“Half the money I spend on advertising is wasted; the problem is I don’t know which half.” – John Wanamaker, a pioneer in modern advertising

We can say the same of enterprise investment in BI, analytics, and big data. Even after over 20 years of attempting to build centralized, scalable information architecture, we found that only a small percentage of an organization’s data is converted into useful information quickly enough to leverage it for better insight and decision making.

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 ideally would like to serve.

Leadership Challenge – The Journey to World-Class

How do you create world-class data-driven insights? If you’re an executive, manager, or team leader, one of your toughest responsibilities is managing and organizing your BI, Reporting, and Analytics initiatives. While the nuances – skillsets, toolsets, mindsets, and datasets – are different for each initiative, the fundamentals of managing, organizing, and structuring are essentially the same.

Almost every Fortune 1000 company’s management is increasingly focused on monetizing data – small data, big data, fast data – and how to gain a real-time competitive edge from their information. How can companies 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, CoE’s, or Shared Services models are structural enablers that enable the corporate strategy to create an enterprise that utilizes data and analytics for business value.

BI CoE’s 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

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, and/or platform development.

Evolution of BI/Reporting/Analytics

  • Data – volume, variety, velocity – is growing faster than budgets
  • Modifying large, existing applications is NOT the path forward
  • Demand is growing, speed to insight is crucial
  • Skills are lagging, new tooling

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

  • Phase 1: 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 department islands satisfied the initial needs of the business, but early success in departmental deployment sowed the seeds for new problems as the applications grew.
  • Phase 2: Successful applications and platforms always expand. The second phase of Analytics (and BI) is where there is tremendous growth, and platform solutions are no 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 truth through the multiple disparate BI systems, and there is not a 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 the one where executives have 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, a costly self-service environment, static reports, departmental solutions, and other issues (figure 2.1) 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 their analytics team, (3) Accelerated product innovation, and (4) 20% reduction in BI support costs.

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Summary

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.

A big reason for establishing a BI CoE is better execution and change management. For BI to take hold as a strategic capability you have to change the culture (how things have historically 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
  • Showcase success, encourage, and reward learning (learn from failure!)

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