- Author
- Chapman, R. E.
- Title
- Using Data Envelopment Analysis to Assess Performance of Manufacturing Extension Centers.
- Coporate
- National Institute of Standards and Technology, Gaithersburg, MD
- Report
- NISTIR 6198, August 1998, 57 p.
- Distribution
- Available from National Technical Information Service
- Keywords
- competitiveness | data envelopment analysis | economic analysis | economic impacts | extension services | linear programming | manufacturing | performance assessment | program evaluation
- Abstract
- The purpose of this report is threefold. First, it describes how Data Envelopment Analysis (DEA) may be applied to assist the Manufacturing Extension Partnership (MEP) Program and its network of Manufacturing Extension Centers (MECs) in assessing performance. DEA is an approach to performance assessment which uses linear programming and principles of frontiere analysis. DEA provides an integrated method for performance assessment which computes a single measure of performance based on multiple outputs and inputs. To accomplish the first purpose, the theory and methodology of DEA are related to MEP operating data focused on the twin informational needs of continuous improvement and program accountability. These operating data include both inputs - staff and financial resources - and outputs - types and levels of services rendered. The second purpose is to apply data from the current NIST/MEP Management Information Reporting System to illustrate ways in which DEA can help MEP headquarters and its network of MECs to measure their performance. Operating data from 51 MECs are analyzed via a series of performance assessment models; each model is a unique combination of inputs and output. The third purpose is to stimulate feedback and discussion among those engaged in MEP performance assessment. DEA provides a method which MEP and its network of MECs can use jointly to make sense of the multi-dimentional nature of MEC performance data. With this report MEP is in a position to initiate further uses of DEA which will prove beneficial to both the MECs and the national program.