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LLKD13 thriving under uncertainty

Okaloa
Okaloa

This document discusses thriving under uncertainty using options thinking and lean kanban principles. It describes how projects are often planned optimistically but end up delivering less than expected due to unforeseen variations. It advocates adopting an options mindset to minimize risks and costs from failures while maximizing learning. This involves using techniques like classes of service, probes, enablers and options expiration dates to balance exploration and exploitation. The overall goal is to absorb variations and make projects more anti-fragile by benefiting from disruptions.

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Thriving under uncertainty with Discovery Kanban London Lean Kanban Day March 2013 patrick.steyaert@okaloa.com @PatrickSteyaert 息 Patrick Steyaert, 2013 Thriving under uncertainty
Options and variation 2 Option 1 Effort = 300MD Most likely delivery = May 31 Variation = 賊10 days Deadline = May 15 Option 2 Effort = 300MD Most likely delivery = May 31 Variation = 賊20 days 息 Patrick Steyaert, 2013 Thriving under uncertainty
Thriving under uncertainty 3 Plan perspective Risk perspective Options perspective (Robust but fragile) (Resilient) (Anti-fragile) 則р variation and 則р absorb variation and 則р thrive from disruption; disruption are not tolerate disruption variation can be tolerated very well without collapsing beneficial Customers/ Users / Stakeholders TEAM FLEXIBLE BOUNDARY 息 Patrick Steyaert, 2013 Thriving under uncertainty
4 Pains and gains in the history of projects Absorbing variation - Classes of Service Thriving on variation - Options Kanban variations 息 Patrick Steyaert, 2013 Thriving under uncertainty
A calamitous history of 5 projects* Project Cost overrun Project Actual traffic Channel tunnel 80% as percentage UK-FR of forecast resund 70% Channel tunnel 18% access link, DE UK-FR Great belt link, 54% Miami metro, 15% DE USA resund coast- 26% Denver 55% to-coast International Airport, USA Conclusion: dont trust Conclusion: dont trust cost estimates usage forecasts *Source: Megaprojects and risk, an anatomy of ambition, Bent Flyvbjerg, Nils Bruzelius and Werner Rothengatter, 2003 息 Patrick Steyaert, 2013 Thriving under uncertainty
IT projects 6 ps of issues that cause most project failures. IT projects >$15 million1 2 45% ssues Bene鍖ts shortfall 56% Delivering large-scale IT projects on time, on budget, and on value, Michael Bloch, Sven Blumberg, and J端rgen Laartz 3 Skill issuesof 17 percent IT projects go so bad that they can 4 Execution issues threaten the very existence of the company (cost overruns of +200% and schedule slippage of nearly 70%) Double Whammy How ICT Projects are Fooled by Randomness and Screwed by Political Intent, Alexander Budzier, Bent Flyvbjerg, Aug 2011. 6 息 Patrick Steyaert, 2013 Thriving under uncertainty
Delusions and deception 則р Imperfect forecasting techniques and inadequate data 7 則р Planning fallacy & optimism bias 則р Strategic misrepresentation and asymmetric information 息 Patrick Steyaert, 2013 Thriving under uncertainty
How projects are sold 8 Gains/Losses f(X) Gain Convexity Unknown X Pain Gain more than pain 息 Patrick Steyaert, 2013 Thriving under uncertainty
9 息 Patrick Steyaert, 2013 Thriving under uncertainty
How projects turn out in practice 10 Gains/Losses f(X) Gain Unknown X Pain Concavity Pain more than gain 息 Patrick Steyaert, 2013 Thriving under uncertainty
11 Variation and disruption 則р Order of magnitude (size) 則р Political intervention 則р Customer 則р Interrupt work 則р Team 則р Technical problems 則р Policies 則р Changing requirements 則р Technology 則р Resources not available 則р Environment 則р Environmental problem(s) 則р 則р 息 Patrick Steyaert, 2013 Thriving under uncertainty
Amplification pain 12 Changes Prioritization Requirements Product Work Failure load / Rework 息 Patrick Steyaert, 2013 Thriving under uncertainty
13 Irreversibility & Lock-in 息 Patrick Steyaert, 2013 Thriving under uncertainty
