a real red pill-blue pill moment — in reference to the old Matrix movies. I took FAIR training several years ago with Jack. I always tease Jack that it's ruined me for other risk assessment methods. Once you learn how to do it right, it's very obvious which are the wrong methods and why you can't use them to assess risk and why it's problematic.

It's really great and valuable training, and now I use it every day. It really does open your eyes to the problems and the risk assessment portion of IT today, and gives a very practical and actionable things to do in order to be able to fix that, and to provide value to your organization.

Are there any updates that we should be aware of in terms of activities within The Open Group and other organizations working on standards, taxonomy, and definitions when it comes to risk?

Hietala: At The Open Group, we originally published a risk taxonomy standard based on FAIR four years ago. Over time, we've seen greater adoption by large companies, and we've also seen the need to extend what we're doing there. So we're updating the risk taxonomy standard, and the new version of that should be published by the end of this summer.

We also saw within the industry the need for a certification program for risk analysts, and so they'd be trained in quantitative risk assessment using FAIR. We're working on that program, and we'll be talking more about it in Philadelphia. Follow the conference on Twitter at #ogPHL.

Along the way, as we were building the certification program, we realized that there was a missing piece in terms of the body of knowledge. So we created a second standard that is a companion to the taxonomy. That will be called the Risk Analysis Standard that looks more at some of that the process issues and how to do risk analysis using FAIR. That standard will also be available by the end of the summer, and, combined, those two standards will form the body of knowledge that we'll be testing against in the certification program when it goes live later this year.

Strong commitment

For those organizations that are looking to get started, in addition to attending The Open Group Conference or watching some of the plenary sessions online, what tips do you have? Are there some basic building blocks that should be in place or ways in which to get the ball rolling when it comes to a better risk analysis?

Freund: Strong personality matters in this. They have to have some sort of evangelist in the organization who cares enough about it to drive it through to completion. That's a stake on the ground to say, "Here is where we're going to start, and here is the path that we are going to go on."

When you start doing that sort of thing, even if leadership changes and other things happen, you have a strong commitment from the organization to keep moving forward on these sorts of things.

I spend a lot of my time integrating FAIR with other methodologies. One of the messaging points that I keep saying all the time is that what we are doing is implementing a discipline around how we choose our risk rankings. That's one of the great things about FAIR. It's universally compatible with other assessment methodologies, programs, standards, and legislation that allows you to be consistent and precise around how you're connecting to everything else that your organization cares about.

Concerns around operational risk integration are important, as well. But driving that through to completion in the organization has a lot to do with finding sponsorship and then just building a program to completion. But absent that high-level sponsorship, because FAIR allows you to build a discipline around how you choose rankings, you can also build it from the bottom up.

You can have these groups of people that are FAIR trained that can build risk analyses or either pick ranges — 1, 2, 3, 4 or high, medium, low. But then, when questioned, you have the ability to say, "We think this is a medium, because it met our frequency and magnitude criteria that we've been establishing using FAIR."

Different organizations culturally are going to have different ways to implement and to structure quantitative risk analysis. In the end it's an interesting and reasonable path to get to risk utopia.

Jones: A good place to start is with the materials that The Open Group has made available on the risk taxonomy and that soon-to-be-published risk-analysis standard.

Another source that I recommend to everybody I talk to about other sorts of things is a book called How to Measure Anything by Douglas Hubbard. If someone is even least bit interested in actually measuring risk in quantitative terms, they owe it to themselves to read that book. It puts into layman's terms some very important concepts and approaches that are tremendously helpful. That's an important resource for people to consider, too.

As far as within organizations, some organizations will have a relatively mature enterprise risk-management program at the corporate level, outside of IT. Unfortunately, it can be hit and miss, but there can be some very good resources in terms of people and processes that the organization has already adopted. But you have to be careful there, too, because with some of those enterprise risk-management programs, even though they may have been in place for years, and thus, one would think over time and become mature, all they have done is dig a really deep ditch in terms of bad practices and misconceptions.

So it's worth having the conversation with those folks to gauge how clueful are they, but don't assume that just because they have been in place for a while and they have some specific title or something like that that they really understand risk at that level.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: The Open Group.

Disclosure: The Open Group is a sponsor of this and other BriefingsDirect podcasts.

Related stories:

• Managing transformation to Platform 3.0 a major focus of The Open Group Philadelphia conference on July 15

• The Open Group Conference Panel Explores How the Big Data Era Now Challenges the IT Status Quo

• Complexity from big data and cloud trends makes architecture tools like ArchiMate and TOGAF more powerful, says expert panel

• Using the Cloud for Big-Data Requires a New Recipe

• Big Data Success Depends on Better Risk Management Practices Like FAIR, Say The Open Group Panelists

• The Open Group Keynoter Sees Big-Data Analytics Bolstering Quality, Manufacturing, Processes

• The Open Group Trusted Technology Forum is Leading the Way to Securing GLobal IT Supply Chains

Businesses and organizations often embrace some, but not all, of these activities. Their legacy and experience with them individually varies greatly. Each business and vertical industry has its own essential variables. And rarely are the trends embraced in unison, with a plan for how to cross-reference and exploit the others in concert.

Moreover, there are even more elements to the current upheaval: The Internet of Things, aka machine-to-machine (M2M), and consumerization of IT (CoIT) implications, as well as the building interest in bring your own device (BYOD). There's clearly a lot of change afoot.

It's no wonder that the coordinated path to so-called Platform 3.0 that includes all of these trends and their inter-relatedness is marked by uncertainty — despite the opportunity for significant disruption.

So how should organizations factor standardization, planning, governance, measurement, and even leadership over the productive adoption of Platform 3.0? The topic was initially outlined in an earlier blog post by Dave Lounsbury, chief technical officer at The Open Group.

These questions will certainly play a big part in the upcoming The Open Group conference beginning July 15 in Philadelphia. While the theme of the conference is Enterprise Transformation with an emphasis on the finance, government, and healthcare sectors, The Open Group is working with a number of IT experts, analysts, and thought leaders to better understand the opportunities available to businesses, and the steps they need to take to best transform amid the Platform 3.0 uptake.

The Open Group vision of Boundaryless Information Flow™ to me forms a large ingredient to helping enterprises take advantage of these convergent technologies. A working group within the consortium will analyze the use of cloud, social, mobile computing, and big data, and describe the business benefits that enterprises can gain from them. The forum will then proceed to describe the new IT platform in the light of this analysis, with an eye to repeatable methods, patterns, and standards.

Registration open

Registration to the conference remains open to attend in person, and many parts of the event will be streamed or available to watch later.

In a lead-up to the conference, The Open Group also organized a Tweet Jam last month around the hashtags #ogP3 and #ogChat to investigate how the early patterns for Platform 3.0 use and adoption are unfolding. I was happy to be the moderator.

Among some of the salient takeaways from the various discussion and the online Twitter chat:

• Speed of technology and business innovation will rapidly change the focus from asset ownership to the usage of services, requiring more agile architecture models to adapt to the rate and impact of such change

• New value networks will result from the interaction and growth of the "Internet of Things" and multiple devices and the expected new connectivity that targets specific vertical industry sector needs

• Expect exponential growth of data inside and outside organizations, converging with increased end-point usage in mobile devices, coupled with powerful analytics, all amid hybrid-cloud-hosted environments

• Leaders will need to incorporate new sources of data, including social media and sensors in the Internet of Things, and rapidly turn the data into usable information through correlation, fusion, analysis, and visualization

• Performance and security implications will develop from cross-technology platforms across more federated environments

• Social behavior and market channel changes will result in multiple ways to search and select IT and business services, engendering new market drivers and effects.

And some tweets of interest from the chat:

• Vince Kuraitis ‏@VinceKuraitis: Great term. RT @NadhanAtHP: @technodad #ogP3 principle of "Infonomics" introduced by @doug_laney #ogChat http://bit.ly/YnxXwe

• jim_hietala ‏@jim_hietala: RT @nadhanathp: @VinceKuraitis Agreed. Introducing new definition for ROI - Return on Information http://bit.ly/VAsuAK #ogP3 #ogChat

• E.G.Nadhan ‏@NadhanAtHP: Boundaryless Information Flow to be introduced into Healthcare @theopengroup conference in July' 13 http://blog.opengroup.org/2013/06/06/driving-boundaryless-information-flow-in-healthcare/ ... #ogChat #ogP3

• E.G.Nadhan ‏@NadhanAtHP: Say hello to the Data Scientist - Sexiest job in the world of #bigdata in the 21st century http://bit.ly/V62TcG #ogChat #ogP3

• Vince Kuraitis ‏@VinceKuraitis: Business strategy and IT strategy converge @ Platform 3.0 #ogp3 #ogChat

Again, registration to the conference remains open to attend in person. I hope to see you there. We'll also be conducting some BriefingsDirect podcasts from the conference, so watch for those in future posts.

Disclosure: The Open Group is a sponsor of BriefingsDirect podcasts.

Related stories:

• The Open Group Conference Panel Explores How the Big Data Era Now Challenges the IT Status Quo

• Complexity from big data and cloud trends makes architecture tools like ArchiMate and TOGAF more powerful, says expert panel

• Using the Cloud for Big-Data Requires a New Recipe

• Big Data Success Depends on Better Risk Management Practices Like FAIR, Say The Open Group Panelists

• The Open Group Keynoter Sees Big Data Analytics Bolstering Quality, Manufacturing, Processes

• The Open Group Trusted Technology Forum is Leading the Way to Securing GLobal IT Supply Chains

• Corporate Data, Supply Chains Remain Vulnerable to Cyber Crime Attacks Says Open Group Conference Speaker

• Open Group Conference Speakers Discuss the Cloud: Higher Risk or Better Security?

A global provider of IT products, procurement, and related services, with more than $4 billion in annual sales, SHI has tapped into the networked economy to improve its business productivity and sales. To learn more about how agile procurement works well, we were joined John D'Aquila, applications support manager at SHI International Corp in Somerset, New Jersey.

