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Need to Anticipate Customer Requirements

The finance strategist must go beyond identifying data customers to understanding their needs well enough to anticipate them before they are critical. Doing so is crucial when it comes to conceptualizing infrastructure and long-range analysis paradigms. The ability to build into the finance strategy scalable infrastructure and relevant soft components depends on knowing what is needed and when. Anticipating data needs may not be difficult when it comes to internal data customers; however, doing so for external data customers may be a challenge. The finance strategist must investigate and understand the strategies of external and internal data customers and must be clear on the current and prospective capability of the finance function to accommodate various needs in various circumstances.

Know the Strategies of Data Customers

Most data customers, like the business itself, are operating in a dynamic environment. Internal data customers are a prime example, as their growth and data needs embody the evolution of the business organization itself. Physical proximity and unity of purpose make keeping in step with growth strategies less taxing for the finance strategist. How about the strategies of external data customers? Companies with external reporting requirements to the Securities and Exchange Commission, for instance, should be in tune with future reporting requirements. Are there particular reporting initiatives on the horizon? How about the Financial Accounting Standards Board (FASB) when it comes to GAAP reporting and disclosure or the federal government when it comes to tax law? Although it may seem difficult to comply with current laws, future rules may represent a greater burden. Understanding these law or rule changes and how they impact the organization in advance will allow for the capability to develop infrastructure, particularly systems and processes that will minimize the impact of change on the organization.

How will the strategist be clear on data customers’ future strategies? Simple research may suffice when it comes to external data customers like the FASB, SEC, or federal government. Solid lines of communication, however, must be in place with internal data customers. Teams or task forces that meet periodically to discuss future strategies are great ways to understand the needs and strategies of internal data customers. This avenue allows for the finance strategist to communicate expectations and plans for development while enabling data customers to do the same. Communicating strategies and growth plans will be effective in creating platforms to handle current needs and expand to manage future ones.
What types of data will be demanded of the organization? Reporting financial data will take many forms; however, all reporting, whether it is for internal or external purposes, will focus on a standard slate of financial statements. Generally, the term “financial statements” refers to the balance sheet (a snapshot of the company at a point in time) and the profit and loss statement. The goal of generating financial statements and reporting financial data is twofold: (1) creating an accurate representation of the company at a specific point in time and (2) summarizing the company’s performance over a period of time. Achieving these two objectives means financial statements that provide internal customers of financial data with information on the company’s ability to pay bills and meet obligations (liquidity) and generate additional equity (net income) for owners. Likewise, financial statements can provide information to certain external customers of data whether they are banks, equity partners, or governmental authorities.

Need for Statistical Data

Not all data needs are financial. Data customers may demand data that is not generated by a general ledger. Information like headcount, accounts receivable aging, bookings, and backlog are examples of vital information that the finance function produces. This data is typically referred to as statistical data. Some nonfinancial data may fall into this definition; however, most of this information is based on, or a derivation from, financial data. Components of fixed asset or reserve rollforwards are prime examples. The beginning and ending balances themselves are standard balance sheet items; components such as disposals, additions, translation adjustment, and the like may not be. How is this data gathered, stored, and interpreted? Statistical data must be considered part of the finance strategy just like other standard general ledger (P&L and balance sheet) data. Internal data customers may be the greatest consumers of statistical information, although certain external filings may demand statistical information as well.

Recognize the Mode of Data Delivery

Part of anticipating data customer needs involves understanding the mode of data delivery most likely to be demanded. The company will have, at some time or another, rigid, well-defined external reporting requirements as well as open-ended, less-defined internal reporting needs. Finance infrastructure addresses these varying needs in different ways. Handling predictable, recurring external reporting requirements may require a reliable consolidation and reporting tool that can generate predesigned P&L and balance sheet reports quickly and easily. The emphasis may be on speed in these circumstances. The demands of the finance organization may be to review results for outliers and articulate variances. If the organization is growing quickly, there may be an ongoing need for standard and nonstandard data analysis. Companies that employ economic value-added (EVA) models or dynamic valuations of the business may seek data to manipulate and fashion into nonstandard forms. Data requirements for these models epitomize the need for data availability as opposed to financial reporting. More complex infrastructure may be required to serve this purpose. Data warehouse and online analytical processing (OLAP) technology are examples of advanced tools that can meet more advanced, open-ended data needs. Because resource requirements will be so disparate between the need for rigid reporting requirements and open-ended data availability, the finance strategist must fully understand and anticipate these different data needs and incorporate the appropriate actions into the finance strategy.