Center-of-excellence analytics models, in which functional departments have analytics groups,

Everyone has data, but the more elusive goal is getting value out of that data  The growing challenge in corporations is how to organize for “data as a platform.” What is the right organizational structure that will help monetize data?

John Wanamaker, considered a pioneer in modern advertising, said: “Half the money I spend on advertising is wasted; the problem is I don’t know which half.” Today, we can say the same of enterprise investment in business intelligence (BI), analytics, and big data.

Even after doing their best for over 20 years to build centralized, scalable information architecture, I found that only a small percentage of organizations’ data is actually converted to useful information in time to leverage it for better insight and decisions.

At both strategic and tactical levels, much of this gap can be explained by the fundamental disconnect in goals, objectives, priorities, and methods between IT professionals and the business users they should ideally serve.

The other challenge facing leadership is the rapid evolution of the data platform (see below.)  How do you create strategies that adapt to a changing landscape?

Leadership Challenge

How do you become a world-class data-driven firm? What portfolio of projects do you execute to mature the capabilities?

If you’re an executive, manager, or team leader, one of your toughest responsibilities is managing and organizing your BI, Reporting or Analytics initiative. While the nuances – skillsets, toolsets and datasets — are different for each initiative, the fundamentals of managing, organizing and structuring are pretty much the same.

Almost every Fortune 1000 company’s management is increasingly focused on monetizing small data, big data or fast data, and how to gain a real-time competitive edge from their information. How can firms achieve positive returns on their analytic investments by taking advantage of the growing amounts of data?

So what’s the right organizational model that will help them achieve the “ten second advantage”? Competency Centers, Centers of excellence (CoE) or Shared Services models are execution models to enable the corporate or strategic vision to create an enterprise that uses data and analytics for business value.

The goal of every World-class CoE is the same – enable the right combination of toolsets, skillsets, mindsets and datasets for better, faster, cheaper and more repeatable analytics, reporting or platform development.

Evolution of BI/Reporting/Analytics

• Data is Growing Faster than Budgets
• Demand is Growing, Speed to Insight is Crucial
• Modifying large, existing applications is NOT the path forward.
• Skills are lagging.. New tooling

As a result, Enterprise BI and Analytics strategies need to evolve.  The evolution tends to happen in 3 phases:

• Department Solutions – Many companies deploy Analytics (and BI) applications as departmental solutions, and in the process, accumulate a large collection of disparate BI technologies – SAP Business Objects, IBM Cognos, Microstrategy, Oracle OBIEE, Microsoft, Qlikview, Tableau, Spotfire etc. – as a result. Each distinct technology supported a specific user population and database, within a well-defined “island of analytics.” At first, these dept islands satisfied the initial needs of the business, but early success in departmental deployment sowed the seeds for new problems as the applications grew.
• Successful applications and platforms always expand. The second phase of Analytics (and BI) is where there is tremendous growth and  platform solutions are longer isolated islands. Instead, they overlap in user populations, data access, and analytic coverage. As a result, organizations are now faced with an untenable situation. The enterprise is getting conflicting versions of the truth through the multiple disparate BI systems, and there is no way to harmonize them without an extraordinary ongoing manual effort of synchronization, validation and quality checks. Equally problematic is the fact that business users are forced to use many different BI tools depending on what data they want.
• The third phase of Analytics (and BI)  is one where the executives had enough. They simply make a decision to rationalize to a single platform or a centralized model that is sold as a “magic nirvana” solution…delivers one version of the truth (golden source of data) to all people across the enterprise. It can access all of the data, administer all of the people, eliminate repetitive data access, reduce the administrative effort, and reduce the time to deploy new BI applications.

“Time to decisions, scope of decisions, disconnected toolsets and cost of decisions” is deemed unacceptable within & across functional areas.  This typically drives a new phase… centralized BI, Reporting or Analytics CoE.

For example, at a Fortune 500 company, costly self-service environment, static reports, departmental solutions and other issues (shown below) forced them to re-think and re-engineer their enterprise BI solution. The firm set new target objectives…(1) Shorter time to insights; (2) Greater leverage for analytics team; (3) Accelerated product innovation and (4) 20% reduction in BI support costs.

While centralization of BI, Reporting and Analytics can enable organizations to reduce their IT delivery costs by up to 40%. However, a failure to align the level of BI, Reporting and Analytics centralization closely to long-term business and IT strategic goals and to manage the transition to centralized delivery carefully can not only erode expected savings from centralization, it can increase the cost of delivering IT services by up to 30-45% compared to a pre-centralization baseline.  This where good management can make a big difference.

