Strategic Business Requirements for Master Data Management Systems
Download as PPTX, PDF7 likes6,665 views
The document outlines the strategic business requirements for master data management (MDM) systems, addressing user uncertainties and divergent expectations in MDM initiatives. It provides a framework for improving communication between companies and software vendors, highlighting design principles and essential requirements for effective MDM systems. The research emphasizes the importance of delivering high-quality master data and offers insights into operational challenges and necessary improvements in current MDM practices.
Strategic Business Requirements for Master Data Management Systems
- 1. Strategic Business Requirements for Master Data Management Systems Boris Otto, Martin Ofner Detroit, IL, August 5, 2011 University of St. Gallen, Institute of Information Management Tuck School of Business at Dartmouth College
- 2. Agenda 1. Motivation and Problem Statement 2. Background 3. Research Approach 4. Design Principles and Business Requirements 5. Evaluation 6. Conclusion Detroit, MI, 08/05/11, B. Otto / 2
- 3. The initial situation in practice User Uncertainty1 Diverging Expectations ■ “What is the proper sequence of “We are flooded by invitations from MDM activities in support of MDM? Must we software vendors to sit together and let have solid data integration and data them present their solutions, which are quality practices and architectures in always supposed to be the solution to all place before dealing with MDM?” our problems. When we meet, it’s always ■ “Most of our current data integration the same: They present something we requirements are batch-oriented in aren’t looking for. Then we tell them our nature, as we work to physically understanding of the world and what our consolidate silos of master data. What real requirements are -- what in return they types of packaged data integration do not want or cannot share. And in the tools will be most relevant for our end, everybody goes his own way, highly purposes?” frustrated because they couldn’t sell their ■ “Has market consolidation already product, we didn’t get an answer to our reached the point where the advantages problems, and both of us spent time in of single-vendor stacks for MDM vain.” outweigh the advantages of a best-of- breed strategy?” ■ What are strategic business requirements to be met by MDM systems? ■ How can these requirements be framed to support communication between user companies and software vendors? Detroit, MI, 08/05/11, B. Otto / 3
- 4. Background: Master Data and MDM Master Data Essential business entities a company’s business activities are based on (customers, suppliers, employees, products etc.)2 Master Data Management (MDM) All activities for creating, modifying or deleting a master data class, a master attribute, or a master data object.3 Aiming at providing master data of good quality (i.e. master data that is complete, accurate, timely, and well structured) for being used in business processes.4,5 Detroit, MI, 08/05/11, B. Otto / 4
- 5. Background: MDM Systems MDM Research Foci Architecture Use Cases6,7 Market Surveys10,11 Patterns8,9 Analytical Leading System Operational Central System Repository Peer-to-peer Detroit, MI, 08/05/11, B. Otto / 5
- 6. Research process according to the principles of Design Science Research12 ANALYSIS ■ Expert interviews13 (02/28/09) to identify and describe problem ■ “Future Search”14 activities (05/07 to 05/14/09) to define objectives of a solution DESIGN & DEMONSTRATION ■ “Future Search” activities to identify design principles ■ Reference modeling15 for framework design ■ Focus groups16 (06/24, 09/29, and 12/02/09) to demonstrate objectives and design principles EVALUATION ■ “Offline” expert evaluation (via email, 11/30 to 12/18/09) ■ Focus group evaluation (05/27/10) COMMUNICATION ■ Presentation to practitioners community (05/27/10) Q1/09 Q2/09 Q3/09 Q4/09 Q1/10 Q2/10 Q3/10 Q4/10 Detroit, MI, 08/05/11, B. Otto / 6
- 7. Structure of the framework of strategic business requirements for MDM Business Context Shortcomings of Strategic MDM Use Current Solutions Cases Design Principles Strategic Business Requirements Framework Detroit, MI, 08/05/11, B. Otto / 7
- 8. The initial situation in practice Current Shortcomings Use Cases ■ No downstream visibility of data ■ Poor business semantics management ■ Risk management and compliance ■ MDM and data quality management separated ■ Integrated customer management ■ “Stovepipe” approach for MDM architectures ■ Business process integration and ■ No consistent master data service approach harmonization ■ No predefined content ■ No “on the fly” mapping and matching ■ Reporting ■ Poor support of centralized management of decentralized/federated datasets ■ IT consolidation ■ No integrated business rules management ■ Poor support of distinction between “global” and “local” data ■ Poor support of compliance issues ■ Insufficient transition management Detroit, MI, 08/05/11, B. Otto / 8
- 9. Design principles Master Data as a Product Deep Market for Integration Master Data Design Principles Process Subsidiarity Quality The Context- “Nucleus” awareness Detroit, MI, 08/05/11, B. Otto / 9
