Measuring the Level of Urgency and Motivation

Financial reporting, whether it is for internal or external purposes, must be prioritized. Finance resources must be dedicated to urgent reporting matters before less important reporting issues are addressed. The challenge for the finance strategist is to determine which matters of reporting deserve attention over others. Financial reporting matters will be segregated into two broad categories: (1) have-to reporting and (2) like-to reporting. Small and emerging companies, midsize companies, and large companies accumulate financial data and perform some reporting on a have-to basis. This have-to umbrella includes federal income tax reporting, state and local tax compliance, and bank loan covenant compliance. Companies that are publicly traded will, in addition to the filings just mentioned, file Form 10Q, 10K, and 8K and other statutory filings with the SEC. The major data customer for haveto reporting is external to the organization, usually a governmental authority. If the company has operations in other countries, it will have foreign tax filings and local statutory filings as well. The motivation for this type of financial reporting is based on negative reinforcement, most notably fines and penalties.
The second category of financial reporting is like-to reporting. This reporting can be used for external or internal data customers. Examples of like-to reporting for external audiences would be the presentation of financial results for potential business combinations and public offerings. Examples for internal audiences would include reporting for bonus measurements or product divestitures. Like-to reporting is motivated by a potential positive end, which could be a payoff from selling the business, an accelerated market cap with an initial public offering, or a performance bonus. Like-to reporting does not come about as a statutory result of operations. The organization will not be sanctioned for not complying with these reporting requirements.

The finance strategist must be careful to sort through reporting needs and understand which reporting initiatives are critical to the organization. Finance infrastructure and related soft components are designed to suit the urgent reporting requirements while lesser reporting needs will either be minimized altogether or passed on to data customers or the finance organization to coordinate. The following example illustrates how motivation impacts the prioritization of reporting compliance tasks:

Edward B. works in the external reporting group of a public company. The deluge of SEC and internal reporting requirements this company has demands the sorting and prioritization of reporting requirements. One of the reporting requirements he deals with is that of the U.S. Census Bureau. Because Edward B.’s company has a manufacturing component, these form requests by the Census Bureau are not only numerous but awkwardly complex. The rainbow of colors and assortment of sizes and shapes of these forms grace his desk every month, it seems. Edward B., like his predecessors, has noticed that there was no real consequence to returning the completed forms late. Additionally, he has found that no one at the Census Bureau ties the completed forms to anything. The only follow-up that is done is an occasional phone call when the forms are not filed on time. These realizations have led to the submission of the same numerical data each quarter or year (whatever the form demands), an exercise as easy as transcribing the same data to new forms each period. In spite of the imposing words stamped on the forms instructing to file or risk penalties and fines, Edward B. discounts the significance of these filings and uses old or dummy information to complete them. Edward B. has networked with his peers in other companies and found that his approach to handling the census forms is no different from that used in most organizations. Because this methodology can be followed with impunity, the results, which fit the level of reinforcement from this data customer, may be less than accurate.

Generally, efforts to assemble financial statements or a particular filing are driven by the intensity of the measure of reinforcement (good or bad) that motivates the organization. Fear of the IRS and dealing with bureaucracy to sort out penalties, interest, and interest on penalties is motivation enough to research all necessary IRS filings and follow through with them. An impending windfall from the purchase of the business by an eager buyer is an example of motivation to prepare comprehensive financial statements in a timely manner. Parlaying the motivation to report financial data to have-to and like-to terms is a simple way of linking actions and results.

Historical versus Prospective Reporting

Key to gaining perspective on reporting needs involves equating have-to and liketo reporting to historical and prospective reporting. Have-to reporting includes state and federal tax returns as well as SEC filings. These reports are usually based on actual events and transactions that have already happened, hence they are historical in nature. Like-to reporting, budgets, forecasts, and financial models are typically forward looking or prospective in nature. As opposed to historical reports, these reports are to some extent based on assumptions. Historical-based reporting, it may seem, has no value to the company other than to keep the organization in compliance with reporting authorities. However, historical data has apparent value to the organization in that it reveals the results of past decisions and hints at the economics of the business environment and how it affected the organization. Historical results, therefore, must be compiled and interpreted properly for any organization to flourish. Depending on the sophistication of the finance function, the organization must be poised to leverage historical data into good decisions.

