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Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
Master Data Governance Best Practices
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Master Data Governance Best Practices

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This presentation illustrates best practices in master data governance through a rich set of case studies. The presentation leverages seven years of in-depth experience in the field from the …

This presentation illustrates best practices in master data governance through a rich set of case studies. The presentation leverages seven years of in-depth experience in the field from the Competence Center Corporate Data Quality.

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  • 1. Audi-Endowed Chair of Supply Net Order Management Best Practices in Master Data Governance Prof. Dr. Boris Otto | Berlin, 2013/9/23
  • 2. Audi-Endowed Chair of Supply Net Order Management Agenda  Master Data as a Business Success Factor  Five Principles for Master Data Governance  Outlook Prof. Dr. Boris Otto | Berlin, 2013/9/23 2
  • 3. Audi-Endowed Chair of Supply Net Order Management Bayer CropScience is a leader in the crop protection market Prof. Dr. Boris Otto | Berlin, 2013/9/23 3
  • 4. Audi-Endowed Chair of Supply Net Order Management Master data quality is a key prerequisite for business process performance1 Data Object “Product Hierarchy” 09 11 012 242 3938 Business Area Business Field Business Segment Active Ingredient Product Group Data not available Data Quality Issues Data not complete Data not consistent Business Process Impact Planning: Demand for active ingredients unknown Revenue reporting: Revenue not transparent on country Segmentation: Risk of poor portfolio planning 1) [EBNER/BRAUER 2011]. Prof. Dr. Boris Otto | Berlin, 2013/9/23 4
  • 5. Audi-Endowed Chair of Supply Net Order Management Johnson & Johnson is a leading producer of consumer products Franchises Headquarter Prof. Dr. Boris Otto | Berlin, 2013/9/23 Skin Care, Baby Care, Consumer Healthcare, OTC Skillman, NJ (USA) 5
  • 6. Audi-Endowed Chair of Supply Net Order Management In early 2008, Johnson & Johnson was suffering from poor master data quality1 “Production was delayed at manufacturing plants” “Project Management did not know what stage products are in” Controlling “Trucks were waiting at the docks for materials to be activated” Portfolio Management and New Product Introduction Inbound Logistics “Purchase orders were not ready on time” Production Sales & Distribution “Defective data was sent to GS1 US” Procurement Financial Accounting “Customers were invoiced wrong” Other Support Processes For less than 30 of products’ dimensions and weights, data was within the allowed 5 % error margin 1) [OTTO 2013]. Prof. Dr. Boris Otto | Berlin, 2013/9/23 6
  • 7. Audi-Endowed Chair of Supply Net Order Management Master data quality drivers affect the entire company Group Division 1 Division 2 Division 3 Business units Business processes Locations Business units Business processes Locations Business units Business processes Locations Compliance to regulations 360 degree view of the customer Integrated and automated business processes “Single Source of the Truth” Prof. Dr. Boris Otto | Berlin, 2013/9/23 7
  • 8. Audi-Endowed Chair of Supply Net Order Management Master data quality evolves over time according to a “jigsaw” pattern Master data quality Time Project 1 Legend: Project 2 Project 3 Master data quality issues. Prof. Dr. Boris Otto | Berlin, 2013/9/23 8
  • 9. Audi-Endowed Chair of Supply Net Order Management The case of Bayer CropScience illustrates the various data quality issues companies have to deal with1 Employees Data Maintenance Training and education inadequate No integrated software support Various software solutions in place Data maintenance not harmonized on global level Data quality not integrated in performance management systems No data quality metrics No continuous data quality monitoring Master data can be edited in target systems No binding rules, standards, operating procedures Too many local rules, exceptions Data Quality Management Standards No “Data Governance” Data quality issues Missing business responsibilities Organization 1) [BRAUER 2009]. Prof. Dr. Boris Otto | Berlin, 2013/9/23 9
  • 10. Audi-Endowed Chair of Supply Net Order Management Corporate Data Quality Management (CDQM)1 comprises six key enablers 1) [OTTO ET AL. 2011]. Prof. Dr. Boris Otto | Berlin, 2013/9/23 10
  • 11. Audi-Endowed Chair of Supply Net Order Management Agenda  Master Data as a Business Success Factor  Five Principles for Master Data Governance  Outlook Prof. Dr. Boris Otto | Berlin, 2013/9/23 11
