J1 2015 "Thinking Fast and Slow with Software Development"
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In the international bestseller Thinking, Fast and Slow, Daniel Kahneman explains how we, as human beings, think and reason and, perhaps surprisingly, how our thought processes are often fundamentally flawed and biased. This session explores the ideas presented in the book in the context of professional software development. Along this journey, the presentation also shares techniques, processes, and models that can help overcome some of the identified limitations of our decision-making abilities. Topics discussed include the “availability heuristic,” which can lead developers to choose the “latest and greatest” technology without proper evaluation; “optimistic bias,” which can blind architects so they can’t see the “unknown unknowns” within a project; and more.
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J1 2015 "Thinking Fast and Slow with Software Development"
- 1. Thinking, Fast and Slow… With Software Development Daniel Bryant Principal Consultant, OpenCredo daniel.bryant@opencredo.com @danielbryantuk
- 2. Think More Deliberately • Our decision making can be flawed… • Apply process and models (as appropriate) • Collaborate more (and better) • Plan, do, check, act… 28/10/2015 @danielbryantuk
- 3. Who Am I? • London Java Community Associate • Adopt OpenJDK and JSR • InfoQ Editor, DZone MVB, Voxxed 28/10/2015 @danielbryantuk • Principal Consultant at OpenCredo • Technical/digital transformation • Java, Golang, CI/CD, DevOps • Microservices, cloud and containers • PhD in Artificial Intelligence
- 4. Pointy-Haired Decision Making… 28/10/2015 @danielbryantuk dilbert.com/strip/2010-08-24
- 5. Our Thinking: A Tale of Two Systems… System 1: fast, instinctive, emotional, subconscious System 2: slower, deliberate, reasoning, conscious 28/10/2015 @danielbryantuk
- 6. 2 + 2 = ? 28/10/2015 @danielbryantuk
- 7. (24 / 2) * (1 / 3) = ? 28/10/2015 @danielbryantuk
- 8. 2 + 2 = 4 (24 / 2) * (1 / 3) = 4 28/10/2015 @danielbryantuk
- 12. Bob is a single male in his 20’s who is bright, quiet, likes science fiction and fantasy, and avoids interacting with people in the real world Which is more probable? • Bob is a programmer • Bob is a programmer and plays MMORPG? 28/10/2015 @danielbryantuk
- 14. Our Thinking: A Tale of Two Systems… System 1: fast, instinctive, emotional, subconscious Rapid, associative, and has systemic errors System 2: slower, deliberate, reasoning, conscious Lazy, and causal (not statistical) 28/10/2015 @danielbryantuk
- 15. Heuristics / biases affecting software delivery 28/10/2015 @danielbryantuk
- 16. Availability Heuristic “If something can be recalled, it must be important” ‘Hipster-itis’ e.g. the ‘best’ architectural style 28/10/2015 @danielbryantuk
- 17. Microservices • The current flavour of the month! – Great ideas, but dangerously over-hyped • Frameworks and products emerging – Virtuous (vicious?) circle – “The bandwagon effect” – Have we found the silver bullet?… 28/10/2015 @danielbryantuk
- 18. Whatever is Available When all you have is a hammer… …everything looks like a nail 28/10/2015 @danielbryantuk
- 19. When all you have is a SOA… …everything looks like a service (please avoid creating the toString() service) 28/10/2015 @danielbryantuk
- 20. When all you have is a Jenkins… …everything looks like a Jenkins Job 28/10/2015 @danielbryantuk
- 21. When all you have is a Spring Framework… …everything looks like an AbstractSingletonProxyFactoryBean 28/10/2015 @danielbryantuk
- 22. Availability: Think Professionally • Stop… engage system 2 • Spike/prototype, experiment, evaluate… • Constant learning – Find trusted mentors – Cultivate blogs – Read the classics 28/10/2015 @danielbryantuk
- 24. Evaluation “I will postpone using this shiny new framework until my peers have validated the proposed benefits with rigorous scientific experiments” - Said by no programmer …ever 28/10/2015 @danielbryantuk
- 25. Raible’s Comparison Matrix 28/10/2015 @danielbryantuk Matt Raible comparison matrix (bit.ly/OxUzad)
- 26. Optimistic Bias “People tend to be overconfident, believing that they have substantial control in their lives” I know what our customers want… …how could I possibly be wrong? 28/10/2015 @danielbryantuk
