Leadership and Project Work
Deborah H. Herting, PMP, CPVA, CPBA

The next generation of Business Leaders will come from today’s project management pool. The same criteria used for C-suite success is executed daily by Project Managers. Project Managers need to be adaptable and understand the interdependence of people throughout an organization. They value communication and use it to build well-functioning teams. In fact, the title, Project Manager, is incomplete. The title should be Project Leader. A Project Leader delegates, negotiates, is politically savvy, navigates organizational complexity and leads their group to success. They utilize social characteristics to positively impact return on investment (ROI). These leaders repeatedly deliver projects on time, within budget and per scope.

For more information, visit our Thought Leadership page to read ‘Leadership and Project Work.’
]]> http://blogs.liquidhub.com/?feed=rss2&p=38268 0 http://blogs.liquidhub.com/?p=38268 http://feedproxy.google.com/~r/LiquidhubBlog/~3/yH0AjjFBmRg/ http://blogs.liquidhub.com/?p=38255#comments Thu, 11 Apr 2013 06:25:19 +0000 admin http://blogs.liquidhub.com/?p=38255 by Peter Classon

When it comes to technology, the evolutionary process never sleeps. Just look at Enterprise Architecture (EA). What started in corporate IT departments as a cutting-edge approach to managing an increasingly large and complex computing environment is now a prerequisite to success. Any organization serious about its future invests time and money in developing, implementing and actively managing their EA framework. Why? Because EA is the great translator. It allows all of a company’s various departments – from marketing and finance to the supply chain and risk management – to make sense of each other. It ensures that everybody is on the same page, speaking the same language. And that makes EA a critical part of any company’s strategy.

But due to competitive pressures and technological innovation, the pace of change in the global marketplace is constant, and EA must adapt and innovate accordingly. Thanks to the recent advancements in Cloud Computing, new technology form factors (think mobile), and the explosion of virtual lives online (think Social Media), technology isn’t just automating prior manual processes, it is becoming the business process. That’s where the next generation of EA comes in. Rather than relying strictly on IT to develop the architecture, business-oriented EA promotes the concept of blending business and IT to drive business goals and strategies, which enables a company to interact with its customers, employees, suppliers and commerce partners in real time across all channels with complete transparency and through numerous technology solutions. Only then can an enterprise can claim to be truly digitized.

At LiquidHub, we have built a comprehensive toolkit for business-oriented Next-Generation EA. Through our experience working in verticals, we have developed expertise across industries and business domains, with specialists who can codify business strategies. For example, a leading North American retail bank client, who was about to spend millions on sound technology strategies for its branch network, asked us to look at a subset of applications to determine if they made sense from a business strategy perspective. Were these apps well suited to the three- to five-year vision of the bank? Were the vendors who supported these apps developing the next-generation banking software? Did the cost of the apps make sense with regard to ROI and NPV for the ‘value’ provided?

The LiquidHub team applied business-oriented EA principles, visiting the vendors and creating capability reference models to show coverage of the apps and whether or not they were in synch with the emerging business strategies. What we discovered was that one app – the biggest one – was outdated technology and wouldn’t support the company’s strategic needs; the second app was supported by a vendor considered highly risky due to size and small customer base so the recommendation was for just an application upgrade; and the third didn’t make financial or strategic sense, as it was a short-term solution soon to be replaced by more comprehensive multi-channel needs facing all banks. In all three cases, we recommended that the client spend a fraction of the original amount to safeguard its current operation and instead invest the money in more long-term goals, such as effective customer engagement, multi-channel interaction technologies and innovative new-model technologies. From an IT perspective, the apps were great; from a business perspective, they were roadblocks to the company’s objectives. That’s how the business-oriented approach works.

Of course, technology is critical. We live in a technology-enabled – and increasingly dependent – world. But as business and technology evolve hand-in-hand, it’s important that companies rethink how to maximize their use of technology through a business lens. Business-oriented EA. That’s the operating model of the future.

