Construction of a master data management strategy. Methodologies and tools

Content

Abstract

1. Introduction
1.1 Problem statement
1.2 Research question
1.3 Objective
1.4 Structure of the paper

2. Fundamentals and Basic terms
2.1 Master data
2.2 master data management
2.3 master data management strategy

3. Methodology for the literature work
3.1 Methodology
3.2 Keywords ans search queries
3.3 Search filter
3.4 Literature sources

4. Resultofthe Work
4.1 Construction of master data management strategy: methodologies and tools
4.1.1 Methodologies
4.1.2 Evaluation of reasearch findings: methodologies
4.1.3 Tools
4.1.4 Ecaluation of research findings: tools

5. Discussion and conclusion
5.1 Discussion
5.2 Conclusion

Literature

Appendix

Construction of a master data management strategy: methodologies and tools

Florette Chamga T.

Heilbronn University, Faculty of Information systems 03.07.2016

Abstract

In a world governed by mobile internet and characterized by an increasing number of active customers on the way, companies have to face the difficulty of implementing an adequate strategy for proper master data management. The drastic increase in active mobile connection of both companies and customers leads to rapid master data growth and therefore points out the necessity of implementing a management strategy. The construction of a master data management strategy implies the interaction of different tools and methodologies. Starting with an overview of existing literature and limiting itself within the given scope, the present review then handles the interaction proper. This constitutes the essential component of this work

Keywords: master data management (MD M), master data management strategy, master data management solution, “Stammdatenpflege ”

1 Introduction

1.1 Problem statement

Check a friend’s address on google map or consult incoming mails using a smartphone is though “normal” task, but also implies and exponential increase of information exchange. Most software systems have lists of data, master data, which is shared and used by several of the applications that make up the system and will also be subjected to an exponential expansion. Furthermore, a company might grow through merger and this logically implies there will be a need to merge all available data which can be a cumbersome task. It would therefore be judicious to think of a strategy to facilitate all this management stuff and thus increase productivity.

1.2 Research question

Just like going to war requires having the necessary weapons, it is important to find out which methodologies and tools are needed to construct or implement a solid data management strategy. By the way: Which methodologies and tools are available to construct a master data management strategy?

The research question can be subdivided into smaller units to ease understanding:

- What is master data? What is MDM? What is a MDM strategy?
- How a master data management strategy has to be constructed?
- Which methodologies are available to construct a master data management strategy?
- Which tools are available to construct a master data management strategy?

1.3 Objective

It is crucial for companies to elaborate a master data management strategy and this has to be done in a way that is convenient, time and cost efficient. Restraining within boundaries set by the research question, this seminar thesis primarily aims at describing the available methodologies and tools facilitating the construction of a master data management strategy.

1.4 Structure of the paper

After presenting the problem statement, the research question and explaining the objective, this work goes forward with the definition of the core concepts, followed by the presentation of the methodologies used for the literature analysis and, finally the outputs of the conducted literature analysis.

2 Fundamentals and Basic terms

2.1 Master data

Master data refers to data repeatedly needed for the operations of a company and therefore must be saved permanently. This could be data related to customers and employees as well as suppliers, constituting one of the company’s core components. Marco Spruit and Katharina Pietzka define master data as “data describing the most relevant business entities, on which the activities of an organization are based, e.g. counterparties, products or employees. In contrast to transactional data (invoices, orders, etc.) and inventory data, master data are oriented towards the attributes” Marco Spruit and Katharina Pietzka, “MD3M: The Master Data Management Maturity Model,” Computers in Human Behavior 51 (2014): 1068-76

Andrew White et al. directly associate master data to a company’s identity and define it as “the consistent and uniform set of identifiers and extended attributes that describe the core entities of the enterprise”. Master data carry certain advantages in the management of business process, “analysis and communication across the enterprise”, such as: their use involves “consistency, simplification and uniformity of process, analysis”. For this reason, organizations apply for master data programs. As “a master data program helps organizations break down operational barriers, thus enabling greater enterprise agility and simplifying integration activities”. Andrew White et al., “Mastering Master Data Management,” Gartner 6, no. October (2014): 1-2.

To specify, what master data is. It is worth considering the opinions of some authors. According to Tyler Graham and Suzanne Selhorn, “the definition of “master” data varies by organization, but can be loosely defined as the nouns that describe all business processes. These nouns might be organisation-specific data, like your list of products or employees. They might be common reference data provided by external service [...] like address Information.” TYLER GRAHAM and SUZANNE SELHORN, Microsoft SQL Server 2008 R2 Master Data Services, 2011.

Since, there is not a uniform definition of master data. Daniel Liebhart mentions Griffin²⁰⁰⁵ in his book [SOA goes real]. Griffin presents a sample explanation, which can be considered as a general definition of the term master data: master data can be regarded as “information's that are necessary to create and support a company-wide system of central business entities as records”. Daniel Liebhart, SOA Goes Real: Service-Orientierte Architekturen Erfolgreich Planen Und Einführen (Carl Hanser Verlag GmbH & Co. KG, 2007).

2.2 Master data management

The Management of master data is an important task in business operation. IBM defines it as “a set of disciplines, technologies and solutions that are used to create and maintain consistent, contextual and accurate business data for all stakeholders”. In other words it is the “must have” toolbox for a company willing to better manage its resources and achieve success. IBM corporation, “Master Data Management : Looking beyond the Single View to Find the Right View .,” no. April (2007).

