Published on

How can we better experience our working?

Published in: Technology


  2. 2. Jabe Bloom CTO Creative Technologis t@cyetain
  3. 3. @cyetain #LeanUXNYC jabe.co/leanuxnyc@cyetain
  4. 4. LeanTX IEN CE EX PER m? wd o we Tea Ho king as a ur W or o@cyetain Some rights reserved by tallkev
  5. 5. ma k ma an… All wo es worker a working on a du n wor ll hum ng o u rk mak n… Al l orker er a d rking on wo a dull huma ork makes w n… All work ll wo an… A rk makes w All w orker orking on w a dull huma n wor m orker ll working o r a Work != Working != Worker o kin g on w dull human… ork makes w an… A worke ll ker a orking on w r a dull hum ork makes an… A s wor All w orke orking on w a dull hum um an… m akes w All w er g on wh work Pin n… ing on a dull huma work make man… s work All workin rker worCarll working oHammering on work ma uman UMANS rk kes wo … A Ho ker n u kes a dull h n… A k makes w Carryingorker orking dull h huma n wor ll w rker a working on an… A k makes wo …Bolunded: orke rWireframe ll hum n wor king o u n Al akes wwo work ller a d rking o Thinkingl huma ork m r a dul g on w Precepthon an… ll ium on ake s Artifactswo A worke workin hu man… ork makes Creating … All k er a du orking worUndelsltwndi n g ing on a dull human work makes man… A a es work w work orker ng on ker a dull hu woakimaality an… rt onk um ing on Rr a dull h i m akes w … All work es wor h uman work mak Al l work worke rking rkin g on uman… ork makes All wo wo wocyetain rker a dull h g on w uman… k makes akes wo ll wor kin a dull h on wor orker @ m A sw ing
  6. 6. L ean T X MAD SCIEN TS Gs & TIS R@cyetain CY BO
  7. 7. @cyetain
  8. 8. g-Ran ge Tr uck-DriverLonIt is possibl e to ‘come tone has bee o’ and reali n driving w ze that.. ithout bein g aware DM Armstro@cyetain ng
  9. 9. losophical Zom biesPhi@cyetain
  10. 10. @cyetain
  11. 11. Div ision of La bour The To take an example… the trade of the pin-maOne man draw s out the wire, keranother straig hts it, a third c uts it I have seen a small manufactory... make... forty-eight thousand pins in a day... @cyetain
  12. 12. One man draws out the wire, another straights it, a third cuts itDRAW OUT WIRE STRAIGHTEN CUT POINT GRIND a fourth points it, a fifth grinds it at the top for receiving the head;@cyetain
  13. 13. Taylor GilbretGantt h@cyetain
  14. 14. @cyetain
  15. 15. FL OW Lin es@cyetain
  16. 16. Nothing is particularly hard if you divide it into small jobs.@cyetain
  17. 17. @cyetain
  18. 18. Economies $$$$ ! of Scale PUSH@cyetain
  19. 19. e lineAll we are doing is looking at the tim from the moment the customer gives us an order Order Timeline $$$ reduce by removing non-value-added wastes h n we collect the cas y to the point whe that time line b And we are reducing added wast es ue- removing the non-val @cyetain
  20. 20. the principal objective of the Toyota production systemwas to produce many models in small quantities.@cyetain
  21. 21. a b c d & & & = ab cd &@cyetain
  22. 22. PUSH ! ! ! ! ?@cyetain PULL
  23. 23. SmithDivision of Labor Ford Flow Li nes Ohno Toyo ta P rod uction S ystem@cyetain
  24. 24. A LI ZATION E PH EM ER the principle o f doing ever m time and ener ore with ever gy per each giv less weight, en level of fun ctional perform ance Buckminster Fu ller@cyetain
  25. 25. observable and thus ly physicalprimari ver the activity of the worker equated with control o@cyetain
  26. 26. ig man ary W mary wigman M@cyetain
  27. 27. Ru dolf Laban@cyetain
  28. 28. Labanotation@cyetain
  29. 29. Say this to you rself In your mind (not outloud)@cyetain
  30. 30. Stand up if you said B to yourself (in your mind)@cyetain
  31. 31. Stand up if you said 13 to yourself (in your mind)@cyetain
  32. 32. Kahneman@cyetain
  33. 33. edge work snapsknowl critical linksupervision@cyetain Fred N ickols
  34. 34. WARNING the know in matchi ledge worker ng individu h a as almost to l work meth tal authorit ods to the faces -Gregerman y ks her or she MAD s varying job ta SCIENTIST@cyetain
  35. 35. Flow & Effectiveness Lean SW & Startup Shewart Ladas Ford Ohno Poppendieck Ries1700 1850 1950 2000 Adam Smith Taylor Gantt Gilbreth Efficiency & Productivity @cyetain
  36. 36. Varia bi lity Shewart Ladas Ford Ohno Poppendieck Ries1700 1850 1950 2000 Adam Smith Taylor Gantt Gilbreth@cyetain
  37. 37. ned roles ed work constrai es s-defin rrowly rom proc les and natransition f fined ru tig htly de k framed wor ion, & connection toward relationship- ity, innovat creativ to fast-and-loose cooperation from tight-and-slow collaboration @cyetain Stowe Boyd