- 10. Strategic business requirements Supports Design ID Requirement Design Area Principle(s) R1 Support of Master Data Product Descriptions Strategy Master Data as a Product R2 Sourcing of Master Data Products Strategy Market for Master Data R3 Integration of External Master Data Sources Strategy Market for Master Data R4 Quality Management of Master Data Products Controlling Process Quality and Services R5 Audit Management of Master Data Products and Controlling Process Quality Services R6 Management of Role Access Rights according to Organization Subsidiarity Data Governance Roles R7 Escalation Management Organization Subsidiarity R8 Support of Usage Monitoring of Master Data Operations Process Quality Products R9 Maintenance for Context-Aware Master Data Operations Context Awareness Products R10 Gauging of Master Data Product consumption Operations Process Quality R11 Requirements Engineering for Master Data Operations Master Data as a Product Products R12 Design and Maintenance of Global/Local Master Operations Process Quality Data Management Processes Detroit, MI, 08/05/11, B. Otto / 10
- 11. Strategic business requirements (cont’d) Supports Design ID Requirement Design Area Principle(s) R13 Internal Customer Support Operations Master Data as a Product R14 Management of Business Rules for Data Operations Process Quality Standards R15 Support of End-to-End Master Data Product Operations Context Awareness Lifecycles R16 Support of Master Data Provenance Tracing Operations Process Quality R17 Data Standards Management Integration The Nucleus Architecture R18 Enforcement of Data Standards Integration The Nucleus Architecture R19 Bottom-up Data Modeling using Heuristics Integration The Nucleus Architecture R20 Delivery of Predefined Content Integration The Nucleus Architecture R21 Maintanance of Global/Local Master Data Model Integration The Nucleus Design Architecture R22 Subscription of Master Data Products Applications Deep Integration R23 Support of Interoperability Standards Applications Deep Integration Detroit, MI, 08/05/11, B. Otto / 11
- 12. Publication as managerial report Co-signed by: Detroit, MI, 08/05/11, B. Otto / 12
- 13. Multi-perspective framework evaluation17 Perspective Description Evaluation Result A Economic No statement on direct business benefits possible at present. Focus groups expect improvements regarding internal and external communication. B Deployment Focus group was considered complete, appropriate, and applicable. Community voted for continuation of initiative. C Engineering Rather informal at present. Software vendors participating in focus group on 05/27/2010 demanded more concrete scenarios. D Epistemological Accepted guidelines and research methods were applied. Detroit, MI, 08/05/11, B. Otto / 13
- 14. Conclusions The framework addresses an acute need in the practitioners’ community Practitioners benefit from the framework as it facilitates internal and external communication The paper adds to the scientific body of knowledge since it presents an abstraction of an information system in a quite neglected area of IS research. Detroit, MI, 08/05/11, B. Otto / 14
- 15. Contact Dr.-Ing. Boris Otto University of St. Gallen, Institute of Information Management Tuck School of Business at Dartmouth College Boris.Otto@unisg.ch Boris.Otto@tuck.dartmouth.edu +1 603 646 8991 Detroit, MI, 08/05/11, B. Otto / 15
- 16. Appendix Endnotes Detroit, MI, 08/05/11, B. Otto / 16
- 17. Endnotes 1) Friedman, T. "Q&A: Common Questions on Data Integration and Data Quality From Gartner's MDM Summit", Gartner, Inc., Stamford, CT. 2) Smith, H.A. and McKeen, J.D. "Developments in Practice XXX: Master Data Management: Salvation or Snake Oil?” Communications of the AIS (23:4) 2008, pp 63-72. 3) Ibid. 4) Karel, R. "Introducing Master Data Management", Forester Research, Cambridge, MA. 5) Loshin, D. Master Data Management Morgan Kaufmann, Burlington, MA, 2008. 6) Dreibelbis, A., Hechler, E., Milman, I., Oberhofer, M., van Run, P., and Wolfson, D. Enterprise Master Data Management: An SOA Approach to Managing Core Information Pearson Education, Boston, MA, 2008. 7) Loshin, D. Master Data Management Morgan Kaufmann, Burlington, MA, 2008. 8) Loser, C., Legner, C., and Gizanis, D. "Master Data Management for Collaborative Service Processes", International Conference on Service Systems and Service Management, Research Center for Contemporary Management, Tsinghua University, 2004. 9) Otto, B. and Schmidt, A. "Enterprise Master Data Architecture: Design Decisions and Options", in: Proceedings of the 15th International Conference on Information Quality (ICIQ-2010), Little Rock, USA, 2010. 10) Radcliffe, J. "Magic Quadrant for Master Data Management of Customer Data", G00206031, Gartner, Inc., Stamford, CT. 11) White, A. "Magic Quadrant for Master Data Management of Product Data", G00205921, Gartner, Inc., Stamford, CT. 12) Peffers, K., Tuunanen, T., Rothenberger, M.A., and Chatterjee, S. "A Design Science Research Methodology for Information Systems Research", Journal of Management Information Systems (24:3) 2008, pp 45-77. 13) Meuser, M. and Nagel, U. "Expertenwissen und Experteninterview", in: Expertenwissen. Die institutionelle Kompetenz zur Konstruktion von Wirklichkeit, R. Hitzler, A. Honer and C. Maeder (eds.), Westdeutscher Verlag, Opladen, 1994, pp. 180-192. Detroit, MI, 08/05/11, B. Otto / 17
- 18. Endnotes 14) Weisbord, M. Discovering Common Ground: How Future Search Conferences Bring People Together to Achieve Breakthrough Innovation, Empowerment, Shared Vision, and Collaborative Action Berrett-Koehler, San Francisco, 1992. 15) Schütte, R. Grundsätze ordnungsmässiger Referenzmodellierung: Konstruktion konfigurations- und anpassungsorientierter Modelle Gabler, Wiesbaden, Germany, 1998. 16) Morgan, D.L. and Krueger, R.A. "When to use Focus Groups and why?" in: Successful Focus Groups, D.L. Morgan (ed.), Sage, Newbury Park, California, 1993, pp. 3-19. 17) Frank, U. "Evaluation of Reference Models", in: Reference Modeling for Business Systems Analysis, P. Fettke and P. Loos (eds.), Idea Group, Hershey, Pennsylvania et al., 2007, pp. 118-139. Detroit, MI, 08/05/11, B. Otto / 18