Boris Otto and Andreas Reichert describe master data management as “an application- independent process” which helps organizations describing, owning and managing core business data entities. Thus, the management process of master data likely seems to be a Business Engineering (BE) task which requires organizational design. Boris Otto and Andreas Reichert, “Organizing Master Data Management: Findings from an Expert Survey,” Proceedings of the 2010 ACM Symposium on ..., 2010, 106-10. Talking of Business Engineering, it acts as interface between knowledge in the field of business administration and information technology and sets it at the disposal of all transformation aspects ranging from presentation to process model and political consideration. Baumöl Ulrike and Jung Reinhard, “Wirtschaftsinformatik in Wissenschaft Und Praxis,” in Wirtschaftsinformatik in Wissenschaft Und Praxis, 2014, 249-69.

Therefore, due to the different points of views, master data management as part of industrial data management is assigned to perform the following tasks:

- Description of master data strategy as well as the essential objectives and enterprise­wide policies and standards for the handling of master data, in the course of which the availability, integrity and security of master data is assured
- Pointing out the necessity of the acquisition administration and maintenance of master data
- Development of an information model for all master data objects at the enterprise level
- Development and maintenance of suitable master data architecture and if needed implementation of master data management and distribution systems

It possesses therefore a suitable element for organizational business management. Legner Christine and Boris Otto, “Stammdatenmanagement,” no. July (2016).

2.3 Master data management strategy

The implementation of a sustainable master data management system is a big challenge faced by almost every company nowadays. It is even more challenging considering the fact that data quality measurement and monitoring has to be done on a continuous base. Precaution has to be taken to ensure a smooth process flow.

Allen Dreibelbis et al. define MDM Strategy as a “value-enabling combination of business and technical components. It needs to include the business participation, business motivation, and overall guidelines from the business”. This is concerned by major issues, objectives, standards and guidelines, which the organization intends to achieve. Central part of this research work, a master data management strategy “addresses a wide variety of business and technical concerns within an enterprise. It is often wise to address these concerns incrementally. Incremental deployment allows significant value to be provided as each phase of an MDM project expands the capabilities of the MDM by integrating additional systems, extending the kinds of data managed, or providing new ways in which the master data may be used”. Allen Dreibelbis et al., Enterprise Master Data Management: An SOA Approach to Managing Core Information, 2008.

Furthermore, defining a strategy to manage master data should always be highlighted because it constitutes the basis of successful MDM development in the enterprise. Companies with a well- defined master data management strategy are more advanced in their development than companies with none. The master data management strategy has to support the business strategy and take the IT strategy into account. This strategy also enables to define a business vison involving activity fields and reflecting wishes and priorities of decision makers. Henrik Packowski, Josef; Baumeier, Strategisches Stammdatenmanagement: Voraussetzung für agile und effiziente Geschäftsprozesse, 18-19, 48-49 (2012).

As mentioned by Martin Hubert Ofner et al., a strategy let decision maker specify directive of the MDM initiative. In other words, a strategy support them by specifying “important principles and guidelines which have an effect on the decisions”. In this case, the main “goals of MDM initiative” should be defined based on the “business benefit”. Thus, it is indispensable to clarify “which type of master data (typically customer, material, and supplier master data), which company units and departments, and which information systems (IS) are to be included”. Martin Hubert Ofner et al., “Management of the Master Data Lifecycle: A Framework for Analysis,” Journal of Enterprise Information Management 26, no. 4 (2013): 472-91.

3 Methodology for the literature work

3.1 Methodology

The process model of “Fettke” and „Webster & Watson” are taken in consideration to elaborate a literature review bringing an approach answering the research question of this seminar thesis.

The process model of “Fettke” describes how the literature review is done, as shown in the figure bellow.

Abbildung in dieser Leseprobe nicht enthalten

Figure 1: Process model for literature analysis according to Fettke

Moreover, the taxonomic classification of reviews according to Fettke has been used to develop a research design regrouping literature into special categories. This helps for example in shedding light on the focus of the research or to clearly identify the audience of the research work. See Table 2.

The “Webster & Watson model” has been used to conceptualize the topic based on relevance. This is done in the course of reading the different available papers. Afterwards, literature will be synthesized through discussion of overall ideas and consideration between the collected concepts. An example of the model is shown in the table 4-6.

3.2 Keywords and search queries

A list of keywords has been used to refine the literature research in order to cover all aspects and details of the topics. A popular search strategy basically consists in distinguishing between key-word and free text entries, whereby the final structure of a search word was often a combination of both.

- Synonyms have been considered during the selection of suitable search key words in order to increase the number of possible matches.
- Free text formulations are used to identify aspects that have not been covered using keywords indexing and hence identify shortcomings.

List of keywords: master data, master data management, MDM strategy, “Stammdatenmanagement-Strategie”, master data methodology, MDM strategy tools, corporate strategy, business strategy, Roadmap for master data management strategy.

A systematic search in the database is performed with a combination of Tags. Each search entry is constructed in the following way: “Master data” AND “management”, “Master data” AND “management” AND “strategy“, “MDM strategy AND tool OR methodology, etc.

3.3 Search filter

Period of interest during research: 2007 - 2016, due to the large proliferation of multitouch smartphones and tablets computers as from the year 2007, there has been a leap in the business world thanks "mobile Internet". This of course automatically leads to an increased amount of master data. Customers and suppliers work on the go and this implies a large master data set. It therefore makes sense to consider a proper range.

Language of research: English and German, two languages are used to optimize the search result.

Keywords: they are used to refine the topic.

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