Complex projects 14 How they are planned How they turn out Convexity Concavity 息 Patrick Steyaert, 2013 Thriving under uncertainty
Absorbing variation 15 Plan perspective Risk perspective Options perspective (Robust but fragile) (Resilient) (Anti-fragile) 則р variation and 則р absorb variation and 則р thrive from disruption; disruption are not tolerate disruption variation can be tolerated very well without collapsing beneficial Customers/ Users / Stakeholders TEAM FLEXIBLE BOUNDARY 息 Patrick Steyaert, 2013 Thriving under uncertainty
Kanban systems Less pain 16 Variable capability Variable demand Capability Bottlenecks Uncertainty Demand Loopbacks Kanban 息 Patrick Steyaert, 2013 Accredited Kanban Training
Cost of delay 17 EXPEDITE Cost/Value FIXED DATE STANDARD INTANGIBLE x time 息 Patrick Steyaert, 2013 Thriving under uncertainty
Classes of service - Minimize Cost 18 of delay while retaining flexibility Cost of delay Urgent Respond Policy 則р critical and immediate EXPEDITE 則р will be pulled immediately cost of delay by a qualified resource 則р cost of delay goes up FIXED DATE 則р will be pulled based on risk assessment Cost of delay significantly after Flexibility deadline (delivering on time) 則р cost of delay is shallow STANDARD 則р will use first in, first out but accelerates before (FIFO) queuing approach to leveling out prioritize pull 則р cost of delay may be INTANGIBLE 則р will be pulled through the significant but is not system in an ad hoc incurred until much fashion later Important Anticipate 息 Patrick Steyaert, 2013 Thriving under uncertainty
Capacity allocation across classes of 19 service EXPEDITE Expedite +1 = +5% Cost/Value Fixed date 4 = 20% FIXED DATE Standard 8 = 50% Intangib le 6 = 30% STANDARD INTANGIBLE x time 息 Patrick Steyaert, 2013 Thriving under uncertainty
Thriving under uncertainty 20 Plan perspective Risk perspective Options perspective (Robust but fragile) (Resilient) (Anti-fragile) 則р variation and 則р absorb variation and 則р thrive from disruption; disruption are not tolerate disruption variation can be tolerated very well without collapsing beneficial Customers/ Users / Stakeholders TEAM FLEXIBLE BOUNDARY 息 Patrick Steyaert, 2013 Thriving under uncertainty
Amplification of gains 21 Opportunities Resources Requirements Product Work User feedback/ Revenue 息 Patrick Steyaert, 2013 Thriving under uncertainty
Opportunity for learning 22 Risk/Options Cost/Value Probes Enablers Table stakes Exceptionals Is there a Can we build What is Protect & exploit need? it? essential? existing value time 息 Patrick Steyaert, 2013 Thriving under uncertainty
Never commit early (unless you 23 know why) Potential option Validate PROBE Potential option Validate ENABLERS Potential Validate option TABLE STAKES Potential option EXCEPTIONAL 息 Patrick Steyaert, 2013 Thriving under uncertainty
Exercising options 24 Potential Exercised Option Option Option 息 Patrick Steyaert, 2013 Thriving under uncertainty
25 Options expire 則р Expedite critical and immediate cost of delay 竪 will be pulled immediately by a qualified resource 則р Fixed date cost of delay goes up significantly after deadline 竪 will be pulled based on risk assessment (delivering on time) 則р Standard cost of delay is shallow but accelerates before leveling out 竪 will use first in, first out (FIFO) queuing approach to prioritize pull 則р Intangible cost of delay may be significant but is not incurred until much later; important but not urgent 竪 will be pulled through the system in an ad hoc fashion 息 Patrick Steyaert, 2013 Thriving under uncertainty
Options have value 26 Gains/Losses f(X) Gain Convexity Unknown X Pain Gain more than pain 息 Patrick Steyaert, 2013 Thriving under uncertainty
Options - Maximize learning, 27 minimize cost of failure Option Exploration 則р Fragmented functionality, PROBE 則р Explore customers Lo-Fi implementation and needs Learning opportunity 則р Minimally coherent end- ENABLERS 則р Explore feasibility to-end functionality and critical quality Cost of failure showing critical quality 則р End-to-end functionality TABLE STAKES 則р Explore what is with standard quality essential for exploitation 則р Broad and detailed EXCEPTIONAL 則р Protect & exploit functionality, Hi-Fi existing value implementation Commitment Exploitation 息 Patrick Steyaert, 2013 Thriving under uncertainty