- 27. Four Factors of Optimistic Bias • Desired end state – Self-enhancement, perceived control • Cognitive mechanisms – Representativeness heuristic, singular target focus • Information about self vs target • Overall mood 28/10/2015 @danielbryantuk
- 28. Optimism: Think Professionally • Define (and share) clear goals • Build, measure, learn… • Remove uncertainty early (bit.ly/1mAb6o4) – “Patterns of Effective Delivery” by Dan North • Software is inherently collaborative… 28/10/2015 @danielbryantuk
- 29. The Three Amigos 28/10/2015 @danielbryantuk www.slideshare.net/chassa/2012-1130alm-dayviennaslideshare
- 30. Pair Mob Programming 28/10/2015 @danielbryantuk benjiweber.co.uk/blog/2014/11/30/the-unruly-mob/ probablyfine.co.uk/papers/mob-programming.pdf www.infoq.com/interviews/zuill-mob-programming
- 31. DevOps: Share the Pain... 28/10/2015 @danielbryantuk
- 32. “Dev-on-call” An occasional spike to the head is a good thing... ...metaphorically speaking • You build it, you run it – Shared responsibility – Communication 28/10/2015 @danielbryantuk
- 33. Remove (or Limit) Uncertainty 28/10/2015 @danielbryantuk
- 34. Check the HiPPO 28/10/2015 @danielbryantuk bit.ly/1xseeXM
- 35. Planning Fallacy “A phenomenon in which predictions about how much time will be needed to complete a future task display an optimistic bias. ” Was your last project completed on time? …and on budget? 28/10/2015 @danielbryantuk
- 36. IT Track Record… • Sainsbury’s Supply Chain Management System – $526m bit.ly/160SnAj • NHS patient record system – £10bn bit.ly/XBzFuV • HealthCare.gov – onforb.es/1k7egyb 28/10/2015 @danielbryantuk
- 37. Most Common Factors for Failure • Unrealistic or unarticulated project goals • Inaccurate estimates of needed resources • Badly defined system requirements • Poor reporting of the project's status • Unmanaged risks • Poor communication among customers, developers, and users • Use of immature technology • Inability to handle the project's complexity • Sloppy development practices • Poor project management • Stakeholder politics • Commercial pressures Source spectrum.ieee.org/computing/software/why-software-fails 28/10/2015 @danielbryantuk
- 38. Most Common Factors for Failure • Unrealistic or unarticulated project goals • Inaccurate estimates of needed resources • Badly defined system requirements • Poor reporting of the project's status • Unmanaged risks • Poor communication among customers, developers, and users • Use of immature technology • Inability to handle the project's complexity • Sloppy development practices • Poor project management • Stakeholder politics • Commercial pressures Source spectrum.ieee.org/computing/software/why-software-fails 28/10/2015 @danielbryantuk
- 39. At the Start: Feedback & Federation • Plan, do, check (showcase), act • Improve estimation (or #noestimates?) • Divide and conquer – SOA, microservices, modules… (systems thinking) – Squads, guilds, chapters 28/10/2015 @danielbryantuk
- 41. A Side Note Even if your upfront planning is good… 28/10/2015 @danielbryantuk
- 42. Things Inevitably Go Wrong… 28/10/2015 @danielbryantuk
- 43. At the End: It’s All About People 28/10/2015 @danielbryantuk www.infoq.com/news/2015/06/too-big-to-fail
- 44. From Macro to Micro… 28/10/2015 @danielbryantuk
- 45. Accept Unknown Unknowns… 28/10/2015 @danielbryantuk dilbert.com/strips/comic/1995-11-10/
- 46. Sunk Cost Fallacy “Any past cost that has already been paid and cannot be recovered should not figure into the decision making process. ” When did you last remove a framework? …or a library? 28/10/2015 @danielbryantuk
- 47. Why Are We Reluctant? • We don’t like being wrong… • Existing effort appears wasted – Endowment effect • Loss aversion – Twice as powerful, psychologically, as gains? 28/10/2015 @danielbryantuk
- 48. Try Not to ‘Sink Costs’ 28/10/2015 @danielbryantuk
- 49. Retrospect Regularly • Did we make the right choice? • When was the ‘last responsible moment’? • What can we learn? • How can we get better? 28/10/2015 @danielbryantuk
- 50. Anchoring Bias “Common tendency to rely too heavily on the first piece of information offered when making decisions. ” How does your manager ask for estimates? …is it an unbiased question? 28/10/2015 @danielbryantuk
