EFQM Excellence Model for Corporate Data Quality Management … · 2016. 2. 27. · Strategic...

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


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


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


Agenda

1. Rationale




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.


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


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

…


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


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)

…


Joint Publication

Supporters/Contributers:

& more.


Agenda

1. Rationale




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


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)


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


6 Enabler selected

31 Questions selected(all)

6 departmentsselected

Overall

Approach to determine the overall maturity level

Each contributes 1/6 to overall score




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


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.


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.


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


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.


Outlook: Joint publication and Benchmarking database


Martin OfnerUniversity of St. GallenInstitute of Information ManagementE-mail: [email protected]: +41 71 224 2893

http://cdq.iwi.unisg.ch

Contact Person


Backup


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


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


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

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