Audi-Endowed Chair of

Supply Net Order Management

Best Practices in Master Data Governance

Prof. Dr. Boris Otto | Berlin, 2013/9/23

Audi-Endowed Chair of

Supply Net Order Management

2Prof. Dr. Boris Otto | Berlin, 2013/9/23

Master Data as a Business Success Factor

Five Principles for Master Data Governance

Outlook

Agenda

Audi-Endowed Chair of

Supply Net Order Management

3Prof. Dr. Boris Otto | Berlin, 2013/9/23

Bayer CropScience is a leader in the crop protection market

Audi-Endowed Chair of

Supply Net Order Management

4Prof. Dr. Boris Otto | Berlin, 2013/9/23

Master data quality is a key prerequisite for business process

performance1

1) [EBNER/BRAUER 2011].

Data Object

“Product Hierarchy”Business

Area

Business

Field

Business

Segment

Active

Ingredient

Product

Group

Data Quality Issues

Data not available

Data not complete

Data not consistent

Business Process

Impact

09 11 012 242 3938

Planning: Demand for active ingredients unknown

Revenue reporting: Revenue not transparent on country

Segmentation: Risk of poor portfolio planning

Audi-Endowed Chair of

Supply Net Order Management

5Prof. Dr. Boris Otto | Berlin, 2013/9/23

Johnson & Johnson is a leading producer of consumer products

Skin Care, Baby Care, Consumer Healthcare, OTCFranchises

Skillman, NJ (USA)Headquarter

Audi-Endowed Chair of

Supply Net Order Management

6Prof. Dr. Boris Otto | Berlin, 2013/9/23

In early 2008, Johnson & Johnson was suffering from poor

master data quality1

Inbound Logistics ProductionSales &

Distribution

Procurement

Financial Accounting

Portfolio Management and New Product Introduction

Controlling

Other Support Processes

“Customers were

invoiced wrong”

“Trucks were waiting

at the docks for

materials to be

activated”

“Production was delayed

at manufacturing plants”

“Purchase

orders were

not ready on

time”

“Project Management did not

know what stage products are in”

“Defective data was

sent to GS1 US”

For less than 30 of products’ dimensions and weights, data was within the allowed 5 % error margin

1) [OTTO 2013].

Audi-Endowed Chair of

Supply Net Order Management

7Prof. Dr. Boris Otto | Berlin, 2013/9/23

Master data quality drivers affect the entire company

Group

Division 2Division 1 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”

Audi-Endowed Chair of

Supply Net Order Management

8Prof. Dr. Boris Otto | Berlin, 2013/9/23

Master data quality evolves over time according to a “jigsaw”

pattern

Legend: Master data quality issues.

Master data quality

TimeProject 1 Project 2 Project 3

Audi-Endowed Chair of

Supply Net Order Management

9Prof. Dr. Boris Otto | Berlin, 2013/9/23

The case of Bayer CropScience illustrates the various data

quality issues companies have to deal with1

Data

quality

issues

Employees Data Maintenance

Data Quality Management Standards Organization

Training and education

inadequate

Data quality not integrated in

performance management systems

Various software

solutions in place

Master data can be edited in

target systems

No integrated software

support

Data maintenance not

harmonized on global level

No data quality

metrics

No continuous data

quality monitoring

No binding rules,

standards, operating

procedures

Too many local rules,

exceptions

No

“Data Governance”

Missing business

responsibilities

1) [BRAUER 2009].

Audi-Endowed Chair of

Supply Net Order Management

10Prof. Dr. Boris Otto | Berlin, 2013/9/23

Corporate Data Quality Management (CDQM)1 comprises six

key enablers

1) [OTTO ET AL. 2011].

Audi-Endowed Chair of

Supply Net Order Management

11Prof. Dr. Boris Otto | Berlin, 2013/9/23

Master Data as a Business Success Factor

Five Principles for Master Data Governance

Outlook

Agenda

Audi-Endowed Chair of

Supply Net Order Management

12Prof. Dr. Boris Otto | Berlin, 2013/9/23

Data Governance and Data Quality Management are closely

interrelated

Legend: Goal Function Data.

Data

Governance

Data Quality

Management

Maximize

Data Quality

Maximize

Data Value

Data Assets

Data

Management

is sub-goal of

supports supports

is led by is sub-function

of

are object of are object of

are object of

Source: Otto, B.: Data Governance, in: WIRTSCHAFTSINFORMATIK, 53, 4, 2011, S. 235-238.

Audi-Endowed Chair of

Supply Net Order Management

13Prof. Dr. Boris Otto | Berlin, 2013/9/23

Data Governance effectiveness still varies widely today1

25.0

30.0

30.0

7.5

7.5

very good good mediocre adequate poor

1) [MESSERSCHMIDT/STÜBEN 2011].

NB: Figures are percentages.

Audi-Endowed Chair of

Supply Net Order Management

14Prof. Dr. Boris Otto | Berlin, 2013/9/23

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.

Audi-Endowed Chair of

Supply Net Order Management

15Prof. Dr. Boris Otto | Berlin, 2013/9/23

Capture Data at the Source

Enter Data “First Time Right”

Measure to Manage

Build up a Data Governance Capability

Scale Capabilities Globally

Five key principles lead to excellence in master data

governance

Audi-Endowed Chair of

Supply Net Order Management

16Prof. Dr. Boris Otto | Berlin, 2013/9/23

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)

Audi-Endowed Chair of

Supply Net Order Management

17Prof. Dr. Boris Otto | Berlin, 2013/9/23

Note taken in a meeting with Johnson & Johnson on November

29, 2011, in Skillman, NJ

Audi-Endowed Chair of

Supply Net Order Management

18Prof. Dr. Boris Otto | Berlin, 2013/9/23

The ideal lifecycle of Data Governance capabilities follows an

“S” curve

Founding Phase „First Time Right“ Cleansing

Legend: E Effectiveness; A Amount of Activity.