The interview is conducted Dana Gardner, Principal Analyst at Interarbor Solutions.

Below are some excerpts.

What's different now about buying and selling IT products and services than, say, three or four years ago?

One thing that has really changed is that IT asset management is a hot topic right now. Customers want to track their purchases much more efficiently than in the past, so they can know exactly how much they have at all times. They want to know if they're over-licensed, under-licensed on the software side, or, as far as hardware goes, they want to make sure that they have enough hardware in stock, but don't have too much. You don't want to have whole closets and warehouses full of equipment.

Streamlined solution

You have to be very precise, and, therefore, you need to have the data about what's going on across your supply chain.

Correct. That's where electronic commerce comes in, in IT asset management. I always say that it starts with a great PO, because we want to make sure that when we receive that purchase order, we have as much information that the customer is going to be looking for us to report on downstream.

Years later, if they come back to us and say, "how many desktops did we purchase over the last three years and who are they for?", the only way we could tell them who it was for is if they told us that information on the purchase order.

So the best way to get that is to have a streamlined solution that everyone is using when they're procuring their desktop PC, versus the situation where one PO came over handwritten, one PO came over via fax, and the level of information on each of those POs would be different.

At SHI, as part of every customer QBR or RFP demonstration, we definitely focus on the shi.com portal, which is a stand-alone website solution to provide them the ability to procure their products from a customized catalog solution.

Then we show them how we can leverage our check-out question process to collect the information, to make sure that every request and purchase order comes over with that same level of information. If a customer has a solution like Ariba, then we explain to them how we can work with that.

Tell us about your organization, how it came about, what you're doing, and why this whole notion of being ultra-efficient across your purchasing processes is essential to your business.

SHI is a global provider of IT products and solutions. We're headquartered in Somerset, New Jersey, and, as you mentioned before, we had over $4 billion in revenue last year. This year, we expect to surpass $5 billion.

The number of employees has doubled in four years. So there is definitely an investment internally to enhance the backbone of SHI, which is the sales force and the operations departments.

One thing that I always like to talk about is that as I walk in in the morning — and all employees walk in — above the SHI logo, it says, "Innovative solutions and world-class support." This reminds every employee, as they walk in, that our customers are the reason we're successful, and the way we retain those customers is by providing those innovative solutions and world-class support.

Customer driven

How are we getting people to be more efficient and more data driven when it comes to procuring their IT services and products?

The whole Ariba process is typically driven by the customer. In the early stages of evaluating a solution, we can tell them, if they ask us which one have you worked with and what are the benefits of each, but typically, the decision has already been made by the time they come to my team.

We'll explain to them our capabilities around that, and how we could seek benefits from little pieces of information on either the punch-out setup request or on the purchase order.

For example, AGCO has been a customer of SHI's for many years. The spend was at some growth, but it was really a slow trend up. Eric Deese is the contractor who is working on the project of enabling Ariba throughout AGCO.

We had a conference call to discuss the requirements and his scheduling and understanding his expectations of what we were going to do. From there, we put the resources in place. We did some testing with Eric, a full test, from the purchase order to invoice, to make sure that everything worked properly. Then, I handed it over to Tammy Wagner, who is the account executive for AGCO.

One thing that we really like to focus on with customers is rather than show them everything we could sell, we show what they actually need and want. So we've tailored a catalog around the requirements that Eric provided to make it easier for his users to find products.

Since we've gone live, the number of products purchased from SHI and the different product lines has tripled. So it's been a great success story.

Single-point purchasing

How are these trends around more process-driven efficiency goals translated into actual savings or efficiencies?

One thing is that they control their spend. In speaking to Eric, he explained that the AGCO users were buying software from everywhere. Some people would buy a shrink-wrap copy of software, which is really not the right way to buy software. They would use their P-Cards, and then they would just do an expense report, so it wouldn't be captured properly within their cost centers and the internal accounting.

Now, he said, all the employees of AGCO are going into the Ariba application and procuring their software from SHI. So maverick spend has been controlled.

Also, we can show Eric the spend with SHI and how it has grown. We work with you. Your overall spend has helped you secure better pricing with the manufacturers and with SHI, which in the long term will turn over savings for AGCO.

As IT organizations, in particular, are looking to move more toward an operations expenditure (OPEX) approach rather than the capital expenditure (CAPEX), they're looking for services, for leasing, and for outsourcing types of services. How is that impacting your business and how does that also impact the buying and selling process?

There has definitely been a trend of more operational expense, versus capital. We notice that customers are no longer treating a desktop as a commodity. It's more of a rental. You're going to use it for a few years and it's no longer going to be expected to run the life of an employee.

So the catalog refresh cycles have changed, as far as the number of items in the catalog. There is definitely standardizing and making sure that everyone in the organization has the same type of product, so they can get better imaging and so forth.

There is also a trend toward bring your own device (BYOD) that has been coming our way. Organizations are telling their employees, "Here is your minimum specifications, you can buy any PC, but it's out of your own pocket. It's up to you to purchase it, but you can bring that to work, whether it's a mobile device or even a laptop."

Today, there may be a customer that only purchases software from SHI. We want to introduce them to the fact that although we were Software House International, we are SHI now, because we sell all products that are IT related — hardware, services, and solutions.

And because we are here at Ariba Live, what are you hearing that excites you. It may be the spot-buying information. Is that something that would be of interest to you?

Yes. I've used Ariba Discovery in the past. I think there were a lot of empty requests we would respond, and then they wouldn't be viewed. I'm expecting that with the Spot Buy, because it will come directly out of the SAP application and will be someone keying in a request and looking for the bids, we'll get better leads from the solution. I'm looking forward to see what comes of it.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: Ariba, an SAP Company.

Disclosure: Ariba, an SAP company, is a sponsor of BriefingsDirect podcasts.

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Managing applications sprawl has long been a burr in the IT saddle, and the popularity of software-as-a-service (SaaS) applications hasn't exactly been a balm on the situation.

As with on-premises applications, the key to SaaS and hybrid apps is getting better visibility and operational data on the applications' health, and then automating the processes across standardized methods and controls.

Easier said than done. That's why the next BriefingsDirect IT innovator interview examines how an online pharmaceutical services provider, Millennium Pharmacy Systems, Inc., has successfully deployed mission critical SaaS applications, and then implemented advanced IT management and operational efficiency processes and systems to keep all the applications up to date, compliant, performant, and protected.

To learn more about how real-world automation and operational efficiencies helps improve their business results and customer retention, we sat down with Leon Ravenna, Vice President of IT and Operations and Information Security Officer at Millennium Pharmacy Systems, Inc., based in Cranberry Township Pennsylvania. The interview is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions. [Disclosure: VMware is a sponsor of BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: You deliver your value via SaaS. What has become key about managing the applications well?

Ravenna: Depending on what the customer needs, we may set up the entire environment for them, networks, wireless, scanners, and printers, or they get to us through their own equipment and internet connections. But it's all SaaS. 

Our SaaS application has 250 separate SQL databases on seven SQL Servers, running in a VMware environment and that helps me dramatically cut my licensing cost for SQL Server and helps to manage them in a high availability way.

I've been here about 14 months. One of the things that we looked at doing right, when I came in, is taking both the data centers that we have -- one is owned and one is a co-located facility -- and eliminating a lot of the older hardware that we had.

What we looked to doing first was consolidating, getting rid of the older hardware, and moving us to a much better state. We are now about 85 percent virtualized. Our  primary datacenter is for our customer-facing application, a SaaS application, built on SQL/.Net and Silverlight, for about 250 nursing care facilities on the East Coast.

Gardner: What have you gotten, in addition to efficiency, perhaps in terms of reliability?

Ravenna: We had a couple of older Dell blade chassis, and inevitably you would lose the power supply or a server, and I just don’t have that now. From an operational standpoint, it just helps to be more efficient. It has the ability to turn new servers up faster. It’s not something that we do all the time, but it helps me be much more efficient. I have a fairly small staff, and my goal is to let them sleep at night.

By having more VMware in place, as I said, about 85 percent virtualized, it allows me to do that. If the server fails, they applications move to a different server. I have the ability to upgrade the servers on the fly. It allows me, from an operational standpoint, to be more secure in what we're doing.

And it helps me lower my cost, because I am not as worried about my HVAC. I have less equipment to worry about. I have less break-fix to worry about. All in all, it helps me be remarkably more efficient.

Gardner: Let’s learn a bit more about Millennium Pharmacy.

Ravenna: We host a system for about 250 nursing-care facilities. This basically controls all of the medications that a patient would need. It does our medical reordering and passes that information in an entirely integrated fashion back to our in-house systems for billing and filling of prescriptions.

As a patient, you don’t have much time with your nurse. The nurse is typically gathering your drugs. We have our own pharmacies that service those homes. We deliver, in a cellophane sealed package, your medications.

These packages say, "Mr. Smith, take this at dinner time." There's a barcode for every drug, and when the nurse gives them the drug, they use a wireless scanner to scan that barcode and it automatically reorders the next set of drugs. We give patients about a three- or four-day supply, as opposed to 45- or 90-day supply, which cuts the cost for the nursing care facility itself. Then, we manage all of that data back to our other systems, that manage the filling of new prescriptions and billing and then we deliver every day.

The healthcare space is fairly stringent, and and getting more so with the new HIPAA regulations. New ones just came out on March 26 of this year, and the enforcement and penalties are much greater. There’s some significant items that have  changed, but really it’s the enforcement and penalties, things around encryption, and protecting customers' data.

We also have to protect confidential information and so we need to be very secure. We're working to implement the new HIPAA regulations so we can be even tighter in that space.

Gardner: This is all done through SaaS and cloud. There are no on-premises installations of your application. Is that right?