- 52. Anchoring: Learn to “Upwardly Manage” • Learn to say no… – Provide explanations and alternatives • Make sure goals/user stories are well-defined – Collaboration – Feedback • Apply PERT estimations (bit.ly/1mGzuoe) 28/10/2015 @danielbryantuk
- 53. A Little More #NoEstimates 28/10/2015 @danielbryantuk ronjeffries.com/xprog/articles/the-noestimates-movement/
- 54. Read Your Way to Tech Leadership (?) 28/10/2015 @danielbryantuk
- 55. Ok, lets wrap this up… 28/10/2015 @danielbryantuk
- 56. System 1 is Awesome! • It saves us from many dangers • Very valuable in many situations – ‘gut feel’, instincts, intuition – Expertise plays a role – Can be used for good • But, I see too much System 1 in IT… 28/10/2015 @danielbryantuk
- 57. We All Make Mistakes… 28/10/2015 @danielbryantuk
- 58. Have a Little Empathy… 28/10/2015 @danielbryantuk
- 59. “You will be the same person in five years as you are today except for the people you meet and the books you read.” - Charlie “Tremendous” Jones (bit.ly/1LAdQkv) 28/10/2015 @danielbryantuk
- 60. Awesome Conferences and Books 28/10/2015 @danielbryantuk
- 62. Summary • Apply process and models (as appropriate) – Listen to system 1, but engage system 2… • Collaborate more (and better) • Learn, do, retrospect, (teach,) repeat - “Think” more deliberately - 28/10/2015 @danielbryantuk
- 63. Thanks for Listening! Comments and feedback are welcomed… daniel.bryant@opencredo.com @danielbryantuk www.infoq.com/author/Daniel-Bryant www.parleys.com/author/daniel-bryant www.muservicesweekly.com 28/10/2015 @danielbryantuk
Editor's Notes
- Many explanations for the optimistic bias come from the goals that people want and outcomes they wish to see.[1] People tend to view their risks as less than others because they believe that this is what other people want to see. These explanations include self-enhancement, self-presentation, and perceived control. Self-enhancement suggests that optimistic predictions are satisfying and that it feels good to think that positive events will happen. People tend to focus on finding information that supports what they want to see happen, rather than what will happen to them Representative heuristic: individuals tend to think in stereotypical categories rather than about their actual targets when making comparisons. The estimates of likelihood associated with the optimistic bias are based on how closely an event matches a person's overall idea of the specific event Individuals know a lot more about themselves than they do about others.[1] Because information about others is less available, information about the self versus others leads people to make specific conclusions about their own risk, but results in them having a harder time making conclusions about the risks of others. This leads to differences in judgments and conclusions about self-risks compared to the risks of others, leading to larger gaps in the optimistic bias
- In behavioral economics, the endowment effect (also known as divestiture aversion) is the hypothesis that people ascribe more value to things merely because they own them (1990 where participants were given a mug and then offered the chance to sell it or trade it for an equally priced alternative good (pens). Kahneman et al. (1990)[2] found that the amount participants required as compensation for the mug once their ownership of the mug had been established ("willingness to accept") was approximately twice as high as the amount they were willing to pay to acquire the mug ("willingness to pay") Loss aversion implies that one who loses $100 will lose more satisfaction than another person will gain satisfaction from a $100 windfall.
- delay commitment until the last responsible moment, that is, the moment at which failing to make a decision eliminates an important alternative. If commitments are delayed beyond the last responsible moment, then decisions are made by default, which is generally not a good approach to making decisions. The key is to make decisions as late as you can responsibly wait because that is the point at which you have the most information on which to base the decision.
- Program Evaluation and Review Technique Three-point estimation technique