Now, more than ever, competitive advantage in business is dependent on gathering financial data, analyzing it and providing current revenue and expense information on products, customers, channels and staff. The ability to ask financial questions and get fast, accurate answers is critical for informed decision making.

Many companies are evaluating various options to achieve this and are investing in data warehouses and data marts to access corporate-wide data. One popular option is to implement a financial data mart. The core value of this decision support tool is the assurance of a single answer to a given question, a single-version-of-the-truth, no matter which user is making the inquiry.

A financial data mart can provide a secure environment for analysis and reporting capabilities for product profitability, activity-based costing, performance measurement and executive information systems (EIS). This fully integrated solution addresses the critical areas of financial reporting and analysis with standardized business rules, processes and procedural calculations.

Why a data mart? Why not an integrated enterprise data warehouse containing financial information? A fully integrated data warehouse is the right answer, but considerations of time and resources drive many companies to look for options. According to a recent International Data Corporation (IDC) report, "The average cost of a data warehouse effort is $2.2 million for hardware, software and people."1 Few companies or business units can afford to wait years or spend millions before realizing the benefits of a data warehouse. Many companies, therefore, use data marts which typically require smaller amounts of source data, fewer data elements to define, fewer business rules to develop for the data transformation/mapping process and simpler data models--making data marts a quick, iterative solution to accessing and analyzing corporate information.

Following are eight critical steps to successful data mart implementation:

  1. Identify and gain support from a business sponsor--who can help develop a clear business case for developing and controlling the scope of the financial data mart.
  2. Define your business requirements and critical success factors. Some of these business requirements may be key ratios or user benefits such as: identifying security and control needs; defining access requirements--Internet, centralize or local access; and determining level of summarization or access to "drill through" to the core data warehouse or operational data store for additional detail.
  3. Understand data sources and business rules. Identify business rules for data cleansing, data source extract logic and meta data. This can be more complicated and time consuming than originally expected, sometimes consuming over 50 percent of the development effort by business users, data architects, data analysts, data modelers and database administrators.
  4. Architect the financial data mart in the context of a high-level strategic data warehouse. Develop the overall framework, strategy and technology for an enterprise data warehouse with incremental subject-oriented or business-unit oriented data marts.
  5. Use an integrated tool set. While a "best-of-breed" approach for data warehouse tools such as ETT (Extract, Transform, Transport), CASE and OLAP may be appropriate for large IT organizations with the technical resources to support multiple vendors and potential integration issues, an integrated toolset from one vendor is more practical for organizations with limited resources.
  6. Use a data warehouse methodology. Business users and IT staff should follow a framework that enforces discipline and ensures rigorous and thorough analysis, design and implementation. A methodology acts as a checklist for identifying and resolving problems and concerns. Use available ETT and OLAP templates and best business practices.
  7. Use prototypes, early and often. During the analysis and design stages, prototypes can be used to demonstrate and validate concepts and functionality with ETT and OLAP tools. They allow business users and IT team members to learn new concepts and software capabilities. Prototypes also allow team members to provide feedback and validate design assumptions.
  8. Work with business partners. For an initial or time-critical data mart project, engage support from software, hardware, communications and consulting partners. This approach will become a cornerstone of a successful implementation by establishing a cooperative environment for obtaining additional technical or business resources to help solve complex design and development issues.

The financial data mart is an invaluable business tool that provides an integrated data source for improved management reporting and profitability controls with shorter closing and budgeting cycles. It increases the accuracy of budgets, forecasts and productivity results to enhance corporate planning and decision making. Employing the preceding guidelines will help ensure a successful implementation of a financial data mart.
1 International Data Corporation (IDC) Report, May 1996.

( The information in this column is general in nature and is not intended to address the specific circumstances of any individual or entity.)

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