Ravenna: Only one facility out of our 250 has their own system. They are large, and one of their requirements was to have their own, but we support the rest of them, approximately 250, all cloud-based. They can get to it from their Internet connection.

All SaaS

Gardner: We're talking about being mission critical, people getting their medicine. We're also talking about being highly efficient. What were some of the requirements in terms of the infrastructure, particularly as we look now towards managing so many different instances and the ability to be agile and fire up new versions of VMware and to get those apps up and running? What were some of your requirements just from a management perspective?

Ravenna: It had to be easy. I have three system engineers. I only have a couple of network engineers. We support, on the network side, approximately 250 VPN tunnels out to customers, and as you said, it's mission critical. If people don’t get their drugs, it’s a bad day. We take that mission very seriously, making sure those systems are up and running.

From an operational or management standpoint, we really need to be monitoring to know what’s happening and when. Having VMware in that mix gives us the ability to make things consistent, but it also helps to  reduce our cost from a licensing standpoint and helps us manage them better, because we can see what’s happening at any given moment.

One of the nice things about VMware is that it’s just rock solid. We're kind of weary of knocking on wood, but it’s rock solid for us. It gives us the ability to move applications on an as-needed basis. We can upgrade things on the fly. In one data center, we are currently on 5.1, and we're moving the other data center to 5.1.

Gardner: So as a mid-market organization, you're resource constrained, you just don’t have a huge stuff, and you need automation. You need to have the ability to manage things, perhaps remotely.

So it's this notion of total approach to management, rather than silos, rather than integration of different management approaches and products together. That just wouldn’t fly. What have you done to improve management?

Ravenna: There are a couple of things. We're evaluating vCenter Operations Management Suite. One of the things that it has  let us do is dramatically reduce the size of our virtual machines (VMs).

Typically, if you're moving from a physical environment, VMware is a lot more efficient and it’s really kind of surprising seeing some of the reports that come back from vCenter Operations Management that tell you, realistically, you are running this server with six gigabytes of memory, but you are only really using one.

It’s a little bit spooky to look at it and ask if we really want to go that far. In some cases we would say, "Yes, let’s go ahead and do that," and it’s been, for the most part, dead-on. We've looked at a couple of things where our gut didn't say it was the right thing, even though it probably was. There's still a little bit of that old-school mentality that says you need to get more resources, when in fact the server may not even need them.

It lets us be a lot more efficient with what we are doing. It lets us manage more efficiently, because I can put more databases or more servers on each VM host.

Gardner: What was the ramp-up in terms of the skills and the running of the management system?

Ravenna: For vCenter Operations Management Suite, it wasn’t too bad at all. We were talking to VMware, and they said it would be potentially beneficial. We started up, ran it, and there really wasn’t that much training that was necessary.

The harder thing was when they came back and said we were over provisioned. That was  making that rationalization that VMware is a lot more efficient than physical hardware. It meant taking some of our servers from 4 GB RAM down to one half that, because that’s where they needed to be. In some cases, you want to be a little bit safe. You ultimately find out that the tool was right, and you were being gun shy.

Move quickly

Gardner: So when you look at the total picture, you need to be agile and able to move your resources quickly. What's next on your radar?

Ravenna: I have an overriding philosophy, after doing this for last 20 plus years. The simpler I can make it, the more I get to sleep. Sleep is a recurring theme and realistically, that means fewer calls during the night.

We're looking to move to vCloud Suite, in particular Site Recovery Manager (SRM), and using the vCenter Operations Management Suite to allow us to be more efficient. It just helps us work better and faster. Some of the key components will help me to be as efficient as possible. I may eventually need  to build out virtual data centers, so the VMware vCloud Director helps me.

My whole goal is to be able to make things as simple as possible and as easy as possible to manage, and these tools let me do that and be more efficient. The VMware Operations Management Suite and the vCloud Suite will help me get there.

Those are some of the key things I'm looking for in the future. For me, having multiple data centers, the ability to have VMware SRM, is just a great thing. It’s getting ready to thunderstorm here, and having the ability to move my services to a different data center that’s about 35 miles away is key.

Gardner: It’s pretty interesting that the notion a one-size-fits-all, plain vanilla, public cloud wouldn’t be attractive to you.

Ravenna: I'm very leery about putting my data just in a cloud with everybody else. It would have to be very specific to the healthcare space, because you end up signing a business associate agreement with me.

It would have to be what I would term carrier-class facilities that can prove they are in the healthcare space, dedicated to being there, and abide by all the HIPAA Rules. We have all of the things like PCI and SSAE 16. Those type things really need to be there and geared toward the healthcare space specifically for me to be able to look at them.

No choice

I'm not a guy who wants to understand electricity or heating and ventilation, but unfortunately in the world that we live today, in the mid-market space, you have your own data centers. You have no choice. You have to play in that game. Anything that I can do that helps me to address those issues to run cooler or run with less equipment is just all goodness.

Gardner: How do you convince the bean counters that this is the right thing to do?

Ravenna: It’s not necessarily a metric, but when you're spending less year over year on equipment, that’s evidence. Every server you buy is going to be in the roughly $5,000-$10,000 range. If I'm not doing that, I'm agile and nimble in being able to say that I can accommodate that.

That's opposed to the old process which was, get the capital done, go to finance, and wait six weeks to get a server, and then put it in. Inevitably there is something that’s constrained. So that six-week lead time becomes eight or ten weeks. It just helps me to move faster and spend a lot less capital money.

One of the things that I mentioned a little bit ago was licensing from a SQL standpoint, but things like backup that are running on a per-processor standpoint within VM drop my overall cost.

One of the things that it’s helpful as well is the dashboarding ability to be able to show what’s going on, what’s happening, and what the environment looks like. vCenter Operations Management Suite gives me that and it's all goodness.

If you're comparing the cost of, say, a two processor server, and you are going to go buy four, five, or six servers, take one of those servers and put that investment into VMware and vCenter Operations Management. You're going to be happier in the long term.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: VMware.

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To learn more about how agile procurement works on the mid-market sell side, we were joined by Cal Miller, vice president of Business Development at Blue Marble Media.

The interview was conducted by Dana Gardner, principal analyst at Interarbor Solutions.

Below are some excerpts.

Tell us a little bit about your company — your size, what services and products you provide. And why is the cloud not intimidating to you as a smaller firm for selling and finding new customers?

Even though we're very, very small, less than $2 million in revenue, we have clients like Georgia-Pacific, Verizon, Ariba, and the CDC. We work with a lot of medium-sized companies and even startups, very small ones. So the whole planet is our opportunity, if you will. We develop video, motion graphics, and animation for sales support, marketing, corporate communications, and just about any type of visual presentation that you might need.

Why go through non-traditional channels to get to new business?

Actually, it's a very overcrowded supplier sector. We're a little different in that we're a turnkey provider. We're not just a "video house." There are many of those out there, and they're good firms, but we're much more strategic. We do well when we begin a project and can interface at a C level with a company and help them come up with the strategy and the solution that eventually drives the message.

Our strength quite often is something that people don't know is even out there. One of the real benefits we found out early on Ariba Discovery is we can help educate people on the process of looking for companies like us, and then hopefully they are going to say, "OK, we'll call you back."

Halfway to goal

As someone who is already on the Ariba Network, they need to know and need to acquire, so they're halfway to finding the goal. You're going to need to go halfway toward them with your specific differentiating value and make that understood.

This notion of spot buying, however, expands that; it allows more than just a structured procurement professional who is looking for services and extends this down to people who are doing ad hoc, occasional, once-in-a-blue-moon types of buying. How has that worked out? Tell me a little bit more about how you even got involved with Ariba Discovery and spot buying at all?

In our world, spot buying is probably half of our total business. Even large companies may only have a need for a high-profile video series once a year, two times a year, or every other year. So the people that are charged with developing that solution quite often aren't the people who are going to be writing the check or making the procurement, and vice versa.

So the real challenge there is to get these people to understand that there is a vetting process. Ariba has provided this service, so a company like us can sit up and say, "Hey, we're a little different than the other guys. Let's engage and start some dialogue."

What have been the results? Let's learn first about how long you've been doing this? What's the timeline on how you have been using Discovery and extending that to that spot buying type of clientele?

It will be a year in a couple of weeks. We took a few months to learn the system, ramp up, and get going, but we've already had a very nice project and contract from a national bank that came through the network. And we have kind of a follow-up project with them. So that will be additional revenue.

We have several opportunities that have been presented to us, and we are in different stages of developing those projects as they move forward.

Even on a few of the introductions that we've passed up, we've made a response, but we knew it wasn't a good fit. We've learned that you still need to respond, because you get that opportunity to almost simulate a face-to-face meeting, because they get to learn about you, and you're building a relationship.

One of the biggest challenges that people on this network don't realize is to not look at your computer screen like it's just another interface computer screen. You're looking through the eyes of Ariba at a real, live person on the other end who can write you a check, and that changes the dynamic of how you communicate through the network.

Circles of engagement

And if it's not a right fit for them, they might have a word-of-mouth, community, or social connection with someone that they could refer you to. So there are concentric circles of engagement.

That happens very often, especially with the larger companies. It's, "These guys can do this. Here, give them a call in three months or pass this on to Joe, because they are going to need this." That's worth its weight in gold. You can't get that by knocking on the door or shooting out a bevy of emails. It just doesn't happen.

Now, as a mid-market company, a smaller company, you are of course price conscious yourself. What was the spend experience when you got involved with Ariba? How did you step into the water?

We had been a supplier to Ariba for about a year and a half, and then it was suggested that we needed to be on the network. We looked at it and started at the basic level. Within about four months, we realized that this is really a good deal. So I spent a lot of time learning more about it, and we immediately upgraded to the Premium Advantage level. It's the best investment we ever made.

