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BERLIN, GERMANY, February 07, 2015 /24-7PressRelease/ -- Today corporate data is among the most important resources enterprises have. With both the volume of the data and the complexity of data structures being more and more on the rise, enterprises see themselves confronted with multiple challenges. "Corporate data is increasingly becoming a resource of strategic importance. Enterprises demand correct and consistent data and must ensure excellent data quality management in order to be able to automate business processes, improve customer service, and respond quickly to changes in the market," says Prof. Boris Otto, head of the Competence Center Corporate Data Quality (CC CDQ).
The CDQ Good Practice Award, which is given by the CC CDQ and the European Foundation for Quality Management (EFQM), acknowledges first-class initiatives in the field of data quality management. This year's competition saw the participation of nine international enterprises. An international jury of researchers and practitioners evaluated the solutions presented regarding their degree of innovativeness, their practical effectiveness (i.e. the concrete benefit for the enterprise brought about by the solution), and efficiency aspects related to their implementation.
Members of the jury were Dr. Carola Carstens (European Commission), Dr. Wolf Engelbach (Fraunhofer Gesellschaft), Prof. Andy Koronios (University of South Australia), Jodi Maciejewski (American SAP User Group, ASUG), Geert Opdenbosch (EFQM), Henning Uiterwyk (eCl@ss), and Lwanga Yonke (International Association for Information and Data Quality, IAIDQ).
Among the finalists was Swisscom IT Service AG. Two years ago the Swiss telecommunications company started doing data quality management for its material master data on a company wide basis. Swisscom initiated a data quality management project to consolidate redundant data processes, identify responsibilities for these processes, and provide necessary system adaptations. By this, Swisscom was able to reduce process lead times by 87,5 % and the effort for data maintenance by 75 %. Furthermore, both customer and stakeholder satisfaction could be increased substantially.
Another competitor that made it to the final round was Stadtwerke Munchen (SWM) GmbH, one of Germany's largest utility companies. In 2008 SWM established a data quality management department to deal with all data quality related tasks in customer service. The solution presented by SWM mainly refers to assessing the profitability of investments in data quality management. To do so, SWM uses a metric and calculation rules by which monetary potentials of damage as well as measures for improving data quality management can be quantified.
While all jury members agreed that the examples of Swisscom and SWM were definitely first-class initiatives in the field of data quality management, the solution most convincing to the jury was the one presented by British pharmaceutical company AstraZeneca. The company is pursuing the strategic goal of creating full supply chain transparency in order to ensure its competitiveness in the long run. From a data perspective, this goal is supported by worldwide governance of the company's product data. The solution presented by AstraZeneca describes a data quality management project comprising four dimensions (people, processes, systems, and data), by which AstraZeneca was able to achieve substantial improvements and/or cost savings in several areas; for example, GBP 600,000 cost savings through elimination of duplicate data (as a result of better training of employees), GBP 7.5 million through reduction of stock (due to improved data quality allowing improved stock planning), GBP 1 million through more efficient data correction measures (achieved by an overall improvement of the data quality rate from 85 % to 97 % within a period of 18 months).
For more information and a video on the 2014 CDQ Good Practice Award, next year's competition including accompanying events, data quality management training seminars, or the work of the CC CDQ, please visit http://cdq.iwi.unisg.ch.
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Competence Center Corporate Data Quality
Corporate Data Quality
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