The Analytic Hierarchy Process and Multi-Criteria Performance Management Systems

Topics: Analytic Hierarchy Process, Pairwise comparison, Law of comparative judgment Pages: 20 (4063 words) Published: October 7, 2010

Stephen L. Liedtka
Assistant Professor of Accounting
Lehigh University

Forthcoming in the November/December 2005 issue of Cost Management


This paper describes how the Analytic Hierarchy Process (AHP), a popular decision-support methodology, is particularly well-suited to the challenges of implementing a multi-criteria performance management system (MCS) such as the Balanced Scorecard. In doing so, the paper describes AHP methodology in detail, and demonstrates AHP by using the method to create a basic MCS for a major airline. Additionally, the paper reports overall airline performance scores generated by the MCS and compares the derived scores to the results from two competing approaches. Of the three sets of results, the AHP-based performance scores correlate highest with annual stock market returns, providing some evidence that AHP yields a superior model for linking strategy to shareholder wealth.

Acknowledgments: The author gratefully acknowledges assistance from Frank Alt, Larry Bodin, Dick Durand, Larry Gordon, Jim Largay, Marty Loeb, Ella Mae Matsumura, and Expert Choice, Inc. 

Address for correspondence: Rauch Business Center, Lehigh University, 621 Taylor Street, Bethlehem, PA 18015, USA. E-mail:



Academics and practitioners long have argued that the traditional use of a single financial measure of firm performance, such as return on investment or residual income, can result in excessive focus on the short-term at the expense of long-term firm health. To promote a comprehensive view of the firm, therefore, researchers advocate the replacement of traditional single-measure systems with sets of financial and nonfinancial performance measures that reflect all vital firm activities. Peter Drucker, for instance, recommended a “balanced stress on objectives” such as market standing, innovation, productivity, physical and financial resources, profitability, manager performance and development, worker performance and attitude, and public responsibility.1 More recently, the Balanced Scorecard (BSC) has gained great popularity by reviving and significantly refining the “balanced stress” concept. Use of a multi-criteria system (MCS) necessitates frequent and often difficult comparisons. Decision makers, for instance, must consider the relative importance of chosen objectives whenever tradeoffs are necessary due to limited firm resources or the existence of inverse relationships among the objectives (e.g., certain cost vs. quality decisions). Further, assessment of overall firm or subunit performance at the end of a period necessitates that decision makers somehow reconcile measurements of the multiple criteria, which vary in nature (e.g., customer-related vs. human resource-related), time frame (historical vs. future-oriented), and measurement unit (e.g., dollars vs. time). The lack of a formal method for prioritizing and comparing strategic objectives and measures limits the usefulness of the BSC and other MCS. Without reliable weightings of strategic objectives, for instance, an MCS does not precisely communicate the firm’s strategy, including the intensity of effort that should be devoted to each objective. In addition, for performance evaluation, lack of a formal decision-support system leaves individuals with an extremely difficult judgment task. In such cases, extant research demonstrates that decision-makers may take suboptimal steps to reduce their cognitive burden. Decision-makers, for instance, show a tendency to ignore BSC measures that are unique to a subunit, choosing instead to consider only those measures that are common across divisions.2 This paper explains how the Analytic Hierarchy Process (AHP), a popular decision-support...
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