Links:
Business-Oriented Architecture Becomes the New Focus

Over the past few years, several trends have appeared on the scene thanks to underutilization and the complexity of managing growing data sprawl. Among those trends is Data-as-a-Service (DaaS). A relatively new concept, DaaS is a cloud-based model that allows users, customers, and consumers to access data on demand, regardless of their own location. Importantly, it represents an opportunity for improving IT efficiency and performance through centralization of resources. With the development and implementation of such technologies as data virtualization, data integration, MDM, service-oriented architecture, business-process management and Platform-as-a-Service (PaaS), DaaS strategies have increased dramatically in recent years.

As the DaaS trend continues to accelerate, so do the questions around it: How do you deliver the right data to the right place at the right time? How do you “virtualize” the data often trapped inside applications? How do you support changing business requirements (analytics, reporting, and performance management) despite ever-changing data volumes and complexity?

Enterprise DaaS strategy & Infrastructure is a core focus area for business unit and enterprise CIOs. Here’s why:

• Enterprise Data Warehouse (EDW) strategies are increasingly moving to cross-enterprise DaaS strategies
• Structured and unstructured data growth is forcing the evolution to DaaS
• As data in application silos move to a centralized corporate/enterprise asset, DaaS infrastructure becomes critical
• To do any form of real-time enterprise analytics, you need DaaS in place first

In the early years of this market, most DaaS was focused primarily on the financial services, telecom and government sectors. However, in the past two years, we have seen a big jump in the number of sectors adopting DaaS, namely healthcare, insurance, retail, manufacturing, e-commerce and media/entertainment.

What is Data-as-a-Service?

We already know that DaaS promotes the concept that data related services – aggregation, quality, cleansing and enriching data and offering it to different systems, applications or mobile users – can be provided and accessed from a centralized location. In addition, DaaS is the major enabler of the Master Data Management (MDM) concept.

Master Data is the Holy Grail of enterprise data management. Most companies focus on a single version of the truth, or Golden Source “Product,” “Customer,” “Transaction” and “Supplier” data. Why? Fragmented, inconsistent product data slows time-to-market and creates supply-chain inefficiencies, resulting in weaker-than-expected market penetration and an increased cost of compliance. Fragmented, inconsistent customer data hides revenue recognition, introduces risk, creates sales inefficiencies, and results in misguided marketing campaigns and lost customer loyalty. Fragmented and inconsistent supplier data reduces efficiency, negatively impacts spend control initiatives, and increases the risk of supplier exceptions.

Here’s where DaaS solutions come in. They provide the plumbing that enables MDM, and have the following advantages:

• Agility (and time-to-market) – Customers can move quickly due to the consolidation of data access and the fact that they don’t need extensive knowledge of the underlying data. If customers require a slightly different data structure or have location-specific requirements, the implementation is easy because the changes are minimal.
• Cost-effectiveness – Providers can build the base with the data experts and outsource the presentation layer, which makes report and dashboard user interfaces more cost-effective. It also makes change requests at the presentation layer easier and more feasible.
• Data quality – Access to the data is controlled via data services, which tends to improve data quality as there is a single point for updates. Once those services are tested thoroughly, they only need to be regression tested, if they remain unchanged for the next deployment.
• Cloud-like efficiency, high availability and elastic capacity – These benefits derive from the virtualization foundation – one gets efficiency from the high utilization of sharing physical servers, availability from clustering across multiple physical servers, and elastic capacity from the ability to dynamically resize clusters and/or migrate live cluster nodes to different physical servers.

DaaS Use Cases

Organizations are looking to solve tough data and process-integration challenges as they start to invest in new business capabilities again. As they explore new opportunities, they also have to make choices that will help both streamline and propel the enterprise forward. DaaS is making geographic or organizational separation of provider and consumer an obsolete notion, while the emergence of Platform-as-a-Service, or PaaS, along with service-oriented architecture (SOA), is rendering the actual platform on which the data resides irrelevant as well.