BI CoE Elements for Faster, Better, Cheaper Execution

BI CoE (could be Analytics CoE,  Big Data CoE or Integration CoE) is an organizing mechanism to align People,  Process,  Technology and  Culture.  The target benefits include:

• Better collaboration between Business and IT
• Increased adoption and use of BI and Analytics in the lines of business.
• Better data management, quality and reporting
• Cost savings from eliminating redundant functions

CoE elements include:

BI Shift:  Moving from Department Focus to Enterprise

As BI moves from departmental focus to enterprise level, the BI CoE structurally can take four different models depending on reporting structure. They can be part of an IT unit reporting to the CIO.  They can be a functional shared services model. They can be part of the corporate shared services model that is leveraged b y all divisions.  Where it reports does matter in terms of influence and scope.

Center of Excellence also make sense in environments where BI is moving from a departmental project focus to a strategic program focus. A tactical “Project” focus has these characteristics…..

• Start & end date with narrow problem or department scope/focus
• Sub-optimal organization and use of skills
• Information & decision latency inadequately addressed

A more strategic “Program” focus has these characteristics….

• Whole-process view; Promoting collaboration and analytic best practices
• Data and analytics managed as strategic assets (shared services)
• Business and IT share ownership of the information environment
• A central point for developing and evolving the analytical infrastructure

If you have a charter to facilitate and promote BI and analytics to achieve business objectives across functional and geographic areas then the CoE model is the right one for you.

Centers of excellence, especially when applied to BI, analytics, performance management processes, can help to address the pain of fast-moving technology, time-to-market compression, and marketplace dynamics that grow more complex by the day.

The complexity of a typical BI and Analytics stack today is astounding. Without a dedicated team and pooled expertise it is hard to imagine how any large organization can navigate the landscape below.  And this is only the technology view if you add the business/functional apps layer then you get a whole different view.

Managing the Complex Information Stack

The biggest challenge facing corporations is the explosion of data and tools (see figure above).

The complexity of the information management stack in a large enterprise is mind boggling. The need to simplify, consolidate and leverage is often a  core driver for establishing a BI  CoE. The opportunity is in helping different business units  and functions capture, analyze and manage all that data and disparate technology tools/platforms.

The “Raw Data -> Aggregated Data ->  Contextual Intelligence -> Analytical  Insights -> Decisions” is a differentiating  causal chain separating winners from the  rest today.  Bringing consistency,  repeatability, reuse and process to this  information supply chain requires  discipline.

As companies have become more global and complex – and simultaneously more integrated – the need for cross-collaboration and more leverage of available resources via a shared services model has become a priority.

That is the reason why best-in-class firms are implementing BI Center of Excellence (CoE) (also called BI Shared Services or BI Competency Centers) for better leverage of investments in people, process and tools/applications.

Organizing a BI/Reporting/Analytics CoE

Most organizations have a mix of BI platforms today. They can be departmental silos, some integrated platforms and some that have a next generation “data-as-a-service” enabling model.

A BI CoE must eventually support all of these models as legacy, current and new all have to be managed.

The objective of establishing BI CoE’s is to create economies of scale by pooling and sharing expertise, people, process and tools/applications rather than letting it become dedicated (or trapped) in departmental, Line of Business (LoB) or functional silos.

The BI CoE defines the structure — roles, responsibilities and processes – and resource mix – onshore or offshore, analysts to administrators — that enable the better execution of enterprise wide projects (especially in global, multi-LoB or matrix organization models). The shared services model is becoming pretty common in public and private sector IT for a variety of apps and infrastructure programs – centralized e-mail; data centers, SAP CoE, Oracle CoE etc.

An analytics CoE builds on the BI platform and provides an integrated environment for predictive and descriptive modeling, data mining, text analytics, model management, forecasting, optimization, simulation, experimental design and more.

The concept of a BI CoE is not new. As early as 2001, Gartner wrote that companies need a BI Competency Center approach (BICC) to develop and focus resources to be successful. Since then, the BICC concept has evolved through various implementations.

What does a BI CoE Actually do?

