1. Cloud computing is the new Internet.  Only ten years ago companies talked about having an Internet strategy – today Internet is simply part of the fabric of organizations.  Likewise, I am predicting that within 10 years we won’t hear customers talk about their cloud strategy — it will simply be the way business is done.
2. Analytics is one of the most important trends – being able to anticipate what will happen next – whether it is a retailer trying to determine what products will be hot or a business trying to anticipate where a problem will emerge.
3. The best new ideas are old ideas re-envisioned. The greatest and hottest companies will be based on taking existing ideas and products and revamping them with newer technologies and inventive go to market initiatives.
4. Platform as a Service (PaaS) is the next hot thing in cloud this coming year. This market will have a rocky evolution since existing Infrastructure as a Service vendors and Software as a Service vendors will all create their version of PaaS tied to their existing offerings.  Needless to say, this will confuse customers.
5. Service Management becomes the defining differentiator for all types of cloud service providers.  Especially as the hybrid cloud becomes the norm, providers will have to provide a required level of privacy, security, and governance depending on the customer need. I expect to see a flood of cloud service management products.
6. While 2011 was the year of innovation, 2012 will be the year of the customer experience. Apple’s success and huge market cap can be, at least in part, attributed to its ability to delight customer with well-executed and well-designed products.  The best new products do not simply give customers what they said they wanted, but anticipate what they didn’t know they wanted until it becomes available.
7. The number of vendors focused on cloud security, governance, and compliance will expand dramatically. The successful companies will focus on protecting all end points – including mobile.
8. Big data will be the most important silver bullet of 2012.  It will indeed be overhyped to the point where every aspect of computing will be tagged as a part of the big data ecosystem.  With that said, it is one of the most important trends because it will provide a set of techniques to enable companies to gain knowledge and insight in new ways from the huge volumes of unstructured data.  The successful companies are those that create solutions focused on solving specific industry problems.  One size does not fit all.
9. Many copycat companies will tank.  Companies like Groupon and Zynga simply do not have the depth of technology or differentiation to have sustainability.  But that will not stop hundreds or perhaps thousands of copycat companies with equally weak value propositions from setting up shop.
10. 10.  It is probably redundant to say that this will be the year of the mobile app. In fast the same could be said for 2011.  But there is a subtle difference. This year will see sophisticated developers focusing on creating applications that can easily move across tablets, laptops, and phones.  The successful companies will make it easy to synchronize data across these devices as well as integrating with related applications. A healthy ecosystem will make the difference between success and failure.

When I started working on my latest book, Smart or Lucky? How Technology Leaders Turn Chance into Success, I thought a lot about what makes one company sustain itself over decades while other companies fade away.  What does innovation really mean and how does it happen? Innovation is not an easy achievement. Many companies that find themselves in trouble proclaim that they will improve their fortunes by through innovation.  While it makes sense it can be somewhat perplexing.  Shouldn’t companies always be focused on innovation? Isn’t it logical to assume that if a company were consistently innovating that they would not get themselves into a mess? One of the biggest problems with companies attempting to innovate is that they often don’t ask the right questions.  What do I mean? Here is the type of questions companies ask customers:

• What features would you like to see in the next rev of our product?
• Are you happy with the products we sell you?
• What is your reaction to our product roadmap?
• How could the roadmap be improved?

Many companies spend lots of money and time establishing customer advisory boards, setting up focus groups and the like to make sure that they are prepared for future customer requirements.  Don’t get me wrong – I think it is important to keep in touch with customers and ask them about the products and services that they use on a regular basis.  For example, every time I go to my local Apple store I get a survey about how satisfied I was with the service I got. If I wasn’t happy, I get a phone call from the store manager.  It’s a nice touch and certainly makes me feel good.  But that alone will not have any influence on whether I buy a new Apple product or not.

So, what should companies be asking customers about what they want? I think they need to focus on customer pain and the white space in the market.  So, if I were that company looking to be innovative here is what I would ask:

• What problems are you looking to solve that you can’t solve right now?
• What is most annoying about working with our company?
• If you could wave a magic wand and three things would change about us, what would they be?
• What direction is your company headed and how can our company help you achieve your aspirations with less pain?

