The dung-beetle's tale: systems-thinking, complexity and the real-world

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Slidedeck for Integrated-EA conference, February 2014.
(It's a conference on enterprise-architecture in the Defence context, hence a somewhat military flavour and various military in-jokes.)

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The dung-beetle's tale: systems-thinking, complexity and the real-world

  1. 1. the futures of business The dung-beetle‟s tale systems-thinking, complexity and the real world Tom Graves, Tetradian Consulting Integrated EA Conference, London, March 2014
  2. 2. A question… Why is it that the simple don‟t stay simple?
  3. 3. Or, more to the point… What can we do about it?
  4. 4. Back in the old days, it had all seemed so simple… we‟d join the armed-forces for the comradeship the glamour the glory…
  5. 5. pride and prestige… CC-BY-NC-ND jhardy1 via Flickr
  6. 6. high expectations… CC-BY-NC-SA drakegoodman via Flickr
  7. 7. but then the muddy reality… CC-BY-NC-SA drakegoodman via Flickr
  8. 8. and kit that didn‟t work so good… CC-BY-NC-SA drakegoodman via Flickr
  9. 9. Move forward a century… We‟d join the armed-forces for the comradeship the glamour the glory…
  10. 10. the pride and prestige… CC-BY-NC-ND 762_photo via Flickr
  11. 11. high expectations… CC-BY-NC-ND panationalguard via Flickr
  12. 12. but the grimy reality… CC-BY-NC simonlongworth via Flickr
  13. 13. kit that works in worrying ways… CC-BY abaporu via Flickr
  14. 14. and mud… CC-BY-NC simonlongworth via Flickr
  15. 15. more mud… CC-BY-NC VAGuardPAO via Flickr
  16. 16. and yet more mud… CC-BY 1-25-sbct via Flickr
  17. 17. What happened? (or didn‟t happen, maybe?)
  18. 18. We want it to be simple… …yet it always turns out to be complex – horribly complex…
  19. 19. So what can we do about it?
  20. 20. How can we control it?
  21. 21. It seems that every attempt to control the complexity makes it more complex.
  22. 22. It may seem like every attempt to control the complexity makes it more complex.
  23. 23. Beyond a certain point, it may seem like every attempt to control the complexity makes it more complex.
  24. 24. Beyond a not-so-certain point, it may seem like every attempt to control the complexity makes it more complex.
  25. 25. Subject to certain provisos, beyond a not-so-certain point it may seem like every attempt to control the complexity makes it more complex.
  26. 26. Subject to certain provisos and special-cases, beyond a not-so-certain point it may seem like every attempt to control the complexity makes it more complex.
  27. 27. Sometimes, subject to certain provisos and special-cases, beyond a not-so-certain point it may seem like every attempt to control the complexity makes it more complex.
  28. 28. Sometimes, subject to certain provisos and special-cases, and in unpredictable ways, beyond a not-so-certain point it may seem like every attempt to control the complexity makes it more complex.
  29. 29. WAAAAHHH!!!
  30. 30. Ahem…
  31. 31. Let‟s, uh, start again… with a pattern, a map, and a guide…
  32. 32. It‟s a very pretty pattern in various different forms…
  33. 33. fractals… CC-BY-NC-SA felix42 Flickr
  34. 34. fractals… CC-BY-NC-ND nakluza via Flickr
  35. 35. fractals… CC-BY fdecomite via Flickr
  36. 36. (it‟s called fractal recursion, but we‟ll talk about that later)
  37. 37. The map likewise has a nice pretty background…
  38. 38. (pretty background)
  39. 39. with two axis-lines that don‟t do very much…
  40. 40. (two axis-lines) before NOW! certain uncertain
  41. 41. two boundary-conditions that move around a bit…
  42. 42. (two boundary-conditions) before NOW! certain uncertain
  43. 43. and four edge-conditions (sort-of) (sometimes) (it‟s kinda complex…)
  44. 44. (four edge-transitions) before edge of uncertainty edge of action edge of innovation edge of panic NOW! certain uncertain
  45. 45. (we‟ll talk about all that later, too)
  46. 46. And our guide… (who isn‟t pretty…) …is a scarab.
