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.)

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. A question…
Why is it
that the simple
don‟t stay simple?

3. Or, more to the point…
What can
we do about it?

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. pride and prestige…
CC-BY-NC-ND jhardy1 via Flickr

6. high expectations…
CC-BY-NC-SA drakegoodman via Flickr

7. but then the muddy reality…
CC-BY-NC-SA drakegoodman via Flickr

8. and kit that didn‟t work so good…
CC-BY-NC-SA drakegoodman via Flickr

9. Move forward a century…
We‟d join the armed-forces
for the comradeship
the glamour
the glory…

10. the pride and prestige…
CC-BY-NC-ND 762_photo via Flickr

11. high expectations…
CC-BY-NC-ND panationalguard via Flickr

12. but the
grimy reality…
CC-BY-NC simonlongworth via Flickr

13. kit that
works in
worrying
ways…
CC-BY abaporu via Flickr

14. and mud…
CC-BY-NC simonlongworth via Flickr

15. more mud…
CC-BY-NC VAGuardPAO via Flickr

16. and yet more mud…
CC-BY 1-25-sbct via Flickr

17. What happened?
(or didn‟t happen, maybe?)

18. We want it to be simple…
…yet it always turns out
to be complex
– horribly complex…

19. So what can
we do about it?

20. How can we
control it?

21. It seems that every attempt
to control the complexity
makes it more complex.

22. It may seem like every attempt
to control the complexity
makes it more complex.

23. Beyond a certain point,
it may seem like every attempt
to control the complexity
makes it more complex.

24. Beyond a not-so-certain point,
it may seem like every attempt
to control the complexity
makes it more complex.

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. 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. 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. 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. WAAAAHHH!!!

30. Ahem…

31. Let‟s, uh, start again…
with a pattern,
a map,
and a guide…

32. It‟s a very pretty pattern
in various different forms…

33. fractals…
CC-BY-NC-SA felix42 Flickr

34. fractals…
CC-BY-NC-ND nakluza via Flickr

35. fractals…
CC-BY fdecomite via Flickr

36. (it‟s called fractal recursion,
but we‟ll talk about that later)

37. The map likewise has
a nice pretty background…

38. (pretty background)

39. with two axis-lines
that don‟t do very much…

40. (two axis-lines)
before
NOW!
certain
uncertain

41. two boundary-conditions
that move around a bit…

42. (two boundary-conditions)
before
NOW!
certain
uncertain

43. and four edge-conditions
(sort-of)
(sometimes)
(it‟s kinda complex…)

44. (four edge-transitions)
before
edge of
uncertainty
edge of
action
edge of
innovation
edge of
panic
NOW!
certain
uncertain

45. (we‟ll talk about all that later, too)

46. And our guide…
(who isn‟t pretty…)
…is a scarab.

47. not this kind of Scarab…
(sorry…)
source not known

48. not this kind of Scarab…
(not-quite-so-sorry…?)
CC-BY-NDhesterjenna via Flickr

49. it‟s this Scarab…
(genus Scarabaeidae…)
(aka dung-beetle…)
CC-BY-NC-ND cottonm via Flickr

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. all shapes and sizes…
CC-BY-NC-ND scotproof via Flickr

52. all shapes and sizes…
(engineers regiment heavy lift unit?)
CC-BY jkirkhart35 via Flickr

53. all shapes and sizes
(American dung-beetle)
(bigger and shinier than most)
(of course?)
CC-BY-NC baggis ores2k via Flickr

54. For most of the time,
life is kinda simple
for our tiny scarab…

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. it finds a nice pile of dung…
CC-BY-NC-SA isaachsieh via Flickr

57. makes some of it into a ball…
CC-BY-NC-ND lowfatbrains via Flickr

58. then rolls it home…
CC-BY-NC-ND wisse via Flickr

59. and comes back for more…
CC-BY-NC-SA marshall-mayer via Flickr

60. (maybe meet up with a few of the guys
down at the bar…?)
CC-BY Happy Days Photo and Art via Flickr

61. And then does it all again…
and again…
and again…
and again…
CC-BY-NC-SA isaachsieh via Flickr

62. Simple.
“Follow the work-instructions”…
that kind of thing, really…

63. (it doesn‟t need to think about it…
it just does it…
…which is why we say this is
„Simple‟)

64. (though some
of that „Simple‟
is pretty clever,
actually…)

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. 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. On the map…
before
(this axis represents „time available
for sensemaking and decision-making‟
before we must take action)
„Simple’
NOW!
certain
uncertain