Exploration versus exploitation 28 Potential option Validate PROBE Exploitation Potential option Validate ENABLERS Potential Exploration option Validate TABLE STAKES Potential option EXCEPTIONAL 息 Patrick Steyaert, 2013 Thriving under uncertainty
29 Real options* An option is the right to do something but not the obligation 則р Options have value 則р Options expire 則р Never commit early (unless you know why) *Ref: Chris Matts & Olav Maassen 息 Patrick Steyaert, 2013 Thriving under uncertainty
The knowledge discovery process 30 Narrative, fragmented, Working product Decision to possibly (i.e. probe, dampen or conflicting enabler,) amplify Potential Exercise Validate Abandoned Option option option option / Continue Coherent, Feedback shared (e.g. user concept feedback) Discovery front-end Development Discovery back-end Forming hypotheses Validating hypotheses 息 Patrick Steyaert, 2013 Thriving under uncertainty
Discovery Kanban Board 31 WIP limits express exploration exploitation balance Exploration Exploitation Legend Expedite Potential Option Exercise Validate Abandon / option option option Continue Fixed date 3/3/9/4 1/1/5/2 1/1/4/2 Probe Standard probe probe 28/3 Intangib Enabler le enabler Intangible Fixed date probe probe F Table Demo for tradeshow table R&D L stakes on 28/3 stakes O W Exceptional Expedite table stakes Overdue regulatory Standard enabler development Framework development FLOW 息 Patrick Steyaert, 2013 Thriving under uncertainty
Kanban variations 32 Delivery Kanban Discovery Kanban 1. Visualize work 1. Visualize options 2. Limit work in progress 2. Minimal options / maximum un- validated assumptions 3. Manage Flow flow of work 3. Manage Flow flow of customer/ 4. Make Process Policies Explicit user acquisition work policies (e.g. in terms of cost of delay) 4. Make Process Policies Explicit option policies (e.g. in terms of 5. Implement Feedback Loops at cost of failure) workflow, inter-workflow and organizational levels 5. Implement Feedback Loops customer feedback loops 6. Improve Collaboratively, Evolve Experimentally (using models/ 6. Improve Collaboratively, Evolve scientific method) Experimentally (using models/ scientific method) 息 Patrick Steyaert, 2013 Thriving under uncertainty
Not just for start-ups 則р Product development (mature product) 33 則р Business-IT programmes 則р Business transformation 則р Lean agile coaching 息 Patrick Steyaert, 2013 Thriving under uncertainty
Thriving under uncertainty 34 Plan perspective Risk perspective Options perspective (Robust but fragile) (Resilient) (Anti-fragile) 則р variation and 則р absorb variation and 則р thrive from disruption; disruption are not tolerate disruption variation can be tolerated very well without collapsing beneficial Customers/ Users / Stakeholders TEAM FLEXIBLE BOUNDARY 息 Patrick Steyaert, 2013 Thriving under uncertainty
Inspiration 35 Knowledge discovery process: http://alistair.cockburn.us/ The+Design+as+Knowledge +Acquisition+Movement 息 Patrick Steyaert, 2013 Thriving under uncertainty
Thank You patrick.steyaert@okaloa.com @PatrickSteyaert 息 Patrick Steyaert, 2013 Thriving under uncertainty
Classifying features 37 Epic Epic Epic Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story 息 Patrick Steyaert, 2013 Anti-fragile projects
Classifying features - probes 38 Epic Epic Epic Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story 息 Patrick Steyaert, 2013 Anti-fragile projects
Classifying features - enablers 39 Epic Epic Epic Enablers Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story 息 Patrick Steyaert, 2013 Anti-fragile projects
Classifying features table stakes 40 Epic Epic Epic Enablers Story Story Story Story Story Story Story Story Story Story Story Story Table stakes Story Story Story Story Story Story Story Story Story 息 Patrick Steyaert, 2013 Anti-fragile projects
