Mismanagement or mismeasurement: The application of DEA to generate performance values and insights from big data

Abstract

Data Envelopment Analysis (DEA) is a well-known frontier valuation method to assess the performance of set of Decision Making Units (DMUs). It derives an overall performance for each DMU based on its efficiency relative to others. All DMUs use the same production function that transfers multiple-input into multiple-output of qualitative and quantitative values. Such big data necessitates the provision of a general framework to guide both researchers and practitioners in the analytical evaluation process for better insights. This chapter proposes a new roadmap to guide future research to implement rigorous and relevant DEA applications. This roadmap consists of five phases: Understand, Prepare, Analyze, Implement, and Monitor (AIM-UP). This roadmap could be used to evaluate the efficiency of resource utilization and the effectiveness of production by the operating processes. Finally, three case studies are used to illustrate DEA implementation, and an up-to-date review of DEA applications is conducted.