Dysfunctionality in Performance Measurement When Outputs are Difficult to Measure: A Research Note

Issues of performance measurement are ubiquitous in modern organizations and are often concerned with evaluations of outputs or efficiency (which encompasses both inputs and outputs) of an entity or process. Examples of output measures include revenue generated, defective units produced, on-time shipments, etc. Efficiency examples include standard cost variances, machine up-time rate, and efficiency scores from input–output models such as Data Envelopment Analysis (DEA). Difficult-to-measure outputs are often included even though they cannot be measured with precision. When outputs of a production process are not easy to measure, serious dysfunctional decision-making can be expected and these problems may be particularly acute when efficiency measurements from input–output models are directly tied to rewards and incentives. Both for-profit firms and public sector organizations may share output measurability problems. In this paper, we examine the possible problems of using input–output models (such as DEA) when outputs are difficult to quantify within an agency theory perspective and illustrate the potential problems using recent proposals in the UK for evaluating and rewarding police unit performance. We conclude that although input–output models, particularly those such as DEA may be useful as a diagnostic tool to assist decision-makers in altering future operating strategies and policies, it has serious limitations when rewards and incentives are attached to the DEA performance evaluations. In our view, overreliance on mechanical, formula-based approaches is potentially a serious threat to improving performance in these situations.