Corporate Data Quality Research and Services Overview. Prof. Dr. Boris Otto, Assistant Professor Milan, March 2012

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1 Corporate Data Quality Research and Services Overview Prof. Dr. Boris Otto, Assistant Professor Milan, March 2012

2 Competence Area Corporate Data Quality Competence Center Corporate Data Quality Business Engineering Institute St. Gallen AG Applied Consortium Research Business Value Transformation BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 2

3 Table of Content Data Quality as a Success Factor for Business Competence Center Corporate Data Quality BEI Project References Team Overview BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 3

4 Data quality is necessary to respond to a number of strategic business requirements 1 Customer-Centric Business Models $ Value Chain Excellence Contractual and Regulatory Compliance BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 4

5 Complexity drivers pose challenges on data quality management Size Revenue Nestlé 2010: 110 billion CHF Federal budget CH 2008: 57 billion CHF Big Data RFID, customer loyalty programs etc. Hyper-Connectivity Social media, data supply chains etc. Corporate Data Quality Globalized Operations Multilingualism, Follow the sun - principle etc. Constant Change M&A, Divestments, Change Management Taylorism Segregation of data creation and data use BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 5

6 Today, companies manage data quality purely in a reactive mode Data quality : Submarines of data quality, e.g. data migration, incorrect reports, process errors). Project 1 Project 2 Project 3 Time No risk management possible No chance to plan and to control budgets and resources No target values for corporate data quality No sustainability of increased data quality High recurring project costs (change requests, external consultants etc.) BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 6

7 Costing for data quality must find a trade-off between preventive and reactive measures Costs (C) C Total costs of data quality Costs related to DQM Follow-up costs in business as a result of data defects DQ Cost-optimal data quality level Data quality (DQ) DQM: Data quality management BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 7

8 Table of Content Data Quality as a Success Factor for Business Competence Center Corporate Data Quality BEI Project References Team Overview BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 8

9 The Competence Center Corporate Data Quality (CC CDQ) responds to urgent issues How does Corporate Data Quality contribute to the strategic business objectives? How does our company compare to others in our peer group? How can we measure our performance in Corporate Data Quality Management? What are the costs and benefits of Corporate Data Quality? How can we establish Data Governance in the company? What is the appropriate degree of standards and regulation for our company? How do we achieve consistent understanding of corporate data? What is the baseline of Corporate Data Quality? Which data architecture is the right one and how do we implement it? How do we benefit from innovative technologies (e.g. Social Media, Linked Data)? BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 9

10 The consortium comprises more than 20 research partner companies AO FOUNDATION ASTRAZENECA PLC BAYER AG BEIERSDORF AG CORNING CABLE SYSTEMS GMBH DAIMLER AG DB NETZ AG E.ON AG ETA SA FESTO AG & CO. KG HEWLETT-PACKARD GMBH IBM DEUTSCHLAND GMBH KION INFORMATION MANAGEMENT SERVICE GMBH MIGROS-GENOSSENSCHAFTS-BUND NESTLÉ SA NOVARTIS PHARMA AG ROBERT BOSCH GMBH SAP AG SIEMENS ENTERPRISE COMMUNICATIONS GMBH & CO. KG SYNGENTA CROP PROTECTION AG TELEKOM DEUTSCHLAND GMBH ZF FRIEDRICHSHAFEN AG NB: Overview comprises both current and past research partner companies. BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 10

11 The CC CDQ Framework in the context of Business Engineering Mandate Strategy document Value management Roadmap Strategy Strategy for CDQ Goals and targets Data quality metrics Data Governance Roles and responsibilities Change management Standards & Guidelines Organization Organization for CDQ CDQ Controlling CDQ Processes and Methods Data life cycle management Business metadata management Data-driven business process management Conceptual corporate data model Data distribution architecture Authoritative data sources local global Corporate Data Architecture Applications for CDQ Software support (e.g. MDM applications) System landscape analysis and planning System BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 11

