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Business model innovation slides - 7/16

Benjamin Cave
Benjamin Cave

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.

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Benjamin Cave Trainer @cave_ben19 July, 2016 On the canvas with open data
Introductions Your name? What does your business do with open data? What is your 5-year vision for data in your business?
Understanding open data business models Session 1 Building a business model Integrating open data into your work Session 2 Session 3
To enhance participants ability to develop new business models for open data Course aim
Understanding open data business models Session 1 Understanding the landscape
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
Business models A business model is the logic of an organization to create value Osterwalder et. al. Business Model Creation
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?
Step 1 Defining the value of your open data service
What is the current value of data to your business? Post-its in 5
Business model innovation slides - 7/16
A value proposition is the solution to your customers problem
Value of open data
Business model innovation slides - 7/16
Business model innovation slides - 7/16
Business model innovation slides - 7/16
What is the problem that open data could solve for your business?
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
Step 2 Finding the right revenue model
What models are working for open data right now?
Sectors of OD businesses
Most popular data types
How they got the data
Open Revenue Models Premium Freemium Cross Subsidy Demand-Platforms Razors/Blades White LabelSupply Platforms Advertising Data Acc.
Business strategies Organisation Boost the brand Platform Collaborate to collect Services Features for funds
Exercise Map the following:
Step 3 Knowing when to start charging
Business model innovation slides - 7/16
29 cities worldwide $10m VC round in 2014 Rapid growth Model: Expansion - led
1,500 developers Three pricing tiers 贈300k annual turnover Model: Flexible price
Premium product set Data supply agreement $930m takeover Model: Acquisition
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
Session 2 Building a business model Creating something that works for you
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
The canvas Image: JAM
The process Image: Harry Verwayen
Business model innovation slides - 7/16
Session 4 Integrating your business model into your work Turning theory into practice
Summarise criteria for reassessing of a business model Analyse future innovation opportunities for open data Outcomes
Step 4 Remodelling
Question What would cause you to reexamine your data business model?
Business model innovation slides - 7/16
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
Creating the incentives for change
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
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
Exercise Play the contribution game 20 minutes
The contribution game
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
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
Round 1 Budget: 100 pounds Reward: 2 * average contribution http://goo.gl/forms/Nm5B2aAwd7xJzb753
Round 2 Budget: 100 pounds Return: 2 * average contribution Punishment: Lowest balance eliminated http://goo.gl/forms/vANFi1GKsXUNgfHy2
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
Round 4 Budget: 100 pounds Reward: 2 * average contribution Present: Closest contribution(s) to average get 10 sweets http://goo.gl/forms/6Q80OkSQjpU36nlp2
Round 5 Budget: 100 pounds Reward: 2 * average contribution Visibility: All contributions made public http://goo.gl/forms/6Iu2Eu6vIntkTdBG3
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
Development incentive Data CompetitionsNetworks Funding
Finding business in open data 1. Opportunity-driven 2. Data-driven 3. Idea-driven 4. Challenge-driven Ease Sustainability
Understanding open data business models Session 1 Building a business model Integrating a business model into your work Session 2 Session 3
Benjamin Cave Trainer @cave_ben19 July, 2016 Thank you

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Business model innovation slides - 7/16

  • 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 customers problem
  • 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?
  • 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
  • 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 贈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
  • 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
  • 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
  • 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
  • 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

Editor's Notes

  • #2: non-profit, non-partisan Founded 1 year ago 15 full time employees TBL and Nigel Shadbold SPACE TO CONVENE, help others use data
  • #11: 10
  • #12: Defining the language of data = licensing, not marketing jargon We help businesses, governments, organisations and individuals understand the power of data across the Data Spectrum by developing clear and relevant language that everyone can understand; training people in its usage; and supporting businesses and governments in applying it to their own data inventories. http://www.theodi.org/data-spectrum http://theodi.org/who-owns-our-data-infrastructure
  • #51: Put into a table