Measurement and control of business processes

Abstract

AbstractIt is widely accepted that any well‐designed organizational process includes a control mechanism through which management decides which aspects of the performance of the process are to be measured and how these measurements are to be used to change the level of resources utilized in the process. Little is known, however, about the best ways to design such a control mechanism for typical business processes. Our goal in this research is to identify control mechanisms for business processes that are effective in different types of environments. In this article we present a system dynamics model of a typical service‐sector business process, such as is used in processing administrative paperwork in insurance, banking, and so on. These processes are subject to random, time‐varying, and non‐postponable demands for service. They are also subject to randomness in processing times, as well as delays in the observation of system performance and in the execution of control actions. We assume management has the dual objectives of maximizing profits (revenues on completed work less the costs of labor employed) and keeping cycle times below a predetermined ceiling. In order to achieve these objectives it observes the state of the process and adjusts its labor force accordingly. Management must chose which of several aspects of process performance to measure (cycle time, backlog, or demand) and the parameters governing the control process. Our analysis highlights the interactions among the demand environment faced by the process (e.g., random or seasonal), the control signal chosen (e.g., cycle time or backlog), and the type of control used (e.g., proportional or differential). Our results suggest that, regardless of the demand environment, a control process based on system backlog is generally more robust than the alternatives in the sense that adequate performance is achieved over a broader range of control parameters. We also find that, in most cases, proportional control by itself is inadequate to provide effective performance and that differential control is a necessary adjunct. We conclude the article with a discussion of the managerial implications of this research. Copyright © 2001 John Wiley & Sons, Ltd.