A fuzzy AHP-based methodology for project prioritization and selection

To improve today’s complex systems composed of personnel, hardware, software and methods, it is necessary to identify, prioritize and select projects to eliminate the causes of underperformance. In this study, a methodology based on fuzzy analytical hierarchy process (FAHP) for decision-making, integrated with cause-and-effect diagrams used in quality improvement studies, is proposed for this purpose. It is assumed that the resources for improvement are scarce and the best use of these is needed. To guide practitioners, the methodology is illustrated with a real-world implementation for identification, prioritization and selection of improvement projects for a poor performing appointment system at a hospital. The cause-and-effect diagram is used to identify and organize the causes and their sub-causes leading to the poor performance, and to create a hierarchy of these by using the information obtained from experts, staff and patients. In order to prioritize the major and sub-causes as potential improvement project topics, FAHP methodology, which utilize human cognition and judgment power based on knowledge and experience, is applied and used for decision-making. The priorities corresponding to each major cause and sub-cause can be used to make a decision on improvement projects and their order due to scarce resources. The methodology is general and can be used in various application domains.