  47. 47. not this kind of Scarab… (sorry…) source not known
  48. 48. not this kind of Scarab… (not-quite-so-sorry…?) CC-BY-NDhesterjenna via Flickr
  49. 49. it‟s this Scarab… (genus Scarabaeidae…) (aka dung-beetle…) CC-BY-NC-ND cottonm via Flickr
  50. 50. optional camouflage lightweight armour all-terrain transmission autonomous missioncontrol sensor pack (you could think of it in military terms, if you like…) CC-BY-NC-ND cottonm via Flickr
  51. 51. all shapes and sizes… CC-BY-NC-ND scotproof via Flickr
  52. 52. all shapes and sizes… (engineers regiment heavy lift unit?) CC-BY jkirkhart35 via Flickr
  53. 53. all shapes and sizes (American dung-beetle) (bigger and shinier than most) (of course?) CC-BY-NC baggis ores2k via Flickr
  54. 54. For most of the time, life is kinda simple for our tiny scarab…
  55. 55. By the way… before we‟d typically place „Simple’ in this region of our map (we‟ll see why, soon) NOW! certain uncertain
  56. 56. it finds a nice pile of dung… CC-BY-NC-SA isaachsieh via Flickr
  57. 57. makes some of it into a ball… CC-BY-NC-ND lowfatbrains via Flickr
  58. 58. then rolls it home… CC-BY-NC-ND wisse via Flickr
  59. 59. and comes back for more… CC-BY-NC-SA marshall-mayer via Flickr
  60. 60. (maybe meet up with a few of the guys down at the bar…?) CC-BY Happy Days Photo and Art via Flickr
  61. 61. And then does it all again… and again… and again… and again… CC-BY-NC-SA isaachsieh via Flickr
  62. 62. Simple. “Follow the work-instructions”… that kind of thing, really…
  63. 63. (it doesn‟t need to think about it… it just does it… …which is why we say this is „Simple‟)
  64. 64. (though some of that „Simple‟ is pretty clever, actually…)
  65. 65. Overall, it‟s another pattern: • sense • make-sense • decide • act (rinse-and-repeat, indefinitely, at every required level) (yep – another kind of fractal-recursion…)
  66. 66. When its Simple doesn‟t work for some level or context… our beetle has to stop and think for a bit. It‟s kinda Complicated… (for a beetle, anyway…)
  67. 67. On the map… before (this axis represents „time available for sensemaking and decision-making‟ before we must take action) „Simple’ NOW! certain uncertain
  68. 68. On the map… before we‟d place „Complicated’ in this region of our map (because it‟s distant in time from the „NOW!‟ of action) (this axis represents „time available for sensemaking and decision-making‟ before we must take action) NOW! certain uncertain
  69. 69. On the map… before „Complicated’ (this axis represents „time available for sensemaking and decision-making‟ before we must take action) (for „Simple’, time-tostop-and-think is a luxury we don‟t have…) NOW! certain uncertain
  70. 70. Our beetle formulates a plan… (See beetle. See beetle stop and think…) CC-BY-NC-ND scotproof via Flickr
  71. 71. Plan versus action before „Complicated’ PLAN edge of action ACTION „Simple’ NOW! certain uncertain
  72. 72. “No plan survives first contact with the enemy”
  73. 73. Plan and action before „Complicated’ rules (we need feedback loops between plan and action) PLAN realities ACTION „Simple’ NOW! certain uncertain
  74. 74. Theory and practice before „Complicated’ THEORY edge of action PRACTICE „Simple’ NOW! certain uncertain
  75. 75. Theory and practice before THEORY What we plan to do, in the expected conditions What we actually do, in the actual conditions PRACTICE NOW! certain uncertain
  76. 76. Theory and practice before “In THEORY, there‟s no difference between theory and practice… …in PRACTICE, there is!” NOW! certain uncertain
  77. 77. Where‟s the complexity? Not much on the surface, it might seem… (unless IT complicates things?)
  78. 78. (before IT…) CC-BY-NC arnolouise via Flickr
  79. 79. (after IT?) CC-BY vintagedept via Flickr
  80. 80. But there‟s a catch… (‟cos there‟s always a catch…) …which is where complexity does come into the picture.