Classifying features exceptionals 41 Epic Epic Epic Enablers Story Story Story Story Story Story Story Story Story Story Story Story Table stakes Story Story Story Story Story Story Exceptionals Story Story Story 息 Patrick Steyaert, 2013 Anti-fragile projects

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LLKD13 thriving under uncertainty

  • 1. Thriving under uncertainty with Discovery Kanban London Lean Kanban Day March 2013 patrick.steyaert@okaloa.com @PatrickSteyaert 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 2. Options and variation 2 Option 1 Effort = 300MD Most likely delivery = May 31 Variation = 賊10 days Deadline = May 15 Option 2 Effort = 300MD Most likely delivery = May 31 Variation = 賊20 days 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 3. Thriving under uncertainty 3 Plan perspective Risk perspective Options perspective (Robust but fragile) (Resilient) (Anti-fragile) 則р variation and 則р absorb variation and 則р thrive from disruption; disruption are not tolerate disruption variation can be tolerated very well without collapsing beneficial Customers/ Users / Stakeholders TEAM FLEXIBLE BOUNDARY 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 4. 4 Pains and gains in the history of projects Absorbing variation - Classes of Service Thriving on variation - Options Kanban variations 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 5. A calamitous history of 5 projects* Project Cost overrun Project Actual traffic Channel tunnel 80% as percentage UK-FR of forecast resund 70% Channel tunnel 18% access link, DE UK-FR Great belt link, 54% Miami metro, 15% DE USA resund coast- 26% Denver 55% to-coast International Airport, USA Conclusion: dont trust Conclusion: dont trust cost estimates usage forecasts *Source: Megaprojects and risk, an anatomy of ambition, Bent Flyvbjerg, Nils Bruzelius and Werner Rothengatter, 2003 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 6. IT projects 6 ps of issues that cause most project failures. IT projects >$15 million1 2 45% ssues Bene鍖ts shortfall 56% Delivering large-scale IT projects on time, on budget, and on value, Michael Bloch, Sven Blumberg, and J端rgen Laartz 3 Skill issuesof 17 percent IT projects go so bad that they can 4 Execution issues threaten the very existence of the company (cost overruns of +200% and schedule slippage of nearly 70%) Double Whammy How ICT Projects are Fooled by Randomness and Screwed by Political Intent, Alexander Budzier, Bent Flyvbjerg, Aug 2011. 6 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 7. Delusions and deception 則р Imperfect forecasting techniques and inadequate data 7 則р Planning fallacy & optimism bias 則р Strategic misrepresentation and asymmetric information 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 8. How projects are sold 8 Gains/Losses f(X) Gain Convexity Unknown X Pain Gain more than pain 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 9. 9 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 10. How projects turn out in practice 10 Gains/Losses f(X) Gain Unknown X Pain Concavity Pain more than gain 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 11. 11 Variation and disruption 則р Order of magnitude (size) 則р Political intervention 則р Customer 則р Interrupt work 則р Team 則р Technical problems 則р Policies 則р Changing requirements 則р Technology 則р Resources not available 則р Environment 則р Environmental problem(s) 則р 則р 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 12. Amplification pain 12 Changes Prioritization Requirements Product Work Failure load / Rework 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 13. 13 Irreversibility & Lock-in 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 14. Complex projects 14 How they are planned How they turn out Convexity Concavity 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 15. Absorbing variation 15 Plan perspective Risk perspective Options perspective (Robust but fragile) (Resilient) (Anti-fragile) 則р variation and 則р absorb variation and 則р thrive from disruption; disruption are not tolerate disruption variation can be tolerated very well without collapsing beneficial Customers/ Users / Stakeholders TEAM FLEXIBLE BOUNDARY 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 16. Kanban systems Less pain 16 Variable capability Variable demand Capability Bottlenecks Uncertainty Demand Loopbacks Kanban 息 Patrick Steyaert, 2013 Accredited Kanban Training
