Esteem and Estimates (Ti Stimo Fratello)

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Esteem and Estimates (Ti Stimo Fratello)

  1. 1. ESTEEM AND ESTIMATIONGaetano MazzantiAgile42Gama-Tech@mgaewsj
  2. 2. Rumeli hisarı
  3. 3. estimates are not “the” problem the problem is inhow we use estimates
  4. 4. why do we estimate?
  5. 5. how do we estimate?
  6. 6. where are you? The Marshall Model of Organizational Evolution
  7. 7. classicdysfunctions in estimates
  8. 8. padding (bottom-up)imposed deadlines/unrealistic goals(top-down)planning fallacy (overoptimism)fractional task time (multitasking)precise values instead of confidenceintervalsno specific risk estimation (knownunknowns, unknown unknowns) itm ent = c omm mat e = e sti
  9. 9. estiqaatsi! (WTF)“we estimate theproject will take 18726.35 hours”
  10. 10. unrealistic targets that’simpossible! that’s why I chose you :-/
  11. 11. fractional task time Task A essiamonoi (50%) Task B essiamonoi (30%) Task C essiamonoi (20%) dthe myth of full capacity
  12. 12. we live in systemsprojects “good”on target estimates padding
  13. 13. being on target !=delivering value
  14. 14. being “good” at estimating !=being good at delivering value
  15. 15. we live insystems... fear stress turnover + R - imposed targets failed or quality challenged + projects* *68% according to Chaos Report 2009
  16. 16. Critical Path Critical PainCritical Chain
  17. 17. traditional planning: single loop “learning” uncertaintyestimation discovery impediments delays plan poor quality over budget more detailed planning
  18. 18. Sisyphusan eternity of useless efforts and unending frustration
  19. 19. judgement and decision making under uncertainty+ other limitations of our mind
  20. 20. the planning fallacyhumans systematically underestimate howlong it will take to do a taskthey are over confident in their ownestimatessaying “estimate better” or “rememberhow long previous tasks took” won’t workdeadlines are more significant indetermining when work will bedone than many of us realize,or would like to admit
  21. 21. overconfidenceclinicians in a study werecompletely certain of thediagnosis antemortem: they werewrong 40% of the timeappearing unsure is considered aweaknessthe admission that one is simplyguessing is unacceptable
  22. 22. estimating others and the pastpeople underestimate their ownbut not others completion timespeople focus on plan-basedscenarios rather than relevantpast experience when predictingpeople undervalue past experience(“this time is different”)
  23. 23. retrospective estimationthe fallacy holds also lookingback to the past:reported time is typically lessthan the actual time
  24. 24. we are good atcomparative estimating
  25. 25. mmm not too good
  26. 26. illusions wecannot resist
  27. 27. anchoringis the height of the tallestredwood more or less than 250 meters? vs what is the height of the tallest redwood?
  28. 28. framing effectodds of survival one month after surgery are 90% vs mortality within one month of surgery is 10% vs mortality within one month of surgery is 1 person out of 10
  29. 29. loss aversionlosses cause much more pain thangainswe don’t close a project when weshould for a small hope of avoidinga loss (not achieving a goal)agreement is difficult to reach(i.e. to renegotiate a contract:your gain is my loss)
  30. 30. affect heuristic “he likes the project so muchthat he thinks costs are low and benefits high”
  31. 31. posture affects estimates (!)when leaning to theleft we produce smallerestimates :-/ Erasmus University research http://medicalxpress.com/news/2011-11-physically-affects-decision-making.html
  32. 32. need for causalitywe attribute causality to events in thepast when in fact no cause-effectrelationship exists (RetrospectiveCoherence)to estimate we need to assume thatcausality existsin a complex environment, this assumptionis not valid
  33. 33. we can’t stand uncertaintywe always look for causalexplanationseven when events are due just tochancewe favor certainty over doubt
  34. 34. welcome touncertainty
  35. 35. being uncertain != I don’t know
  36. 36. uncertain !=unpredictable
  37. 37. approximately right vs perfectly wrong