  38. 38. @cyetain CONSTRAINTS
  39. 39. onstraints $ C@cyetain
  40. 40. Business Team Technology Market@cyetain
  41. 41. Business Market Team Technology@cyetain
  42. 42. iation rm ed Constraints Based on is inte Market & Customer NeedD Team Minim al Con strain Market ts Mark On et & C ustom er@cyetain
  43. 43. in... The futu re is uncerta ery ertainty is at the v rigogine But this unc ya P an creativity. -Il heart of hum@cyetain UNCERTAINTY
  44. 44. are the I Know WW hat hat Options? I Want@cyetain
  45. 45. A Proc ess Model of Innovation@cyetain
  46. 46. BDUF Big Design Up Front Compone nts tion duc Pro DeliProblem very e ! Queu tion Solu BDOB Big Delivery Out Back@cyetain
  47. 47. L ess Planning GO FASTER@cyetain
  48. 48. n tion Compone nts tio ra p e O en tion G uc od Pr onProblem at i ve ion nt cti at e ele ov S n rim In xpe E @cyetain
  49. 49. to BE How NT EF FI CIE COST@cyetain
  50. 50. Sufficient Design is where Lean meets Craft If you take the time to craft code of little or moderate value to users, youre wasting time & money. Are All Fe atures Created Equal? I dont think so. Joshua Kerievsky@cyetain
  51. 51. s Yo ur Eff orts Focu Optional Active Decision Model Components Text@cyetain
  52. 52. ent to mitm nts as Com strai D e f er Con onal OSSIBLE rthog AS P O L ONG Experimentation@cyetain
  53. 53. Business Team Technology Market@cyetain
  54. 54. Ho w to eE ffective B@cyetain
  55. 55. Active Decision Model Option Generation@cyetain
  56. 56. One Prob lem per ime nts Mul tipl e Ex NOT e u can’t decid s because yo Multipl e Problem@cyetain
  57. 57. Kill 5 0-80% o f your ideas Failing H ere is WAST E@cyetain
  58. 58. Ho w to FAST ER GO@cyetain
  59. 59. Eff iciency Flow how long does deliver a piece it take to of work? eHow l ong did wactually spend ?wor king on it times longer s take 10 to 20 Typical organization they actually ething than to deliver som spent wo rking on it Hakan Forss @cyetain
  60. 60. Flow Efficiency STEP ONE STEP TWO STEP THREE FINISHED between 95-85% of Cycle Time@cyetain
  61. 61. Process Efficiency STEP ONE STEP TWO STEP THREE FINISHED between 5-15% of Cycle Time@cyetain
  63. 63. Bottle Neck THIS THIS THIS at beginning of is a is a is a Process Not Problem Bottle Neck Batch Transfer NonInstantly Available May cause excess capacity Problem Resource Problem@cyetain
  64. 64. W=L/ λ ob is equ al to the average o fi nish a j d by theTime i t takes t the syste m divide umber o f jobs in n process ing rate@cyetain
  65. 65. The Effect of UtilizationQueue Utilization @cyetain
  66. 66. @cyetain
  67. 67. @cyetain
  68. 68. @cyetain
  69. 69. tain ties, n wit h cer ill ill begi ut i f he w m an w ub ts, b s, he If a l end in do ith d oubt h e shal to begin w o nten t rtain ties. be c in ce shal l end cis B acon -Fran@cyetain
  70. 70. Experiment Experiment Experiment@cyetain
  71. 71. Option Experimentation Generation@cyetain
  72. 72. Experiment Experiment Experiment@cyetain
  73. 73. Option Experimentation Generation Experiment Experiment Experiment Experiment Experiment Experiment Experiment Experiment Experiment@cyetain
  74. 74. ke an s li se em ngs th at f thi e... ab ful lo t o on to J ti a w a en time! tt e ay sam o p he t latt al@cyetain
  75. 75. o tion t atten be paid eed to that n items ber of the numincreases an ever i ncreasing able to do gap betw , and wh een what at (s)he p an indiv erceives n idual is c ecessary t ognitivel o do y ncis Heyl ighen @cyetain Fra
  76. 76. E T IC T O R N E N Y B C E M C A N N H E@cyetain
  77. 77. CYBORGS orates exogenous components incorpself-regulatin g control pt it to new environments in order to ada nfred Clynes@cyetain Ma
  78. 78. brains about human at is specialWh ips onsh lati s ple x re aid com ps, and ep & s, pro o de ruct int nst nter cal co Andy Clark to e ogi ility nbiol ab no w ith@cyetain
  79. 79. e most of its ns to make th The brain lear completion ple pattern capacity for sim 4 X 4 = 16, 2 X 7 = 14acting in concert with pen and paper,storing the intermediate results outside the brain e lic resourc nal symbo dy Clark tion to the exter An dovetails its opera @cyetain
  80. 80. eC yborgs FavoritOne of my@cyetain
  81. 81. AC yb org akeYou Can M KA NB AN@cyetain
  82. 82. h Yo ur P rocess Sketc@cyetain
  84. 84. Leave the Dial in One Place too long... bad things happen@cyetain
  85. 85. @cyetain
  86. 86. Jim Benso n Donald Reinertsen Staff of TLC avid And erson D David Snowden@cyetain