  • 17. Cost of delay 17 EXPEDITE Cost/Value FIXED DATE STANDARD INTANGIBLE x time 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 18. Classes of service - Minimize Cost 18 of delay while retaining flexibility Cost of delay Urgent Respond Policy 則р critical and immediate EXPEDITE 則р will be pulled immediately cost of delay by a qualified resource 則р cost of delay goes up FIXED DATE 則р will be pulled based on risk assessment Cost of delay significantly after Flexibility deadline (delivering on time) 則р cost of delay is shallow STANDARD 則р will use first in, first out but accelerates before (FIFO) queuing approach to leveling out prioritize pull 則р cost of delay may be INTANGIBLE 則р will be pulled through the significant but is not system in an ad hoc incurred until much fashion later Important Anticipate 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 19. Capacity allocation across classes of 19 service EXPEDITE Expedite +1 = +5% Cost/Value Fixed date 4 = 20% FIXED DATE Standard 8 = 50% Intangib le 6 = 30% STANDARD INTANGIBLE x time 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 20. Thriving under uncertainty 20 Plan perspective Risk perspective Options perspective (Robust but fragile) (Resilient) (Anti-fragile) 則р variation and 則р absorb variation and 則р thrive from disruption; disruption are not tolerate disruption variation can be tolerated very well without collapsing beneficial Customers/ Users / Stakeholders TEAM FLEXIBLE BOUNDARY 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 21. Amplification of gains 21 Opportunities Resources Requirements Product Work User feedback/ Revenue 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 22. Opportunity for learning 22 Risk/Options Cost/Value Probes Enablers Table stakes Exceptionals Is there a Can we build What is Protect & exploit need? it? essential? existing value time 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 23. Never commit early (unless you 23 know why) Potential option Validate PROBE Potential option Validate ENABLERS Potential Validate option TABLE STAKES Potential option EXCEPTIONAL 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 24. Exercising options 24 Potential Exercised Option Option Option 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 25. 25 Options expire 則р Expedite critical and immediate cost of delay 竪 will be pulled immediately by a qualified resource 則р Fixed date cost of delay goes up significantly after deadline 竪 will be pulled based on risk assessment (delivering on time) 則р Standard cost of delay is shallow but accelerates before leveling out 竪 will use first in, first out (FIFO) queuing approach to prioritize pull 則р Intangible cost of delay may be significant but is not incurred until much later; important but not urgent 竪 will be pulled through the system in an ad hoc fashion 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 26. Options have value 26 Gains/Losses f(X) Gain Convexity Unknown X Pain Gain more than pain 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 27. Options - Maximize learning, 27 minimize cost of failure Option Exploration 則р Fragmented functionality, PROBE 則р Explore customers Lo-Fi implementation and needs Learning opportunity 則р Minimally coherent end- ENABLERS 則р Explore feasibility to-end functionality and critical quality Cost of failure showing critical quality 則р End-to-end functionality TABLE STAKES 則р Explore what is with standard quality essential for exploitation 則р Broad and detailed EXCEPTIONAL 則р Protect & exploit functionality, Hi-Fi existing value implementation Commitment Exploitation 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 28. Exploration versus exploitation 28 Potential option Validate PROBE Exploitation Potential option Validate ENABLERS Potential Exploration option Validate TABLE STAKES Potential option EXCEPTIONAL 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 29. 