And for us as a small company, and many of you listening may be able to identify with this, we have all these different marketing and sales-support options out there, and they are all good tools in their own right. But if you have limited time and budget, to me it was a no-brainer. This is the best way to make use of our time, get the quality of leads that we need, and make the contacts that we're looking for at a C level.

And that seems to be especially the case when an organization like yours has a significant, maybe even a majority, portion of your sales in that ad-hoc spot-buying type of engagement.

Very well summarized, Dana. That's very true. For a company like us, we would love to get ongoing contracts, but in our world and with the product and service we offer, it doesn't come that way. So spot buying is going to be the focus of how we utilize our partnership with Ariba.

I wish this had been around 20 years ago.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Ariba, an SAP Company.

Disclosure: Ariba, an SAP company, is a sponsor of BriefingsDirect podcasts.

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There's no hotter topic — and nothing more top of the mind these days — than cloud computing. Not surprisingly, HP has made that a major focus at day two of Discover.

To put some context around it all, BriefingsDirect assembled chief evangelist at HP Software, Paul Muller; Christian Verstraete, chief technologist for Cloud Solutions at HP; and Tom Norton, vice president for Big Data Technology Services at HP. The panel was moderated by Dana Gardner, principal analyst at Interarbor Solutions.

Below are some excerpts.

Christian, tell us about the state of the market before we get into HP's response to it.

Verstraete: What's happening in the market today, is that on one end, you have startups that are rushing to the cloud very quickly, that use cloud and don't use anything else, because they don't want to spend a penny on building up an IT department.

On the other extreme, you have very large corporations that look at all the things that are unknown around cloud and are sticking their toe in the water.

And you have everything possible and every possible scenario in the middle. That's where things are getting interesting. You have forward-looking CIOs who are embracing clouds, and understand how cloud can help them add value to the business and, as such, are an important part of the business.

You have other CIOs who are very reluctant and that prefer to stay managing the traditional boat, if I can put it that way, in keeping and providing that support to our customers. It's a interesting market right now.

Muller: The challenge that both vendors and consumers have is that one size does not fit all. When you find yourself in that situation, you only have two responses available to you.

If you're a one-trick pony, if you have only got one technology, one approach, then it's one size fits all. Henry Ford, one of your fellow countrymen, once said that you can have the car in any color you want, so long as it's black.

It's a great idea in terms of simplifying what your choices are, but it doesn't help you if you're an enterprise that's struggling to deal with complexity and heterogeneity.

We believe that there are three absolutely critical priorities that anyone looking into cloud should have. The first is confidence. Confidence, because you are moving typically mission-critical services in it. Even if it's develop and test, you're counting on this to work.

The second is consistency. There is absolutely nothing to be gained by having a cheap cloud service, on one hand, and then having to retrain people in order to use that, because it's completely different from your internal systems. It's just moving costs around. So consistency is absolutely critical.

The third piece we talk about all the time, choice. You should have your choice of operating system, database, and application development environment, whether it's Java or .NET, you shouldn't have to compromise when you're looking at cloud technology. So it's those three things — confidence, consistency, and choice.

Giving users choice

Here at Discover, we're hearing a lot about a variety of announcements for Converged Cloud. Let's look at a couple of these major aspects of the announcements and then delve into how they come together, perhaps forming a whole greater than the sum of the parts.

The first part, Christian, is this real emphasis on OpenStack and the Cloud OS. So give us a quick overview of where HP is going with OpenStack and Cloud OS, and how that relates to some of the requirements that we've just discussed?

Verstraete: What we want to do across the different clouds that we offer — private cloud, the managed cloud, and the public cloud — is a capability to be able to port workloads very quickly to build some consistency around them.

Cloud OS is all about that. It's about building a consistent infrastructure environment or infrastructure management environment to do that. And that's where we are using OpenStack.

So what is cloud OS? Cloud OS is nothing more than HP's internal OpenStack distribution, with a set of additional functionalities on top of it, to provide a second-to-none infrastructure-as-a-service (IaaS) delivery that can then be used for our private cloud, our managed cloud, and is already used for our public cloud.

That's the first thing that we announced. We are building on top of that. It's an evolution of what we started about a year and a half ago with Converged Cloud. So we just keep moving and working around with that.

We also announced that we not only support Cloud OS in our traditional blade environment and our x86 servers, but also on the newly announced HP Moonshot servers. That combination may become interesting when we start talking about the "internet of things" and a number of other things in that particular area. It will also provide our customers with the capability to test and play with Cloud OS through a sandbox. So there's a lot of emphasis on that.

One-trick pony

It also seems that you are expanding your support of different virtual machines (VMs), so heterogeneity is supported. As Paul Muller pointed out, it's supporting all the various frameworks. Is there something fundamentally different about the way HP is going about this cloud support with that emphasis on openness vis--vis some of the other approaches?

Verstraete: Many of the other players, many of our competitors, have what Paul mentioned earlier, a one-trick pony. They're either in the public space or the private space, but with one hypervisor. Where we're starting from, and that's the essence of Converged Cloud, is to say that a company going to cloud is not one size fits all. They're going to need a combination of different types of clouds to provide, on one hand, the agility that they need, and, on the other hand, the price point that they're looking for.

They'll put some stuff in their private cloud, and they'll put some other stuff in the public cloud. They'll probably consume software-as-a-service (SaaS) services from others. They'll probably put some things into a managed cloud. It's going to be a combination of those, and they're going to have to handle and live with that combination.

The question is how to make that easy, and how to allow them to access all of that through one pane of glass, because you don't want to give that complexity to the end users. That's exactly where Cloud OS is starting to play. Cloud OS is the foundation for us to do that.

Tom Norton, seeing that this field is very diverse in terms of the needs and requirements, it seems like a perfect fit for lots of consulting, professional, and support services, but we don't often hear about them in conjunction with cloud. Tell us a little bit about why the market is ripe for much more emphasis on the services portion here?

Norton: As you start to take advantage of the varying services that are available through the cloud, or that you want to present to the cloud, the varying presentation formats, the varying architectures are an issue for whether you're a startup or in the enterprise.

From a consulting perspective, you need to have a strategy and understand the challenges and complexities of that hybrid type of delivery or that hybrid consumption, and establish some type of design for how that's going to be used and presented. So consulting becomes very important the more you start to consume or present cloud-based-type services.

When you start thinking of that design and that whole approach from balancing across the network to balancing the infrastructure component pieces, you need to have some kind of consistent support structure. One of the most expensive parts of this is going to be how you support those different environments, so that if you have an issue, you're not doing component-based support anymore. You need a holistic-based cloud support.

For organizations truly to transform themselves as an IT organization and be able to present their service, which in many cases is an application, that app may be something presented internally to business units because the business units are getting some value, or even externally to a customer or to a customer's application.

Those apps are designed, in many cases, in either a more mainframe-based environment or also in the distributed environment. When you start thinking of presenting it as a service, there are other considerations that need to take effect.

You start looking at how that application performs in terms of more virtualized and automated environments. You also think about how you can manage that application from a service perspective. How do you monitor the application? How is it metered in terms of the presentation? How is that application presented within a service portfolio or a service catalog? How do you then manage and monitor the application for service operations? The user demands an end user experience for meeting a certain service level.

When you think of modernizing applications to a cloud-based presentation, there are multiple layers that have to be considered to even address the applications. When you think about the application piece and the work that needs to be done, you also have to think about the management component pieces of it.

That's why you'll hear of services around, say, cloud design services that will enable us to take a look at that service portfolio, look at the service catalog, and understand the application presentations and how you can ensure quality delivery and ensure that you're meeting those service levels, so that business can continue to take advantage of what that application provides to them.

So from an application perspective, you have both the cloud design piece that's referred to that, but, at the same time, you have to address the complexities of the application.

Managing devices

Verstraete: Tom, allow me to add one point. You talked about the application, but the next point associated with that is, on what device am I going to consume that application? Increasingly, we're seeing bring your own device (BYOD), and it's not just PCs, but also tablets, phones, and all of the other things.

We have to have the capability to manage those devices and make sure that we have the appropriate security levels and that they're compliant, so that I can run my enterprise applications on those devices without any trouble. That complements all of this.

Dana, to go back to a question that you had earlier, this is where all of these things are starting to come together. We talked about Cloud OS and the infrastructure and the environment, so that I could build on my applications. We talked about the Application Transformation Services, which allow us to put those applications on top of that. And we're talking about the other extreme, which is consuming those applications, and the devices on which we are starting to consume those applications.

Regardless of whether this is in a private cloud, a managed cloud, or a public cloud, that's where you start seeing the different parts and the different pieces coming together.

Why is the hybrid model so important with HP strategy?

Verstraete: Whether companies like it or not, most large enterprises today already have a hybrid model. Why? Because they have a lot of shadow IT, which is consumed outside the control of IT. It's consumed from external services, being in most of the cases public clouds. So that's already a fact of life.

Why is that used? Because there's a feeling from the business user that the CIO can't respond fast enough. So the CIO had better understand the potential issues related to the security and compliance of what is happening, and start acting on it.

He can't speed up his delivery of what the business is looking for by developing everything himself and taking the old fashioned approach. I choose an application. I test the application for six months. I install the application. I configure the application, and two years down the road, I deliver the application to the business users.

What becomes clear quickly to a lot of CIOs is that if they take a hard and cold look at their workloads, not all workloads are the same. Some of them are very specific to the core of what the enterprise is doing. Those should stay within their private cloud.

There are a bunch of other things that they need to deliver. Frankly, they are no different from what their competitors are doing. Do those need to be in a private cloud or could they be in another type of environment, a managed cloud, or public cloud? That automatically brings you to that hybrid environment that we're talking about.

New core competency

Paul Muller, how is hybrid perhaps the new core competency for IT, managing hybrid processes and hybrid systems and managing the continuum?

Muller: Again, Dana, you get to the core of the issue here, which is that it's about a shift. This is a generational shift in how we think about building, buying, and integrating IT services in the service of the business or the enterprise, depending on where you work.