A BI CoE has responsibility for the program and portfolio governance, projects, vendor management, practices, software, architecture, infrastructure, and software licenses. It is responsible for building and executing the plans, priorities, infrastructure, and competencies that different groups need. Typical range of functions in a BI CoE include:

• Contract management
• Management of licences
• Support/Help desk BI
• Business Analytics
• Data model management
• Data warehouse administration
• Architecture
• Solution Management –  New Features, Enhancement and Upgrades
• Production system management
• Consulting to business units
• Prioritization of BI projects
• Management of Strategy
• Training and Change Management

A well structured BI CoE drives various enterprise-wide data integration initiatives, including data warehousing, data migration, data consolidation, data synchronization, and data quality, as well as the establishment of data hubs, data services, cross-enterprise data exchange, and integration competency centers.

There are a variety of roles within a BI CoE – Executive Sponsors, BI Leadership, Program and Project managers, Business Analysts, Architects, Administrators, Developers, Data Stewards, Data Modelers, and Data warehouse analysts.

A BI CoE’s influence transcends that of a typical business unit implementation, playing a crucial central role in creating the framework for Service Level Agreements (SLA), business change management and strategic roadmaps. The BI CoE via the PMO, ensures that information and best practices are disseminated and shared through the entire organization so that everyone can benefit from successes and failures.

The BI CoE also plays an important change management role facilitating interaction among the various geographies, cultures and units within the organization. Knowledge transfer, enhancement of analytic skills, coaching and training are central to the mandate of the BI CoE.

The figure below from Data Management Association (www.dama.org) captures the data management foundational elements and the overarching management elements that need to be in place to pull it together.

BI CoE – Managing the Project Lifecycle

A key aspect of the BI CoE is to manage and make critical decisions  along the end-to-end lifecycle of the project. This is not easy to do in a large corporation with multiple stakeholders.

Creating the Business Case for BI CoE

BI and analytics investments are skyrocketing as companies come out of recession.  To manage these investments a BI CoE structure makes sense.  The business case drivers include:

• Operational efficiency —More-effective support and use of information. More-relevant, accurate, consistent and timely information.
• Strategic transformation —Use information to transform enterprise performance.
• Lower Total Cost of Ownership (TCO) — More-efficient use of technology. Remove technical and operational obstacles and redundancies.

Despite the drivers, the best-practice companies undertake BI CoE models after a few successful implementations of BI at various departments and business units.  The business case is to ensure the following:

• Make sure BI investments are closely tied to enterprise strategy (Cost Savings, Cost Avoidance, Risk Avoidance, and Better Reporting)
• Make sure BI Infrastructure, Platforms, Tools, Applications and People investments are coordinated
• Make sure there is singular focus and direct accountability for BI, analytics and performance management programs.

The time of BI CoE has come.  “Data -> Intelligence -> Insights -> Decisions” is a core causal chain in business execution. The previous execution of BI was about recording transactions in large data warehouses with rather simple front-end analytics. Today, the BI applications are about users extracting, manipulating, and analyzing the data on demand so they can create insights and make better decisions.

Summary

It’s becoming a data-driven world. Every firm is awash in data, but the problem is figuring out how to organize so we can do something about it.

A BI CoE is a cross-functional shared services structure for supporting the effective implementation of BI, Performance Management, Information Management and Analytics across an organization.

BI CoE role is primarily to:

• Consolidate specialized expertise
• Foster and grow the analytical community;
• Ensure extensible infrastructure;
• Establish BI and Analytics as a repeatable process
• Assess optimal mix of capabilities, tools and paradigms for skill levels and evolve as needed

A big reason for establishing a BI CoE is change management. For BI to take hold as a strategic capability you have to change the culture (how things have always been done).   Culture is the hardest to change, but very important!

• Align the organization with the strategic direction and sustainable value creation
• Value data and information as strategic assets
• Best practices continuously refined and promoted
• Show case success, encourage and reward learning (learn from failure!)

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A good decision,  made in the absence of knowledge,  is merely a lucky one.

Notes and References

1. http://en.wikipedia.org/wiki/Center_of_excellence
2. BI CoE’s are often referred to as BI Shared Services or BI Competency Center.
3. http://www.sas.com/consult/bicc.html
4. How to Establish an Analytical Center of Excellence to Maximize the Value from Your Data and Analytics Investment (http://support.sas.com/resources/papers/proceedings10/173-2010.pdf)
5. See also http://www.niteo.com/BICenterExcellence.html for a perspective from NEC on how to structure a BI CoE.