Article

Enterprise Master Data Architecture: Design Decisions and Options

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Abstract

The enterprise-wide management of master data is a prerequisite for companies to meet strategic business requirements such as compliance to regulatory requirements, integrated customer management, and global business process integration. Among others, this demands systematic design of the enterprise master data architecture. The current state-of-the-art, however, does not provide sufficient guidance for practitioners as it does not specify concrete design decisions they have to make and to the design options of which they can choose with regard to the master data architecture. This paper aims at contributing to this gap. It reports on the findings of three case studies and uses morphological analysis to structure design decisions and options for the management of an enterprise master data architecture.

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... However, one of the shortcomings of these frameworks is that they lack details regarding decision criteria and design in the master data application architecture domain. To overcome this situation, a comprehensive morphological analysis and a single-case study investigation were conducted by[21] and [24]. However, these studies do not provide any support for practical decision-making. ...
... Based on this, an 'enterprise architecture' is specified by [13, pp.2-3] as " a coherent whole of principles, methods, and models that are used in the design and realization of an enterprise's organizational structure, business processes, information systems, and infrastructure " . An 'information architecture' is a sub-architecture of information systems within the enterprise architecture, and a 'master data architecture' is considered as an information architecture that focuses on a specific data type, namely master data [24]. A master data architecture consists of two main parts: the conceptual master data model, which describes key business objects of enterprises and their relationships [5, p.63, 24], and the master data application architecture, which contains applications for creating, storing and updating instances of the master data attributes defined by the conceptual master data model [24, 36]. ...
... An 'information architecture' is a sub-architecture of information systems within the enterprise architecture, and a 'master data architecture' is considered as an information architecture that focuses on a specific data type, namely master data [24]. A master data architecture consists of two main parts: the conceptual master data model, which describes key business objects of enterprises and their relationships [5, p.63, 24], and the master data application architecture, which contains applications for creating, storing and updating instances of the master data attributes defined by the conceptual master data model [24, 36]. The paper focuses on the second part, the master data application architecture. ...
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Requirements such as integrated view of the customer or global business process integration make enterprise wide management of master data a prerequisite for achieving business goals. The master data application architecture, as a part of enterprise master data management, plays a critical role in enterprises. Choosing the right master data application architecture is a controversial subject in many enterprises. Unfortunately, the current state of the art in research does not provide sufficient guidance for enterprises dealing with this subject. The paper aims at overcoming this gap in research by presenting a decision model for supporting enterprises in the decision-making process regarding the choice of the right master data application architecture. To design the model, Multiple-Criteria Decision Analysis and Design Science Research Methodology were applied.
... Especially in multinational enterprises, these needs for enterprise-wide collaboration, coordination and interoperability are faced by ambiguous definitions of enterprise data 1 across multiple business units, legal contexts, as well as geographical regions, numerous stakeholders and missing responsibilities for enterprise data, multiple distributed, heterogeneous, internal and external applications storing and managing enterprise data in a redundant and inconsistent manner, and a variety of business processes using and managing enterprise data with different goals. Enterprise data in multinational enterprises can be described with regard to the characteristics time reference, change frequency, volume volatility and existential independence [3]. Enterprise data stores and describes characteristics of a company's core business entities, e.g. ...
... Shared access, replication , and flow of enterprise data in order to ensure data quality is controlled in the enterprise data architecture [4] . Enterprise data architecture aims to support collaborative use and management of enterprise data by providing an enterprise data model, enterprise data applications and a description of data flow between applications [3, 5]. Therefore, it is necessary to assess, describe and document business requirements to be met by enterprise data on an attribute level. ...
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Collaboration and coordination within multinational enterprises need unambiguous semantics of data across business units, legal contexts, cultures etc. Therefore data management has to provide enterprise-wide data ownership, an unambiguous distinction between "global" and "local" data, business-driven data quality specifications, and data consistency across multiple applications. Data architecture design aims at addressing these challenges. Particularly multinational enterprises, however, encounter difficulties in identifying, describing and designing the complex set of data architectural dimensions. The paper responds to the research question of what concepts need to be involved to support comprehensive data architecture design in multinational enterprises. It develops a conceptual model, which covers all requirements for defining, governing, using, and storing data. The conceptual model is applied in a case study conducted at a multinational corporation. Well-grounded in the existing body of knowledge, the paper contributes by identifying, describing, and aggregating a set of concepts enabling multinational enterprises to meet business requirements.
... In operating the retail business, especially fashion retail, the master data model (MDM) has often been generic from standard EIS. Generic MDM's rule out product specific characteristics presented that in turn normally has been expected to be handled in e.g. a product data management (PDM) or product life-cycle management (PLM) system (Fitzpatrick et al., 2012; Otto and Schmidt, 2010; Murphy et al., 2005). As PDM/PLM in many cases only are loosely connected to the EIS (ERP) there is a many risk of loss of meaningfulness between the systems, and the quality and relevance of the MDM is therefore focal to establish coherency between products, business and systems (Silvola et al., 2011; Sammon et al., 2010; Russom, 2006). ...
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Retailing, and particularly fashion retailing, is changing into a much more technology driven business model using omni-channel retailing approaches. Also analytical and data-driven marketing is on the rise. However, there has not been paid a lot of attention to the underlying and underpinning datastructures, the characteristics for fashion retailing, the relationship between static and dynamic data, and the governance of this. This paper is analysing and discussing the data dimension of fashion retailing with focus on data-model development, master data management and the impact of this on business development in the form of increased operational effectiveness, better adaptation the omni-channel environment and improved alignment between the business strategy and the supporting data. The paper presents a case study of a major European fashion retail and wholesale company that is in the process of reorganising its master data model and master data governance to remove silos of data, connect and utilise data across business processes, and design a global product master data database that integrates data for all existing and expected sales channels. As a major finding of this paper is fashion retailing needs more strict master data governance than general retailing as products are plenty, designed products are not necessarily marketed, and product life-cycles generally are short.
... The study of Boris Otto and Alexander Schmidt [7], in which different data requirements from different sectors are 978-1-7281-0858-2/19/$31.00 2019 IEEE examined, shows the role of industrial needs in the decisions to be made for the system to be established. ...
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... Today, central data architectures are the prevailing approach to ensure the quality of corporate data, i.e. data on key business objects in a company (e.g. suppliers, materials, customers) (Otto and Schmidt 2010; Dreibelbis et al. 2008). Central data architectures are based on the principle of a " single source of the truth " which is often held in a central database. ...
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An analysis of research methodologies In The information systems research challenge
  • I Benbasat
Benbasat, I. "An analysis of research methodologies." In The information systems research challenge, F. W. McFarlan, Ed. Harvard Business School, Boston, 1985, pp. 47-85
Master Data Management Is Applicable in Down Economies and in Times of Growth
  • A White
  • J Radcliffe
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