Accurate prospective reporting by nature adds value to the company’s strategic direction. Budgets and forecasts provide performance benchmarks and give the organization a way to communicate results to external data customers, if necessary. Business and financial models based on historical performance are typically heavier on the prospective side. These models provide the backbone for acquisitions, divestitures, and mergers—significant events in the business life cycle. Following this logic, it stands to reason that companies would do everything in their power to ensure maximum effort is put into prospective (like-to) reporting while minimizing the effort and time put into historical (have-to) reporting. Understanding these relationships will require revisiting the role of motivation and how it drives the finance function.

Historic Needs

Success in the early years of the business is heavily dependent on the ability of management/owners to optimize resources. Resources, whether money or people, are typically scarce in the early years of business development. While historical data may be nonexistent or sparse in a young company, as time passes a track record of performance will be established. The ability to view the past and assess the use of resources will hinge on accurate financial reporting.
Gauging historical performance against both peers and the company itself will augment decision making as the company moves from an emerging/developmental stage to a more stable, mature stage. Do results reflect decisions made by management or a fortuitous environmental event? Is the reverse true for bad results? As the management team and the company mature, analysis and decision making will become a matter of generating good data on past performance and knowing why (or why not) certain results were achieved.

Accessing historical data is the foundation of developing reporting and analysis capabilities. Part of the maturation process involves creating financial statements or reports that analyze the relevant aspects of the business, whether it is time, geographies, or a combination of the two. The evolution of these tools is an indication of how the decision-making framework is developing. For example, analysis needs that focus on performance results for a current period will give way to bilevel variance reports comparing current and prior-period performance. Bilevel variance reports may evolve into trilevel variance reports comparing current, to prior, to budget data.

The need for information to make decisions will drive finance function development as a particular suite of suitable reporting tools anchored by historical data becomes the mainstay of decision support. The need to discern and strategize will grow as the business becomes more complex. Accommodating this increased need for analysis will demand tools that not only interpret past performance but predict future performance as well.

Future Needs

Just as management will have a need to review the company’s past performance, the need to be prospective (via budgets and forecasts) with company results will become imperative as the business grows. The company eventually will confront the need to grow and expand, which will lead to the difficult task of having to assess future performance with a fair level of accuracy. Estimating future resource needs and creating expectations for stakeholders are examples of needs that require reliable prospective reporting.

Excluding extraordinary circumstances, the ability of the company to flourish in a changing environment will depend to a large extent on the finance function’s capacity to generate and interpret accurate prospective financial reports on a regular basis. Budgets and forecasts are an example of prospective financial statements that will serve recurring, prospective reporting needs. How will the company perform next month, quarter, or year? Does it take time for the company to ramp-up resources to penetrate/grow relevant markets? If the supply chain is complex, which is often the case with manufacturing organizations, there will be heavy reliance on budgeted revenue numbers to position production or distribution channels to meet expectations. Budgeted P&Ls may be prepared for one-, five-, or 10-year time periods. Forecasts must blend actual results with budgeted numbers to derive short-term targets, typically a year in advance.

Analysis and decision making will hinge on financial reporting tools that interpret data generated by the data flow process. Comparing actual results to budget results in a given period will give an indication of the company’s performance. The organization may discover a need to budget balance sheet items for cash flow purposes or otherwise, in addition to P&L items. Although this is more complex and not as widely practiced as budgeting P&L items, mastering this aspect of budgeting may prove to be vital in developing the finance function.

Other Issues in Preparing Financial Statements

Much like choosing accounting methodologies that fit the business, preparing formal financial statements or less formal reports will require focusing on certain key dependencies. Chief of these dependencies is the need for good information. For financial reporting to have value to the organization, the finance function must be able to generate accurate and timely information. Understanding data customers and their needs is also crucial to establishing a sound reporting function. These considerations of the multilevel approach to strategizing dictate the finance function’s ability to dispense data in addition to its capacity to gather, process, and analyze data. Having a grasp of the business and industry in which it operates is key to developing an effective reporting function. The finance strategist must work closely with operations and management personnel to ensure that the finance function and strategy is suited for reporting information adequately. Finally, the need to consult with experts to interpret GAAP cannot be discounted. This is particularly critical for organizations that have statutorially defined reporting requirements. Understanding how to treat transactions particular to the business and/or industry will aid in ensuring that data is captured, processed, and classified properly by the finance function, especially where reporting is highly automated.