Improving data quality for performance measures: results from a GAO study of verification and validation
The Government Performance and Results Act, and many other efforts to initiate performance reporting, bring attention to the characteristics and quality of the data underlying performance measures. The study summarized here looked for examples of useful practices that federal agencies are developing...
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| Veröffentlicht in: | Evaluation and program planning 2001-02, Vol.24 (1), p.83-94 |
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| creator | Divorski, S. Scheirer, M.A. |
| description | The Government Performance and Results Act, and many other efforts to initiate performance reporting, bring attention to the characteristics and quality of the data underlying performance measures. The study summarized here looked for examples of useful practices that federal agencies are developing to ‘verify and validate’ their performance information, as required by the Results Act. We developed a framework to organize our findings. The framework contains four major approaches to assess and improve data quality: (1) fostering organizational commitment and capacity for data quality; (2) assessing the quality of existing data; (3) responding to data limitations identified during assessments of data quality; and (4) building quality into the development of performance data. Specific strategies within each approach are illustrated with examples from the six agencies we studied. |
| doi_str_mv | 10.1016/S0149-7189(00)00049-5 |
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| ispartof | Evaluation and program planning, 2001-02, Vol.24 (1), p.83-94 |
| issn | 0149-7189 |
| language | eng |
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| source | RePEc; Elsevier ScienceDirect Journals Complete; Worldwide Political Science Abstracts |
| subjects | Accountability Data Collection Data Quality Evaluation Methods Evaluation Research Federal Government Government Agencies Organizational Effectiveness Performance Based Assessment Performance Factors Public Administration |
| title | Improving data quality for performance measures: results from a GAO study of verification and validation |
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