EFQM Excellence Model for Corporate Data Quality Management (CDQM)

The trend towards the data economy (Newman 2011) leads to increasing requirements for the quality of a companys data resource. In particular global enterprises must manage corporate data quality to address a number of strategic challenges. Examples are compliance to legal regulations and contractual obligations, global business process harmonization and integration, integrated customer management (360-degree-view), corporate reporting needs such as spend analysis in purchasing, and the ongoing trend of value chain integration. In an attempt to manage data as a product (Wang et al. 1998) and to transfer quality management principles from the world of physical goods to intangible assets such as data, a number of enterprises started to establish corporate data quality management as a organizational function. The rationale behind these efforts is the ambition to manage corporate data quality preventively - rather than reactively. The idea is to take care of data quality before data defects occur and not clean up after they have occurred.With this being a step into the right direction enterprises are confronted, though, with a number of new issues. Examples are:* How tell whether you are doing a good job in establishing preventive quality management for your corporate data?* How determine the baseline from which you start and how know where to go?* How measure the progress that you made?* How tell whether you are doing as good as the peers in your industry?The Competence Center Corporate Data Quality (CC CDQ, see http://cdq.iwi.unisg.ch) at the University of St. Gallen, Switzerland, has taken up these questions and proposed a maturity model for corporate data quality management. The CC CDQ is a consortium research (Österle Otto 2010) project in which practitioners from large enterprises such as Astra Zeneca, Bayer, Bosch, Deutsche Telekom, Nestlé, Novartis, and Siemens work closely with academic researchers to design models, methods, and solutions for corporate data quality management.The development of the maturity model followed a Design Science Research (Hevner et al. 2004) approach. The work was started in 2008 with the analysis of requirements and the collaborative specification of the objectives within the CC CDQ. A first artifact design was presented and discussed within the scientific community in early 2009 (Hüner et al. 2009). In parallel, the researchers approached the European Foundation for Quality Management (EFQM) in order to use an existing standard for the design of the maturity model. In the second quarter of 2009, a memorandum of understanding was signed between EFQM and the CC CDQ documenting the mutual agreement to collaboratively develop an EFQM Excellence Model for Corporate Data Quality Management. Also in 2009, a second version of the model design was presented and discussed at AMCIS with a particular focus on the management of the models complexity (Ofner et al. 2009). The maturity model has been continuously revised and updated based on feedback from EFQM, the CC CDQ, and pilot application in user companies (Corning Cable Systems, Syngenta among others).In early April 2011, the EFQM Excellence Model for Corporate Data Quality Management was officially released and sent out to all members of the worldwide EFQM organization (EFQM 2011). In addition to that, an online benchmarking platform went productive offering a self-assessment service to interested enterprises (https://benchmarking.iwi.unisg.ch/).Following the principles of consortium research and Design Science Research the CC CDQ seeks to further disseminate the results of its research and - in an effort to further improve the model - asks for feedback to the current version. The current version of the model is available under https://benchmarking.iwi.unisg.ch/Framework_for_CDQM.pdf.