In the past, the Internal Revenue Service (IRS) has experienced declines in enforcement productivity as measured by cases closed per Full Time Equivalent. Increasing enforcement productivity through a variety of enforcement improvement projects is one strategy being pursued by IRS. Evaluating the benefits of different projects requires good measures of productivity. In addition, IRS's ability to correctly measure its productivity has important budget implications. GAO was asked to illustrate available methods to better measure productivity at IRS. Specifically, our objectives were to (1) describe challenges that IRS faces when measuring productivity, (2) describe alternative methods that IRS can use to improve its productivity measures, and (3) assess the feasibility of using these alternative methods by illustrating their use with existing IRS data.

Measuring IRS's productivity, the efficiency with which inputs are used to produce outputs, is challenging. IRS's output could be measured in terms of impact on taxpayers or the activities it performs. IRS's impacts on taxpayers, such as compliance and perceptions of fairness, are intangible and costly to measure. IRS's activities, such as exams or audits conducted, are easier to count but must be adjusted for complexity and quality. An increase in exams closed per employee would not indicate an increase in productivity if IRS had shifted to less complex exams or if quality declined. IRS can improve its productivity measures by using a variety of methods for calculating productivity that adjust for complexity and quality. These methods range from ratios using a single output and input to methods that combine multiple outputs and inputs into composite indexes. Which method is appropriate depends on the purpose for which the productivity measure is being calculated. For example, a single ratio may be useful for examining the productivity of a single simple activity, while composite indexes can be used to measure the productivity of resources across an entire organization, where many different activities are being performed. Two examples show that existing data, even though they have limitations, can be used to produce a more complete picture of productivity. For individual exams, composite indexes controlling for exam complexity show a larger productivity decline than the single ratio method. On the other hand, for exams performed in the Large and Mid-Size Business (LSMB) division, the single ratio understates the productivity increase shown, after again controlling for complexity. By using alternative methods for measuring productivity, managers would be better able to isolate sources of productivity change and manage resources more effectively. More complete productivity measures would provide better information about IRS effectiveness, budget needs, and efforts to improve efficiency.

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