Project Management Software Selection Using Analytical Hierarchy Process

By Sutterfield, J. S.; Swirsky, Steven et al. | Journal of Management Information and Decision Sciences, July 2008 | Go to article overview

Project Management Software Selection Using Analytical Hierarchy Process


Sutterfield, J. S., Swirsky, Steven, Ngassam, Christopher, Journal of Management Information and Decision Sciences


INTRODUCTION

Decision Analysis involving multiple variables and objectives that can be quantified is rather commonplace. The methods for solving such problems are rather well established. One simply quantifies with some measure the variables and objectives involved in the problem, then chooses the appropriate solution methodology, obtains the necessary data and calculates an answer. However, with problems involving variables and objectives that cannot be measured, or at best can be only partly measured, the solution approach is not always so clear. This is particularly true when the variables and objectives involve personal preferences. The approach frequently taken with such problems is to simply prioritize the decision considerations and try to choose a solution that maximizes the desired decision quantities at minimum cost. Although this may not be too difficult with a limited number of decision quantities, it can become very difficult when the number of such quantities is large. In addition, the problem becomes vastly more complex when some of the decision quantities are in mutual conflict. Thus, making rational decisions under such circumstances may become extraordinarily difficult.

A number of techniques are available for arriving at decisions having multi-attributes. Unfortunately, most of them require that the attributes be measurable. When the attributes are of a more qualitative nature, the multi-attribute problem becomes much more difficult to handle. Herein lies the value and power of Analytical Hierarchy Process (AHP). With AHP it is possible to give a qualitative type problem a quasi-quantitative structure, and to arrive at decisions by expressing preferences for one attribute over another, and testing whether the preferences are rational consistent.

In this paper, we use AHP to analyze the selection process for project management software (PMS). We approach this problem by treating the PMS features offered by various companies as attributes. We then have a group of PM professionals evaluate the various features as to their importance and desirability. From these evaluations, paired comparison matrices are developed. Next, a set of matrices is developed for each software provider that evaluate just how well each provider's software satisfies each attribute. A consistency ratio is then computed to determine how rigorously rational consistency has been maintained in the analysis. Ordinarily, an AHP analysis would end here, but we extend our analysis by using the Student's "t" test for small sample sizes to determine a confidence interval within which the responses should lie. This analysis fills a void in the literature by demonstrating a perfectly generalized process for solving a practical multi-attribute decision problem, and for arriving at a high level of confidence that a rational decision will have been made.

LITERATURE REVIEW

AHP was originally conceived by Thomas L. Saaty as a structured method for solving problems involving decision variables or decision attributes, at least some of which, are qualitative, and cannot be directly measured (Saaty, 1980). It met with almost immediate acceptance and was applied to a wide range of problems. Very soon it began to be applied to executive decisions involving conflicts in stakeholder requirements and strategic planning (Saaty, 1982; Arbel & Orgler, 1990; Uzoka, 2005). The real power of AHP consists in its use of fairly elementary mathematics to structure complex problems in which decisions involve numerous decision makers, and multiple decision variables. Another facet of the power of the AHP approach consists in its ability to impose a quasi-quantitative character on decision problems in which the decision variables are not necessarily quantitative. The power and versatility of AHP are demonstrated by the wide range of problems to which the approach has been applied. …

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