  81. 81. It‟s about dependencies…
  82. 82. Our beetle depends on dung. (and the right kind of dung, at that…) CC-BY-NC-SA isaachsieh via Flickr
  83. 83. It depends on the right animal… CC-BY alois_staudacher via Flickr
  84. 84. to make that dung. CC-BY-NC-SA isaachsieh via Flickr
  85. 85. It depends on the right feed… CC-BY-NC-ND paperpariah via Flickr
  86. 86. for the right animal… CC-BY alois_staudacher via Flickr
  87. 87. to make that dung. CC-BY-NC-SA isaachsieh via Flickr
  88. 88. And it depends on the right ecosystem… CC-BY-NC-SA j33pman via Flickr
  89. 89. for the right feed… CC-BY-NC-ND paperpariah via Flickr
  90. 90. for the right animal… CC-BY alois_staudacher via Flickr
  91. 91. to make that dung. CC-BY-NC-SA isaachsieh via Flickr
  92. 92. But if these guys decide to diversify… CC-BY-NC cannykev via Flickr
  93. 93. into goatburgers… CC-BY ramnagant via Flickr
  94. 94. it could be bye-bye to the ecosystem… CC-BY wonker via Flickr
  95. 95. and all too soon, maybe, bye-bye to anything else… CC-BY-NC-ND oxfam via Flickr
  96. 96. Which is bad news for our dung-beetle, because… CC-BY-NC-SA marshall-mayer via Flickr
  97. 97. the right kind of animal… CC-BY alois_staudacher via Flickr
  98. 98. …makes the right kind of dung CC-BY-NC-SA isaachsieh via Flickr
  99. 99. but the wrong kind of animal… CC-BY ramnagant via Flickr
  100. 100. …makes the wrong kind of dung. CC-BY robertnyman via Flickr
  101. 101. No right dung anywhere in range equals no dung-beetle. Oops… CC-BY-NC-SA marshall-mayer via Flickr
  102. 102. What can our poor dung-beetle do?!?
  103. 103. How can it take control of all of this?!?
  104. 104. it‟s not this kind of Scarab… source not known
  105. 105. it‟s only this kind of scarab… CC-BY-NC-ND djbones via Flickr
  106. 106. so it can‟t demolish McDonalds… (sorry…) CC-BY-NC-SA raster via Flickr
  107. 107. If it were human, it might try to plot out all of the variables and interdependencies in a systems-map…
  108. 108. systems-relationship map
  109. 109. …which, yes, does work… (sort-of…) (sometimes…) (it‟s kinda complicated…)
  110. 110. But even a dung-beetle would soon discover there are very real limits to the usefulness of that type of Complicated.
  111. 111. which leaves our poor beetle kinda lost in the desert… CC-BY-NC-ND firesika via Flickr
  112. 112. Where‟s a good map when you need one?!?
  113. 113. How‟s about this map? before NOW! certain uncertain
  114. 114. We‟ve noted its vertical-axis… before (represents „time available for sensemaking and decision-making‟ before we must take action) NOW! certain uncertain
  115. 115. …let‟s look at its horizontal-axis before (represents an arbitrary spectrum from „absolute-sameness‟ [left-side] to „absolute-difference‟ [right-side]) NOW! certain uncertain
  116. 116. A bunch of similar scales… sameness uniqueness high-probability standardised low-probability customised high-dependability reusability low rate of change unique low-dependability bespoke high rate of change
  117. 117. What, no numbers? before by intent, there are no numbers on either axis… it‟s to map criteria for tactics – relationships, not „absolutes‟ NOW! certain uncertain
  118. 118. We don‟t need no steenkin‟ numbers! (but we do need options for varying tactics…) CC-BY-NC-SA isaachsieh via Flickr
  119. 119. The Simple (or Complicated) would prefer to try to „take control‟ of everything… but…
  120. 120. …„control‟ won‟t work on everything…
  121. 121. Take control! Impose order! “Insanity is doing the same thing and expecting different results” (Albert Einstein) ORDER (IT-type rules do work here) certain uncertain
  122. 122. Order and unorder “Insanity is doing the same thing and expecting different results” edge of uncertainty “Insanity is doing the same thing and expecting the same results” (Albert Einstein) (not Albert Einstein) ORDER UNORDER (IT-type rules do work here) (IT-type rules don‟t work here) certain uncertain
  123. 123. Same and different A quest for certainty: analysis, algorithms, identicality, efficiency, business-rule engines, executable models, Six Sigma... An acceptance of uncertainty: experiment, patterns, probabilities, „designthinking‟, unstructured process... SAMENESS UNIQUENESS (IT-systems do work well here) (IT-systems don‟t work well here) certain uncertain
  124. 124. Why skills are needed… What is always going to be uncertain or unique? What will always be „messy’? („Messy‟ – politics, management, wickedproblems, „should‟ vs „is‟, etc.) Wherever these occur, we‟re going to need human skill…
  125. 125. Certain and uncertain before questions „Complicated’ (ANALYSE) edge of uncertainty „Ambiguous’ (EXPERIMENT) answers (we need feedback loops between analysis and experimentation) NOW! certain uncertain
  126. 126. Complexity includes themes such as wicked-problems
  127. 127. Tame- and wicked-problems • definable formulation • static „solution‟ • clear end-point • solution is true/false • each essentially same • finite dependency • no defined formulation • dynamic „re-solution‟ • no clear end-point • solution is good/bad • essentially unique • infinite dependency ‘TAME’ ‘WICKED’ („control‟ can work here) („control‟ can‟t work here) certain uncertain
  128. 128. Terms such as „complexity science‟ may unintentionally mislead: physical-sciences apply mostly in the „tame‟-space… most „complexity-science‟ applies in the „wicked‟-space.
