Valuation of master data as an asset

© 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


Agenda

� Business Engineering Institute

� Motivation and Basic concepts

� Determination of monetary value for master data as an asset

� Conclusion & outlook


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


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


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


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


Agenda






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


consider potential selling

maximize sales price in case of selling

Income (old + new)Yield = * 100%

Investment (old + new)


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


satisfy Bob

Objectives


calculate yield




CEO/CFO

Bob

DQ Manager

Alice


calculate yield




maximize income

keep or increase value of assets

Objectives

provide high master data quality � BPM

provide usable data

minimize complaints from data consumers


satisfy stakeholders (CEO/CFO)

Objectives

Master Data (Intangible Asset )House (Tangible Asset)

justify investments


emphasize the role of asset management

justify investments(ROI)


emphasize the role of DQ management


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]


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


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


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


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


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


Agenda






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


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


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


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


Agenda

� Motivation

� Basic concepts




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


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


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

Data & Analytics

Valuation of master data as an asset