  38. 38. we need (some) predictability forportfolio management, budgeting,release planning, etc.
  39. 39. Agile to the rescue?
  40. 40. estimates& the Manifesto processes and toolsindividuals and interactions comprehensive doc entworking software omm itm e ! = c sti mat e contract negotiationcustomer collaboration following a planresponding to change
  41. 41. Agile to the rescue?small tasks (stories) comparative sizing short time-scale fast feedback
  42. 42. “estimating and planningcan (and should) belightweight.you should stop whenfurther planning is notlikely to lead to improveddecisions worth the extraeffort” Mike Cohn
  43. 43. when starting a projectwe simply want a rough idea of size and an understanding of (un)certainty
  44. 44. do a pre-mortem!
  45. 45. Agile has ritualized estimationactivitiesthere is some goodand some bad in this
  46. 46. planning pokerrocks.. really? .conversation rocksrelative estimation treated as ranges...kind of rocks initially these should bestory points & velocitymay become dysfunctional
  47. 47. biggest value of theestimation process is conversation (exploring, discovering) instead of sizingwe should call it just understanding
  48. 48. velocity & variability33#30#27# average#velocity# UCL#24# LCL# velocity#21#18#15# 1*Feb# 1*Mar# 1*Apr# 1*May# 1*Jun# 1*Jul# 1*Aug# 1*Sep#
  49. 49. velocity related smellsall sprints end with a100% story completion rateall sprints have thesame velocityvelocity is increasingregularly at each sprint
  50. 50. estimation == waste? “time spent estimating is time not spent doing value adding stuff” mmm, yes and no...
  51. 51. fromlearning to estimates
  52. 52. an alternative to Story Points? just count thenumber of Stories
  53. 53. we can use historical data (story count) to predictscope delivery on a given date and to estimate cost (ROI) of story delivery
  54. 54. counting & measuringinstead of estimating
  55. 55. measure cycle (lead) timebacklog to do in progress test done 1 2 2 F C A E G D B H I J cycle time lead time
  56. 56. selection & pullbacklog to do in progress test done 1 2 2 F C B A G E D  H ? I J
  57. 57. flow, pull & commitmentcommitment = starting somethingcommit only when you pullless WIP = less commitment =more options
  58. 58. “ok, but I need to sign a contract!” contract: a piece of paper todefine consequences when theresno trust and something goes wronguse data from the pastacknowledge your ignoranceconstantly monitor progresscross your fingers(optional) be transparent withyour client
  59. 59. esteem and respect
  60. 60. respect estimates !=commitments
  61. 61. imposed deadlinestop-down deadlines force people tocompromise, motivation goes downno control over the scope or schedule, onlyone variable left: quality.if bonus is tied to delivering on-time theonly way to achieve that goal is tocut corners C T! S PE RE NO
  62. 62. rebooting teamsexecs need to understand/respectwhat makes a system work and whatmakes it (un)predictableyou can’t reboot teams, project toproject, putting together differentpeople each time and expect to havepredictable outcomes C T! S PE RE NO
  63. 63. pretending decisions are shared“shared” decisions (estimates) are often extorted C T! S PE RE NO
  64. 64. bullying“when will it be done?” == I dont trust you C T! S PE RE NO
  65. 65. the right questions RES it will PEC T take 3 days why not 2? why not 4?
  66. 66. safe to fail culture RES PEC T mistakes are fine! (within boundaries) you need to learn from them
  67. 67. limit WIP RES PECwhen you limit WIP you are Thelping the team:finishing stuffmaking fewer commitmentsgiving them options
  68. 68. in closing1.traditional approaches fail(they ignore uncertainty and complexity)2.our mind will anyway deceive us3.Agile can help but beware offalling into the same trap as 1.4.respect is key
  69. 69. estimates cant be wrong theyre estimates! "accurate estimates" or"improving estimates" => just a waste of time
  70. 70. estimates are not “the” problem the problem is inhow we use estimates
  71. 71. looking at our models andassuming they might be wrong is the heart of respect Liz Keogh
  72. 72. Gaetano Mazzanti @mgaewsjgaetano.mazzanti@gmail.com

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