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. 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. Our beetle formulates a plan…
(See beetle. See beetle stop and think…)
CC-BY-NC-ND scotproof via Flickr

71. Plan versus action
before
„Complicated’
PLAN
edge of
action
ACTION
„Simple’
NOW!
certain
uncertain

72. “No plan survives first contact
with the enemy”

73. Plan and action
before
„Complicated’
rules
(we need feedback
loops between plan
and action)
PLAN
realities
ACTION
„Simple’
NOW!
certain
uncertain

74. Theory and practice
before
„Complicated’
THEORY
edge of
action
PRACTICE
„Simple’
NOW!
certain
uncertain

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. Theory and practice
before
“In THEORY,
there‟s no difference
between theory
and practice…
…in PRACTICE,
there is!”
NOW!
certain
uncertain

77. Where‟s the complexity?
Not much on the surface,
it might seem…
(unless IT complicates things?)

78. (before IT…)
CC-BY-NC arnolouise via Flickr

79. (after IT?)
CC-BY vintagedept via Flickr

80. But there‟s a catch…
(‟cos there‟s always a catch…)
…which is where complexity
does come into the picture.

81. It‟s about dependencies…

82. Our beetle depends on dung.
(and the right kind of dung, at that…)
CC-BY-NC-SA isaachsieh via Flickr

83. It depends
on
the right
animal…
CC-BY alois_staudacher via Flickr

84. to make that dung.
CC-BY-NC-SA isaachsieh via Flickr

85. It depends
on the
right feed…
CC-BY-NC-ND paperpariah via Flickr

86. for
the right
animal…
CC-BY alois_staudacher via Flickr

87. to make that dung.
CC-BY-NC-SA isaachsieh via Flickr

88. And it depends on
the right ecosystem…
CC-BY-NC-SA j33pman via Flickr

89. for the
right feed…
CC-BY-NC-ND paperpariah via Flickr

90. for
the right
animal…
CC-BY alois_staudacher via Flickr

91. to make that dung.
CC-BY-NC-SA isaachsieh via Flickr

92. But if these guys
decide to diversify…
CC-BY-NC cannykev via Flickr

93. into goatburgers…
CC-BY ramnagant via Flickr

94. it could be bye-bye
to the ecosystem…
CC-BY wonker via Flickr

95. and all too soon, maybe,
bye-bye to anything else…
CC-BY-NC-ND oxfam via Flickr

96. Which is bad news for
our dung-beetle, because…
CC-BY-NC-SA marshall-mayer via Flickr

97. the right
kind of
animal…
CC-BY alois_staudacher via Flickr

98. …makes the right kind of dung
CC-BY-NC-SA isaachsieh via Flickr

99. but the
wrong kind
of animal…
CC-BY ramnagant via Flickr

100. …makes the wrong kind of dung.
CC-BY robertnyman via Flickr

101. No right dung anywhere in range
equals no dung-beetle.
Oops…
CC-BY-NC-SA marshall-mayer via Flickr

102. What can
our poor dung-beetle
do?!?

103. How can it
take control
of all of this?!?

104. it‟s not this kind of Scarab…
source not known

105. it‟s only this kind of scarab…
CC-BY-NC-ND djbones via Flickr

106. so it can‟t demolish
McDonalds…
(sorry…)
CC-BY-NC-SA raster via Flickr

107. If it were human,
it might try to plot out
all of the variables
and interdependencies
in a systems-map…

108. systems-relationship map

109. …which, yes, does work…
(sort-of…)
(sometimes…)
(it‟s kinda complicated…)

110. But even a dung-beetle
would soon discover
there are very real limits
to the usefulness
of that type of Complicated.

111. which leaves our poor beetle
kinda lost in the desert…
CC-BY-NC-ND firesika via Flickr

112. Where‟s a good map
when you need one?!?

113. How‟s about this map?
before
NOW!
certain
uncertain

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. …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. 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. 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. We don‟t need no steenkin‟
numbers!
(but we do need options for varying tactics…)
CC-BY-NC-SA isaachsieh via Flickr

119. The Simple
(or Complicated)
would prefer to try
to „take control‟
of everything…
but…

120. …„control‟ won‟t work
on everything…

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. 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. 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. 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. 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. Complexity
includes themes such as
wicked-problems

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. 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. Use the right models
for each domain...
don’t mix them up!