It's about a couple of key shifts. It's about the balance of power shifting from IT to the business. We have probably said this countless times over the last three decades, but the simplicity, the focus on user experience, the ease with which competitive services can be procured from outside by laypeople from an IT standpoint has created a symmetry in the relationship between business and IT that no one can afford to ignore.

The second generational shift is the speed with which people expect response to their ideas. Techniques like agile and dev-ops are changing the way we think about building and delivering services.

Finally, to your point, it used to be that you either build or you buy, you either outsourced everything or you did it all yourself. Now, we live in a world where you can consistently do both. I don't believe that the majority of IT professionals are ready for that new reality in terms of processes and people, not to mention the software stack, the infrastructure stack, on which they're building services.

There's a lot of work to be done. It sounds daunting. The good news is that if you take a smart approach, some of the work that Tom and our Professional Services and Technologies Services team have been working on, it helps ease that transition and avoid people repeating the mistakes of some of the early adopters that we have seen.

Access to expertise

Tom Norton, as we factor what Paul said about transitioning the organization from supporting technology to supporting the continuum of a hybrid approach, how big a change is that for an organization?

Norton: It's a significant change, when you think of how traditional support structures have been. When you look at more complex systems, and you can think of a hybrid cloud environment as being a complex cloud system itself, traditionally support structures have been component-based and they've been infrastructure-based, or application-based. So you look at a storage support solution, or you may look at a network support solution or a compute solution itself.

When you start thinking of a complex system, like a cloud model, and especially a hybrid cloud model, where you have varying delivery mechanisms and varying supporting structures, supporting that can be a very complicated issue. It's one that many organizations are unprepared to do, especially if they're going to try to approach it strategically, as opposed to being a opportunistic-type cloud environment.

What IT is trying to do today and the question they keep asking is how they can view this as being that kind of ecosystem that has a singular support structure to it, where they can get access to expertise.

That's what HP is stepping up to do. With our own experience, across the spectrum, building on-premises and private, working in the managed infrastructure places, we have public cloud experience and we also have the experience of the integration across all of those.

The benefit from a services perspective for our customers is that we can help break down those isolated barriers in singular cloud services that a customer is consuming and give them a support structure that bridges all of those and truly approaches a converged support structure for managing that hybrid environment. That's what we're working towards, and that's where our announcements have been all about.

What is the most important change that HP has brought to the cloud landscape with this series of announcements?

Verstraete: Two things — first, and you hit the nail earlier, the whole concept of hybrid cloud, looking at multiple ways and multiple clouds to address the needs of the business. And second, within that frame of hybrid cloud, making sure that there is consistency across the different clouds, and that's where we're using OpenStack.

Paul Muller, what's different in your mind about what HP has been doing this week?

Muller: It is all about accelerating the introduction of applications and improving the user experience. It is not about technology for technology's sake. The single biggest difference.

Differentiated

And lastly, Tom, what jumps out at you as a differentiator in terms of the market in general and what HP is doing?

Norton: I think the market is looking for someone that can help with the integration component pieces of it. As the hybrid and heterogeneous deployments continue to grow and more and more services are offered that way, organizations need help consolidating that into a more integrated approach, so they have that kind of overall cloud concepts that give them the value they are looking for. So it's becoming more and more about integration.

Disclosure: HP is a sponsor of BriefingsDirect podcasts.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.

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HP's innovations in its Converged Cloud portfolio, announced today at HP Discover 2013 in Las Vegas, are aimed at better ushering large enterprises from legacy to hybrid cloud environments.

Despite the great interest in SaaS and cloud, many large enterprises are still grappling with the right mixture of on-premises, hosted, and various cloud deployment models for their applications, infrastructure, and data. And the formula for picking which apps and assets should run where will be a changing one, as business goals, economic pressures, and technology advances all conspire to make last year's IT model obsolete. Ongoing.

HP officials say the next phase of a common OpenStack-based architecture for HP's private, managed, and public cloud offerings recognizes this dynamic environment. Not only does one-size cloud not fit all, no company can predict what their risk path is, nor how well cloud will work for them in coming years. That's why choice and operating environment standardization — and not just price — must be the critical requirements for cloud adoption.

"You should have your choice of operating system, database, and application development environment, whether it's Java or .NET, you shouldn't have to compromise when you're looking at cloud technology," said chief evangelist at HP Software, Paul Muller. "We have focused on ensuring that the cloud infrastructure, the workloads, the automation, the compliance tools, everything around that, are focused on optimizing the application experience."

But HP also acknowledges that where cloud clearly makes sense, a quick path to its benefits must be made. And so HP also announced new software and services to accelerate time to market for private cloud implementations, and unveiled new capabilities in HP's managed and public cloud solutions under the Converged Cloud banner.

Research commissioned on behalf of HP predicts that by 2016, around 75 percent of enterprise IT will be delivered across private, managed, and public clouds. Further, half of the respondents believe that open standards are important in the emergence of cloud computing. This indicates that customers want an open, hybrid cloud solutions to generate new opportunities, drive competitive differentiation, and lower the cost of operations, said HP.

HP Cloud Operating System (OS) is therefore an open and extensible cloud technology platform that leverages the community strength of OpenStack technology to enable workload portability, simplified installation and enhanced life cycle management across hybrid clouds, said HP.

HP CloudSystem, HP's private cloud offering, already embeds Cloud OS technology. To help customers get started quickly with an initial private cloud deployment, HP also is offering the HP CloudSystem Enterprise Starter Suite. This solution allows organizations to get started with rich application cloud services, and reduces upfront costs by up to 20 percent with the bundled offering.

Christian Verstraete, chief technologist for Cloud Solutions at HP, explained the importance of Cloud OS. "What we want to do across the different clouds that we offer — private cloud, the managed cloud, and the public cloud — is a capability to be able to port workloads very quickly to build some consistency around them," he said. "Cloud OS is all about that. It's about building a consistent infrastructure environment or infrastructure management environment to do that. And that's where we are using OpenStack."

Open Stack distribution

"So what is Cloud OS? Cloud OS is nothing more than HP's internal OpenStack distribution, with a set of additional functionality on top of it, to provide a second-to-none infrastructure-as-a-service (IaaS) delivery that can then be used for our private cloud, our managed cloud, and is already used for our public cloud," said Verstraeta.

But while HP is making an OpenStack-based cloud platform environment, it is bundling hardware and software-defined infrastructure so that the ease of deployment — similar to appliance benefits — makes those seeking openness a value and simplicity offer they can't refuse.

Inexpensive and energy-stingy HP Moonshot servers also will be offered with HP Cloud OS, providing simplified provisioning and management for specific cloud workloads, such as dedicated hosting and large-scale websites. HP Cloud Services also leverages HP Cloud OS technology. To encourage customers to evaluate and understand the benefits of an OpenStack-based architecture for their cloud needs, HP is offering HP Cloud OS Sandbox for experimentation at no cost.

Forty three percent of respondents in the HP-commissioned survey said that finding the right strategic partner to get them started was a barrier to cloud adoption. So to help guide customers, HP introduced the HP Converged Cloud Professional Services Suite.

HP announced such new services designed to help customers take advantage of the cloud. These new offerings include HP Converged Cloud Support, HP Cloud Design Service, HP Cloud-ready Networking Services, HP Proactive Care for CloudSystem, and HP Cloud Security Risk and Controls Advisory Services, as well as enhancements to HP Applications Transformation to Cloud Services.

"From a consulting perspective, you need to have a strategy and understand the challenges and complexities of that hybrid type of delivery or that hybrid consumption, and establish some type of design for how that's going to be used and presented. So consulting becomes very important the more you start to consume or present cloud-based-type services," said Tom Norton, vice president for Big Data Technology Services at HP.

"This is not just a technology decision that you need guidance on. It's structuring contracts and understanding how to deal with termination of service — what happens to the intellectual property (IP) you have in the cloud. That's where having advice from seasoned experts can help you avoid some of the pitfalls of cloud adoption," said Muller.

"With our own experience, across the spectrum, building on-premises and private, working in the managed infrastructure places, we have public cloud experience and we also have the experience of the integration across all of those," said Norton.

HP Enterprise Services has enhanced its portfolio of cloud service offerings to address increased customer needs for mobile and enterprise applications. These include:

• HP Enterprise Cloud Services for Enterprise Applicationsthat give clients choice and flexibility when integrating and deploying applications in the cloud while maintaining business continuity and ensuring data security.

• HP Mobile Enterprise Cloud Solution that provides a fully managed and integrated set of mobile consulting and management services to securely enable applications and data sharing from many device types.

• HP Enterprise Cloud Services- Private Cloud that enables clients to quickly adopt cloud services by designing, building and managing a complete Infrastructure as a Service that creates the foundation for an enterprise-wide shared IT services model.

• HP Cloud Security Risk and Control AdvisoryServices, a new offering in the HP professional services portfolio that helps clients safeguard their information, manage potential for data breaches and remain compliant while transitioning applications to public, private and hybrid clouds.

Engaging customers

In addition, HP Autonomy introduced the Autonomy Marketing Cloud, a cloud-based version of the Autonomy Marketing Performance Suite, enabling organizations to understand, attract, engage, and convert customers in real time.

New HP Cloud Services capabilities make it easier and faster for enterprises to simplify the development and deployment of applications in the public cloud. Enhancements include:

• Access to new, larger-instance types that enable users to run big data analyticsand high-performance computing workloads in the public cloud.

• New virtual private cloud network functionality, powered by software-defined networkingthat provides advanced security when connecting their public cloud to on-site networks.

• New custom image uploading that increases customer productivity by simplifying the setup and deployment of instances with images unique to their business requirements.

• A new Bulk Import Service that speeds application delivery by allowing users to provide hard drives for direct data upload into HP Cloud Block Storage and HP Cloud Object Storage.