DaaS has many use cases for the enterprise:

1. Providing a single version of the truth
2. Integrating data from multiple systems of record
3. Enabling real-time business intelligence (BI)
4. Processing high-performance scalable transactions
5. Federating views across multiple domains
6. Improving security and access
7. Integrating with cloud and partner data and social media
8. Delivering real-time information to mobile apps
9. Conducting an enterprise-wide search

DaaS Elements

Say a client decides it’s time to take the next step. Where does that client begin to enable MDM strategy and build a data-as-a-service offering for the rest of the organization?

These are the elements a company needs in order to take that next step:

1. Data acquisition – It can come from any source, including data warehouses, emails, portals, third-party data sources
2. Data stewardship and standardization – Boil it down to a standard manual or auto-magic
3. Data aggregation – Stick build data warehouse for acquisition. This has a strong service and technology-driven quality-control mechanism, which is very different from “let’s write 100 ETL programs”
4. Data servicing – Via web services, extracts, reports, etc. Make it easy for the end user to consume the data, either via machine-to-machine or directly through the reporting universe

All of these capabilities come together around the data logistics chain. The last few decades have seen a dramatic shift in how companies handle data. Increasingly, they are shifting away from hierarchical, one-dimensional enterprise data-warehouses (EDW) with fixed data sources to a fragmented network of strategic partnerships with external data sources. Not surprisingly, this phenomenon causes ripple effects throughout the old data logistics network. DaaS at its core can address this problem of fragmentation.

Behavioral Politics around DaaS

In many organizations, the individuals who own the data have control. They can determine who is in the know; they can shape the “story.” One of the key benefits of DaaS is fast, low-cost access to the data. Removing barriers to data access will impact current data owner’s level of control.

So a best-practice case study informs us that a DaaS effort focused on critical enterprise data must be a joint effort between business and IT, and often requires senior executive (e.g. CEO, CTO, etc.) support to get past the potential problem of ownership issues. Senior-level engagement is typically driven by ROI business cases, and this may be part of an engagement or offering.

The challenge for DaaS may be more around organizational alignment than technical deployment. A key driver of a DaaS environment is the integration of data from multiple systems of record. Those different systems are likely to have different data definitions and hierarchies. In these types of situations, metadata management and data integration services are critical.

In addition, the market leaders want to position themselves as experts who know and understand the underlying data, largely so that everyone else in the organization doesn’t have to become one. As a result, domain expertise is a crucial component to any successful DaaS strategy.

Summary

As a combination of applications and technologies, DaaS consolidates, cleans and augments source enterprise data, and synchronizes it with all applications, business processes and analytical tools. The goal behind it is to achieve significant improvements in operational efficiency, reporting and fact-based decision making. To that end, key requirements of any DaaS strategy include domain knowledge, application knowledge, people/talent, processes and technology platforms.

Notes

1) Platform as a Service (PaaS) is being applied to Enterprise Data

When it comes to technology, the evolutionary process never sleeps. Just look at Enterprise Architecture (EA). What started in corporate IT departments as a cutting-edge approach to managing an increasingly large and complex computing environment is now a prerequisite to success. Any organization serious about its future invests time and money in developing, implementing and actively managing their EA framework. Why? Because EA is the great translator. It allows all of a company’s various departments – from marketing and finance to the supply chain and risk management – to make sense of each other. It ensures that everybody is on the same page, speaking the same language. And that makes EA a critical part of any company’s strategy.