E

A

Audi-Endowed Chair of

Supply Net Order Management

19Prof. Dr. Boris Otto | Berlin, 2013/9/23

It is not a perfect world, though

2008 2009 2010 2011

1. CDM unit launched

2. Data creation workflow

3. DQ metrics launched

1.

2.

3.

Pattern I

2008 2009 2010 2011

1. DG project launched

2. Address to board

3. DQ metrics launched

4. „Community“ approach

proposed

5. DG council launched

1.

2.

Pattern II

3.

4.

5.

2007 2008 2009 2010

1.

1. CDM unit launched

2. Progress report to the board

proposed

3. Inventory data quality

assessment

4. CDM reorganized

2.

3. 4.

Pattern IIIE E E

A A A

Legend: E Effectiveness; A Amount of Activity; CDM Corporate Data Management; DQ Data Quality; DG Data

Governance.

Audi-Endowed Chair of

Supply Net Order Management

20Prof. Dr. Boris Otto | Berlin, 2013/9/23

Data RequestData Quality

CheckApproval of Data Quality

Creation of Data Record

Data quality must before assured before transaction MM01 is

executed …

Audi-Endowed Chair of

Supply Net Order Management

21Prof. Dr. Boris Otto | Berlin, 2013/9/23

… which is easier said than done ...

34+

Audi-Endowed Chair of

Supply Net Order Management

22Prof. Dr. Boris Otto | Berlin, 2013/9/23

… with so many different stakeholders involved.

R&D Marketing SalesProduction Purchasing

Quality

Management

Planning Financial

AccountingControlling Materials

Management

Warehouse

Management

11+

Audi-Endowed Chair of

Supply Net Order Management

23Prof. Dr. Boris Otto | Berlin, 2013/9/23

Many companies assess the lifecycle costs of their master data

assets

Before use 200 EUR(Creation of new code)

2.500 EUR - -

During use 175 EUR(Code change)

1.500 EUR 2.400 EUR(3.000 CHF)

2.861 EUR

After use 133 EUR - - -

Audi-Endowed Chair of

Supply Net Order Management

24Prof. Dr. Boris Otto | Berlin, 2013/9/23

1) [FOHRER 2012].

Data must be captured at the source of the knowledge about it

Audi-Endowed Chair of

Supply Net Order Management

25Prof. Dr. Boris Otto | Berlin, 2013/9/23

1) [EBNER/BRAUER 2011].

A data quality index is an effective performance management

tool at Bayer CropScience

84

86

88

90

92

94

96

98

100

11/2009 01/2010 03/2010 05/2010 07/2010 09/2010 11/2010 01/2011

Asia Pacific

Europe

Latin America

North America

[%]

Evolution of Material Master Data Quality

Audi-Endowed Chair of

Supply Net Order Management

26Prof. Dr. Boris Otto | Berlin, 2013/9/23

Johnson & Johnson has reached a six sigma data quality level1

Evolution of Material Master Data Quality

1) [OTTO 2013].

Audi-Endowed Chair of

Supply Net Order Management

27Prof. Dr. Boris Otto | Berlin, 2013/9/23

Data Governance at Bosch engages different roles on different

organizational levels across the company1

Master Data

Owner X

Executive Management

Master Data Management

Steering Committee

…

corporate sector/

corporate department

Responsibility

in relevant units (data

maintenance/ application)

IT ProjectsIT platforms, IT target systems

Overall responsibilityfor a master data class

(specialist/organizational

level)

Master Data

Owner A

Master dataclass 1

Master dataclass N

report

Governance

Function

working group /

competence team

ConceptsConcepts

Governance

Function

…

Master Data

Officer

…

Master Data

Officer

e. g. Supplier master data Chart of accounts

Inte

rdis

cip

linary

(MD

Ow

ner, IT

, ..)

1) [HATZ 2008].

Audi-Endowed Chair of

Supply Net Order Management

28Prof. Dr. Boris Otto | Berlin, 2013/9/23

The “business case” for Data Governance and Corporate Data

Quality must take into account their very nature

Energy Networks Highway Networks Corporate Data Quality

Audi-Endowed Chair of

Supply Net Order Management

29Prof. Dr. Boris Otto | Berlin, 2013/9/23

Master Data as a Business Success Factor

Five Principles for Master Data Governance

Outlook

Agenda

Audi-Endowed Chair of

Supply Net Order Management

30Prof. Dr. Boris Otto | Berlin, 2013/9/23

Many enterprises are on the way towards a new corporate data

architecture

Data in the outer circles is of higher “fuzziness”,

volume, change frequency…

Data in the outer circles is of less

control, criticality, unambiguity…

“Nucleus Data”

(Customer master

data, product master

data etc.)

“Community Data”

(Geo-information,

GTIN, addresses

etc.)

“Open Big Data”

(Tweets, social media

streams, sensor data etc.)

Audi-Endowed Chair of

Supply Net Order Management

31Prof. Dr. Boris Otto | Berlin, 2013/9/23

SAP and the CC CDQ have published a joint white paper

Audi-Endowed Chair of

Supply Net Order Management

32Prof. Dr. Boris Otto | Berlin, 2013/9/23

The Competence Center Corporate Data Quality (CC CDQ)

channels “best practices” of market-leading companies

NB: Past and present partner companies.

Audi-Endowed Chair of

Supply Net Order Management

33Prof. Dr. Boris Otto | Berlin, 2013/9/23

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

Audi-Endowed Chair of

Supply Net Order Management

34Prof. Dr. Boris Otto | Berlin, 2013/9/23

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.