In other infrastructure news at Discover, HP yesterday unveiled Project HAVEn, which leverages HP's analytics software, hardware, and services to create big-data-ready analytics applications and solutions. HAVEn pulls together the growing army of HP analytics technologies and capabilities — from Autonomy to Vertica to ArcSight and more — allowing all kinds of data and information to be exploited in unison, with the dependencies and relationships mappable and hidden insights attainable across sources.

Disclosure: HP is a sponsor of BriefingsDirect podcasts. My travel to HP Discover 2013 was paid for by HP.

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• Insurance leader AIG drives business transformation and IT service performance through center of excellence model

• HP BSM software newly harnesses big-data analysis to better predict, prevent, and respond to IT issues

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• HP Discover Performance Podcast: McKesson Redirects IT to Become a Services Provider That Delivers Fuller Business Solutions

The next edition of the HP Discover Performance Podcast Series brings together three HP executives to dig into one of the biggest news events at the HP Discover 2013 Conference this week in Las Vegas, the Project HAVEn unveiling.

There has been a lot said about big data in the last year and HP has made a big announcement around a broader vision for businesses to help them gain actionable intelligence from literally a universe of potential sources and data types.

To learn how, BriefingsDirect assembled Chief Evangelist at HP Software, Paul Muller; Chris Selland, Vice President of Marketing at HP Vertica, and Tom Norton, Vice President for Big Data Technology Services at HP. The panel was moderated by Dana Gardner, principal analyst at Interarbor Solutions. [Disclosure: HP is a sponsor of BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: Fairly recently, only critical data was given this high-falutin' treatment for analysis, warehousing, applying business intelligence (BI) tools, making sure that it was backed up and treated almost as if it were a cherished child.

But almost overnight, the savvy businesses, those who are looking for business results, are more interested in all the data of any kind so that they can run their businesses better, and find insights in the areas that they maybe didn’t understand or didn’t even know about.

So what do you think has happened? Why have we moved from this BI-as-sacred ivory tower approach to now more pedestrian?

Competitive issue

Selland: First-and-foremost, it’s really become a competitiveness issue. Just about every company will pay attention to their customers.

Selland

You can tell senior management that this data is important. We're going to analyze it and give you insights about it, but you start realizing that we have an opportunity to grow our business or we're losing business, because we're not doing a good enough job, or we have an opportunity to do better job with data.

Social media has been the tip of the arrow here, because just about all industries all of a sudden realize that there is all data out there floating around. Our customers are actually talking to each other and talking about us, and what are we doing about that? That’s brought a lot of attention above and beyond the CIO and made this an issue that the CMO, the CFO, the COO, the CEO start to care about.

Big data is about far more than social media, but I do think social media gets a lot of the credit for making companies pay a lot more attention. It's, "Wait a minute. There is all this data, and we really need to be doing something with this."

Muller: In the conversations that I'm having consistently around the globe, executives, both CIOs, but also non-IT executives, are realizing that "big" data is probably not the most helpful phrase. It’s not the size of the data that matters, but it’s what you do with it.

Muller

It’s about finding the connections between different data sets to help you improve competitiveness, help you improve efficiency if you are in the public sector, help you to detect fraud pattern. It's about what you do with the data in that connected intelligence that matters.

To make that work, it’s about not just the volume of data. That certainly helps, not having to throw out my data or overly summarize it. Having high-fidelity data absolutely helps, but it’s also the variety of data. Less than 15 percent of what we deal with on a daily basis is in structured form.

Most of the people I meet are still dealing with information in rows and columns, because traditionally that’s what a computer has understood. They’ve not built for the unstructured things like video, audio, images, and for that matter, social, as Chris just mentioned.

Finally, it’s about timeliness. Nobody wants to might be making tomorrow’s decision with last week’s data, if that makes sense. In other words, with a lot of the decisions we have to make, it’s usually done through a revision mirror, which is not helpful, if you're trying to operate today’s thoughts as well.

Variety of systems

Selland: I have a love-hate relationship with the term "big data." The love part is the fact that it really has been adopted. People gravitate to it and are starting to realize that there is something here they need to pay attention to. And that’s not just IT.

And this is really what’s driven the HAVEn initiative and the HAVEn strategy. We have this tremendous portfolio of assets here at HP -- from software to hardware to services -- and HAVEn is about putting that portfolio behind these different analytic engines – Vertica, IDOL, Logger, and Hadoop -- that complement each other.

Broad strategy

So how do we bring this together under a single broad strategy to help companies and global enterprises get their hands around all of this, because it’s a lot more than big? Big data is great. It’s great that the term is taken off, but it’s a lot bigger than that.

Norton: Both Paul and Chris mentioned that data platforms and data analysis have been around for years, but this is still a shift.

Norton

The traditional systems or platforms that IT is used to providing are now becoming legacy. In other words, they're not providing the type of service level to meet the workload demands of the organization. So IT is faced with the challenge of how to transform that BI environment to more of a data refinement model or a big data ecosystem, if you want to still hang on to big data as a term.

So the business is now demanding action from IT.

The ability to respond quickly to this platform transformation is what we want to help our customers do from our technology services' perspective. How can we speed the maturity or speed the transformation of those traditional BI systems? Business have to have relevant and refined information available to them at the time they need it -- whether it’d be 1.5 seconds or 15 hours.

The business needs the information to be able to compete and IT needs to be able to adapt, to have that kind of flexible, secure, and high-performing platform that can deal with the different complexities of raw data that’s available to them today.

Gardner: Let’s get back to the news of the day, Project HAVEn. What it is?

Selland: I talked about the tip of the spear before. In this case the tip of the spear are our analytic engines, our analytic platforms, the Vertica Analytics Platform, Autonomy IDOL, ArcSight Logger. HAVEn is about taking this entire HP portfolio and then combining those with the power of Hadoop.

There are a number of Hadoop distributions, and we support them all. It's taking that software platform, running it on HP’s Converged Infrastructure, wrapping HP’s services around it, and then enabling our customers, our channel partners, our systems integrators, and our resellers to build these next-generation analytic-enabled solutions and big-data analytic-enabled solutions.

Changing the business

When you're talking to businesspeople, you can't talk about platforms and you can’t talk about speeds and feeds. When you say Hadoop to a businessperson they usually say, "God bless you," these days.

You have to talk about customer analytics. You have to talk about preventing fraud. You have to talk about being able to operationally be more effective, more profitable, and all of those things that drive the business. It really becomes more-and-more a solutions discussion.

HAVEn is the HP platform that provides our customers, our partners, and of course, our consultants, when our customers choose to have us do it for them, the ability to deliver these solutions. They're big-data solutions, analytic-enabled solutions. They're the solutions that companies, organizations, and global enterprises need to take their businesses forward and to make their customers more satisfied to become more profitable. That's what HAVEn is all about.

Gardner: How then do you put this into business terms, so they can get just how powerful this really is?

Muller: That’s ultimately the question. Let me just give you an example that we talk about and that I share with people quite frequently, and it usually generates a bit of a smirk. We’ve all been on the telephone and called a company or a public service, where you've been told by the machine that the call will be monitored for quality of service purposes. And I am sure we’re all thinking, "Gosh, if only."

The scary part is that all those calls are recorded. They're not only recorded, but they're recorded digitally. In other words, they're recorded to a computer. Almost all of that data is habitually thrown away, unless there is an exception to the rule.

If there is a problem with the flight or if there is some complaint about the call that escalates the senior management, they may eventually look at it. But think about how much information, how much valuable insight is thrown away on a daily basis across a company, across the country, across the planet. What we've aimed to do with HAVEn is liberate that information for us to find that connected intelligence.

In order to do that, we get back to this key concept that you need to be able to integrate telemetry from your IT systems. What’s happening inside them today? For example, if somebody to send an email to somebody outside of the company, that typically will spawn a question that asks who they send that email to? Was there an attachment there? Is it a piece of sensitive information or not? Typically that would require a person to look at it.

Finally, it's to be able to correlate patterns of activity that are relevant to think about revenue, earnings, or whatever that might be. What we're able to do with the HAVEn announcement is combine those concepts into one integrated platform. The power of that would be something like in that call center example. We can use autonomy technology to listen to the call, to understand people's emotions, and whether they’ve said, "If you don't solve this problem, I'm never going to buy from you again."

Take that nugget of information, marry that to things like whether they are a high net worth customer, what their spending patterns have been, whether they're socially active, are they more likely to tell people about their bad experience, and correlate that all in real-time to help give you insight. That's the sort of being the HAVEn can do it, and that's a real world application that we're trying to communicate in business.

Norton: I have one more example of what Paul has just indicated. Take healthcare, for example. We're working with the healthcare providers. There are some three-tier healthcare providers. A major healthcare organization could have as many as 50 different business units. These separate business units have their own requirements for information that they want to feed to hospital systems.

Centralized structure

So you have a centralized organizational IT structure. You have a requirement of a business unit within the organization that has its own processing requirement, and then you have hospital systems that buy and share information with the business unit.

Think about three-tiered structure and you think of some of the component pieces that HAVEn brings to that. You have IT which can manage some of those central systems that becomes that data lake or data repository, collecting years and years of historical healthcare information from the hospital systems, from the business units, but also from the global healthcare environment that could be available globally.

IT provides this ecosystem around the data repository that needs to be secured, and and that data pool needs to be governed.

Then, you combine that with information that's coming publicly and needs to be secured. You have those corner pieces which are natural to the Hadoop distributed system inside that data lake that keeps that repository of healthcare information.

The business unit has a requirement because it wants to be able to feed information to the healthcare providers or the hospital systems, and to collect from them as well. Their expectations of IT is that they may need instant response. They may need a response from a medical provider in seconds, or they may look at reporting on changes in healthcare in certain environmental situations that are creating change in healthcare. So they might get daily reporting or they might have half-day reporting.

