valuation of master data as an asset
TRANSCRIPT
© BEI St. Gallen – Barcelona, 24th April 2015, B. Wiesing / 1
Valuation of master data as an asset
Bernd Wiesing Research Project Partner
Barcelona, 24th April 2015
© BEI St. Gallen – Barcelona, 24th April 2015, B. Wiesing / 2
Agenda
� Business Engineering Institute
� Motivation and Basic concepts
� Determination of monetary value for master data as an asset
� Conclusion & outlook
© BEI St. Gallen – Barcelona, 24th April 2015, B. Wiesing / 3
Business Engineering InstituteA spin-off of the University of St. Gallen
St. GallenHEADQUARTERS
2003FOUNDATION
Prof. Dr. Österle CHAIRMAN
Thomas ZerndtCEO
DivisionsCORPORATE DATA QUALITY MANAGEMENTSOURCING IN THE FINANCIAL INDUSTRYINDEPENDENT LIVING
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The Competence Center Corporate Data Quality (CC CDQ) comprises 30 partner companies
NB: Overview comprises both current and past research partner companies.
ABB LTD. AO FOUNDATION ASTRAZENECA PLC BAYER AG BEIERSDORF AG
CORNING CABLE SYSTEMS GMBH
DAIMLER AG DB NETZ AGDRÄGERWERK AG & CO.
KGAAE.ON SE
ERICSSON AB ETA SA FESTO AG & CO. KG HEWLETT-PACKARD GMBH IBM DEUTSCHLAND GMBH
KION INFORMATIONMANAGEMENT SERVICE
GMBHMERCK KGAA
MIGROS-GENOSSENSCHAFTS-BUND
NESTLÉ SA NOVARTIS PHARMA AG
OSRAM GMBH ROBERT BOSCH GMBH SAP AGSCHWEIZERISCHE
BUNDESBAHNEN SBBSCHAEFFLER AG
SIEMENS ENTERPRISE COMMUNICATIONS GMBH &
CO. KGSWISSCOM AG
SYNGENTA CROP PROTECTION AG
TELEKOM DEUTSCHLAND GMBH
ZF FRIEDRICHSHAFEN AG
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The CDQ Framework
Strategy
Organization
System
CDQ Controlling
Applications for CDQ
Corporate Data Architecture
Organizationfor CDQ
CDQ Processes and Methods
Strategy for CDQ
local global
MandateStrategy documentValue management
Roadmap
Goals and targetsData quality metrics
Data GovernanceRoles and
responsibilitiesChange
managementStandards &
Guidelines
Data life cycle managementBusiness metadata managementData-driven business process management
Conceptual corporate data
modelData distribution
architectureAuthoritative data
sources
Software support (e.g. MDM applications)System landscape analysis and planning
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Achieved results provide a “tool box” for establishing Corporate Data Quality Management
EFQM Excellence Model for Data Quality Management
Data Quality ManagementStrategy Design Method
Reference model for Data Governance
Method for establishing Data Governance
Method for integrating DQ in process management
Method for specifying data quality metrics
Method for master data integration
Reference model for DQ Management software
386
DQ-Cockpit
0 1000
I
II
III
386
DQ-Cockpit
0 1000
I
II
III
Sponsor
Data Owner
Corporate Data Steward
Fachlicher Datensteward
Technischer Datensteward
SDQM-Komitee
Daten-steward-
Team
Lebenszyklus-management für
Stammdaten
Metadaten-management und
Stammdaten-modellierung
Qualitäts-management für
Stammdaten
Stammdaten-integration
Querschnitt-funktionen
Administration
A
Stammdatenanlage StammdatenpflegeStammdaten-deaktivierung
Stammdaten-archivierung
Datenmodellierung Modellanalyse
Datenanalyse Datenanreicherung Datenbereinigung
Datenimport Datentransformation Datenexport
Automatisierung Berichte SucheWorkflow-
management
Änderungs-management
Benutzerverwaltung
Metadaten-management
B
C
D
E
F
1 2 3 4
1
1
1
1
1
2
2
2
2
2
3
3
3
3 4
MDS
Quelle 1 Quelle 2 Quelle m
Ziel 1 Ziel 2 Ziel n
MDS
Ziel 1 Ziel 2 Ziel nTran
sakt
ion
Koe
xist
enz
Strategische Anforderungen und WertbeitragA
ProzesseB OrganisationC QualitätssicherungD ArchitekturE
Umsetzungsplan (Transformation)F
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Agenda
� Business Engineering Institute
� Motivation and Basic concepts
