EFQM Excellence Model for Corporate Data Quality Management (CDQM) Martin Ofner Bad Soden, November 19 th, 2010 Institute of Information Management (IWI2) Chair of Prof. Dr. Hubert Österle
Agenda 1. Rationale 2. Excellence Model for CDQM: Design and Components 3. Excellence Model for CDQM: Application and Examples CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 2
CDQ Framework Impact on company goals Mandate Strategic scope Strategic action plan Data Governance Roles and responsibilities Change management Standards & Guidelines Strategy Organization CDQ Organization CDQ Strategy CDQ Controlling CDQ Processes and Methods KPI system Measurement process Dimensions of data quality Data life cycle management Metadata management Methods and processes Integration object model Architecture scenarios Distribution architecture Data storage architecture lokal global Integration Architecture for CDQ Applications for CDQ System Software for master data management Business Data dictionaries Integration tools CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 3
Typical situation regarding the establishment of CDQM Scope unclear, no structured approach Progress control and strategic alignment needed Plan to learn from others Companies require an instrument to assess and improve the progress and performance of their CDQM initiatives CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 4
Agenda 1. Rationale 2. Excellence Model for CDQM: Design and Components 3. Excellence Model for CDQM: Application and Examples CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 6
EFQM Model for Excellence Enabler criteria cover what an organization does. The Results criteria cover what an organization achieves. Results are caused by Enablers. Enabler Results People 10% People Results 10% Leadership 10% Strategy 10% Processes, Products, Services 10% Customer Results 15% Key Performance Results 15% Partnership & Resources 10% Society Results 10% Innovation and Learning Weightings are assigned to each criteria and are used to determine the final score. Enablers are improved using feedback from Results and rootcause analysis. CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 7
EFQM Framework for CDQM 1 Enabler criteria cover what an organization does in terms of CDQM. The Results criteria cover what an organization achieves in terms of CDQM. Results are caused by Enablers. Enabler Results Strategy People Results Controlling Organization Operations Customer Results Key Performance Results Data Architecture Applications Society Results Innovation and Learning 1) The Framework was jointly developed by EFQM and CC CDQ to promote sound practice in CDQM across Europe Enablers are improved using feedback from Results and rootcause analysis. CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 8
Model in detail - Enabler Goal 1A. Strategy for data quality management is developed, reviewed and updated based on the organization s business strategy Guidance points Determining, analyzing, documenting and communicating the impact of data quality on business objectives and operational excellence Formalizing, reviewing and updating strategy, objectives and processes for data quality management which meet stakeholders need and expectations and which are aligned with the business strategy CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 9
CDQM Maturity Levels Level Description V. Fully completed Excellent results in all areas Outstanding solution found; no significant further improvement imaginable IV. Major progress made Clear proof of successful implementation Regular verifications and substantial improvement But approach is still not fully applied in all areas III. Substantial progress made Proof that initiative is seriously established Successful implementation in a number of areas A number of examples of verification and improvement identifiable, but the full potential is by far not fully exploited yet II. Minor progress made Some indications of a positive development identifiable Casual, more accidental verifications that have led to some improvement Positive results in very specific areas I. Not yet started No initiative identifiable Some good ideas expressed, but still wishful thinking is predominant CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 10
Model in detail - Results Perception measures Performance Indicators Internal customer satisfaction regarding the services of corporate data quality management Demand of support in projects related to corporate data quality management Acceptance and use of provided corporate data quality related standards and procedures by the internal customers Number of internal customers (e.g. business units) already addressed Number of change requests to business object model in a certain period of time (quality of description) Number of reported incidents (related to data quality) CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 11
Joint Publication Supporters/Contributers: & more. CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 12
Agenda 1. Rationale 2. Excellence Model for CDQM: Design and Components 3. Excellence Model for CDQM: Application and Examples CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 13
Case of a German utilities provider Company s Profile Germany's largest municipal company: energy and water supply, swimming pools, public transport, telecommunication and all related services 7 000 employees and a total revenue of 4.7 billion in 2007 Initial situation Data Quality Management initiative established in 2009 Provides standards, processes, services, and guidelines for the business segment Customer Management Internal customer s needs and requirements unclear Area of improvements (from a business perspective) unidentified CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 14