Does your company ask these types of questions? I would guess that the answer is probably no.  Most companies have a well-honed machine of internal and external individuals that focus 100 percent of their attention on surveying customers.  They produce reports so that they can prove to their management and shareholders that they are focused on the customer.  If a company wants to innovate it has to change the way it thinks about innovation and satisfying customers. Isn’t that what innovation is all about?

I remember attending a Hewlett-Packard meeting for industry analysts in the early 1990s and hearing HP proudly declare that it was becoming a software company. Software had turned into a stronger driver of revenue in the computer industry than hardware, and HP management had realized that it had to make the shift to sustain its growth. I raised my hand and asked Lew Platt, HP’s president at the time, how much of overall revenue he anticipated would come from software within five years. His answer: by the end of the decade, about 10 percent.

Today, software is less than 3 percent of HP’s revenue. Clearly the transition has been difficult. The latest news is that HP may be considering a poison pill to fend off angry investors. They along with many analysts were rattled by Leo Apotheker’s announcement that HP would spin off its PC business and spend heavily to acquire software company Autonomy—and then rattled again by Apotheker’s abrupt replacement at the helm by former eBay chief Meg Whitman.

Such seismic moves would be unsettling in any company, but the real problem is that HP is not trusted to execute on its new strategy well. Fundamentally, people just do not see software as part of HP’s DNA.

DNA sounds like a soft thing and it is. It’s the company’s deeply embedded belief system, its prevailing ethics, and the way people within the company interact with each other and with customers. It governs an organization’s cultivation of its intellectual capital—how it leverages what it already knows how to do, and how it evolves its offering based on changing market demands. You see evidence of companies’ different DNAs in the ways they react to risks and opportunities. One company might be patient enough to allow a new strategy to evolve while another panics when returns don’t start coming quickly or positively enough. Usually when people talk of DNA they’re raising questions of corporate culture: Does the company rely on consensus among managers or are strategies and tactics directed from the top? How does the company deal with dramatic change? Is change viewed as a natural evolution that is necessary for the health of the company or is it seen as a threat to survival? How does the company nurture home-grown talent?

But just as in biology, DNA doesn’t start with these soft, impressionistic manifestations. It starts with the hard and detailed set of instructions that give rise to them. In a company setting, that would be the economics of its business model.

The DNA that has been in HP’s bones from the start is all about excellence in hardware engineering. Hewlett and Packard set out to create high-quality electronic equipment that was more accurate and precise and less expensive than competing products. That DNA served it well over several decades; even through the 1990s, HP succeeded through its ability to innovate with hardware, and its strong focus on quality won it strong customer loyalty. It was when HP decided to go beyond dabbling in software that its troubles began. Despite its clear excitement about the idea of becoming a software giant, HP did not seem to internalize the very different model of a software-driven company.

Companies that focus on hardware first can usually understand the economics of software intellectually, but at the day-to-day organizational level they don’t act as though they get them. With hardware markets, money is spent upfront to develop a system. However, once that product is launched, revenue streams in quickly and evenly. The lifecycle of that product may be a year or so, depending on the competitive environment. Then, the hardware company does the same thing again.

By contrast, when software is delivered to the market, it may take a year or even several years before it becomes a well-accepted and profitable endeavor. But that time investment is rewarded, because when software proves useful to customers its longevity is assured. Customers tend to stay with a software product for many years, continually investing in yearly maintenance agreements and follow-on products. A hardware company accustomed to instant feedback, in the form of revenues, on its products’ market success often panics at the slow pace of the software market revenue model. This is what I’ve observed at HP. As it has tried to invest in software, again and again it has killed products off before they had time to mature.

Many companies that have decided to shift course have done so largely through acquisitions, and HP is surely no exception. From the late 1980s through the present day, HP has acquired hundreds of software companies. Some were large and well-known entities such as Opsware, Mercury Interactive, and the recently announced Autonomy Software. Other companies such as Bluestone Software, Dazel, Novadigm, SPI Dynamics (to name a few) were emerging leaders in their day. While all of these acquisitions had potential to help HP grow software into a significant business, there was a problem: There wasn’t an overall, well-thought-out plan for how these technologies would be absorbed and combine to create a sustainable advantage.