� Determination of monetary value for master data as an asset
� Conclusion & outlook
© BEI St. Gallen – Barcelona, 24th April 2015, B. Wiesing / 8
Asset
The value of an asset is the basis for many decisions
Asset Owner
Bob
Asset Manager
Alice
maximize income
keep or increase value of the house
Objectives
rent apartments
keep the “quality” standard of the house
have minimum of complaints from renters
do preventive maintenance
satisfy Bob
Objectives
justify investments
Purpose of valuation
emphasize the role of asset management
provide basis for investment decision
calculate yield
Purpose of valuation
consider potential selling
maximize sales price in case of selling
Income (old + new)Yield = * 100%
Investment (old + new)
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The view on the house as a tangible asset is similar to the view on Master Data as an intangible asset
Asset Owner
Bob
Asset Manager
Alice
maximize income
keep or increase value of the house
Objectives
rent apartments
minimize complaints
keep the “quality” standard of the house
do preventive maintenance
satisfy Bob
Objectives
provide basis for investment decision
calculate yield
Purpose of valuation
consider potential selling
maximize sales price in case of selling
CEO/CFO
Bob
DQ Manager
Alice
provide basis for investment decision
calculate yield
Purpose of valuation
consider potential selling
maximize sales price in case of selling
maximize income
keep or increase value of assets
Objectives
provide high master data quality � BPM
provide usable data
minimize complaints from data consumers
do preventive maintenance
satisfy stakeholders (CEO/CFO)
Objectives
Master Data (Intangible Asset )House (Tangible Asset)
justify investments
Purpose of valuation
emphasize the role of asset management
justify investments(ROI)
Purpose of valuation
emphasize the role of DQ management
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The valuation of intangible assets influences more than ever the evaluation of the market capitalization
17% 32%68% 80% 80%
83% 68%32% 20% 20%
0%
50%
100%
1975 1985 1995 2005 2010
Tangible Assets
Intangible Assets
Market Capitalization of S&P 500
Company
Monetary assets
Equity Value
Tangible assets
Intangible assets
Value of non-current active liabilities
==
+
+
+
Ocean Tomo – the intellectual capital equity (2011), Intellectual Capital Equity, in: http://www.oceantomo.com/about/intellectualcapitalequity [21.10.2014]
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Intangible asset and related characteristics relevant for valuation are defined by IFRS1
An intangible asset is an identifiable non-monetary asset without physical substance. Such an asset is identifiable when it is separable, or when it arises from contractual or other legal rights.
IFRS Definition of intangible assets
Can master data be classified and valuated as intangible asset?
1IFRS : International Financial Reporting Standards (www.ifrs.org)
Identifiable (differentiation from a company’s goodwill)
Main characteristics relevant for valuation
Controllable (authority to dispose to procure the future economic benefit)
Economic beneficial (promising a future economic benefit, either income or cost saving)
1
2
3
Brands PatentsLogos Licenses
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CEO/CFO
Bob
is part
of
Maximizing the value of master data asset is an objective of DQ Managers
Data GovernanceData Quality Management
Optimize data quality
Maximize value 1
of data asset
Data Assets
Data Management
is subordinate objective of
supports supports
is led by
are objects of are objects of
are objects of
Key: Objective Function Data
Source: Otto, B.: Data Governance, in: WIRTSCHAFTSINFORMATIK, 53, 4, 2011, S. 235-238.
