Agile portfolio management decision-making
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Agile portfolio management decision-making

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Agile portfolio management decision-making Presentation Transcript

  • 1. Handle the known and unknownwith portfolio management
  • 2. Agile PORTFOLIOMANAGEMENT is about Picture investments strategies anddecision-making in an uncertain and fast moving world
  • 3. What is classic portfolio management? “Portfolio management for new products is a dynamic decision process wherein the list of active products and R&D projects is constantly revised. It is about balance, the optimal investment mix between risk versus return, maintenance versus growth, and short-term versus long-term new product projects.” Waterfall Dr Robert G Cooper, author of “Portfolio Management for new Agile products”, and the Stage-Gate process
  • 4. Financial and economical model are usedto MAXIMIZE the VALUE of the portfolio
  • 5. Financial models for investment selectionsPossible investmentsNew system platformProject AlfaProject BravoProject CharlieProject EchoCurrent platformNew design for a product-range Which projects should we choose to start/finish and in what order?
  • 6. Some common financial models NPV ROI IRR Bang for The Buck Index ECV how much and how fast
  • 7. Financial models for investment selectionsPossible investments NPV IRR ROINew system platform 10 M€ 50 % 5Project Alfa 4 M€ 110 % 4Project Bravo 6 M€ 200 % 1Project Charlie 9 M€ 140 % 5Project Echo 2 M€ 190 % 6Current platform 1 M€ 400 % 3New design for a product-range 20 M€ 110 % 10
  • 8. “Financial models kills innovation” Clayton M. Christensen, “Innovation killers”
  • 9. “…over-reliance on strictly financial data may lead to wrong decisions, simple because financial data are often wrong!” Dr Robert G Cooper, author of “Portfolio Management for new products”, and the Stage-Gate process
  • 10. My assumption #1:Value is not only measured by the unit cash money, but it isstill an important input
  • 11. Some common scoring modelsCelanese CoD DuPont projects relative each other
  • 12. The Celanese Scoring Model Rating scale   Key Factors   1   4   7   10   Rating   Probability of technical success   < 20%   40%   70%   >90%   4   Probaability of commercial success   < 20%   40%   70%   >90%   5   Small/break Payback < 7 Payback = Payback < 3 Reward   even   years   5 years   years   10   Business Strong Strategy fit   Low   Somewhat   Supports   support   1   Strategic Several Support Vast array of Leverage   Dead end   opportunities   more BU   opportunities   4   Sum   24  
  • 13. Scoring models for investment selectionsPossible investments Celanese CoDNew system platform 24 3Maintenance on product Alfa 30 2New feature for product Bravo 15 4Maintenance of product Charlie 12 5Incremental of product Echo 22 1New feature for current platform 13 1New design for a product-range 6 1
  • 14. But… The scoring models tend to have imaginary precision, produce halo effect and have no relation to limitation of resources
  • 15. My assumption #2:Decision-making of investments is complex
  • 16. My assumption #3:Agile principles and values are a better approachfor handling uncertainty and innovation
  • 17. “Complexity and Agile is a marriage made in heaven.” http://vimeo.com/30596502 Dave Snowden, Complexity and knowledge management researcher
  • 18. 1. Address complexity with complexity2. Use a diversity of perspectives3. Assume dependence on context4. Assume subjectivity and coevolution5. Anticipate, adapt, explore6. Develop models in collaboration7. Shorten the feedback cycle8. Steal and tweak Jurgen Appelo, Management3.0
  • 19. Ok, so what have we got… Relative data Complexity Financial data Agile values and principles
  • 20. Use relative scoring-models which includes financial data     Ra$ng  scale       Key  Factors   1   5   10   Ra$ng   Strategy  alignment   Low   Moderate   Strongly       Team  energy  factor                           Low   Moderate   High       Bang  for  the    Buck   Index   <  1   1-­‐1.5   >  1.5       Probability  of   Technical  Success   Low   Moderate   High       Es$mated  customer   value   Low   Moderate   High       Time-­‐to-­‐makret   cri$cal   Low   Moderate   High       Sum         0  
  • 21. Use different factors for different investments     Ra$ng  scale           Ra$ng  scale      Key  Factors   1   5   10   Ra$ng   Key  Factors   1   5   10   Ra$ng  Strategy  alignment   Low   Moderate   Strongly       Strategy  alignment   Low   Moderate   Strongly      Team  energy  factor                           Low       Moderate   High       Ra$ng  scale       Key  Factors   1   5   Team  energy  factor                           Low   10   Ra$ng   Moderate   High      Bang  for  the    Buck   Bang  for  the    Buck  Index   <  1   1-­‐1.5   >  1.5       Strategy  alignment   Low   Moderate   Index   Strongly       <  1   1-­‐1.5   >  1.5      Probability  of   Team  energy  factor                           Low   Moderate   Probability  of     High    Technical  Success   Low   Moderate   High       Bang  for  the    Buck   Technical  Success   Low   Moderate   High      Es$mated  customer   Index   Es$mated  customer  value   Low   Moderate   High    <  1     1-­‐1.5   >  1.5       value   Low   Moderate   High      Time-­‐to-­‐makret   Probability  of   Time-­‐to-­‐makret  cri$cal   Low   Moderate   High       Technical  Success     Low   Moderate   cri$cal   High       Low   Moderate   High      Sum       0   Es$mated  customer   Sum         0   value   Low   Moderate   High       Time-­‐to-­‐makret   cri$cal   Low   Moderate   High       Sum         0  
  • 22. Score projects collaborative Use the collective knowledge by invite teams and other people who might be of help to bring different perspectives
  • 23. Review the portfolio often Measure the factors regular against delivered projects and change them when needed. Re-score regular, perhaps after every release.
  • 24. Break projects into smaller project to increase the flexibility If the projects are small the decisions can be made more often, the portfolio is more prepared for changes and delivers value faster to customers. Smaller projects are easier to estimate and contains less uncertainty.
  • 25. Score and reduce assumptions Most of the scorings are based on assumptions, score the projects based on an assumption factor. Projects with high assumption factor are more prone to failure. Work continuously to reduce unverified assumptions. Assumptions lead to the dark side. if (ASSUMPTION, “The price of the product is based on the assumption that a customer will pay just as much in Europe as in US.” == TRUE) then project = (“Success”);
  • 26. Keep the portfolio in balance Maintenance Incrementals Innovations Now Soon Future Possible investments Scoring Scoring Type Assumptions management Teams Investment New system platform 24 30 Innovation High Project Alfa 30 20 Maintenance Medium Maintenance Project Bravo 15 16 Incremental Low Incremental Project Charlie 10 12 Incremental Low Innovations Project Echo 15 1 Maintenance High Current platform 22 14 Incremental High New design for a 8 40 Incremental Low product-range
  • 27. Agile portfolio thinking1.  Use relative scoring-models which includes financial data2.  Use different factors depending on type of investment3.  Score the projects collaboratively4.  Review and update the portfolio plan often5.  Keep the projects as small as possible for flexibility6.  List and reduce assumptions that may be false7.  Keep the portfolio in balance, secure long-term innovation investment
  • 28. But this is only my ideas… What is yours? How do you chose which projects to start?
  • 29. Me… Johan Oskarsson johan-oskarsson @johanoskarsson www.captaintrouble.com Johan.oskarsson@knowit.se +46 073 3355778