This document outlines an open data business model training course consisting of 4 sessions: Session 1 introduces business models and open data value propositions. Participants define open data uses and revenue models. Session 2 uses a business model canvas to develop open data product/service models. Session 3 discusses pricing, acquisitions, and reassessing models due to market/data/customer changes. Session 4 emphasizes turning theory into practice by incentivizing open data strategies and finding business opportunities in open data competitions and challenges.

1. Benjamin Cave –
Trainer
@cave_ben19 July, 2016
On the canvas with open data

2. Introductions
Your name?
What does your business do with open data?
What is your 5-year vision for data in your business?

3. Understanding open
data business models
Session 1
Building a business model
Integrating open data into
your work
Session 2
Session 3

4. To enhance participants’ ability to
develop new business models for open
data
Course aim

5. Understanding open data business
models
Session 1
Understanding the landscape

6. Define the purpose of a business model
Define the value of open data to your business
Describe key archetypes of open data business models
Outcomes

7. Business models
‘A business model is the logic of
an organization to create value’
Osterwalder et. al. Business Model Creation

8. Purpose
Assess the value of open
Get beyond the ‘zero sum’ of data
Connect your data considerations to
business value
Biggest question
What customer problem could open data
solve?

9. Step 1 – Defining the value of your open
data service

10. What is the current value of data to
your business?
Post-its in 5

12. A value proposition is the solution to
your customer’s problem

13. Value of open data

17. What is the problem that open data
could solve for your business?

18. What is the value of open data?
Open data is free - value no-longer comes from data itself, but
products and services – added value developed for the market
Ease of use
Behaviour change
Improve innovation
Increase performance
Reduce client cost
Reduce your costs
Reduce risk
Increase accessibility
Build new partnerships
Improve a brand
Solidify value proposition
Benchmark your performance

19. Step 2 – Finding the right revenue model

20. What models are working
for open data right now?

21. Sectors of
OD
businesses

22. Most
popular
data types

23. How they
got the
data

24. Open Revenue Models
Premium Freemium
Cross Subsidy
Demand-Platforms
Razors/Blades
White LabelSupply Platforms
Advertising Data Acc.

25. Business strategies
Organisation – Boost the brand
Platform – Collaborate to collect
Services – Features for funds

26. Exercise
Map the following:

27. Step 3 – Knowing when to start charging

29. 29 cities worldwide
$10m VC round in 2014
Rapid growth Model:
Expansion -
led

30. 1,500 developers
Three pricing tiers
£300k annual turnover Model:
Flexible
price

31. Premium product set
Data supply agreement
$930m takeover
Model:
Acquisition

32. Pricing considerations
1. Calculate the price to the customer of retrieving
data on their own
2. Add time/inconvenience estimate
3. Divide by likely number of future uses
4. Add any in-kind value estimate
The above should be higher than the cost
of the product for 50% of likely customers

33. Session 2
Building a business model
Creating something that works for you

34. Use the Osterwalder Business Model Canvas
Lead a group discussion on developing a business model canvas
Produce a complete business model canvas for their
product/service
Outcomes

35. The canvas
Image: JAM

36. The process
Image: Harry Verwayen

38. Session 4
Integrating your business model into
your work
Turning theory into practice

39. Summarise criteria for reassessing of a business model
Analyse future innovation opportunities for open data
Outcomes

40. Step 4 – Remodelling

41. Question
What would cause you to
reexamine your data
business model?

43. When to Innovate
1. Changes in the market
2. Changes in the data
3. Changes in the customer needs
4. Changes in the team
5. Changes in the product performance

44. Creating the incentives for change

45. Why create incentives?
Open data benefits the organisation but some people will lose out
Those who resist perceive the current state as ‘pareto optimal’; any benefit
to one person bringing at least equal harm to others.
Incentives allow rational actors to pursue their interests while contributing to
the goals of your open data strategy

46. Incentives to implement
A key driver of positive strategy adoption is strong, well-aligned incentives
Different functions within the organisation respond to different incentives
Finding the right incentives to overcome differences, harness competition
and encourage collaboration is a priority for strategy architects

47. Exercise
Play the contribution game
20 minutes

48. The contribution game

49. Rules
Every player starts with 100 pounds
Each round the player decides how much to contribute to a ‘public pot’
between 0 and 100 pounds
The public pot pays everyone double the average contribution of all players
Every player ends the round with their share of the public pot plus anything
they did not contribute

50. Example
3 players
Player 1 gives 60 pounds, player 2 gives 40 pounds and player 3 gives 20 pounds
The average contribution to the public pot is therefore 40 pounds
Each player receives 2*40 pounds from the public pot to add to their leftover money
So player 1 has 120 pounds, player 2 has 140 pounds and player 3 has 160
pounds

51. Round 1
Budget: 100 pounds
Reward: 2 * average contribution
http://goo.gl/forms/Nm5B2aAwd7xJzb753

52. Round 2
Budget: 100 pounds
Return: 2 * average contribution
Punishment: Lowest balance eliminated
http://goo.gl/forms/vANFi1GKsXUNgfHy2

53. Round 3
Budget: 100 pounds
Return: 2 * average contribution
Reward: If the average end balance > 150 pounds, everyone
gets a sweet
http://goo.gl/forms/RHtk4xX56B0Oi3203

54. Round 4
Budget: 100 pounds
Reward: 2 * average contribution
Present: Closest contribution(s) to average get 10 sweets
http://goo.gl/forms/6Q80OkSQjpU36nlp2

55. Round 5
Budget: 100 pounds
Reward: 2 * average contribution
Visibility: All contributions made public
http://goo.gl/forms/6Iu2Eu6vIntkTdBG3

56. Strategic Incentives
Incentive Metric Pros Cons
Overall Quantity Numeric Target Collective action,
scale of result
Free-rider problem,
less useful data
Selected Quantity List of Targets Useful data, equal
contributions
Time-intensive, unit
resistance
Competitive Reward Number from Unit Competitive drive,
broad engagement
Less useful data,
penalise success
Competitive Sanction Number from Unit Overcome apathy,
broad participation
Race to the middle,
Hostile environment
Impact Reward Qualitative Maximise results,
focus resources
Free-rider problem,
inconsistent

57. Development incentive
Data
CompetitionsNetworks
Funding

58. Finding business in open data
1. Opportunity-driven
2. Data-driven
3. Idea-driven
4. Challenge-driven
Ease Sustainability

59. Understanding open
data business models
Session 1
Building a business model
Integrating a business
model into your work
Session 2
Session 3

60. Benjamin Cave –
Trainer
@cave_ben19 July, 2016
Thank you