  129. 129. Use the right models for each domain... don’t mix them up!
  130. 130. Complexity also includes unintended-consequences (a classic driver for wicked-problems…)
  131. 131. INTENDED CONSEQUENCE CC-BY soldiersmediacenter via Flickr “engage hearts and minds…”
  132. 132. UNINTENDED CONSEQUENCE CC-BY soldiersmediacenter via Flickr “how to get kids killed…”
  133. 133. Think VUCA: • Volatile • Uncertain • Complex • Ambiguous
  134. 134. Where to map complexity? „Complicated’ „COMPLEX’ some people might place Complexity in just one domain „Simple’ „Chaotic’
  135. 135. Where to map complexity? before „Complicated’ „Ambiguous’ yet in reality, Complexity is everywhere! „Simple’ „Not-known’ NOW! certain uncertain
  136. 136. Many meanings of ‘Complexity’… (and of „Chaos‟ or „Chaotic‟, too) – we need to embrace them all (not make the Simplistic assertion that only one kind is „the real complexity‟…)
  137. 137. Complexity: they‟re both right… Roger Sessions: John Seddon: “eliminate complexity!” “embrace complexity!” (Simple Iterative Partitions; Snowman) (Vanguard Method; „failure-demand‟) SAMENESS UNIQUENESS (most IT-type models do work well for this) (most IT-type models don‟t work well for this) certain uncertain
  138. 138. They‟re both right, because of fractal recursion… - a point we can illustrate via Mandelbrot…
  139. 139. not this kind of Mandel Brot… CC-BY-NC squeakychu via Flickr
  140. 140. this kind of Mandelbrot… CC-BY-NC-SA Michael-Maclean via Flickr
  141. 141. fern CC-BY-NC-SA gjshepherd via Flickr
  142. 142. fractal recursion… CC-BY-NC somersetbob via Flickr
  143. 143. self-similarity at every scale… CC-BY-NC somersetbob via Flickr
  144. 144. self-similarity at every scale… CC-BY-NC catdancing via Flickr
  145. 145. always similar, yet always different… CC-BY usfwsnortheast via Flickr
  146. 146. every point expresses the pattern… every point describes every other point… CC-BY-NC-SA sharman via Flickr
  147. 147. Fractal recursion means that every point includes its own: • Simple • Complicated • Ambiguous („Complex‟) • Not-known („Chaotic‟)
  148. 148. NOTE: „self-similar‟ is not the same as „the same‟… „high-probability‟ does not mean „will always happen‟… „low-probability‟ does not mean „will never happen‟…
  149. 149. Use the right tactics for each domain... don’t mix them up!
  150. 150. But the beetle says… “it‟s too easy to hide in theory here…” CC-BY-NC-ND scotproof via Flickr
  151. 151. At some point we need to stop theorising (or hypothesising – to be pedantic) and get back in touch with the real-world, in real-time… - down into the „Not-known‟…
  152. 152. or, colloquially… CC-BY-NC-SA Tom Graves
  153. 153. Back to the real-world again… before „Complicated’ (exploration, improvisation and invention all happen here) „Simple’ „Ambiguous’ edge of innovation „Not-known’ NOW! certain uncertain
  154. 154. Here, even a dung-beetle… CC-BY-NC-ND kishlc via Flickr
  155. 155. can learn how to fly! CC-BY-NC-ND kishlc via Flickr
  156. 156. All invention – everything ‘new’ – at first appears here, in the Not-known…
  157. 157. invention… CC-BY-NC-ND nuwandalice via Flickr
  158. 158. invention… CC-BY-NC-ND Science Museum via Flickr
  159. 159. invention by Emett… BY David Sweeney via YouTube
  160. 160. invention by Emett… BY David Sweeney via YouTube
  161. 161. invention… CC-BY-NC-ND European Patent Office via Flickr
  162. 162. invention… CC-BY-SA thebakkenmuseum via Flickr
  163. 163. inventions that haven‟t happened yet…? CC-BY OpenPlaques via Flickr
  164. 164. Idea and hypothesis before „Ambiguous’ (EXPERIMENT) hypothesis principles edge of innovation news (we need feedback loops between idea and hypothesis) ‘the new’ „Not-known’ (EXPLORE) NOW! certain uncertain
  165. 165. Where do new ideas come from? “Accept the burden of uncertainty… be comfortable with being uncomfortable.” CC-BY-NC-SA grrrl via Flickr
  166. 166. Where do new ideas come from? “I can tell you things all day long, but you have to put your ass in the seat to really learn.” CC-BY-NC USArmyEurope via Flickr
  167. 167. We also come at this from the other direction - over from the Simple, in real-time action, across the edge of panic…
  168. 168. Across the edge of panic before „Simple’ (ENACT) edge of panic „Not-known’ (EXPLORE) NOW! certain uncertain
  169. 169. CC-BY-SA lumachrome via Flickr The Rules. (Everything You Need To Know For Your Job)
  170. 170. routine… © Orange County Flight Center via atulgawande.com
  171. 171. HUH? the real-world don‟t match the rules??