This is the other “hard” part of DNA: strategy. People often talk of the “roadmap” a company needs to be successful, specifying not just what areas they will focus on but how these components form a solution to customers’ problems. An equally good term for this master plan is DNA. Given HP’s status as the largest IT company in the world, it is shocking that it does not have a comprehensive software strategy worthy of its leadership role. But at HP it has simply never emerged.

And so the softer elements never congealed either into any recognizable new shape. There was no software leader in the company who was allowed to mature and grow. There were a succession of software leaders who could have grown into important leaders given time but none lasted more than a couple of years. Other internal talent was either overlooked or left for greener pastures.

Here’s my belief: When a company sees a new business direction as its savior instead of seeing that change as what it is, the change cannot be successful. At HP, acquisitions have tended to be trumpeted and welcomed as potential saviors of its future. (Never mind that the same was said of the last one, and it is now yesterday’s news.)

In order to reassure investors, and ensure its continuing viability, it needs to have a software business executing on a viable software strategy, and deeply rooted in an acceptance of software economics. HP’s DNA has led to its predicament today. Only its DNA can save it.

The Inaugural Hurwitz & Associates Predictive Analytics Victory Index is complete!

By Fern Halper

For more years than I like to admit, I have been focused on the importance of managing data so that it helps companies anticipate changes and therefore be prepared to take proactive action. Therefore, as I watched the market for predictive analytics really emerge I thought it was important to provide customers with a holistic perspective on the value of commercial offerings. I was determined that when I provided this analysis it would be based on real world factors. Therefore, I am delighted to announce the release of the Hurwitz & Associates Victory Index for Predictive Analytics! I’ve been working on this report for a quite some time and I believe that it will be very valuable tool for companies looking to understand predictive analytics and the vendors that play in this market.

(continue to rest of Fern’s blog)

It is inevitable that data would emerge as the most complex and important topics of the next decade. The expansion of the amount and types of data that we have been accumulating across more systems—physical and virtual, applications, and electronic devices – is astounding.  These environments generate huge amounts of data – from structured to unstructured – and with increasing use of digital images, social media, and data streams this explosion of data is continuing beyond what we could have imagined. Many organizations have created workarounds to manage these large volumes of complex data using warehouses, data marts, and moving subsets of data into an analytic tool.  But in my view we have reached a tipping point where these approaches aren’t enough as much of these data remain in their existing silos.

Making matters worse, there is no way to leverage this data based on the context of the business problem being addressed. Enterprises need a big data strategy that enables query and analysis across different sources and types of data.  The key to success in the future will require that all of this data be managed in new ways.

Some of the initial big data use cases have evolved from the problem that occurs when applications generate huge volumes of data – like search engine data, information generated from gene screening, or when a company is trying to analyze customer buying patterns incorporating both traditional structured customer data with unstructured customer call center notes. Many technical early adopters are assuming that big data is synonymous with Hadoop (a way to break data into small fragments of work in a way that they can be executed and analyzed efficiently across a highly distributed hardware environment.  Hadoop (managed by the Apache standards organization) has been closely associated with the difficulty of handling large volumes of data generated from web environments.  While Hadoop is extremely important, it is still immature and will require time to evolve.

Making things more complicated is that many vendors in the market are slapping the big data moniker on whatever technology they happen to be offering at the moment.  But capturing the value of big data is one of the most critical challenges for companies and it needs a thoughtful and innovative approach. So, if big data is much bigger than web data management, what is it? In brief, big data is the ability to manage the huge amounts of data in a way allows customers to gain business value no matter how the volume of data, the form of that data, or the status of that data. It is a big issue that will take many years to address.  It is the ability to manage massive amounts of structured and unstructured data at a petabyte scale.

