Kai M. Hüner

Design alternatives for the evaluation of design science research artifacts

Within a consideration of cost effectiveness the evaluation of design science research artifacts is of major importance. In the past, a plenitude of approaches has been developed for this purpose -- partly artifact-specific, partly artifact-neutral. Nonetheless, there is a lack of a comprehensive overview over existing methods as well as a systemization of those with regard to fundamental structuring criteria. The paper at hand surveys existing methods and introduces a framework that equally supports the designer and the user of artifact evaluation approaches. Subsequent to the embedding of the framework into the design science research process two exemplary application scenarios are described.

Towards a maturity model for corporate data quality management

High-quality corporate data is a prerequisite for world-wide business process harmonization, global spend analysis, integrated service management, and compliance with regulatory and legal requirements. Corporate Data Quality Management (CDQM) describes the quality oriented organization and control of a companys key data assets such as material, customer, and vendor data. With regard to the aforementioned business drivers, companies demand an instrument to assess the progress and performance of their CDQM initiative. This paper proposes a reference model for CDQM maturity assessment. The model is intended to be used for supporting the build process of CDQM. A case study shows how the model has been successfully implemented in a real-world scenario.

Collaborative management of business metadata

Legal provisions, cross-company data exchange and intra-company reporting or planning procedures require comprehensively, timely, unambiguously and understandably specified business objects (e.g. materials, customers, and suppliers). On the one hand, this business metadata has to cover miscellaneous regional peculiarities in order to enable business activities anywhere in the world. On the other hand, data structures need to be standardized throughout the entire company in order to be able to perform global spend analysis, for example. In addition, business objects should adapt to new market conditions or regulatory requirements as quickly and consistently as possible. Centrally organized corporate metadata managers (e.g. within a central IT department) are hardly able to meet all these demands. They should be supported by key users from several business divisions and regions, who contribute expert knowledge. However, despite the advantages regarding high metadata quality on a corporate level, a collaborative metadata management approach of this kind has to ensure low effort for knowledge contributors as in most cases these regional or divisional experts do not benefit from metadata quality themselves. Therefore, the paper at hand identifies requirements to be met by a business metadata repository, which is a tool that can effectively support collaborative management of business metadata. In addition, the paper presents the results of an evaluation of these requirements with business experts from various companies and of scenario tests with a wiki-based prototype at the company Bayer CropScience AG. The evaluation shows two things: First, collaboration is a success factor when it comes to establishing effective business metadata management and integrating metadata with enterprise systems, and second, semantic wikis are well suited to realizing business metadata repositories.

Product data quality in supply chains: the case of Beiersdorf

A number of business requirements (e.g. compliance with regulatory and legal provisions, diffusion of global standards, supply chain integration) are forcing consumer goods manufacturers to increase their efforts to provide product data (e.g. product identifiers, dimensions) at business-to-business interfaces timely and accurately. The quality of such data is a critical success factor for efficient and effective cross-company collaboration. If compliance relevant data (e.g. dangerous goods indicators) is missing or false, consumer goods manufacturers risk being fined and see their company’s image damaged. Or if logistics data (e.g. product dimensions, gross weight) is inaccurate or provided not in time, business with key account trading partners is endangered. To be able to manage the risk of business critical data defects, companies must be able to a) identify such data defects, and b) specify and use metrics that allow to monitor the data’s quality. As scientific research on both these issues has come up with only few results so far, this case study explores the process of identifying business critical product data defects at German consumer goods manufacturing company Beiersdorf AG. Despite advanced data quality management structures such defects still occur and can result in complaints, service level impairment and avoidable costs. The case study analyzes product data use and maintenance in Beiersdorf’s ecosystem, identifies typical product data defects, and proposes a set of data quality metrics for monitoring those defects.

The Effect of Using a Semantic Wiki for Metadata Management: A Controlled Experiment

A coherent and consistent understanding of corporate data is an important factor for effective management of diversified companies and implies a need for companywide unambiguous data definitions. Inspired by the success of Wikipedia, wiki software has become a broadly discussed alternative for corporate metadata management. However, in contrast to the performance and sustainability of wikis in general, benefits of using semantic wikis have not been investigated sufficiently. The paper at hand presents results of a controlled experiment that investigates effects of using a semantic wiki for metadata management in comparison to a classical wiki. Considering threats to validity, the analysis (i.e. 74 subjects using both a classical and a semantic wiki) shows that the semantic wiki is superior to the classical variant regarding information retrieval tasks. At the same time, the results indicate that more effort is needed to build up the semantically annotated wiki content in the semantic wiki.

Fachliches Metadatenmanagement mit einem semantischen Wiki

ZusammenfassungUm aktuellen Herausforderungen weltweiter Märkte begegnen zu können, brauchen Unternehmen ein einheitliches Verständnis ihrer Geschäftsobjekte. Einerseits sind regionale Spezifika zu unterstützen, um weltweit agieren und z.B. günstige Produktionsstandorte nutzen zu können. Andererseits sind einheitliche Daten-strukturen für unternehmensweite Analysen erforderlich, um z.B. globale Einkaufsstrategien umsetzen und vorteilhafte Einkaufskonditionen aushandeln zu können. Zusätzlich müssen Geschäftsobjekte neue Anforderungen seitens des Markts und regulierender Institutionen möglichst schnell abbilden — und das weltweit und konsistent. Ziel eines effektiven Managements von Geschäftsobjekt-Metadaten ist somit die Bereitstellung aktueller, detaillierter, flexibler und gleichzeitig unternehmensweit konsistenter Metadaten (z.B. technische undfachliche Spezifikationen, anwendungsspezifische Informationen zur korrekten Nutzung). Zur Unterstützung dieser Aufgabe stellt der Beitrag das Konzept eines fachlichen Metadatenkatalogs vor und diskutiert einen Wiki-basierten Prototyp, der gemeinsam mit dem Unternehmen Bayer CropScience realisiert wurde. Die Evaluation des Prototyps zeigt, dass sich insbesondere semantische Wikisgutzur Realisierung eines fachlichen Metadatenkatalogs eignen.

Unternehmensweites Datenqualitätsmanagement: Ordnungsrahmen und Anwendungsbeispiele

Das Marktumfeld vieler Unternehmen zeichnet sich heutzutage einerseits durch kurze Innovationszyklen und kurze Markteinfuhrungszeiten aus. Andererseits wachst die zu beherrschende Komplexitat z. B. durch global harmonisierte Geschaftsprozesse und weltweit einheitlichen Kundenservice. Beides fuhrt dazu, dass Entscheidungen im Unternehmen in immer kurzeren Abstanden und auf Grundlage einer wachsenden Menge an Informationen getroffen werden mussen.