  • 12. Audi-Endowed Chair of Supply Net Order Management Data Governance and Data Quality Management are closely interrelated is sub-goal of Maximize Data Value supports supports is led by Data Governance Maximize Data Quality is sub-function Data Management of Data Quality Management are object of are object of are object of Data Assets Legend: Goal Function Data. Prof. Dr. Boris Otto | Berlin, 2013/9/23 Source: Otto, B.: Data Governance, in: WIRTSCHAFTSINFORMATIK, 53, 4, 2011, S. 235-238. 12
  • 13. Audi-Endowed Chair of Supply Net Order Management Data Governance effectiveness still varies widely today1 7.5 7.5 25.0 30.0 30.0 very good good mediocre adequate poor 1) [MESSERSCHMIDT/STÜBEN 2011]. NB: Figures are percentages. Prof. Dr. Boris Otto | Berlin, 2013/9/23 13
  • 14. Audi-Endowed Chair of Supply Net Order Management What issues does upper management see with regard to Data Governance? The case of Syngenta  Business benefits  “Keep in mind to balance costs for double-handling on one hand and of high discipline on the other.”  “Emphasize usability of MDM, its value.”  Organizational readiness  “Data owners and data stewards are terms people don‘t understand. Be educational and promotive.”  “Organizational maturity differs in the divisions.”  Data Governance implementation and execution     “What’s the migration path? Are there intermediate staging gates?” “Is it a journey or can one make a choice? Or both?” “How to integrate this strategy into the program of next year?” “How to integrate the 35,000 ft view with daily operations?” NB: Selected quotes from a series of eight interviews with line managers conducted in October and November 2011. Prof. Dr. Boris Otto | Berlin, 2013/9/23 14
  • 15. Audi-Endowed Chair of Supply Net Order Management Five key principles lead to excellence in master data governance Build up a Data Governance Capability Enter Data “First Time Right” Capture Data at the Source Measure to Manage Scale Capabilities Globally Prof. Dr. Boris Otto | Berlin, 2013/9/23 15
  • 16. Audi-Endowed Chair of Supply Net Order Management Typically, Data Governance capabilities have first to be built up NB: Based on data from eight cases (Bayer CropScience, Corning Cable Systems, DB Netz, Deutsche Telekom, Johnson & Johnson, Robert Bosch, Syngenta, ZF) Prof. Dr. Boris Otto | Berlin, 2013/9/23 16
  • 17. Audi-Endowed Chair of Supply Net Order Management Note taken in a meeting with Johnson & Johnson on November 29, 2011, in Skillman, NJ Prof. Dr. Boris Otto | Berlin, 2013/9/23 17
  • 18. Audi-Endowed Chair of Supply Net Order Management The ideal lifecycle of Data Governance capabilities follows an “S” curve E Founding Phase „First Time Right“ Legend: E  Effectiveness; A  Amount of Activity. Prof. Dr. Boris Otto | Berlin, 2013/9/23 Cleansing A 18
  • 19. Audi-Endowed Chair of Supply Net Order Management It is not a perfect world, though E E Pattern I E Pattern II Pattern III 5. 3. 4. 3. 2. 1. 2. 1. 4. 2. 3. 1. A 2008 2009 2010 2011 1. CDM unit launched 2. Data creation workflow 3. DQ metrics launched A 2008 1. 2. 3. 4. 2009 2010 2011 DG project launched Address to board DQ metrics launched „Community“ approach proposed 5. DG council launched A 2007 2008 2009 2010 1. CDM unit launched 2. Progress report to the board proposed 3. Inventory data quality assessment 4. CDM reorganized Legend: E  Effectiveness; A  Amount of Activity; CDM  Corporate Data Management; DQ  Data Quality; DG  Data Governance. Prof. Dr. Boris Otto | Berlin, 2013/9/23 19
  • 20. Audi-Endowed Chair of Supply Net Order Management Data quality must before assured before transaction MM01 is executed … Data Request Prof. Dr. Boris Otto | Berlin, 2013/9/23 Data Quality Check Approval of Data Quality Creation of Data Record 20
  • 21. Audi-Endowed Chair of Supply Net Order Management … which is easier said than done ... 34+ Prof. Dr. Boris Otto | Berlin, 2013/9/23 21
  • 22. Audi-Endowed Chair of Supply Net Order Management … with so many different stakeholders involved. R&D Production Quality Management Planning Purchasing Financial Accounting Marketing Controlling Sales Materials Management 11+ Warehouse Management Prof. Dr. Boris Otto | Berlin, 2013/9/23 22
  • 23. Audi-Endowed Chair of Supply Net Order Management Many companies assess the lifecycle costs of their master data assets Before use 200 EUR 2.500 EUR - - 1.500 EUR 2.400 EUR 2.861 EUR (Creation of new code) During use 175 EUR (Code change) After use 133 EUR Prof. Dr. Boris Otto | Berlin, 2013/9/23 (3.000 CHF) - - - 23