A few weeks ago I attended IBM’s big data summit.  During this event IBM made it clear that it is viewing big data in the context with its information management strategy.  Like many vendors in the market, IBM is wasting no time in putting a stake in the ground around Big Data.  IBM is viewing big data as a way to holistically bring together all of the elements of corporate data.  There are three dimensions to the way IBM is planning its approach to data: variety (different types of data), velocity (the speed required to manage the data), and volume (the amount of data in the mix).  While the IBM big data strategy is evolving, there were five key take-aways from the meeting:

• Gaining insight from unstructured data requires powerful analytic engines to process and analyze in real-time
• Big data requires Internet scale; it is not for the timid.
• For customer to get a handle on massive amounts of data requires levels of abstraction with the right user interface based on the type of user (developer, business executive, etc.)
• What do you need to know from your data? It depends on what business you are in and how you can leverage both your structured and unstructured data. This requires sophisticated management of both structured combined with unstructured data based on well-defined master data management.  Even more fundamental is the requirement to have a way to query that data for both employees and the entire partner community.
• The way you analyze this data is the key. You need to understand the context of the information so you are looking at the right elements in the right way.  Separating the information that is noise from the information that is insight is imperative.  A misreading of the results can send a business down the wrong path with potentially catastrophic results.

IBM is making a significant investment in analytics and applying this to big data.  As IBM executives who spoke at this meeting were quick to admit, it is early in the evolution of big data.  IBM is trying to execute an ambitious strategy of bringing together hardware, all varieties of information management, with service management software, and middleware combined with industry frameworks and best practices.  The vision will take time to mature but I believe it is based on the right customer pain.

I joined LinkedIn in 2007. I can’t remember why. After connecting to a few dozen people, I still couldn’t fathom what the purpose of LinkedIn was, especially for an already-established professional. Yes, I knew these people, but to what end were we connecting on this site? But for some reason I stayed on for the ride, more as an experiment than in any effort to gain value. I was fascinated with the platform this company was building and wondered what its business model might be. Even after I gave up wondering, I kept adding links.

Fast forward four years and LinkedIn is a public company with a market cap of more than $9 billion and revenues of about $400 million. I’m shaking my head at how lucky its founder Reid Hoffman turned out to be. At the same time, I’m beginning to appreciate how he and his colleagues were smart.

For the rest of the article, click on this link.

HP finds itself in a complicated position. While the technology giant’s second-quarter revenue increased by 3%, its relatively new CEO, Leo Apotheker, was forced to lower the forecast for revenue for the fiscal year. He blamed the Japan earthquake, the anemic PC market, and a troubled services organization.

Wall Street did not take kindly to the news. While HP was once the technology leader that could do no wrong, market watchers are now concerned that the company does not have a clear strategy to overcome its problems. Not surprisingly, the stock price has tumbled.

Click on this link to read the rest of this article.

This transition did not happen over night.  In the early days of open source it was hard to get a customer to take the movement seriously.  Customers were afraid of being stuck with orphaned software that was hard to manage and left to the whims of developers.  In those days customers had a right to be worried. All open source offerings were not created equal. There were many instances of companies with failing software products that attempted to keep products alive by offering these products to the open source community.  Many of these efforts lasted a few short and painful months before the products went to the forgotten product graveyard.  More recently companies like Sun Microsystems, before its acquisition by Oracle, proclaimed that portions of the Java language and its Solaris operating system would become open source. Ironically one of Sun’s early triumphs was its ability take to take one of its most important assets in the late 1980s – its network file system – and put it into the public domain.  While this bold action, as I talk about in Chapter 1 of my new book, had very positive yet a short term impact on Sun’s fortunes. The company was not able to sustain its early success.

But things started to change when software companies like Red Hat with strong commercial approach to managing and maintaining the Linux operating system, JBoss middleware, and now cloud computing software began actively collaborating with well-respected standards organizations.  Organizations with strong leadership like the Apache Foundation, the Open Group, the OMG, the Eclipse Foundation, and the  Distributed Management Task Force (DMTF) have partnered closely with vendors ranging from IBM to VMware to support the requirements for interoperability.

