Encourage Effective Decision Making with the Analytic Hierarchy Process

  • by Michael Szardenings, Senior Developer, SAP AG
  • December 15, 2009
The Analytic Hierarchy Process (AHP) is an effective, multi-criteria decision-making method that helps you to assign logical, concrete values to your choices so you can make more informed judgments. Learn how to use AHP to intelligently structure and analyze complex problems and more easily synthesize your data with your criteria.
Key Concept

Named for a Greek oracle, the Delphi method is a technique for getting a consensus among experts in a given field (e.g., project management or recruitment) to participate anonymously in a panel and answer a few rounds of questionnaires. The facilitator solicits proposals (e.g., decision criteria) using a questionnaire and then summarizes the anonymous answers and circulates them back to the experts for comment or change. Typically, after two or three such rounds, the range of answers decreases and a consensus is reached that provides input into AHP’s decision-making process. One advantage is that the Delphi method reduces any overt influence from the opinions of other participants that are common in face-to-face meetings. If there are several decision makers, it’s advisable to use the Delphi method to define the criteria set.

A typical SAP customer project can be extremely complex, with high susceptibility to change, many stakeholders to manage, a variety of interrelationships with other ongoing projects, risks that are difficult to identify, and an inexact or shifting definition of scope. Decision makers must resolve numerous problems while satisfying multiple criteria, whether they are selecting an SAP project manager, a new technological solution, or a time-compression strategy. Such decisions — made in an increasingly complicated and rapidly changing business environment and potentially resulting in huge consequences — are too often founded on a haphazard, inexact combination of experience, logic, and inarticulate feelings. Unfortunately, while decision making necessarily tops the list of requisite management skills, few project managers have any actual training in it.

You can fill this gap using AHP. Thomas L. Saaty (an American mathematician at the University of Pittsburgh) first introduced this powerful and flexible method in the 1970s. Since then, the method has extended to the business realm in areas such as quality management, supplier selection, transportation route selection, human capital management, resource allocation, and forecasting. In fact, a number of prominent companies and organizations, such as NASA, General Motors, IBM, AOL, Hewlett-Packard, BP, Shell, Boeing, and NATO, have adopted it as an important tool.

I begin by explaining some basic AHP concepts: building a decision problem hierarchy, making pairwise comparisons, and analyzing sensitivity to change. (Decision problems are questions with a yes-or-no answer, depending on some input parameter.) Then, I show how AHP works on a sample project-management decision problem: selecting an SAP project manager. Finally, I explore several typical decision problems that occur during SAP implementations and provide sample decision hierarchies for them. After reading this article, you should be able to use AHP to intelligently structure and analyze complex problems, more easily synthesize your data with your criteria, and so lay a solid, rational foundation for making decisions in real-world situations.

Michael Szardenings

Michael Szardenings is a senior developer in the SAP IMS organization. Working in the Systems Management Group within IMS, Michael is responsible for all kinds of Windows printing from SAP systems. He started his career in 1989 in the IBM Research and Development Lab in Germany, with the development of various user interface components for IBM mainframe computers. As SAP IBM came together on several joint venture projects in the systems management area, which includes job scheduling and printing, Michael’s focuses switched to SAP. He joined SAP in 2001.

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