Business Models in the Data Economy: A Case Study from the Business Partner Data Domain

PD Dr.-Ing. Boris Otto, Dr.-Ing. Stephan Aier

Leipzig

February 27, 2013

Business Models in the Data Economy: A Case Study from

the Business Partner Data Domain

© IWI-HSG – Leipzig, February 27, 2013, Otto, Aier / 2

Agenda

1. Introduction

2. Related Work

3. Research Methodology

4. Results Presentation

5. Conclusion and Outlook


1.1 Motivation and Research Question

First proposals to view data as a resource were made in the 1980s (Wang et al. 1993;

Goodhue et al. 1988)

Concepts for managing physical goods were transferred to managing the “data

resource”, e.g. TDQM (Levitin & Redman 1998; Wang 1998)

The relevance of business partner data was recognized when studying “corporate

household data” (Madnick et al. 2002)

The practitioners’ community observes the emergence of the “data economy” (Newman

2011)

How and why do business models of business partner data providers differ?


1.2 Business Partner Data: An Example from a Global Electrical

Engineering and Manufacturing Group

Organisational

Data

+Name

+Block indicator

Identification

+Unique identifier

+Chamber of

commerce no.

Contact Data

+Division

+Telephone

+Email

Data Source

+System ID

+Local System ID

Address Data

+Street and city

+Country

+ZIP code

Banking

Information

+Bank

+IBAN

+BIC code

Purchasing Data

+Currency

+Incoterms

Hierarchy

Information


2.1 Related Work on Business Model Theory

Foundations of Business Model Theory

Resource-Based View of the Firm (Wernerfelt 1984; Barney 1991)

Industrial Organization Perspective (Bain 1968)

The Strategy Process Perspective (Ginsberg 1994)

Strategic Resources are according to Barney (1991):

Valuable

Rare

In-imitable

Non-substitutable

Examples of recent business model work

Business model generation (Osterwalder & Pigneur 2010)

Electronic business models (Zott & Amit 2010)


Market level, e.g. five forces

Offering level, e.g.

generic strategies

Activity and

organizational

level, e.g. value chain

Resource level, e.g. RBV

Market level, e.g. five

forces

and capital and labour

MARKET / INDUSTRY

Customers (1) Competition (2)

Offering (3)

Physical component Price/Cost Service component

THE FIRM

Scope of management (7) ACTIVITIES AND ORGANISATION (4)

RESOURCES (5)

SUPPLIERS (6) Factor Markets Production Inputs

Longitudinal

dimension,

e.g. constraints on

actors, cognitive and

social limitations (7)

Human Physical Organizational

2.2 Business Model Framework by Hedman & Kalling (2003)


3.1 Research Methodology

Case study research was applied to study a contemporary phenomenon in its natural

environment (Benbasat et al. 1987; Eisenhardt 1989)

Research process according to five guiding points proposed by Yin (2002)

Conceptual framework following the business model approach by Hedman & Kalling

(2003)

Case selection within a focus group (Morgan & Krüger 1993)

Data collection through interviews, internal presentations, public records


4.1 Case Study Overview

Avox Bureau van Dijk

(BvD)

Dun & Bradstreet

(D&B)

Factual Infochimps InfoGroup One

Source

Customers n/a 6,000 clients,

50,000 users.

100,000 from

various industries.

n/a n/a Several thousands.

Competitors Interactive Data,

SIX Telekurs.

D&B, among

others.

BvD, among others. Similar offering

as Infochimps.

Similar offering as

Factual.

D&B, among

others.

Offering One million

entities, three

service types, web

services.

85 million

companies, data

and software

support, web

services, sales

force.

177 million

business entities,

data and related

services, web

services, sales

force.

Open data

platform, API use

for free or at a

charge.

15,000 data sets,

open data platform,

four different

pricing models,

web service.

18 million

companies, 20

million executives,

data and software,

web service.

Activities and

organization

Data retrieval,

analysis, cleansing

and provision

Monitoring of

mergers and

acquisitions, data

analysis and

provision.

Data collection and

optimization,

provision of quality

data services.

Data mining,

data retrieval,

data acquisition

from external

parties.

Data collection,

infrastructure

development,

hosting, and

distribution.

Selection of

content providers,

data collection,

“data blending”,

data updates.

Resources 38 analysts to

verify and cleanse

data, central

database

500 employees in

32 offices, central

database (ORBIS).

More than 5,000

employees, central

database

21 employees,

central open data

platform.

Less than 50

employees, central

data platform.

104 employees.

Factor and

production inputs

Third-party

vendors, official

data sources,

customers.

More than 100

different data

sources.

Official sources,

partnering, contact

to companies

Open data

community.

Open data

community.

50 “world-class”

suppliers, 2,500

data sources.

Scope of

management

International

coverage, co-

creation,

partnering.

Global coverage,

alliances, data,

software,

consulting.

Global coverage. Start-up

company.

Start-up company. Global coverage.


4.2 Business Model Analysis: Offering in the Case of InfoChimps

Pricing model “Baboon” “Brass Monkey” “Silverback” “Golden Ape”

Fee free 20 USD/month 250 USD/month 4,000 USD/month

Allowed API calls

per month

100,000 500,000 2,000,000 15,000,000

Allowed calls per

hour

2,000 4,000 20,000 100,000


4.3 Key Resources of Business Partner Data Providers

Valuable Rare Inimitable Non-

substitutable

Labor Yes No No No

Expertise and Knowledge Yes Yes No Yes

Database Yes Yes No Yes

Information Technology and

Procedures Yes No No No

Network Access and Relationships Yes Yes Yes Yes

Capital Yes Yes No No


4.4 Business Model Patterns for Business Partner Data Providers

Pattern I

Buyer-Supplier

Relationship

Pattern II

Community Sourcing

Pattern III

Crowd Sourcing

Legend: Business Partner Data Provider Business Partner Data Consumer Data Source

Data flow.


4.5 Resource Allocation Patterns

Information Technology and

Procedures

Network Access and

Relationships

Expertise and Knowledge

Capital

Labor

Database

low high medium

Factual, Infochimps

Avox

BvD, D&B,

InfoGroup One

Source


5.1 An Analysis and Positioning Framework for Business Partner Data

Providers

crowd-sourced data

unmanaged data

budget pricing

low market share

(or) niche offering

high market share

broad offering

Avox Factual

D&B

self-sourced data

managed data

premium pricing

established crowd-sourcer well-established traditional supplier

new market entrant niche provider


5.2 Conclusion and Outlook

Findings

Three business model pattern exist

A positioning framework is suggested

Contribution

Among the early papers addressing business partner data domain

Results may be applied for business models around “intangibles” in general

Practitioners may benefit from the analysis of the domain

Limitations

Small case base

Explorative nature of study, threats to generalizability


PD Dr.-Ing. Boris Otto

University of St. Gallen

Institute of Information Management

[email protected]

+41 71 224 3220

Your Speaker

This research was supported by

the European Commission through the «NisB – The Network is the

Business» project

and the Competence Center Corporate Data Quality (CC CDQ) at the

University of St. Gallen.


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