The most important consequence of the growing importance and legitimacy of open source is that it levels the playing field.  In reality, it is a lot harder for a single company to corner a market based simply on convincing partners and customers to standardize on a single system.  Now I am not naive, it is still possible for a company to gain dominance in a market segment with a proprietary approach.  For example, while Apple uses a Linux based operating system, its software is proprietary.  Apple’s loyal customers accept this because of the perceived elegance of the solution.  In essence, you can only corner a market when you offer customers something that solves a problem or changes the customer experience in a significant way.

Cloud computing adds an interesting dimension to the open source approach.  As cloud computing matures more customers will demand interoperability both at the API level, the data level, and at the applications level.  So, I was particularly interested in Red Hat’s latest efforts related to cloud computing open source.  The company is focused on two initiatives: Cloud Forms and Open Shift. Cloud Forms is intended as an Infrastructure as a Service (IaaS) initiative to help customers implement a private or hybrid cloud from a lifecycle perspective.   This initiative focuses on portability, virtualization, and integration with public cloud services.  Open Shift is focused on focused on Platform as a Service (PaaS).  Therefore, it is designed to provide an open development platform to support a variety of language options including Java, Ruby, and Python.  It is too early to determine whether this effort will become widely adopted by customers. But it is indeed a step in the right directions.  The fact that Red Hat is working closely with the Apache foundation is a good step in the right direction.  As with any open source initiative it will require that a broad community of developers work on expanding and deepening the implementation of this approach so it will take time and a lot of effort.  The downside of this open development process is that it takes a long time for efforts like Cloud Forms and Open Shift to mature to the point where they are ready for the average commercial corporation.  However, the benefit of an open source development effort is the power and wisdom of thousands of contributors.

Traditionally, System vendors have relied on partners to expand the coverage of their platforms. With the cloud, the requirement to have a strong partner ecosystem will not change. If anything, partners will be even more important in the cloud than they have been in traditional computing delivery models.  This is because with cloud computing, the barriers to leveraging different cloud-based software offerings – platform as a service and Software as a Service are very low. Any employee with a credit card can try out just about anything.  I think that the Amazon.com issues will be seen in the future as a tipping point for cloud computing. It, in fact, will not be the end to cloud but it will change the way companies view the way they select cloud partners.  Service management, scalability, and reliability will become the selection standard – not just for the end customer but for partners as well.

So, I was thinking about the cloud partnership model and how it is evolving. I expect that the major systems vendors will be in a perfect position to begin to reassert their power in the era of the cloud.  So, I decided to take a look at how IBM is approaching its partnership model in light of cloud computing.  Over the past several months, IBM has been revealing a new partnership model for the cloud computing market.  It has been difficult for most platform vendors to get noticed above the noise of cloud pioneers like Amazon and Google.  But this is starting to change.  It is not hard to figure out why.  IBM believes that cloud is a $181 billion business opportunity and it would like to grab a chunk of that opportunity.

Having followed IBM’s partnering initiatives for several decades I was not surprised to see a revamped cloud partnering program emerge this year. The new program is interesting for several different reasons.  First, it is focused on bringing together all of IBM’s cloud offerings across software, developer relations, hardware, and services into a single program.  This is important because it can be intimidating for an ISV, a Value Added Reseller, or a systems integrator to navigate the complexity of IBM’s offerings without some assistance.  In addition, IBM has to contend with a new breed of partners that are focused on public, private, and hybrid cloud offerings.

The new program is called the Cloud Specialty program and targeted to cover the entire cloud ecosystem including cloud builders (hardware and software resellers and systems integrators), Service Solution Providers (software and service resellers), Infrastructure Providers (telecom providers, hosting companies, Managed Service Providers, and distributors), Application Providers (ISVs and systems integrators), and Technology Providers (tools providers, and appliance vendors).