But due to competitive pressures and technological innovation, the pace of change in the global marketplace is constant, and EA must adapt and innovate accordingly. Thanks to the recent advancements in Cloud Computing, new technology form factors (think mobile), and the explosion of virtual lives online (think Social Media), technology isn’t just automating prior manual processes, it is becoming the business process. That’s where the next generation of EA comes in. Rather than relying strictly on IT to develop the architecture, business-oriented EA promotes the concept of blending business and IT to drive business goals and strategies, which enables a company to interact with its customers, employees, suppliers and commerce partners in real time across all channels with complete transparency and through numerous technology solutions. Only then can an enterprise can claim to be truly digitized.

At LiquidHub, we have built a comprehensive toolkit for business-oriented Next-Generation EA. Through our experience working in verticals, we have developed expertise across industries and business domains, with specialists who can codify business strategies. For example, a leading North American retail bank client, who was about to spend millions on sound technology strategies for its branch network, asked us to look at a subset of applications to determine if they made sense from a business strategy perspective. Were these apps well suited to the three- to five-year vision of the bank? Were the vendors who supported these apps developing the next-generation banking software? Did the cost of the apps make sense with regard to ROI and NPV for the ‘value’ provided?

The LiquidHub team applied business-oriented EA principles, visiting the vendors and creating capability reference models to show coverage of the apps and whether or not they were in synch with the emerging business strategies. What we discovered was that one app – the biggest one – was outdated technology and wouldn’t support the company’s strategic needs; the second app was supported by a vendor considered highly risky due to size and small customer base so the recommendation was for just an application upgrade; and the third didn’t make financial or strategic sense, as it was a short-term solution soon to be replaced by more comprehensive multi-channel needs facing all banks. In all three cases, we recommended that the client spend a fraction of the original amount to safeguard its current operation and instead invest the money in more long-term goals, such as effective customer engagement, multi-channel interaction technologies and innovative new-model technologies. From an IT perspective, the apps were great; from a business perspective, they were roadblocks to the company’s objectives. That’s how the business-oriented approach works.

Of course, technology is critical. We live in a technology-enabled – and increasingly dependent – world. But as business and technology evolve hand-in-hand, it’s important that companies rethink how to maximize their use of technology through a business lens. Business-oriented EA. That’s the operating model of the future.

links

Business-Oriented Architecture Becomes the New Focus

#3 Teambuilding and Project Work
By Deborah H. Herting, PMP, CPVA, CPBA

Peter Drucker says that leaders “don’t think “I.” They think “we;” they think “team.” I agree! Effective teambuilding is about finding a way to connect with others, build relationships and establish an environment of collaboration, encouragement, trust and respect. It’s about rewarding successes yet cohesively supporting each other when the going gets tough. And, for those who have managed projects, there is an understanding that multiple challenges occur during execution as each project journeys toward successful delivery.

So, how can a project manager build a team where its members want to work together and are supportive in the best and worst of times? To begin, it’s prudent for the project manager to be disciplined at project initiation. They set expectations. As the team proceeds through Tucker’s model of forming, storming, norming, performing and adjoining, an intuitive leader will know when the team starts functioning as a unit. As the team becomes self-functioning, with team members caring and sharing for one another, trust increases. The project manager can step back from day to day tasks and re-direct from a managerial role to that of increasing leadership oversight. The project manager provides team direction, continues to build stakeholder relationships and proactively manages risks and issues.

Lastly, communication is key. It is important to openly communicate and elicit feedback. Included in feedback is active listening and adapting as necessary. To promote teamwork, taking the time to level-set terminology and to find common agreement needs to be a priority. When team members “buy into” the initiative they will work harder. Also, when their voices are heard they will relax and tend to be more creative. When open communication takes place, all stakeholders remain informed; all questions are answered and risk is mitigated.

Teambuilding is an art which over time and with practice can mean the difference between successful project delivery or a failed project. Think “we” not “I” and build a team that communicates openly and wants to invest their time and talents into the initiative. At delivery everyone will be celebrating a collective success and realize their individual contributions helped to make it happen. Project management is 80% art and 20% science (Steven W. Flannes, PhD and Ginger Levin, DPA).