Performance assessment scheme for disaster relief operations

Abstract

The significant growth of natural disasters, together with the declining financial support from governments, and the increasing competition for scarce donations have heightened the need for transparency and accountability in disaster relief operations. As important as it is, majority of humanitarian organizations merely report their performance achievement by annual financial reports which provide insufficient information about operational transparency and effectiveness. Performance assessment of disaster relief operations is challenging due to the complexity of field operations, operational constraints, unreliable and imprecise information. As a result, most humanitarian organizations have limited information, awareness, skill, and technological necessities to formulate and implement suitable performance assessment scheme. Existing performance measurement frameworks are largely theoretical and are ill-equipped in dealing with fuzzy and imprecise information. They also lack an overall integrated performance score that incorporates both financial and non-financial performance indicators. This necessitates a thorough investigation to formulate an improved performance assessment scheme based on relevant performance indicators. In this research, the objective is to formulate a performance assessment scheme for disaster relief operations. Data was gathered based on the case study method using questionnaire survey and direct interviews with the logistic practitioners from prominent Malaysian based humanitarian organizations. A conceptual model for disaster relief operations performance indicators and their causal interrelationships based on Balanced Scorecard (BSC) perspectives were developed to establish a foundation for the performance assessment. This causal model clustered performance indicators into the four BSC’s perspectives, namely beneficiaries and donors, internal processes, financial, and learning and innovation. The model provides an overall view of the related performance indicators and their interdependencies. Then, the Analytical Hierarchy Process (AHP) was employed to establish the weight and priority of the performance indicators. The outcomes of AHP analysis serve as inputs to a multistage fuzzy inference system. This system addresses uncertain and imprecise input data for performance measurement. The proposed approach integrates multiple performance indicators and provides an overall performance score for individual BSC’s perspectives as well as a global performance score. As a proof-of-concept, a prototype demonstrator was developed using MATLAB. The flexibility of the method allows decision-makers to address the complexity in the performance assessment for disaster relief operations. The fuzzy inference scheme provides better flexibility compared to the AHP scheme. The utility of the fuzzy inference scheme lies in its ability to support decision making in surmounting the challenges posed by the complexity of performance evaluation with respect to imprecise performance data. The proposed performance assessment schemes collectively guide decision-makers about important and relevant criteria for performance assessment in disaster relief operations, facilitates a more detailed and multi-dimensional performance assessment of relief operations, and suggests performance indicators that decision-makers should focus for operational performance improvement.