The focus of the cloud specialty program is not different than other partnering programs at IBM. It is focused on issues such as expanding the skills of partners, building revenue for both IBM and partners, and providing go to market programs to support its partners.  IBM is the first to admit that the complexity of the company and its offerings can be intimidating for partners.  Therefore, one of the objectives of the cloud specialty program is to clarify the requirements and benefits for partners. IBM is creating a tiered program based on the different types of cloud partners.  The level of partner investment and benefits differ based on the value of the type of partner and the expectation of those partners.  But there are some common offerings for all partners. All get early access to IBM’s cloud roadmap, use of the Partnerworld Cloud Specialty Mark, confidential updates on IBM’s cloud strategy and roadmap, internal use of LotusLive, networking opportunities. In addition, all these partners are entitled to up to $25,000 in business development funds.   There are some differences.  They include:

• Cloud builders gain access to business leads, and access to IBM’s lab resources. In exchange these partners are expected to have IBM Cloud Reference architecture skills as well as cloud solutions provider and technical certification. They must also demonstrate ability to generate revenue. Revenue amounts vary based on the mix of hardware, software, and services that they resell.  They must also have two verified cloud references for the previous calendar year.

• Service Solution Providers are provided with a named relationship manager and access to networking opportunities. In exchange, partners are expected to use IBM cloud products or services, demonstrate knowledge and skills in use of IBM cloud offerings, and the ability to generate $300,000 in revenue from the partnership.

• Infrastructure Providers are given access to named IBM alliance manager, and access to business development workshops. In exchange, these partners are expected to use IBM’s cloud infrastructure products or services, demonstrate skills in IBM technology. Like service solution providers they must use and skills in IBM cloud offerings, have at least $300,000 a year in client references based on two cloud client references

• Application Providers are given access to a named IBM alliance manager, and access to business development workshops. They are expected to use IBM cloud products or services, have skills in these technologies or services, and a minimum of $100,000 a year in revenue plus two cloud client references.

• Technology Providers get access to networking opportunites, and IBM’s cloud and services assessment tools.  In exchange, these partners are required to demonstrate knowledge of IBM Cloud Reference architecture, have skills related to IBM’s cloud services. Like application providers, these partners must have at least $100,000 in IBM revenue and two client references.

What does IBM want? IBM’s goals with the cloud specialty program is to make it as attractive as possible for prospective partners to chose its platform. It is hoping that by offering financial and technical incentives that it can make inroads with cloud focused companies. For example, it is openings its labs and providing assistance to help partners define their offerings. IBM is also taking the unusual step of allowing partners to white label its products.  On the business development side, IBM is teaming with business partners on calls with prospective customers.  IBM anticipates that the impact on these partners could be significant – potentially generating as much as 30% gross margin growth.

Will the effort work? It is indeed an ambitious program. IBM will have to do a good job in explaining its huge portfolio of offerings to the prospective partners. For example, it has a range of services including CastIron for cloud integration, analytics services, collaboration services (based on LotusLive), middleware services, and Tivoli service management offerings.  In addition, IBM is encouraging partners to leverage its  extensive security services offerings.  It is also trying to encourage partners to leverage its hardware systems. One example of how IBM is trying to be more attractive to cloud-based companies like Software as a Service vendors to to price offerings attractively. Therefore, it is offering a subscription-based model for partners so that they can pay based on usage – the common model for most cloud platform vendors.

IBM is on the right track with this cloud focused partner initiative.  It is a sweeping program that is focused on provides a broad set of benefits for partners. It is pricing its services so that ISVs can rent a service (including IBM’s test and development cloud) by the month — an important issue in this emerging market.  It is also expecting partners to make a major investment in learning IBM’s software, hardware, and services offerings. It is also expecting partners to expand their knowledge of the markets they focus on.

Even when data centers are able to improve their efficiency, they still do not lack resources.  What data centers lack is the organizational structure to enable provisioning of those resources in a proactive and efficient way.  The converse is also true: data centers lack the ability to reclaim resources once they have been provisioned.

So, I maintain that the problem with the data center is not a lack of resources but rather the management and the automation of those resources.  Imagine an organization leverages the existing physical resources in a data center by adding self-service provisioning and business process rules for allocating resources based on business need.  This would mean that when developers start working on a project they are allocated the amount of resources they need – not what they want. More importantly, when the project is over, those resources are returned to the pool.

This, of course, does not work for every application and every workload in the data center. There are applications that are highly specialized and are not going to benefit from automation. However, there indeed can increasingly large aspects of computing that can be transformed in the private cloud environment based on truly tuning workloads and resources to make the private cloud as elastic as what we think of as a ever expanding public cloud.