Goals of the Self-Assessment Determine the maturity of the DQM (As-is) Define target values (To-be) Identify areas of high priority Recommend actions for improvement (List of actions) CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 15
Self-Assessment approach I. Preparation II. As-is analysis III. Action planning Activities Define scope and goals Identify and analyze stakeholders Select interviewees Choose self assessment technique Conduct interviews Assess interviews Analyze results Analyze internal and external dependencies Plan actions for improvement Select and adapt criteria Stakeholder analysis Maturity results List of actions Communication plan Benchmarking results Results List of company-specific criteria Strengths and area of improvements Priority analysis Statisical analysis CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 16
Approach to determine the overall maturity level Overall 6 Enabler selected Each contributes 1/6 to overall score 31 Questions selected (all) Each contributes 1/31 to overall score Each contributes 1/6 to overall score 6 departments selected CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 17
Data collection Example 1A 1B Frage Bew ertung Priorität Existieren strategische Ziele und Werte für das Datenqualitäts-management im GFL KM und IN-PK (in dokumentierter und kommunizierter Form)? Unterstützen die strategischen Ziele und Werte des Datenqualitäts-managements die Geschäftsstrategie?.. Teilkriterium Handlungsbedarf Angestrebt. Verbess. 2011 25.00% 3 0.75 18.75% 25.00% 3 0.75 18.75%.......... Collected during interviews for each question Calculated for each question NB: Figure in project language. Data anonymized CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 18
Final Results Strategie 32.14% Applikationen 100% 80% Führungssystem Organisation 25.00% 25.00% Strategie 60% 40% Datenarchitektur Befähiger Prozesse 25.00% 20% 0% Datenarchitektur 25.00% Applikationen 40.00% Führungssystem Prozesse Gesamtbewertung 28.69% 0% 20% 40% 60% 80% 100% Erreichter Reifegrad Organisation Ist-Ergebnis 2010 Soll-Ergebnis 2011 NB: Figure in project language. CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 19
Overview of main findings 1. Data quality is a topic of high priority among all participants 2. Increase of CDQM communication neccessary 3. Missing global roles and responsibilities prevent effective CDQM measures 4. CDQM process not transparent 5. Enabler with highest priority: Strategy, Organization and Processes CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 20
Priority Analysis 1.00 0.90 0.80 0.70 Handlungsbedarf 0.60 0.50 0.40 0.30 0.20 0.10 0.00 1A 1B 1C 1D 1E 1F 1G 2A 2B 2C 2D 2E 3A 3B 3C 3D 3E 4A 4B 4C 4D 4E 5A 5B 5C 5D 6A 6B 6C 6D 6E Strategie Organisation Prozesse & Methoden Führungssystem Datenarchitektur Applikationen Handlungsbedarf Zu beobachten (Schwellenwert) Dringender Handlungsbedarf (Schwellenwert) NB: Figure in project language. Data anonymized CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 21
Components of the overall Maturity Assessment Service Maturity Model EFQM Excellence Model for CDQM as maturity model Covering all relevant aspects and tasks of CDQM Appraisal Method and Tools EFQM Self-Assessment for CDQM as procedure model EFQM RADAR as appraisal method Questionnaire technique Award-simulation technique Benchmark Database Growing database with reference values of already conducted Self-Assessments Various reports (for example, compare to best-in-class, compare to industryaverage, etc.) Best Practices Comprehensive collection of best practices for CDQM Lessons learned that can be used to eliminate identified weak points NB: Figure in project language. CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 22
Outlook: Joint publication and Benchmarking database CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 23
Contact Person http://cdq.iwi.unisg.ch Martin Ofner University of St. Gallen Institute of Information Management E-mail: Martin.Ofner@unisg.ch Phone: +41 71 224 2893 CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 24
Backup CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 25
RADAR Logic Results Relevance and usability Scope Integrity Performance Trends Targets Comparisons Causes Plan and develop Approach Approach Sound Integrated Required Results Deploy Approaches Assess & Refine Approaches and Deployment Deployment Implemented Systematic Assess & Refine Measurement Learning and Creativity Innovation and Improvement CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 26
Automotive GmbH 1 Germany-headquartered machine manufacturer and automotive industry supplier 270,000 employees, 290 manufacturing sites worldwide, and an annual turnover of 46 billion (in 2008) Assessments conducted for 5 enable criteria and 6 master data classes (Questionnaire technique) Detailed analysis of a single corporate data class Summary 1) Anonymized due to organizations communication policy NB: Figures in project language CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 27
Case ZF Friedrichshafen AG Global supplier of driveline and chassis technology delivering components and systems to the automotive, marine, rail, and aviation industries, as well as for industrial applications 60,000 employees, 120 locations in 26 countries Assessments conducted for 6 divisions, 6 enabler and 7 corporate data classes Detailed analysis of a single corporate data class Summary NB: Figures in project language CC CDQ2 Bad Soden 11/19/2010, M. Ofner / 28