A Multidimensional and Visual Exploration Approach to Project Prioritization and Selection

Abstract

In project management, many decisions are made based on multiple attributes (dimensions) of project data. However, these dimensions are usually condensed into one or two indicators in the analysis process. For example, projects are commonly prioritized using a scoring approach: they are evaluated according to predefined categories, which are then aggregated into one or two priority numbers. We argue that aggregated scores may only offer a limited view of project importance. Such scores tend to hide information that may effectively distinguish projects; this often leads decision makers to ignore the possible differences masked by aggregation. This paper presents a visual exploration approach that integrates human intuition and maintains the multidimensionality of project data as a decision basis for project prioritization and selection. The approach is based on the examination of portfolio perceptual maps, generated by a clustering technique. The research provides a useful and complementary approach for decision makers to analyze project portfolios