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Platform Strategy and Digital Ecosystems

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Platform Strategy and Digital Ecosystems

  1. 1. Platform Strategy & Ecosystems Open Business Conference May 6th 2014
  2. 2. Warming Up
  3. 3. Let’s take a look at the 5-year predictable horizon
  4. 4. The world will be faster, more connected, with a billion more participants in the global economy.
  5. 5. A rising middle class in Brazil, India, China, and Indonesia will adopt devices first and computers second, leaping the digital divide.
  6. 6. Gen-Y consumers and employees will be in their 30s, defining the conventions for work and play styles.
  7. 7. 4G wireless will be broadly available and 5G will be in limited deployment.
  8. 8. Carrier networks will be optimized for traffic against specific services and media types.
  9. 9. Consumer devices will be dominant, but small devices for data sensing and processing will make up a significant percentage of mobile and Internet traffic.
  10. 10. Most commerce will be initiated via mobile devices and completed on a range of platforms.
  11. 11. Most transactions, when executed, will be multi-party: between the app and the underlying services.
  12. 12. Social media with effective partitions and channels will be the dominant mode of communication.
  13. 13. User attention will continue to fragment, alternately directing and being directed by a range of apps.
  14. 14. Data will be a unit of value and a mechanism of lock-in.
  15. 15. Industries will be platform-shaped, with a dominant player occupying the high-margin platform position and pushing others to supporting roles.
  16. 16. What is a Platform Business Model?
  17. 17. Product to Platform
  18. 18. Product to Platform
  19. 19. Product to Platform
  20. 20. A platform business model is defined as follows: It is a business model which builds value for multiple sides in a given market by consolidating customers, simplifying market- wide processes, and rewarding each player in the value network between the value network and the customers.
  21. 21. There are many examples of platform business models in action today.
  22. 22. Eisenmann, Parker, Van Alstyne (2006),“Strategies for Two- Sided Markets,”
  23. 23. There are many examples of digital platform business models in action today.
  24. 24. 1. Desktop OS: Unix, Mac, Windows 2. PDAs: Palm, Psion, Newton 3. Game Consoles: Wii, Xbox, PlayStation 4. Network Switches: Cisco, IBM, HP 5. Multimedia: Adobe/Flash, MS/Silverlight, Google-Apple/HTML5 6. Payment Systems: PayPal, Google Checkout, Visa, Apple, Mobile Felica 7. Mobile Devices: iPhone, Android, Symbian, Blackberry 8. Enterprise Systems: Salesforce, Oracle, i2, IBM, SAP 9. Social Networks: Facebook, MySpace, LinkedIn, Monster, Twitter 10. Batteries: Sony, Panasonic, Sanyo, A123 11. Web Search: Google, Bing+Yahoo!, Baidu 12. eBooks: Amazon, iPad, Nook, Sony 13. Smart Grids: IBM etc. 14. Health Care: Microsoft, WebMD, IBM etc. Eisenmann, Parker, Van Alstyne (2011), “Platform Envelopment,” Strategic Management Journal.
  25. 25. Platform businesses are built on network effects. The more network effects, the stronger the platform.
  26. 26. Kindle Usr Book PSP Usr Gam Zune Usr Mus MicrosoftSonyAmazon Eisenmann, Parker, Van Alstyne (2011), “Platform Envelopment,” Strategic Management Journal. MP3 User Musi c Video TV Games Dvpr Web HTML eBooks Publi Calls User Apple
  27. 27. Openness is a critical element of all platform businesses.
  28. 28. Eisenmann, Parker, Van Alstyne (2011), “Platform Envelopment,” Strategic Management Journal.
  29. 29. V4 V3 Price q1 p1 Quantity V1 V2 Platform sponsor gives away platform value. Partners build apps for installed base, adding new layers of value. Platform sponsor benefits from increased sales & royalties. Partners benefit from cost savings and installed base. Parker, Van Alstyne (2011), “Innovation, Openness & Platform Control,”
  30. 30. Platform models generate profit through first and third party usage.
  31. 31. Most firms can only concentrate on most valuable apps Profits increase when others add to platform’s “Long Tail” Parker, Van Alstyne (2011), “Innovation, Openness & Platform Control,”
  32. 32. Platform models build digital ecosystems through virtuous cycles.
  33. 33. We view Digital Ecosystems to be the digital counterparts of biological ecosystems, exploiting the self-organising properties of biological ecosystems, which are considered to be robust, self-organising and scalable architectures that can automatically solve complex, dynamic problems. Digital Ecosystems are a novel optimisation technique where the optimisation works at two levels: a first optimisation, migration of agents (representing services) which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. “ G. Briscoe, P. DeWilde IEEE Conference on BIONETICS (2006)
  34. 34. A digital ecosystem is a distributed, adaptive, open socio-technical system with properties of self-organization, scalability and sustainability inspired from natural ecosystems. Digital ecosystem models are informed by knowledge of natural ecosystems, especially for aspects related to competition and collaboration among diverse entities. “ Various authors Wikipedia: Digital Ecosystem
  35. 35. [Ecosystem Competition] Kishore S. Swaminathan (2009), Chief Scientist, Accenture
  36. 36. This approach of common platforms and shared incentives is the path to digital ecosystem success.
  37. 37. One Last Thought
  38. 38. Given current abundance of choices and scarcity of user attention, compelling experiences must deliver platform capabilities and content to users. Without such experiences, an ecosystem fails to thrive.
  39. 39. Weill & Woerner (2013), “Optimizing Your Digital Business Model,” MIT Sloan Management Review
  40. 40. Thank you Please send questions and comments to: @sramji

Notas del editor

  • 2011 Parker & Van Alstyne
  • We created an Ecosystem-Oriented Architecture of Digital Ecosystems by extending Service-Oriented Architectures with distributed evolutionary computing, allowing services to recombine and evolve over time, constantly seeking to improve their effectiveness for the user base. Individuals within our Digital Ecosystem will be applications (groups of services), created in response to user requests by using evolutionary optimisation to aggregate the services. These individuals will migrate through the Digital Ecosystem and adapt to find niches where they are useful in fulfilling other user requests for applications. Simulation results imply that the Digital Ecosystem performs better at large scales than a comparable Service-Oriented Architecture, suggesting that incorporating ideas from theoretical ecology can contribute to useful self-organising properties in digital ecosystems.