Heuristics for Becoming a Learning Organisation

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In a world of Big Bang Disruption, the need for learning organisations is greater than ever. Businesses need to develop people so they are able to continuously solve new problems, rather than focussing on implementing solutions to previous problems.

This presentation explores how heuristics can be used to enable this problem solving capability. It introduces a set questions which can be used to encourage creative thinking from multiple perspectives, from understanding the problems, to imagining the desired impacts and then designing potential interventions.

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Heuristics for Becoming a Learning Organisation

  1. 1. Heuristics for Becoming a Learning Organisation Karl Scotland @kjscotland http://KarlScotland.com http://AvailAgility.co.uk
  2. 2. Descriptive not Prescriptive
  3. 3. Heuristic: involving or serving as an aid to learning, discovery, or problem solving by experimental and especially train-and-error methods. of, or relating to exploratory problem-solving techniques that utilise self-educating techniques (as the evaluation of feedback) to improve performance Mirriam-Webster Dictionary
  4. 4. Heuristics Replace Rules
  5. 5. we need a clear rule for when (or who) can break the rules and heuristics that apply on the other side of the boundary. If you have to break the rules then that is OK, it will happen, but you have to then follow the heuristics. cognitive-edge.com : Rules is Rules, Jan 29 2013
  6. 6. Disorder Complicated Knowable Causality Good Practice Sense – Analyse Respond Simple Known Causality Best Practice Sense – Categorise - Respond Complex Retrospective Causality Emergent Practice Probe – Sense - Respond Chaotic Incoherent Causality Novel Practice Act – Sense - Respond Ordered Unordered Cynefin
  7. 7. Heuristics Support Substitution
  8. 8. a simple procedure that helps find adequate, though often imperfect answers to difficult questions. The word comes from the same root as eureka. Daniel Kahneman
  9. 9. Consider the letter K. Is K more likely to appear as the first letter in a word OR as the third letter?
  10. 10. Heuristics Guide Towards New Possibilities
  11. 11. rules of thumb – that guide us towards a solution by way of organised exploration of the possibilities. Roger Martin
  12. 12. The Knowledge Funnel Mystery Heuristics Algorithm Validity Reliability
  13. 13. Inductive - what is Deductive – what must be Abductive – what might be
  14. 14. Flow Value Potential Study Share Stabilise Sense Search System Interventions Impacts
  15. 15. What systemic problem, difficulty or frustration are we trying to address, and who is experiencing it? System
  16. 16. Outputs … create Outcomes … which have Impact
  17. 17. More stories like this… Fewer stories like that…
  18. 18. What stories might be told about the work going through a perfect process which has reliability and efficiency? Flow Impacts
  19. 19. What stories might be told about the work creating an unbeatable product which has validity and effectiveness? Value Impacts
  20. 20. What stories might be told about the work being done by passionate people who have flexibility and euphoria? Potential Impacts
  21. 21. Flow Value Potential Process Product People Reliability Validity Flexibility Efficiency Effectiveness Euphoria
  22. 22. Study the context Share the understanding Stabilise the work Sense the capability Search the landscape
  23. 23. What could be done to learn more about customer and stakeholder needs, the resultant demand, and how that demand is processed? Study Interventions
  24. 24. Customer Demand Process Empathy Interviews Demand Analysis Value Stream Mapping
  25. 25. What information is important to share, and how can tokens, the inscriptions on them, and their placements, create a common understanding? Share Interventions
  26. 26. Dimensions ! Scope ! Time ! People ! Cost ! Quality ! Priority ! Status ! Capability ! Demand ! Value ! Issues ! Risks ! Constraints ! Dependencies ! Assumptions ! ?
  27. 27. TIPs Token Inscription Placement
  28. 28. What policies could help limit work in process, and remove unnecessary or unexpected delays or rework? Stabilise Interventions
  29. 29. Policies !  WIP Limits !  Definitions of Done/Ready !  Scheduling !  Classes of Service !  Defects !  Cadences
  30. 30. What measures and meetings might create insights and guide decisions on potential interventions? Sense Interventions
  31. 31. ODIM Outcome Decisions Insights Measures
  32. 32. Do it fast Do the right thing Do it right Do it on time Keep doing it
  33. 33. Cadences ! Scheduling ! Planning ! Reporting ! Reviewing !  Retrospection !  Releasing !  Learning !  ?
  34. 34. What small experiments could be run to safely learn the impact of different interventions? Search Interventions
  35. 35. Double Loop Learning Results Strategies & Techniques Assumptions
  36. 36. Background: What do you want to learn and why? Frame the Experiment: What is your Problem Statement? Write the Problem Statement from the Define worksheet here. What pain or problem is being experienced? [Customer Segment] needs a way to [describe job to be done], (because|but|surprisingly) [describe insight]. Hypothesis to Test [Specific repeatable action] will create [expected result]. Is this hypothesis falsifiable? Experiment Details Describe the experiment you plan to run and how you are going to attempt to falsify your hypothesis. Safety: How is the experiment safe to run? Describe how the experiment is safe to run. Describe how you will recover from running the experiment upon completion or if you discover it isn’t safe to run. Measures What will you measure to invalidate your hypothesis? What will you measure to indicate the experiment is safe to run? What will you measure to indicate you should amplify the experiment? Measures can be Qualitative and Quantitative. Experiment Backlog Stack ranked list of actions needed to run the experiment. Next Steps: Given what you learned, what’s next? Experiment Results and Learnings Describe what you learned from the experiment? Did you invalidate your hypothesis or does it live on? Experiment Name: Owner: Mentor: Date: V 1.0
  37. 37. If we can’t generate 5-10 options for a solution it means we are overly constrained and have too little diversity. Jabe Bloom
  38. 38. http://kanban-thinking.net
  39. 39. ? ?
  40. 40. Thank You! Karl Scotland @kjscotland http://KarlScotland.com http://AvailAgility.co.uk http://kanban-thinking.net

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