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Unleash the Power of the CFO

A holistic approach to finance information yields enterprise-wide results.

by Tim Duning and Chet Robinson

Recent global economic turmoil has significantly increased the influence of CFOs in the corporate board-room. More than ever, they are expected to guide and inform a company’s most strategic and critical decisions. As they take up this challenge, however, many are impeded because their organizations’ finance information is too often scattered in disparate silos making it inconsistent, incomplete and inaccessible.

Small wonder that nearly 60% of finance executives say they spend too much time collecting and aggregating data or would like to rely less on IT to access and analyze data, according to a 2010 TDWI Best Practices Report, “Transforming Finance: How CFOs Use Business Intelligence to Turn Finance from Record Keepers to Strategic Advisors.”

A key driver of this complexity is the fact that the finance function involves myriad tasks including revenue reporting, cash management, procurement, budgeting and forecasting, treasury and profitability analysis. The requirements of these multiple functions are a microcosm of the enterprise data management struggle.

The diverse needs of various finance teams often lead to inflexible, siloed data environments, which develop over time as individual groups, operating under tight deadlines, create their own quick fixes instead of taking a systematic approach in sync with the needs of their colleagues. The result is both inefficiency and duplication.

The Big Picture

What’s needed is a holistic approach to enhance the CFO’s ability to get an integrated, detailed view of performance that meets stakeholder expectations. A next-generation reference architecture—with a data warehouse acting as the platform for integrated information—can accomplish this by delivering a more complete view across all finance functions while building consensus among them and their supporting IT resources.

The Value of Being World-Class

Shareholders find investing in world-class companies financially rewarding. The Hackett Group, a leading global consultancy, produces an annual report on the best practices observed among its clientele of Fortune 500 companies.

It identifies as world-class those companies in the top quartile of both efficiency (executing at the lowest cost for the greatest return) and effectiveness (focusing on the right strategic activities). On average, world-class companies have a finance cost as a percentage of revenue that is almost half that of their peers (0.60% vs. 1.13%) and produce a return on equity that is 2.4 times that of their peers.

To illustrate this point, consider this hypothetical scenario from Narian Entertainment Inc., a fictitious enterprise:

Clark Reynolds, financial planning and analysis manager, is charged with preparing a six-month profitability projection for the company’s MP3 music player that is sourced or manufactured from locations in Taiwan, France and Texas. The CFO suspects the item’s contribution margin is deteriorating and wants a recommendation on whether to discontinue it.

An IT project on costing at the individual product ID level would be great for this type of request, Reynolds knows, but it is unlikely because such CFO requests come only once every three or four quarters. To build his case, he instead relies on two analysts: George Adams in Financial Reporting and Margaret Chu in Purchasing.

Adams struggles because the monthly data he receives for financial reporting from the enterprise resource planning system does not break out results to the level of the MP3 player. It would take three days to get a flat file dump from the invoicing and payables system in Texas and even longer to get cost details from Taiwan and France. Plus Adams anticipates losing another day or two receiving, validating and consolidating the data from multiple sources.

While Chu has access to the purchase costs for the materials used to make the MP3 player from the three sites, she is never sure that the cost basis and definitions are consistent. For example, she has found instances in which sales tax and shipping costs were handled differently by location, making it an ongoing ordeal to get a consistent definition of product cost.

Then there’s the inability to systematically manage vendor master data and hierarchies in a way that provides a clear understanding of supplier relationships. Time and again Chu has uncovered separate procurement contracts with multiple suppliers owned by a common parent company. As a result, Narian is missing out on substantial quantity purchase discounts that a single procurement contract with the parent company would provide.

With only four days to report to the CFO, Reynolds must make do with the incomplete information—mostly historical and projected gross margins—his team can muster. Based on this, he makes his best recommendation and hopes it isn’t too flawed.

They may not realize it, but Reynolds, Adams and Chu would all benefit from a targeted data management initiative that established:

• One central system for product costs
• A data management structure that assigned consistent cost definitions and associated allocation calculations
• Consistent vendor master data and hierarchy management tools
• Self-service BI tools that leverage a common data source and speed data access

Finance managers from many companies face these same types of obstacles. Each function tends to see its problems in a vacuum and fails to recognize how an improved information environment could benefit not just them but many of their colleagues. And most teams would struggle to build separate business cases that would persuade IT to address their respective challenges. What they don’t understand is that one focused project built around a reference architecture could yield benefits for all of them.

Understand Each Other

Enterprises that leverage a centralized data warehouse lead their peers in efficiency and effectiveness. According to The Hackett Group’s 2010 Finance Book of Numbers, world-class companies use data warehouses or data marts to support business performance initiatives by a ratio of more than 2-to-1 as compared to their peer group.

7 Key Elements Make up the Next-Generation Reference Architecture

Click to enlarge

A next-generation reference architecture seamlessly integrates seven key elements that all finance information delivery systems require (see figure):

1. Data warehouse foundation. Consisting of the finance-specific elements of an enterprise data environment, a finance data warehouse (FDW) is uniquely capable of serving as a systems integration platform that both links financial details to the operational data, and simplifies provision of consistent data to countless applications and users.

2. Data sourcing. User confidence is ensured by moving data from source systems into the FDW where it is transformed. This provides the transparent audit trail needed to tie exact copies of source transactions to the transformed data in the FDW.

3. Accounting hub. To ensure integrity of the FDW, it must reconcile reliably to the general ledger (GL). An accounting hub enables transparency into the complex aggregations and accounting rules that turn operational system transactional data into summary automated postings in the GL. This provides for a three-way reconciliation among the FDW, GL and operational systems.

4. Financial and human capital data integration and analytics. General ledger, human resource and other key enterprise resource planning data are critical elements of financial analysis. Data integration and analytics capabilities source and organize this data in the FDW into a business context for different finance functions (e.g., GL, procurement or payroll) to speed analysis and report development.

5. Calculation engines and applications. A complete infrastructure must integrate pre-packaged software applications and calculation engines with standard business rules that deliver enterprise-wide profitability, risk, planning, forecasting and allocation capabilities.

6. Business intelligence (BI) and reporting tools. To field ever-evolving information requests, analysts need an ad hoc environment that provides access to data from multiple sources. If several BI tools exist within an enterprise environment, a common data warehouse foundation where metrics and calculations are managed helps drive consistent results across tools.

7. Data management. To ensure that analysis recommendations are as sound as possible, transparency, data quality and common rules application throughout the data lifecycle is critical. A well-executed data management strategy secures an auditable trail from source to end report.

—T.D. and C.R.

Defining a simple architecture and the role of the components within makes it easy to visualize joint opportunities across business and IT departments to resolve information problems and build a roadmap for continuous improvement.

To do so, IT needs to recognize how integrating data from numerous systems into a warehouse and using it as an integration platform for various finance applications will reduce infrastructure costs and improve responsiveness. At the same time, finance must grasp how access to reliable, relevant and actionable information can enable significant, renewable process cost reductions in areas like procurement and financial reporting while empowering professionals to gain new insights that increase profitability. Odds of success are maximized once each audience understands the other.

Tim Duning works as a solutions development director within the Teradata Finance and Performance Management team.

Chet Robinson is a communications and deployment manager with the same team.