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.

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
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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)
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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
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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
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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
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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
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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
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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.
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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
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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
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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
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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
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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
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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
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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
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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
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21. Audi-Endowed Chair of
Supply Net Order Management
… which is easier said than done ...
34+
Prof. Dr. Boris Otto | Berlin, 2013/9/23
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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
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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)
-
-
-
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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
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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
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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
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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
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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.)
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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
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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
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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
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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
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