29 Real options* An option is the right to do something but not the obligation 則р Options have value 則р Options expire 則р Never commit early (unless you know why) *Ref: Chris Matts & Olav Maassen 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 30. The knowledge discovery process 30 Narrative, fragmented, Working product Decision to possibly (i.e. probe, dampen or conflicting enabler,) amplify Potential Exercise Validate Abandoned Option option option option / Continue Coherent, Feedback shared (e.g. user concept feedback) Discovery front-end Development Discovery back-end Forming hypotheses Validating hypotheses 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 31. Discovery Kanban Board 31 WIP limits express exploration exploitation balance Exploration Exploitation Legend Expedite Potential Option Exercise Validate Abandon / option option option Continue Fixed date 3/3/9/4 1/1/5/2 1/1/4/2 Probe Standard probe probe 28/3 Intangib Enabler le enabler Intangible Fixed date probe probe F Table Demo for tradeshow table R&D L stakes on 28/3 stakes O W Exceptional Expedite table stakes Overdue regulatory Standard enabler development Framework development FLOW 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 32. Kanban variations 32 Delivery Kanban Discovery Kanban 1. Visualize work 1. Visualize options 2. Limit work in progress 2. Minimal options / maximum un- validated assumptions 3. Manage Flow flow of work 3. Manage Flow flow of customer/ 4. Make Process Policies Explicit user acquisition work policies (e.g. in terms of cost of delay) 4. Make Process Policies Explicit option policies (e.g. in terms of 5. Implement Feedback Loops at cost of failure) workflow, inter-workflow and organizational levels 5. Implement Feedback Loops customer feedback loops 6. Improve Collaboratively, Evolve Experimentally (using models/ 6. Improve Collaboratively, Evolve scientific method) Experimentally (using models/ scientific method) 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 33. Not just for start-ups 則р Product development (mature product) 33 則р Business-IT programmes 則р Business transformation 則р Lean agile coaching 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 34. Thriving under uncertainty 34 Plan perspective Risk perspective Options perspective (Robust but fragile) (Resilient) (Anti-fragile) 則р variation and 則р absorb variation and 則р thrive from disruption; disruption are not tolerate disruption variation can be tolerated very well without collapsing beneficial Customers/ Users / Stakeholders TEAM FLEXIBLE BOUNDARY 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 35. Inspiration 35 Knowledge discovery process: http://alistair.cockburn.us/ The+Design+as+Knowledge +Acquisition+Movement 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 36. Thank You patrick.steyaert@okaloa.com @PatrickSteyaert 息 Patrick Steyaert, 2013 Thriving under uncertainty
  • 37. Classifying features 37 Epic Epic Epic Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story 息 Patrick Steyaert, 2013 Anti-fragile projects
  • 38. Classifying features - probes 38 Epic Epic Epic Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story 息 Patrick Steyaert, 2013 Anti-fragile projects
  • 39. Classifying features - enablers 39 Epic Epic Epic Enablers Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story Story 息 Patrick Steyaert, 2013 Anti-fragile projects
  • 40. Classifying features table stakes 40 Epic Epic Epic Enablers Story Story Story Story Story Story Story Story Story Story Story Story Table stakes Story Story Story Story Story Story Story Story Story 息 Patrick Steyaert, 2013 Anti-fragile projects
  • 41. Classifying features exceptionals 41 Epic Epic Epic Enablers Story Story Story Story Story Story Story Story Story Story Story Story Table stakes Story Story Story Story Story Story Exceptionals Story Story Story 息 Patrick Steyaert, 2013 Anti-fragile projects