A project prioritization approach considering uncertainty, reliability, criteria prioritization, and robustness

Given the limitation of resources in organizations (time, money, staff, material, etc.), deciding which projects should be given priority – among many competing projects – is a constant and continuous challenge for decision makers. As a result, a proliferation of methods and solutions for project prioritization has been developed, each with its own strengths and limitations. In this paper, we propose a hybrid approach for prioritizing projects taking into consideration four pervasive challenges in decision making: 1) uncertainty (imprecision and vagueness) of human decisions, 2) reliability (extent of sureness) of decision makers, 3) systematic identification of selection criteria, and 4) robustness of decision making (reasonable tolerance against insignificant changes to decision makers' evaluations during the process). In doing so, we propose integrating Z-numbers theory with Quality Function Development (ZQFD), four Multi-Criteria Decision-Making (Z-MCDM) methods, ensemble ranking aggregation, and sensitivity analysis. The proposed method is then applied in a real-world organization with twenty IT projects to illustrate how our approach might be used in practice. Furthermore, we elaborate on the trustworthiness of the proposed method in light of 16 criteria available in the literature of structured decision making. •Project prioritization is a constant challenge for organizations.•A hybrid model is proposed to simultaneously address four issues in this decision.•Issues are uncertainty, reliability, identification of criteria, and robustness.•Model integrates QFD, z-numbers, MCDM, and sensitivity analysis.•A case study illustrates how the proposed approach may be used in practice.