The document analyzes 14 Finnish companies that utilize open data to identify different business models. Five profiles were identified: 1) extract and transform data, 2) data analysis, 3) providing user experiences, 4) commercial data publishing, and 5) general findings that standardized APIs and adding value to raw data are important. The analysis found a lack of commercial activity in extracting and transforming data and opportunities in private data publishing and utilizing media companies as user experience providers.

1. Open Data Value Network
Tomi Kinnari, Aalto University School of Business
Juho Lindman, Hanken School of Business
Matti Rossi, Aalto University School of Business
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2. Identifying value network of open data
• Business model analysis
– Offering
– Resources
– Relationships
– Revenue model
– Management mindset
• Method
– Case study with 14 Finnish companies
• Time of interviews
– March-May 2012
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3. 14 Finnish companies were interviewed
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4. Apps 4 Finland as a starting point for
selecting the companies
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5. Five profiles were identified
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6. 1. Extract & transform
• Extract and transform as part of
data analyzing
– Data extraction and
transformation is necessary
before any data analysis can
be performed
• Extract and transform as separate
business
– No commercial activity has yet
risen
– Example: soRvi toolkit by
Louhos shows lots of potential
• Revenue model: none found
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7. 2. Data analysers
• Data visualizers
– Create novel visualizations
combining open data from
different sources
– Example: Hahmota taxtree offers
unique visualization method
• Algorithm based analysis
– Example : Asiakastieto with 40
M€ revenue
• Revenue model
– Project work
– Transaction based pricing
– Modular ecosystem
– Pro-bono
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8. 3. User experience provider
• Utilize open data to create
attractive website or mobile client
– Most popular (7 out of 14
companies)
– Example: Duunitori.fi plots job
openings on a map and
enriches them with other data
sources
• Revenue model
– Advertisements
– One-time fee
– Subscription
– Crowd funded
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9. 4. Commercial data publisher
• Co-creation with open license
– Example: With Reittiopas API
HSL saves client development
and maintenance costs
– Example: Helsingin Sanomat
Vaalikone data publishment
• Co-creation with restricted
license
– Example: The Guardian Open
Platform
• Revenue model: cost savings
with crowd sourcing and co-
creation
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10. General findings
• Private data publishing holds
lots of potential
• Extract & transform lacks
commercial activity in Finland
• Standardized APIs and
information formats important
for the scalability and continuity
of the open data business
• The value of raw data is 0 €,
without an service adding value
to it
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11. Example:
How to utilize the results?
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12. Simplified Open Data Value Network
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13. Media companies positioned similarly as
user experience providers
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14. Two opportunity avenues
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