Within HAVEn, you look at Vertica, to drive that immediate satisfaction of that query that comes from the hospital system. Combine that with Hadoop and combine that with the kind of data-governance models that Autonomy brings. Then, look at security policies around the sensors from patients that are being sent to that hospital system. That combination is a very powerful equation. It's going to enable that business to be very successful in terms of how it handles information and how it produces it.

When we start looking at that integration of those components, that's what's driving IT, because they need that very flexible and responsive data repository that can provide that type of insight that the hospital systems need from that from the business unit that's driving the healthcare IT organization itself.

Those are the fits even in a large enterprise, where you can take that platform and apply it in an industry sense, and it makes complete sense for that industry overall.

Gardner: HP has, of course, been a very large company with a long heritage, but are we really stepping outside of the traditional role that HP has played? It sounds as if HP is becoming a business-services company, not a technology services company.

Bridging the gap

Selland: Yes and no. First of all, we do need to acknowledge that there is a need to bridge the gap between the IT organization and the business organization, and enable them to talk the same language and solve problems together.

First of all, IT has to become more of an enabler. Second, and I mentioned this earlier and I really want to play this up, it's absolutely an opportunity for our partners. HP has a number of assets, but one of our greatest assets is HP's partner network -- our partner ecosystem, our global systems integrators, our technology partners, even our services providers, our training providers, all of the companies that work in and around the global HP.

We can't know every nuance of every business at HP. So the HAVEn initiative is very much about enabling our partners to create the solutions we're creating. We're using our own platform to create solutions for the core audiences that we serve, which in many cases, are things like IT management solutions or security solutions which are being featured and will continue to be featured.

We're going to need to get into all of these different nuances of all of these different industries. How do these companies and organizations compete with each other in particular verticals? We can’t possibly know all of that. So we're very reliant on our partners.

The great news is we have, we have what I believe, is the world's greatest partner network and this is very much about enabling those partners and those solutions. In many cases, those solutions will be delivered by partners and that’s what the solutions are all about as well.

Gardner: Now that we put together the various platforms, given the whole is greater than the sum of the parts in terms of a business value, what's the vision beyond that to making these usable, exploitable?

Are there APIs and tools or is that something also that you are going to look to the partners for, or both? How does it work in terms of the go-to-market?

Selland: There absolutely are APIs and tools. We need to prime the pump, to some degree, with building and creating some of our own solutions to show what can be done in the markets we serve, which we're doing, and we also we have partners on board already.

If you look at the HAVEn announcements, you'll see partners like Avnet and Accenture and other partners that are already adopting and building HAVEn-based solutions. In many cases, we've started delivering to customers already.

It's really a matter of showing what can be done, building what can be built, and delivering them. I mentioned earlier the crossing-the-chasm moment we're having. The other thing that happens, when you get into this market, is you're moving from its being purely a CIO decision to where the business starts getting involved.

Great ROI

There is great return on investment (ROI), there's this big data analytic solution we're going to enable, and we are going to build to deliver better customer loyalty. We are going to better customer retention and lower churn. The first thing I need to say is, "Okay, show me the numbers, show me the money." Those are Jerry Maguire terms, and the best way to do that is show examples of other companies that have done it.

You've got to get that early momentum, but we're already in the process of getting it, and we've already got partners on board. So we're really excited.

Gardner: Given what we've now seen with the HP Discover announcements with HAVEn, how HP is uniquely positioned in big data?

Muller: Insight without action is a bit like saying that you have a strategy without execution. In other words, it’s pretty close to hallucination, right?

The ability to take that insight and then reflect that into your business rapidly is critical. I have a point of view that says that almost every enterprise is defined by software these days. In other words, when you make an insight and you want to make a change, you're changing the size. If you are Mercedes, you're changing one of the 100 million lines of code in your typical S class. Some of the major based around the planet now hire more programmers than Microsoft has working on Windows today.

Most companies are defined by software. So when they do get in an insight, they need to rapidly reflect that insight in the form of a new application or a new service, it’s typically going to require IT.

Absolutely critical

Your ability to quickly take that insight and turn that into something a customer can see, touch, and smell is absolutely critical, and using technique like Agile delivery, increasing automation levels, DevOps approaches, are all critical to being able to execute to get to that.

Selland: It's not just big data, but helping our customers be successful in leveraging big data is a core focus and a core pillar of HP strategy. So first of all it’s focus.

Second of all, it’s breadth. I talked about this earlier, so I don’t want to repeat myself too much. The software, hardware, and converged cloud assets, capabilities of services, and of course their service’s portfolio -- all of the resources that the global HP brings to bear -- are focused on big data.

And it’s also the uniqueness. Obviously, being an HP Software Executive, I'm most familiar with the software. If you really look at it, nobody, none of HP’s competitors, has anything like Vertica. None of HP’s competitors have anything like IDOL. None of HP’s competitors has anything like ArcSight Logger. None of HP's competitors has the ability to bring those assets together and get them interoperating with each other and get them solving problems and building solutions.

Then, you take our partner channel, wrap it around that, and you combine it with the power of open-source industry initiatives like Hadoop. HP has very much openness of the core of everything we're doing.

You’ve got to have a broad enough portfolio to know that you’ve got the confidence and the assets to eventually solve the problem, but at the same time start with understanding the problem, the industry, and solutions. This is where our service is, and this is where our partner ecosystem comes into play. And having the breadth of the portfolio of software/hardware and cloud services to be able to deliver on it is really what’s it’s all about, but there is no one-size-fits-all answer to the question we just asked.

Norton: HP actually has, from a services' perspective, a unique approach to this. You've seen it before in the cloud and you've seen it before in the days of IT transformation, where we started looking at that transformation experience.

Through our services' groups within HP, we have the ability from an information management and analytics approach to work with companies to understand the business value that they're trying to drive with information, and ideally try to understand what data is available to them today that is going to provide that business aligned information.

Through the Big Data Discovery Experience workshops, we're able to ask, "What is the business I am capable of doing with the data they have available to them today, and how can that be enhanced with alternative data sources that may fall outside of the organization today?"

As we mentioned earlier, it’s that idea of what can be done. What's the art of the possible here that is going to provide value to the organization? Through services we can take that all the way down, then say, now once you have got the idea, that says I’ve got a road map for analytical value and the management of the information that we have, and we could have made available to the businesses.

Then, you can align that, as I mentioned before, through IT strategies where you do the same thing. You align the business to IT and ask how IT is going to be able to enable those actions that the business wants to take on that information.

Entire lifecycle

So there's an entire lifecycle of raw material data to business-aligned and business-valued information through a service’s approach, through a consultative approach, that HP is able to bring to our customers.

That’s unique, because we have the ability through that upfront strategy from business value of information to the collection and refinement of raw materials and meeting in the middle in this big data ecosystem. HP can supply that from end to end, all the way from software to hardware to services, it's very unique.

Muller: I’ve got to summarize this by saying that the great part about HAVEn is that you can pretty much answer any question you could think of. The challenge is whether you can think of smart questions to ask.

Selland: Let me give you a tangible example that I was reading about not long ago in The Wall Street Journal. They were talking about how the airline industry is starting to pay attention to social media. Paul talked before about intersections. What do we mean by intersections?

This article in The Wall Street Journal was talking about how airlines are starting to pay attention to social media, because customers are tweeting when they're stuck at the airport. My flight is delayed, and I am upset. I'm going to be late to go visit my grandmother -- or something like that.

So somebody tweets. Paul tweets "I'm stuck at the airport, my flight is delayed and I am going to be late to grandma’s house." What can you really do about that besides respond back and say, "Oh, I'm sorry. Maybe I can offer you a discount next time," or something like that? But it doesn’t do anything to solve the problem.

Think about the airline industry, customer loyalty programs or frequent-flyer programs. Frequent-flyer programs were among the first customer loyalty problems. They have all this traditional data, as well which some might call customer relationship management (CRM). In the airline industry, they call it reservation systems.

I gave the example before about a jet engine throwing off two terabytes of data per hour. By the way, on any flight that I'm on, I want that to be pretty boring data that just says all systms are go, because that’s what you want.

At the same time, you don’t want to throw it away, because what if there are blips, or what if there are trends? What if I can figure out a way to use that to do a better job of doing predictive maintenance on my jets?

Better job

By doing a better job of predictive maintenance on my jets, I keep my flights on time. By keeping my flights on time, then I do a better job of keeping my customers satisfied. By keeping my customers more satisfied, I keep them more loyal. By keeping my customers more loyal, I make more money.

So all of this stuff starts to come together. You think about the fact there is a relationship between these two terabytes per hour of sensor data that’s coming off the sensors on the engine, and the upset customers, and social media tweeting in the airport. But if you look at the stuff in a stove-piped fashion, we don’t get any of that.

How do we start to bring this stuff together? This stuff does not sit in a single database and it’s not a single type of structure and it’s coming in all over the place. How do I make sense of it?

As Paul said very well, ask smart questions, figure out the big picture, and ultimately make my organization more successful, more competitive, and really get to the results I want to get to. But really, it’s a much, much bigger set of questions than just "My database is getting really big. Yesterday, I had this many terabytes and I am adding more terabytes a day." It’s a lot bigger than that.

We need to think bigger and you need to work with an organization that has the breadth of resources and the breadth not just inside the organization but within our partnerships to be able to do that. HP has got the unmatched capability to do that, in my view, and that’s why this HAVEn initiative is so very exciting and why we have such great expectations from this.

HAVEn is really about the future, the competitiveness of the business, and IT becoming an enabler for that. It’s about the CIO, really having a chance to play a key role in driving the strategy of the business, and that’s what all CIOs want to do.

We have these inflection points in the marketplace, the last one was like 12 years ago, when the whole e-business thing came along. And, while I just used a competitor's tag line, it changed everything. The web did change everything. It forced businesses to adapt, but it also enabled the lot of businesses to change how they do business, and they did.

