Multidimensional SME Performance Evaluation: Upgrading to Data Warehousing & Data Mining Techniques

Sylvain Delisle (), Mathieu Dugré and Josée St-Pierre ()
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Sylvain Delisle: UQTR - Université du Québec à Trois-Rivières
Mathieu Dugré: UQTR - Université du Québec à Trois-Rivières
Josée St-Pierre: INRPME - Institut de recherche sur les PME - UQTR - Université du Québec à Trois-Rivières, UQTR - Université du Québec à Trois-Rivières

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Abstract: We present a fully implemented expert diagnostic system which evaluates the performance of SMEs on a benchmarking basis. The system has been in use for several years and has gone through a constant and quite challenging evolution in order to meet both the needs of research and the production of benchmarking reports. We discuss why we decided to upgrade our system with data warehousing and data mining techniques. At the time of writing, we are about to activate the new data warehouse and start our experimentations with data mining techniques—newest results will be available when the conference will be held. We think data warehousing and data mining will allow us to significantly extend our knowledge on SMEs, and further improve our performance evaluation model.

Keywords: Benchmarking; Data Warehousing; Data Mining; Diagnosis; Expert Systems; Performance; SME (search for similar items in EconPapers)
Date: 2004-06
Note: View the original document on HAL open archive server: https://hal.science/hal-01704918
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Published in The 2004 International Conference on Information and Knowledge Engineering, Jun 2004, Las Vegas, United States

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