Qualitätsorientiertes Artikelstammdatenmanagement und dessen wirtschaftliche Effekte auf die Prozesskette aus Sicht eines globalen Artikelstammdatenpools

In essence, this dissertation is the proof that both the quality of item master data and the management of this data in daily work processes on both retailer and supplier side arena t sufficiently considered. In order to investigate this aspect, the first step is to lay down the theoretical foundations for the terms data quality, item master data and their management. It also classifies the benefits of a better data quality such as cost savings, faster flow of goods and increased customer satisfaction from the supplier perspective with respect to the use of data in retail trade. Furthermore, it takes the difficulty of capturing such benefits in terms of concrete profitability into account. In the second step, the item master data quality will be defined through six distinct data quality dimensions and operationalized for usage in the field. These are correctness, consistency, completeness, standard conformity, trustworthiness and authorized accessibility. All six dimensions were measured and evaluated in eleven supplier case studies of the German consumer goods market, all customers of the item master data pool 1WorldSync, in the years 2014 to 2015. Additionally, two dimensions, correctness and trustworthiness, were measured in the sense of a data crunch on the data pool side and in five retailers of the German food and drugstore trade. The main focus of the data quality measurement is therefore on the interoperable item master data exchange via the Global Data Synchronization Network (GDSN) as standard of Global Standard 1 (GS1). The case studies were evaluated in a multi-case design. The results of the individual cases are compared in terms of pattern recognition. In addition to a comparison between the achieved versus self-assessed data quality of the suppliers, the extent of the Item Master Data Quality Management (IMDQM) related to the areas of knowledge and organization - determined with the help of a scoring model at the sup-pliers -were measured. Based on the findings of the case studies and the consistency check recommendations for the optimization of the data quality for suppliers, retailers and their used data pool were derived. The data crunch was aimed at gathering information on how data quality initiatives on the supplier side affect the data pool and retailers. This is achieved by investigating if and how supplier data changes on the way to a retailera s IT system. The critical debate and evaluation related to the economic effects of an improved data quality is also part of the results. The discussion focuses on the extent to which it is worth investing in improved data quality for suppliers. An attempt is made to answer the question whether the improvement across the value chain really pays off. This dissertation is aimed at professionals in the scientific and business communities, who deal with the topics item master data and their quality optimization