Now, we're at another one, a very critical inflection point. It really does change everything, and there is still some skepticism out there. Is this big-data thing real? We think it’s very real and we think you're going to see more-and-more examples. We're working with customers today or showing some of those examples how it really does change everything.

Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: HP.

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Unveiled at HP Discover 2013, Project HAVEn leverages HP’s analytics software, hardware, and services to create big-data ready analytics applications and solutions.

HAVEn tackles some very big issues, both for the IT market and for HP. For the market, data and information remain fragmented, uncoordinated and hard to manage. At the same time, enterprises want to be able to use all the data they can access to better understand their businesses, users, and markets.

So HAVEn pulls together the growing army of HP analytics technologies and capabilities -- from Autonomy to Vertica to ArcSight and more -- allowing all kinds of data and information to be exploited in unison, with the dependencies and relationships mappable and hidden insights attainable across sources. And that insight can come from any type of information or content (Autonomy), with great speed and scale (Vertica) and associate with machine and IT systems data (ArcSight).

For HP, HAVEn shows the analytics whole is greater than the sum of the product parts, and presents a rationalization and uber value from its business intelligence, data and big data acquisitions and developments of the past five years. It also shows an agnostic approach to Hadoop, and an inclusive architecture alignment across analytics products and technologies, which is welcome.

According to a study commissioned by HP nearly 60 percent of companies surveyed will spend at least 10 percent of their innovation budget on big data this year. The study also found, however, that more than one in three organizations have failed with a big data initiative. [Disclosure: HP is a sponsor of BriefingsDirect podcasts. My travel to HP Discover 2013 was paid for by HP.]

HAVEn combines proven technologies from HP Autonomy, HP Vertica, HP ArcSight, and HP Operations Management, as well as key industry initiatives such as Hadoop, enabling clients and partners to:

• Avoid vendor lock-in with an open architecture that supports a broad range of analytics tools.
• Protect investments with support for multiple virtualizationtechnologies.
• Speed time to value with highly optimized hardware solutions.
• Gain value from 100 percent of information, including structured, semistructured and unstructured data, via HP’s portfolio of more than 700 connectors into HAVEn.

Chris Selland, Vice President of Marketing at HP Vertica, explained the initiative: "The tip of the spear are our analytic engines, our analytic platforms, the Vertica Analytics Platform, Autonomy IDOL, ArcSight Logger. HAVEn is about taking this entire HP portfolio and then combining those with the power of Hadoop."

The first integrated big data analytics solution built on HAVEn is HP Operations Analytics, which delivers insight into all aspects of IT operations. The solution allows organizations to consume, manage, and analyze massive streams of IT operational data from a variety of HP products, including HP ArcSight Logger and the HP Business Service Management portfolio, as well as third-party sources.

HP Enterprise Services has introduced HP Actionable Analytics Services. These solutions will enable clients to implement analytics and extract insight hidden within big data, as well as streamline key organizational processes, such as customer offers, procurement, supply chain and inventory operations.

Paul Muller, Chief Evangelist at HP Software, explained the value of analytics: "It’s not the size of the data that matters, but it’s what you do with it. It’s about finding the connections between different data sets to help you improve competitiveness, help you improve efficiency if you are in the public sector, help you to detect fraud pattern. It's about what you do with the data in that connected intelligence that matters."

Big-data consulting

HP Technology Services has also expanded its Big Data Consulting Practice to ensure optimal IT infrastructure performance as well as support for increasing big data demands. New offerings include IT Strategy and Architecture, System Infrastructure, and Protection services that enable clients to align their IT infrastructure to organizational goals, while achieving compliance with industry standards and government regulations.

"The traditional systems or platforms that IT is used to providing are now becoming legacy. In other words, they're not providing the type of service level to meet the workload demands of the organization. So IT is faced with the challenge of how to transform that BI environment to more of a data refinement model or a big data ecosystem," said Tom Norton, Vice President for Big Data Technology Services at HP.

"The ability to respond quickly to this platform transformation is what we want to help our customers do from our technology services' perspective. How can we speed the maturity or speed the transformation of those traditional BI systems which are more sequential and more structured to be able to deal with the demands of the business to have relevant and refined information available to them at the time they need it, whether it’d be 1.5 seconds or 15 hours," said Norton.

HP also announced two additional products to help that effort:

• The HP Vertica Community Edition—free, downloadable software that delivers the same functionality of the HP Vertica Analytics Platform Enterprise Edition with no commitments or time limits, allowing clients to analyze up to one terabyteof data before investing in an enterprise-wide solution.
• The HP Autonomy Legacy Data Cleanup—information governance solution that helps clients analyze legacy data, lower costs, and reduce risks while driving value from big data. With this solution, organizations can access, understand and classify, as well as defensibly dispose of outdated and unnecessary legacy information, while retaining data deemed valuable for production applications.

Selland summed up the initiative this way, "You have to talk about customer analytics. You have to talk about preventing fraud. You have to talk about being able to operationally be more effective, more profitable, and all of those things that drive the business. It really becomes more-and-more a solutions discussion.

"HAVEn is the HP platform that provides our customers, our partners, and of course, our consultants, when our customers choose to have us do it for them, the ability to deliver these solutions. They're big-data solutions, analytic-enabled solutions. They're the solutions that companies, organizations, and global enterprises need to take their businesses forward and to make their customers more satisfied to become more profitable. That's what HAVEn is all about, the fundamental story behind the HAVEn initiative."

In other infrastructure news today at Discover, HP expanded the company's Converged Storage portfolio with a solid-state optimized all-flash HP 3PAR StoreServ system. It has also announced a StoreOnce Virtual Storage Appliance (VSA) that promises to cut the cost of small site backup by 65 percent.

The HP 3PAR StoreServ 7450 Storage system delivers more than 550,000 input/output operations per second with less than 0.7 millisecond response time. Flash-specific caching algorithms dynamically adjust read/write granularity to reduce latency and speed transactions. In addition, HP 3PAR Priority Optimization software assures performance for specific workloads to improve overall productivity.

HP StoreOnce VSA deploys as a virtual machine on existing industry-standard servers, eliminating the need for customers to purchase dedicated hardware. It enables backup as a service offering for hosting providers and lowers costs for enterprise remote office protection. In addition, HP StoreOnce VSA reduces physical hardware requirements by up to 50 percent and energy costs by up to 70 percent.

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Titled the State of Customer Integration 2013, the report finds that the biggest stumbling block on the path to data integration is an increasingly complex IT environment. While customer relationship management (CRM) systems are increasingly transitioning to cloud, the report found, enterprise resource planning (ERP) and business intelligence (BI) systems remain in silos behind the firewall.

“Businesses are struggling to reach the connected enterprise nirvana,” noted Lou Guercia, CEO of Scribe. “With the continued move to cloud and complex hybrid environments, the lack of integration between these systems is becoming clearer and significantly slowing business value.”

Respondents also reported that almost half of budget ownership of core business systems now resides outside of IT, indicating a sea change toward chief marketing officers (CMOs) having an increasing stake in IT budget decisions in the years ahead.

Although IT continues to own a sizeable portion of the budget, sales, operations and marketing departments together are responsible for 48 percent of the planned systems investments in 2013. In addition, while almost half of business respondents (44 percent) plan to invest more in their business systems in 2013, the majority (60 percent) plan to take a cautious approach – increasing their customer-facing systems investment by no more than 20 percent compared to 2012.

Cloud has penetrated all core business systems with CRM leading the way. Some 26 percent of businesses report a pure cloud environment for CRM, while ERP and BI systems are still predominantly on-premise (with only six percent and five percent respectively reporting cloud adoption). In addition, the growing importance of hybrid environment support for customer data is clear, as 47 percent of businesses and 73 percent of third-party systems integrators point to hybrid environment support as either a top priority or "important" for their CRM strategy.

The majority of businesses (73 percent) and systems integrators (80 percent) report revenue growth as top priority, but they are also quick to note as top priorities the need for increased customer satisfaction and increased revenue per customer.

The importance of CRM and core business system integration to support customer-focused business growth is clear, said privately owned Scribe, based in Manchester, NH. In fact, businesses report measuring the success of their CRM data integration initiatives based on CRM satisfaction (at 45 percent), complete customer view (at 43 percent), and CRM system adoption (at 41 percent).

However, with the majority of respondents noting integration between CRM and business intelligence (74 percent), CRM and customer support systems (73 percent), and CRM and marketing automation (71 percent) as a top priority, only 16 percent of business respondents report full integration among their various business systems. When compared to 15 percent reporting full integration in 2012, it is evident that organizations still have a long way to go to fully integrate customer data across core business systems. While only 10 percent report a complete lack of integration, partial integration is still the norm.

Among additional findings:

• Businesses expect their CRM systems to have the ability to share data among key departments, and companies prioritize the value of CRM data integration in terms of its ability to drive accuracy and consistency of customer information
• The majority of systems integrators(84 percent) and businesses (71 percent) rate mobile CRM as either important or top priority for their CRM strategy in 2013
• The lowest levels of reported between-systems integration are between CRM and ERP (13 percent) and CRM and social (10 percent)
• Custom code continues to be the way the majority (48 percent) of businesses report integrating their systems – but that is a significant drop from 2012 when 59 percent reported doing so
• Most businesses (64 percent) still do not have a formal process for evaluating their CRM data integration progress, yet failure to integrate CRM with other critical business systems is driving 18 percent of respondents to switch to a new system in 2013.

For a copy of the report, check here. Scribe will also host a webinar on June 13 at 11 a.m. EDT. Register here.

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Over recent years a number of technologies -- cloud, mobile, big data, social -- have emerged and converged to disrupt the way we engage with each other in both our personal and business lives. Most of us are familiar with the buzz words, including "the Internet of things," "machine-to-machine (M2M)," and "consumerization of IT," but what do they mean when they act in concert? How can we treat them as separate? How can we react best?

Understanding opportunities

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