  172. 172. WAAAAHHH!!!
  173. 173. …which is why there‟s the other side to that checklist… - to keep the panic at bay…
  174. 174. emergency… © Orange County Flight Center via atulgawande.com
  175. 175. Key items that users may forget in panic… FLY THE AIRPLANE © Orange County Flight Center via atulgawande.com
  176. 176. The other learning-loop… before (we need real-time feedback loops between certainty and uncertainty) fears „Simple’ (ACTION) edge of panic „Not-known’ (EXPLORE) options NOW! certain uncertain
  177. 177. That feedback-loop across the edge of panic is where, and how, on-the-spot answers arise out there in the field…
  178. 178. strange yet useful innovations… CC-BY-NC simonlongworth via Flickr
  179. 179. pragmatic answers to in-the-field needs… CC-BY-NC simonlongworth via Flickr
  180. 180. refusing to face the uncertainty is what strands us here… CC-BY-SA afiler via Flickr
  181. 181. It‟s almost time to wrap up this tale…
  182. 182. Making sense of complexity Use context-maps such as SCAN to identify what may or must change what is or is not certain how these vary over time and what to do with each
  183. 183. Linking it all together before questions „Complicated’ edge of uncertainty (ANALYSE) „Ambiguous’ (EXPERIMENT) answers rules edge of action „Simple’ (ENACT) realitie s principles edge of innovation news fears edge of panic „Not-known’ (EXPLORE) options NOW! certain uncertain
  184. 184. Common themes in each domain before order unorder COMPLICATED AMBIGUOUS (analyse) (experiment) reciprocation resonance (algorithms) recursion reflexion (patterns, guidelines) SIMPLE plan actual NOT-KNOWN (enact) (explore) regulation rotation (rules) reframe rich-randomness (principles) NOW! certain uncertain
  185. 185. Remember that it‟s recursive before C C C NOW! S certain A S N S A A N N uncertain
  186. 186. A surgical example… before patient identity patient condition theatre booking equipment plan verify identity surgery plan surgical-staff availability consumables action-records family behaviour pre-op complications change of emergency theatre-availability action NOW! certain uncertain
  187. 187. A surgical example… before patient identity theatre booking equipment plan we need to be certain about all of these verify identity consumables action-records NOW! certain uncertain
  188. 188. A surgical example… before patient condition we expect (and plan for) uncertainty about these surgery plan surgical-staff availability change of theatre-availability NOW! certain uncertain
  189. 189. A surgical example… before we don‟t expect these to happen, but we need contingency-plans and guiding-principles for all of them family behaviour pre-op complications emergency action NOW! certain uncertain
  190. 190. But to let our brave dung-beetle have the last words… always remember… CC-BY-NC-ND wisse via Flickr
  191. 191. in ancient Egypt… the scarab rolled the sun along its course… CC-BY isawnyu via Flickr
  192. 192. a helpmate and advisor to the gods… CC-BY-NC-SA theheartindifferentkeys via Flickr
  193. 193. and even in the present-day… CC-BY-SA swanksalot via Flickr
  194. 194. dung-beetles have right of way… CC-BY-NC-SA arthur_chapman via Flickr
  195. 195. Something to think about, perhaps? CC-BY-ND-SA ores2k via Flickr
  196. 196. “What’s the Thank you!
  197. 197. Further information: Contact: Tom Graves Company: Tetradian Consulting Email: tom@tetradian.com Twitter: @tetradian ( http://twitter.com/tetradian ) Weblog: http://weblog.tetradian.com Slidedecks: http://www.slideshare.net/tetradian Publications: http://tetradianbooks.com Books: • The enterprise as story: the role of narrative in enterprisearchitecture (2012) • Mapping the enterprise: modelling the enterprise as services with the Enterprise Canvas (2010) • Everyday enterprise-architecture: sensemaking, strategy, structures and solutions (2010) • Doing enterprise-architecture: process and practice in the real enterprise (2009)

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