Spanning the business: financial performance management provides a glimpse at probable outcomes and trends in performance.

Changing regulation, increased competitive pressure, globalization and Wall Street demand for more detailed and accurate information have pushed financial reporting to become top-of-mind in business management. While businesses are totted to implement often ambiguous and complex regulatory changes, there's also a movement toward performance-based management and the balanced scorecard. Financial performance management is fast becoming the answer to address those challenges.

Financial performance management goes far beyond standard accounting. Financial performance measures and indicators are both quantitative and diagnostic, telling us what happened and why, and giving us a good indication of probable outcomes and trends in performance. Many of these measures, such as Shareholder Value Added--a widely prescribed financial measure--are complex formulas requiring information from all areas of the business, as well as data from external third-party databases.

The challenge lies in managing more complex and detailed financial transaction data, relationships and analytics while maintaining the integrity of the accounting process. Today the current sets of business-specific applications for accounting, management, statistical and statutory reporting are no longer adequate. Technically speaking, the databases associated with the applications are slow to change, are often proprietary and cannot handle the data volumes that are now required. Additionally, data is not accessed easily or shared across functions, and it must be untangled from the current level of summarization and made available in its most atomic form to provide necessary flexibility.

More progressive companies are using data warehouse technologies and the associated principles and practices to engineer a solution to address these challenges. This isn't a light undertaking, nor a quick fix, but a necessary strategic realignment of information processing to prepare for the next generation of regulation and reporting.

The data warehouse is employed to store historical and detailed financial transactions, relationally associated with accounting, journal entries and ledger accounts. Likewise, financial data and metrics are relationally associated with data from across the business operations such as sales, underwriting, claims, and across different business units or lines of business. By running analytics on the data warehouse, the general ledger system becomes simplified and thin, leaving the analytic and reporting burdens to the data warehouse. Also, the financial data can now be integrated into analysis throughout the organization, enabling management to make decisions about distribution management, for instance, with a far greater understanding of the full economic impact of those decisions.

In the data warehouse, data is managed at the atomic level, enabling the details of each business transaction, not its aggregate or average, to become it financial marker and delivering transparancy down to the lowest level of detail.

The data warehouse also enables broader and deeper associations across dimensions of the business enterprise and becomes the single source for a shared data resource and a "single version of the truth." The same information is used to evaluate performance, from product and business development, through channel and geographic distribution, underwriting and claims, and customer service. Because companies can use a common data source for all statistical, operational and management reporting, there's a significant improvement in reconciliation, reporting time and cost.

Coupled with analytic and reporting tools that are actively applied against the data warehouse in near real-time, companies are able to quickly draw out, analyze and report on all levels of available data. A good example is the use of analytical fraud event detectives to identify and root out instances of fraud as suspect transactions occur. This advanced form of data warehousing is known as active data warehousing because it not only involves traditional reporting, analytics and predictive modeling but also active analysis of data as it's being produced.

The data warehouse is an effective technology as applied to the full spectrum of financial performance--from standard reporting to deep analytics to near real-time tracking of complex events. While regulatory noncompliance can result in penalties, fines and, most importantly, a loss of reputation, advanced information solutions will bring together not only the information required to comply with regulation hut also the information necessary to outperform the competition, while also bringing financial performance into the heart of the business enterprise.

Contributor Michael Helms is an insurance industry consultant with Teradata, a division of NCR. He may be reached at [e-mail].