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Institute of Information Management (IWI2)Chair of Prof. Dr. Hubert Österle
EFQM Excellence Model for Corporate Data Quality Management (CDQM)
Martin OfnerBad Soden, November 19th, 2010
© CC CDQ2 – Bad Soden 11/19/2010, M. Ofner / 2
Agenda
1. Rationale
2. Excellence Model for CDQM: Design and Components
3. Excellence Model for CDQM: Application and Examples
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CDQ Framework
Strategy
Organization
System
CDQ Controlling
Applications for CDQ
Integration Architecture for CDQ
CDQ Organization
CDQ Processes and Methods
CDQ Strategy
lokal global
Impact on company goals
Mandate
Strategic scope
Strategic action plan
KPI system
Measurement process
Dimensions of data quality
Data Governance
Roles and responsibilities
Change management
Standards & Guidelines
Data life cycle management
Metadata management
Methods and processes
Integration object model
Architecture scenarios
Distribution architecture
Data storage architecture
Software for master data management
Business Data dictionaries
Integration tools
© CC CDQ2 – Bad Soden 11/19/2010, M. Ofner / 4
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
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Agenda
1. Rationale
2. Excellence Model for CDQM: Design and Components
3. Excellence Model for CDQM: Application and Examples
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EFQM Model for Excellence
ResultsEnabler
Innovation and Learning
People Results10%
Customer Results
15%
Society Results10%
Key Performance
Results15%
Leadership10%
People10%
Partnership & Resources
10%
Strategy10%
Processes, Products, Services
10%
Enabler criteria cover what an organization does.
Weightings are assigned to each criteria and are used to determine the final score.
Enablers are improved using feedback from Results and root-cause analysis.
The Results criteria cover what an organization achieves. Results are caused by Enablers.
© CC CDQ2 – Bad Soden 11/19/2010, M. Ofner / 8
EFQM Framework for CDQM1
ResultsEnabler
Innovation and Learning
People Results
Customer Results
Society Results
Key Performance
Results
Enabler criteria cover what an organization does in terms of CDQM.
Enablers are improved using feedback from Results and root-cause analysis.
The Results criteria cover what an organization achieves in terms of CDQM. Results are caused by Enablers.
1) The Framework was jointly developed by EFQM and CC CDQ to promote sound practice in CDQM across Europe
Controlling
Strategy
Organization
Applications
Data Architecture
Operations
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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 / 10
CDQM Maturity Levels
V.Fully completed
Level Description
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
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Model in detail - Results
Perception measures
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
…
Perfor-mance
Indicators
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 / 12
Joint Publication
Supporters/Contributers:
& more.
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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 / 14
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
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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)
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Self-Assessment approach
Define scope and goals Identify and analyze
stakeholders Select interviewees Choose self assessment
technique Select and adapt criteria
Stakeholder analysis Communication plan List of company-specific
criteria
I. Preparation
II. As-is analysis
Conduct interviews Assess interviews Analyze results
Maturity results Benchmarking results Strengths and area of
improvements Priority analysis Statisical analysis
III.Action planning
Analyze internal and external dependencies
Plan actions for improvement
List of actions
Activ
ities
Res
ults
© CC CDQ2 – Bad Soden 11/19/2010, M. Ofner / 17
6 Enabler selected
31 Questions selected(all)
6 departmentsselected
Overall
Approach to determine the overall maturity level
Each contributes 1/6 to overall score
Each contributes 1/31 to overall score
Each contributes 1/6 to overall score
© CC CDQ2 – Bad Soden 11/19/2010, M. Ofner / 18
Data collection
Collected during interviews for each question
Calculated for each question
Teil-kriterium
Frage Bew ertung Priorität Handlungs-bedarf
Angestrebt. Verbess. 2011
1A
Existieren strategische Ziele und Werte für das Datenqualitäts-management im GFL KM und IN-PK (in dokumentierter und kommunizierter Form)?
25.00% 3 0.75 18.75%
1B
Unterstützen die strategischen Ziele und Werte des Datenqualitäts-managements die Geschäftsstrategie?
25.00% 3 0.75 18.75%
..
..
.. .. .. ..
Example
NB: Figure in project language. Data anonymized
© CC CDQ2 – Bad Soden 11/19/2010, M. Ofner / 19
Final Results
28.69%
40.00%
25.00%
25.00%
25.00%
25.00%
32.14%
0% 20% 40% 60% 80% 100%
Gesamtbewertung
Applikationen
Datenarchitektur
Prozesse
Organisation
Führungssystem
Strategie
Erreichter Reifegrad
Befä
hige
r
0%
20%
40%
60%
80%
100%Applikationen
Datenarchitektur
Prozesse
Organisation
Führungssystem
Strategie
Ist-Ergebnis 2010 Soll-Ergebnis 2011
NB: Figure in project language.
© CC CDQ2 – Bad Soden 11/19/2010, M. Ofner / 20
Overview of main findings
Data quality is a topic of high priority among all participants1.
Enabler with highest priority: Strategy, Organization and Processes5.
Increase of CDQM communication neccessary2.
CDQM process not transparent4.
Missing global roles and responsibilities prevent effective CDQM measures3.
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Priority Analysis
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
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 Führungs-system
Organisation Prozesse & Methoden
Daten-architektur
Applikationen
Hand
lung
sbed
arf
Handlungsbedarf Zu beobachten (Schwellenwert) Dringender Handlungsbedarf (Schwellenwert)
NB: Figure in project language. Data anonymized
© CC CDQ2 – Bad Soden 11/19/2010, M. Ofner / 22
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 industry-average, 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 / 23
Outlook: Joint publication and Benchmarking database
© CC CDQ2 – Bad Soden 11/19/2010, M. Ofner / 24
Martin OfnerUniversity of St. GallenInstitute of Information ManagementE-mail: [email protected]: +41 71 224 2893
http://cdq.iwi.unisg.ch
Contact Person
© CC CDQ2 – Bad Soden 11/19/2010, M. Ofner / 25
Backup
© CC CDQ2 – Bad Soden 11/19/2010, M. Ofner / 26
RADAR Logic
Results Relevance and usability
Scope Integrity
Performance Trends Targets Comparisons Causes
Plan and developApproach
DeployApproaches
Assess & RefineApproaches and
Deployment
Required Results
Approach Sound Integrated
Deployment Implemented Systematic
Assess & Refine Measurement Learning and Creativity Innovation and Improvement
© CC CDQ2 – Bad Soden 11/19/2010, M. Ofner / 27
Automotive GmbH1
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)
1) Anonymized due to organizations’ communication policy
Detailed analysis of a single corporate data class Summary
NB: Figures in project language
© CC CDQ2 – Bad Soden 11/19/2010, M. Ofner / 28
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
SummaryDetailed analysis of a single corporate data classNB: Figures in project language