Authors:
Manik Madhikermi
1
;
Sylvain Kubler
2
;
Andrea Buda
1
and
Kary Främling
1
Affiliations:
1
Aalto University, Finland
;
2
University of Luxembourg, Luxembourg
Keyword(s):
Data Quality, Multi-criteria Decision Making, Analytic Hierarchy Process, Decision Support Systems.
Related
Ontology
Subjects/Areas/Topics:
Business Cases and Cost/Benefit Analysis
;
Data Engineering
;
Data Management and Quality
;
Information Quality
;
Organizational Concepts and Best Practices
Abstract:
Businesses are increasingly using their enterprise data for strategic decision-making activities. In fact, information, derived from data, has become one of the most important tools for businesses to gain competitive edge. Data quality assessment has become a hot topic in numerous sectors and considerable research has been carried out in this respect, although most of the existing frameworks often need to be adapted with respect to the use case needs and features. Within this context, this paper develops a methodology for assessing the quality of enterprises' daily maintenance reporting, relying both on an existing data quality framework and on a Multi-Criteria Decision Making (MCDM) technique. Our methodology is applied in cooperation with a
Finnish multinational company in order to evaluate and rank different company sites/office branches (carrying out maintenance activities) according to the quality of their data reporting. Based on this evaluation, the industrial partner wants to
establish new action plans for enhanced reporting practices.
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