| It is known that an organization can dramatically improve the efficiency of its operations by applying the practices of its best-performing internal units throughout the organization---a process known as "internal benchmarking." However, identifying the best performers (or "benchmarks") can be difficult to accomplish for a large organization, especially if the operations, conditions, or priorities vary amongst all of its internal subunits. The swift and accurate identification of benchmarks in a large, complex organization will enable the managers to improve the overall efficiency of the system. This study examined the use of data envelopment analysis (DEA) to identify benchmarks in the context of a large internal benchmarking problem. Additional methodologies were also developed and examined in conjunction with DEA. These methodologies were applied to a real-world data set of a large parcel delivery service and the results indicated that data envelopment analysis is a valuable benchmarking tool. |