DQ Manager
Alice
1 Composition of value of master data as an asset and the added value generated by master data
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Master Data can be categorized as noncurrent intangible asset
Eberhard, R. (2012), Unterscheidung zwischen Umlaufvermögen und Anlagevermögen, in: die Warenwirtschaft
Assets
Tangible Intangible
Acquired AcquiredInternally generated Internally generated
Current assets
Current assets
Current assets
Current assets
Non-current assets
Non-current assets
Non-current assets
Non-current assets
Classification of master data
Current Assets Noncurrent Assets
Main characteristics single usage repeated usage
Current-Value depreciation permissible permissible
Example cash, inventory buildings, equipment
German HGB § 248 (2) was
changed 29th May 2009
to allow capitalization of
internally generated
intangible assets
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Master DataValue of master data
Business scenariosAdded value of master data
+ Ability to apply
+ Uniqueness
+ Context
+ Proper acting
+ Volition
+ Meaning
+ Syntax
The value of Master Data is to create the power for actions
Symbol
Data
Information
Knowledge
Power
Action
Competency
Competitiveness
Based on “Wissenstreppe” North (1999) http://qib.f-bb.de/wissensmanagement/thema/wissen/wissenstreppe.rsys
Determine the value
Enable added value
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Three approaches come into consideration for the valuation of intangible assets
Valuation methods for intangible assets 1
Market approach Cost approachIncome approach
Market Value Added Value Value
1 Based on Creutzmann, A. (2006), Bewertung von Intangible Assets, in: BewertungsPraktiker (2006), Nr. 2, S. 17
Value is based on market price or comparable
transactions
Value is based on the future cash flow
Value is based on reproduction or historical
cost
Very High Very High High but Reasonable
Valuation approach
Concept
Output
Complexity of application in case
of master data 2
2 Result of self-assessment
Focus for valuation of master data
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Agenda
� Business Engineering Institute
� Motivation and Basic concepts
� Determination of monetary value for master data as an asset
� Conclusion & outlook
© BEI St. Gallen – Barcelona, 24th April 2015, B. Wiesing / 17
Valuation of master data considering only historical cost leads to not acceptable values
Number of material master (e.g. finished products) 300,000Historical cost per material master data asset 250 USDAsset value 75,000,000 USD
The approach doesn’t consider if the valuated data assets are used or not1
Weaknesses of the approach
Valuation using historical cost
Master data are often not considered holistically (e.g. including BoM, local data, etc.) 2The quality of valuated data hasn’t been considered3Historical cost for master data are often covered through overheads4Calculated values are often implausible for the top management5
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The method provides an approach for the impairment of master data value
Master data lifecycle processesImpairment
driver
Valuation method for master data as an asset 1
Master data use cases
Impairment type
“Recoverability”Fair value
“Quality”Master data & Transactional data
“Usage”Quantitative view on past and future
Impairment method
Lowest value principleConsider master data
quality indicatorCheck usage within relevant
business processes
Impairment share 2 5% - 10% 10% - 20% 70% - 85%
1) Use similar procedure as for revaluation of physical stocks (e.g. for each master data asset you can choose only one impairment type) 2) Will differ by business and industry sector (e.g. manufacturer or web distributor). Example above for manufacturer
Technique to calculate
impairment loss 2
- External market- Internal (e.g. low cost)
DQ-Indicator drives impairment by DQ classes (e.g.):- if DQ > 99% then impairment 0%- if DQ > 90% then impairment 10%- if DQ > 75% then impairment 20%- if DQ > 50% then impairment 40%- If DQ <=50% then impairment 80%
Usage drives impairment byusage classes (e.g.):
- if not used 12 mon. then imp. 30% - If not used 18 mon. then imp. 60%- If not used 24 mon. then imp. 90%- If not used 36 mon. then imp. 100%
Valuation approach Historical cost
Value Carrying Value (Book Value) = Historical Cost – Impairment Loss
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Asset value is calculated based on impairment losses
Usage
Quality
Recoverability
Classno.