12 Achieved results provide a tool box for establishing Corporate Data Quality Management EFQM Excellence Model for Corporate Data Quality Management Method for specifying business-relevant data quality metrics Reference model for Data Governance Method for establishing Data Governance Analysis and modeling method for integrating data quality in business process management Method for master data integration Design patterns for data architecture Reference model for Master Data Quality Management software BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 12

13 The CC CDQ research service portfolio rests on three pillars I II III Research on Demand Network & Benchmarking Bilateral Project Full access to the CC CDQ knowledge pool Customized research studies Case studies within the peer group Analysis of the state of the art in research and practice Active participation in leading edge research Leveraging a global research network 5 two-day consortium workshops p.a. In-depth benchmarking groups Moderation and coordination of peer group Best practice presentations Access to a network of CDQ professionals Access to highly-qualified PhD students and graduate students Use of professional platform (seminars, lectures etc.) Individual CDQ maturity assessment Individual project results (e.g. data governance design, metric design, data architecture analysis) Moderation of internal workshops Training and knowledge transfer (in-house seminars etc.) Individual support of CDQ programs BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 13

14 Table of Content Data Quality as a Success Factor for Business Competence Center Corporate Data Quality BEI Project References Team Overview BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 14

15 BEI is a trusted partner for designing and implementing Corporate Data Quality strategies Bühler AG Drägerwerke AG & Co. KGaA Elektrizitätswerke des Kantons Zürich LIDL Stiftung & Co. KG Master data processes Software evaluation Master data strategy Data governance Implementation roadmap Maturity assessment Data quality metrics Master data strategy Data governance Implementation roadmap OTTO Group Master data strategy RWE IT GmbH Stadtwerke München SWM Services GmbH Swisscom IT Services AG Conceptual data model Data architecture Maturity assessment Maturity assessment Master data strategy BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 15

16 BEI offers a comprehensive service portfolio 25 days Maturity Assessment Strategy Measurement Organization Processes Architecture 15 days Strategy Design 25 days Metrics Specification 15 days Analysis and Recommendations 30 days Data Supply Chain Design 20+ days Business Metadata Design 20 days Cockpit Design 25 days Data Governance and Organizational Design 30+ days Workflow Implementation 10 days Software Evaluation (CDD) 10 days Software Evaluation (Cockpit) 20+ days Implementation and Roll-out 20+ days CDD Implementation 30+ days Implementation 10 days CDQM Check-up (Functionality) Legend: CDD - Corporate Data Dictionary. BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / days Sofware Evaluation (CDQM)

17 Table of Content Data Quality as a Success Factor for Business Competence Center Corporate Data Quality BEI Project References Team Overview BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 17

18 The combined team at IWI-HSG and BEI leverages sound research and consulting expertise IWI-HSG Prof. Dr. Hubert Österle Dr. Boris Otto Verena Ebner Clarissa Falge Ehsan Baghi BEI Dr. Dimitrios Gizanis Dr. Kai Hüner Martin Ofner Andreas Reichert Max Zurkinden Wolfgang Dietrich Peter Mayer* BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 18

19 Customers and partners benefit from an unmatched pool of knowledge and expertise Contacts in the overall CC CDQ community Members in the XING Community Bilateral Project Workshops Best Practice Presentations Consortium Workshops Partner Companies Scientific Researchers/PhD Students Competence Center BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 19

20 CC CDQ Resources on the Internet Institute of Information Management at the University of St. Gallen Business Engineering Institute St. Gallen Competence Center Corporate Data Quality CC CDQ Benchmarking Platform https://benchmarking.iwi.unisg.ch/ CC CDQ Community at XING BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 20

21 Contact Details Dr.-Ing. Boris Otto University of St. Gallen Institute of Information Management Tel.: BEI St. Gallen St. Gallen, March 2012, Dr. Boris Otto / 21

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