  • 24. Audi-Endowed Chair of Supply Net Order Management Data must be captured at the source of the knowledge about it 1) [FOHRER 2012]. Prof. Dr. Boris Otto | Berlin, 2013/9/23 24
  • 25. Audi-Endowed Chair of Supply Net Order Management A data quality index is an effective performance management tool at Bayer CropScience 100 [%] 98 96 94 Evolution of Material Master Data Quality 92 90 Asia Pacific 88 Europe Latin America 86 North America 84 11/2009 01/2010 03/2010 05/2010 07/2010 09/2010 11/2010 01/2011 1) [EBNER/BRAUER 2011]. Prof. Dr. Boris Otto | Berlin, 2013/9/23 25
  • 26. Audi-Endowed Chair of Supply Net Order Management Johnson & Johnson has reached a six sigma data quality level1 Evolution of Material Master Data Quality 1) [OTTO 2013]. Prof. Dr. Boris Otto | Berlin, 2013/9/23 26
  • 27. Audi-Endowed Chair of Supply Net Order Management Data Governance at Bosch engages different roles on different organizational levels across the company1 Executive Management report corporate sector/ corporate department Master Data Owner A Master Data Owner X Master Data Officer … Master Data Officer … Governance Function Governance Function Concepts for a master data class (specialist/organizational level) Concepts Interdisciplinary (MD Owner, IT, ..) Overall responsibility Responsibility in relevant units (data maintenance/ application) Master Data Management Steering Committee working group / competence team IT Projects Master data class 1 … e. g. Supplier master data 1) [HATZ 2008]. Prof. Dr. Boris Otto | Berlin, 2013/9/23 IT platforms, IT target systems Master data class N Chart of accounts 27
  • 28. Audi-Endowed Chair of Supply Net Order Management The “business case” for Data Governance and Corporate Data Quality must take into account their very nature Energy Networks Prof. Dr. Boris Otto | Berlin, 2013/9/23 Highway Networks Corporate Data Quality 28
  • 29. Audi-Endowed Chair of Supply Net Order Management Agenda  Master Data as a Business Success Factor  Five Principles for Master Data Governance  Outlook Prof. Dr. Boris Otto | Berlin, 2013/9/23 29
  • 30. Audi-Endowed Chair of Supply Net Order Management Many enterprises are on the way towards a new corporate data architecture Data in the outer circles is of less control, criticality, unambiguity… Data in the outer circles is of higher “fuzziness”, volume, change frequency… “Nucleus Data” (Customer master data, product master data etc.) “Open Big Data” (Tweets, social media streams, sensor data etc.) Prof. Dr. Boris Otto | Berlin, 2013/9/23 “Community Data” (Geo-information, GTIN, addresses etc.) 30
  • 31. Audi-Endowed Chair of Supply Net Order Management SAP and the CC CDQ have published a joint white paper Prof. Dr. Boris Otto | Berlin, 2013/9/23 31
  • 32. Audi-Endowed Chair of Supply Net Order Management The Competence Center Corporate Data Quality (CC CDQ) channels “best practices” of market-leading companies NB: Past and present partner companies. Prof. Dr. Boris Otto | Berlin, 2013/9/23 32
  • 33. Audi-Endowed Chair of Supply Net Order Management Your Speaker Univ.-Prof. Dr. Ing. Boris Otto TU Dortmund University Audi-Endowed Chair of Supply Net Order Management LogistikCampus Joseph-Fraunhofer-Straße 2-4 D-44227 Dortmund Boris.Otto@tu-dortmund.de Prof. Dr. Boris Otto | Berlin, 2013/9/23 33
  • 34. Audi-Endowed Chair of Supply Net Order Management References [BRAUER 2009] B. BRAUER, Master Data Quality Cockpit at Bayer CropScience, 4. Workshop des Kompetenzzentrums Corporate Data Quality 2 (CC CDQ2), Universität St. Gallen, Luzern, 2009. [EBNER/BRAUER 2011] V. EBNER, B. BRAUER: Fallstudie zum Führungssystem für Stammdatenqualität bei der Bayer CropScience AG. In: HMD - Praxis der Wirtschaftsinformatik 48 (2011), S. 64-73. [FOHRER 2012] M. FOHRER, 2012. Driving Corporate Data Quality @ Hilti through the use of Consumer Technology. 10. CC CDQ3-Workshop. Bregenz: Universität St. Gallen, Institut für Wirtschaftsinformatik. [HATZ 2008] A. HATZ, BOSCH Master data Management, 6. CC CDQ Workshop, St. Gallen, 2008. [MESSERSCHMIDT/STÜBEN 2011] M. MESSERSCHMIDT, J. STÜBEN: Verborgene Schätze: Eine internationale Studie zum Master-Data-Management, PricewaterhouseCooopers AG, 2011 [OTTO ET AL. 2011] B. OTTO, J. KOKEMÜLLER, A. WEISBECKER, D. GIZANIS: Stammdatenmanagement: Datenqualität für Geschäftsprozesse. In: HMD - Praxis der Wirtschaftsinformatik 48 (2011), S. 5-16. [OTTO 2013] B. OTTO, 2013. On the Evolution of Data Governance in Firms: The Case of Johnson & Johnson Consumer Products North America. In: SADIQ, S. (ed.) Handbook of Data Quality - Research and Practice. Berlin: Springer. Prof. Dr. Boris Otto | Berlin, 2013/9/23 34

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