Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets: 126 (International Series in Operations Research & Management Science) - Hardcover

Reseña del editor

Managers are often under great pressure to improve the performance of their organizations. To improve performance, one needs to constantly evaluate operations or processes related to producing products, providing services, and marketing and selling products. Performance evaluation and benchmarking are a widely used method to identify and adopt best practices as a means to improve performance and increase productivity, and are particularly valuable when no objective or engineered standard is available to define efficient and effective performance. For this reason, benchmarking is often used in managing service operations, because service standards (benchmarks) are more difficult to define than manufacturing standards. Benchmarks can be established but they are somewhat limited as they work with single measurements one at a time. It is difficult to evaluate an organization’s performance when there are multiple inputs and outputs to the system. The difficulties are further enhanced when the relationships between the inputs and the outputs are complex and involve unknown tradeoffs. It is critical to show benchmarks where multiple measurements exist. The current book introduces the methodology of data envelopment analysis (DEA) and its uses in performance evaluation and benchmarking under the context of multiple performance measures.

Contraportada

It is difficult to evaluate an organization’s performance when there are multiple inputs and multiple outputs to the system. The difficulties are further enhanced when the relationships between the inputs and the outputs are complex and involve unknown tradeoffs. This book introduces DEA as a multiple-measure performance evaluation and benchmarking tool. The focus of performance evaluation and benchmarking is shifted from characterizing performance in terms of single measures to evaluating performance as a multidimensional systems perspective.

This second edition improves a number of DEA spreadsheet models and provides a DEAFrontier software for use with Excel 2007. Several new DEA models and approaches are added. For example, a new DEA-based supply chain model (chapter 8) and DEA models for two-stage processes (Chapter 14) are new additions to the book. Models with restricted multipliers are also discussed and added into the DEAFrontier software. A detailed use of sensitivity analysis in identifying critical measures under DEA is provided. A demonstration of how to use the DEAFrontier software is provided at the end of related chapters.

Conventional and new DEA approaches are presented and discussed using Excel spreadsheets ― one of the most effective ways to analyze and evaluate decision alternatives. The user can easily develop and customize new DEA models based upon these spreadsheets. Spreadsheets are updated and modified for use with Excel 2007.

This book also provides an easy-to-use DEA software ― DEAFrontier. This DEAFrontier is an Add-In for Microsoft® Excel and provides a custom menu of DEA approaches which include more than 150 different DEA models. DEAFrontier softwares are provided for both Excel 97-2003 and Excel 2007 and can solve up to 100 DMUs. It is an extremely powerful tool that can assist decision-makers in benchmarking and analyzing complex operational efficiency issues in manufacturing organizations as well as evaluating processes in banking, retail, franchising, health care, public services and many other industries.

For a free version of DEAFrontier, please visit www.deafrontier.com.