BI Competency Centers: Do CFOs Help or Hinder?

Intelligent Enterprise Editor-in-Chief Doug Henschen moderated a webinar last week titled “Business Intelligence Competency Centers (BICCs): Many Choices, Many Pitfalls” sponsored by Forrester Research. With BI now considered “table stakes,” panelists Boris Evelson and James Kobielus of Forrester, BI consultant Claudia Imhoff and Capgemini’s Joe Moye discussed how enterprises can drive greater value from their BICC investments.

One recommendation was to cross-pollinate BICCs with other CCs in areas such as Business and IT Governance; Enterprise Architecture; Data Warehousing, Data Quality and Data Integration; ERP, CRM, Supply Chain Management, etc. While this makes perfect sense, doesn’t it seem ironic that we still need to encourage coordination after the costly lessons we (hopefully) learned from propagating BI application stovepipes?

Side note: With many of the CCs above revolving not just around competencies but applications and processes, it was interesting that James suggested BICCs be renamed BISCs (BI Solution Centers). We'll keep an eye on a Forrester report in queue on this topic for October.

The idea of coordinating CCs reminds me of conversations I’ve had with an aerospace and defense company that extended their BICC with specialized data integration technology for key applications. As a result of tapping into finance data, the company is supporting deeper BI analytics based on time-sensitive operational insights.

To boost synergy between CCs, one panelist suggested overlapping them and allowing personnel on the teams to create hybrid roles. This brings to mind the success story of a cosmetics company that adopted a war room approach to unite IT and line of business experts for projects.

The most interesting part of the discussion involved who should own a BICC: IT or line of business. Not surprisingly, opinions varied, with Evelson advocating for ownership by C-level business executives and Imhoff taking a more IT-centered approach. Evelson added that most of the successful BI environments he’s seen have had strong business ownership (for more check out his keynote at the Computerworld BI Perspectives conference Sept. 8th). Imhoff underscored the need for technical acumen beyond the skills of the business analyst – areas such as data integrity, data quality and database performance. (Rajan Chandras takes this a step further on his Intelligent Enterprise blog post, urging readers to explore the qualifications needed to influence BICC success)

Imhoff asserted that CCs should not report to the CEO’s or CFO’s offices, going so far as to suggest that CFOs may infuse too much of a finance or accounting flavor. It’s hard for me to imagine many business decisions that don’t impact profitability, competitive advantage or shareholder value, but since time ran out on the webinar, let’s open up that part of the discussion here.

What do you think? Are CFOs the best stewards of these BI centers?

Continuous Planning Architecture, Phase 2

Back in April, Kimberley Bermender posted on the finance systems architecture needed to support a continuous planning environment. The overall design goals included:

• Lower cost of maintenance,
• Standards-based data integration,
• Support of accurate, near real-time views into operations,
• A platform to support detecting, modeling, selecting and implementing change and then measuring results.

The main ingredients were:

• financial and operational data stores,
• an analytic (OLAP) engine – with reporting, and
• planning applications

Inherent in the architecture is the movement of data between data stores and OLAP cubes, as well as fact and metadata management. To build on that architecture, “phase 2” can include two other components that build on those design goals and get you closer to enterprise performance management nirvana.

The first is master data (or ‘reference’ data) management, and the second is a common enterprise performance management rules or calculation engine.

Master data management includes the tracking and control processes of data relationships (especially hierarchies) and instances across the enterprise. For example, product sales for a store in Ft. Collins, CO could roll-up to a ‘Central’ region one quarter, and then to the ‘West’ region the next quarter after a re-org. It’s important to keep track of which region it belonged to when doing quarter over quarter comparisons and other management reporting (not to mention statutory reconciliation and reporting). And that hierarchy could be contained in the store reporting application, the sales forecasting system, the G/L, the customer relationship management (CRM) system, and so on. Right now, those relationships are probably being manually managed and ‘lightly’ controlled. Our more complex financial systems require more automation and more rigorous control over master/reference data. And it certainly addresses at least the first 2 design considerations of Kimberley’s architecture.

For more on master data, see this DMReview landing page.

The second component is a central business rules/calculation engine. In any enterprise performance management environment, users can easily get bogged down in the definitions of data and information. For example, that Ft. Collins store could be looking at a ‘revenue’ report and not know if it’s booked revenue, commissionable revenue, recognized revenue, and so on. And even when they find out what kind of revenue it is, there can be a question of it’s accuracy: how did head office calculate it, where did they get the data from, and does it include intercompany sales or not?

Having one business rules engine lets the enterprise define ‘recognized revenue’ once, with control over the algorithms, the data refresh frequency, the data sources, and so on. Once the rules engine has certified a number, it can be used by all other enterprise performance management systems: planning can use it for prior actuals, strategic financial models can use it for long term scenarios, same store sales dashboards can use it for ranking, and so on.
The three-fold goal is to get better transparency into financial information (how did we get that number), better accountability (finance owns and certifies the number), more efficiency (define it once, don’t reinvent the wheel), and ‘believe-ability’ (start debating what to do about the results, not where the number came from).

Here’s a good article by Robert Blasum in DM Review on central rules (he also connects them to master data management)

Thanks to Kimberley and the team for letting me guest blog, please feel free to visit the Business Foundation blog over at http://businessfoundation.typepad.com/