Usage class (month) Impairment percentage
No. of assets
Historical cost(USD)
Impairment loss (USD)
Asset value(USD)
1 new product (released) 0% 20,000 5,000,000 0 5,000,0002 < 12 0% 60,000 15,000,000 0 15,000,0003 >=12 and <18 30% 20,000 5,000,000 1,500,000 3,500,0004 >=18 and <24 60% 30,000 7,500,000 4,500,000 3,000,0005 >=24 90% 70,000 17,500,000 15,750,000 1,750,0006 >=36 100% 100,000 25,000,000 25,000,000 0
TOTAL 300,000 75,000,000 46,750,000 28,250,000
Class no.
Data quality level (%) Impairment percentage
No. of assets
Historical cost(USD)
Impairment loss (USD)
Asset value(USD)
1 < 50 80% 20,000 5,000,000 4,000,000 1,000,0002 >=50 and <75 40% 20,000 5,000,000 2,000,000 3,000,0003 >=75 and <90 20% 10,000 2,500,000 500,000 2,000,0004 >=90 and <99 10% 10,000 2,500,000 250,000 2,250,0005 >=99 0% 20,000 5,000,000 0 5,000,000
TOTAL 80,000 20,000,000 6,750,000 13,250,000
a) created low cost 10.000 products of usage class 1 (new value 120 USD instead of 250) � Impairment Loss = 1,300,000 USDb) managed via variant configurator starting next year, 5000 products with 100 USD for VC� Impairment Loss = 750,000 USD
Exemplary
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Valuation of master data considering historical cost and impairment loss leads to an acceptable asset value
Impairment type Impairment loss Impairment shareTotal asset
impairment share
Usage 46,750,000 USD 84% 62%
Quality 6,750,000 USD 12% 9%
Recoverability 2,050,000 USD 4% 3%
TOTAL 55,550,000 USD 100% 74%
Historical cost per master data asset (material master, BOM, routing, etc.) 250 USD
Number of master data asset 300,000
Historical cost 75,000,000 USD
Impairment loss -55,550,000 USD
Master data asset value 19,450,000 USD
Exemplary
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Agenda
� Motivation
� Basic concepts
� Determination of monetary value for master data as an asset
� Conclusion & outlook
© BEI St. Gallen – Barcelona, 24th April 2015, B. Wiesing / 22
The valuation contributes to achievement of objectives planned by CEO/CFO and DQ manager
Valuation of Master Data Asset
Consider the value of master data as an intangible asset for
the balance sheet
Master data investment justification
Master data performance management
Separation of master data value from company’s goodwill
Providing benchmarking foundation
Transferring the value of master data into a measurable
intangible asset
Manage the value of master data as an intangible
noncurrent assets
Supporting value based corporate management
Emphasizing the importance of master data management as a
corporate function
CEO/CFO
Bob
DQ Manager
Alice
CEO/CFO will support (and push) DQ Manager
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Conclusion and outlook
Apply the method in 2015 in context of two companies for customer master data and product master data
Outlook
Investigate the income approach aiming at calculation of added value of master data
Provide a SAP-based customizing approach for calculation of historical cost based on running lifecycle processes
Evaluate the method in in 2015 with CDQ Partners
Initiate a project for the calculation of added value of master data in 2016
Master data can be classified as intangible noncurrent asset
A distinction must be made between the • value of master data as an asset and • added value generated by master data
Valuation of master data based only on the historical costs leads to inacceptable value of master data asset
The valuation of master data contributes to achievement of objectives planned by Data Quality manager and CFO/CEO
Carrying Value (Book Value) = Historical Cost – Impairment Loss
Conclusion
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Contact Information
Bernd WiesingBEI St.Gallen AGCC Corporate Data [email protected]: +49 160 909 21 547
http://www.bei-sg.chBusiness Engineering Institute St. Gallen
http://cdq.iwi.unisg.chCompetence Center Corporate Data Quality
https://benchmarking.iwi.unisg.ch/CC CDQ Benchmarking Platform
http://www.xing.com/net/cdqmCC CDQ Community at XING