130. Complexity
also includes
unintended-consequences
(a classic driver for wicked-problems…)

131. INTENDED CONSEQUENCE
CC-BY soldiersmediacenter via Flickr
“engage hearts and minds…”

132. UNINTENDED CONSEQUENCE
CC-BY soldiersmediacenter via Flickr
“how to get kids killed…”

133. Think VUCA:
• Volatile
• Uncertain
• Complex
• Ambiguous

134. Where to map complexity?
„Complicated’
„COMPLEX’
some people might place
Complexity in just one domain
„Simple’
„Chaotic’

135. Where to map complexity?
before
„Complicated’
„Ambiguous’
yet in reality,
Complexity is everywhere!
„Simple’
„Not-known’
NOW!
certain
uncertain

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. 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. They‟re both right, because
of fractal recursion…
- a point we can illustrate via Mandelbrot…

139. not this kind of Mandel Brot…
CC-BY-NC squeakychu via Flickr

140. this kind of Mandelbrot…
CC-BY-NC-SA Michael-Maclean via Flickr

141. fern
CC-BY-NC-SA gjshepherd via Flickr

142. fractal recursion…
CC-BY-NC somersetbob via Flickr

143. self-similarity at every scale…
CC-BY-NC somersetbob via Flickr

144. self-similarity at every scale…
CC-BY-NC catdancing via Flickr

145. always similar, yet always different…
CC-BY usfwsnortheast via Flickr

146. every point expresses the pattern…
every point describes every other point…
CC-BY-NC-SA sharman via Flickr

147. Fractal recursion means that
every point includes its own:
• Simple
• Complicated
• Ambiguous („Complex‟)
• Not-known („Chaotic‟)

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. Use the right tactics
for each domain...
don’t mix them up!

150. But the beetle says…
“it‟s too easy to hide in theory here…”
CC-BY-NC-ND scotproof via Flickr

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. or, colloquially…
CC-BY-NC-SA Tom Graves

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. Here, even a dung-beetle…
CC-BY-NC-ND kishlc via Flickr

155. can learn how to fly!
CC-BY-NC-ND kishlc via Flickr

156. All invention
– everything ‘new’ –
at first appears here,
in the Not-known…

157. invention…
CC-BY-NC-ND nuwandalice via Flickr

158. invention…
CC-BY-NC-ND Science Museum via Flickr

159. invention by Emett…
BY David Sweeney via YouTube

160. invention by Emett…
BY David Sweeney via YouTube

161. invention…
CC-BY-NC-ND European Patent Office via Flickr

162. invention…
CC-BY-SA thebakkenmuseum via Flickr

163. inventions that haven‟t happened yet…?
CC-BY OpenPlaques via Flickr

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. Where do new
ideas come from?
“Accept the burden
of uncertainty…
be comfortable
with being
uncomfortable.”
CC-BY-NC-SA grrrl via Flickr

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. We also come at this
from the other direction
- over from the Simple,
in real-time action,
across the edge of panic…

168. Across the edge of panic
before
„Simple’
(ENACT)
edge of
panic
„Not-known’
(EXPLORE)
NOW!
certain
uncertain

169. CC-BY-SA lumachrome via Flickr
The Rules.
(Everything You Need To Know For Your Job)

170. routine…
© Orange County Flight Center via atulgawande.com

171. HUH?
the real-world don‟t match the rules??

172. WAAAAHHH!!!

173. …which is why there‟s
the other side
to that checklist…
- to keep the panic at bay…

174. emergency…
© Orange County Flight Center via atulgawande.com

175. Key items
that users
may forget
in panic…
FLY THE
AIRPLANE
© Orange County Flight Center via atulgawande.com

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. That feedback-loop
across the edge of panic
is where, and how,
on-the-spot answers arise
out there in the field…

178. strange yet useful
innovations…
CC-BY-NC simonlongworth via Flickr

179. pragmatic
answers to
in-the-field needs…
CC-BY-NC simonlongworth via Flickr

180. refusing to face the uncertainty
is what strands us here…
CC-BY-SA afiler via Flickr

181. It‟s almost time
to wrap up this tale…

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. 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. 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. Remember that it‟s recursive
before
C
C
C
NOW!
S
certain
A
S
N
S
A
A
N
N
uncertain

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. 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. 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. 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. But to let our brave dung-beetle
have the last words…
always remember…
CC-BY-NC-ND wisse via Flickr

191. in ancient Egypt…
the scarab rolled the sun along its course…
CC-BY isawnyu via Flickr

192. a helpmate and advisor to the gods…
CC-BY-NC-SA theheartindifferentkeys via Flickr

193. and even in the present-day…
CC-BY-SA swanksalot via Flickr

194. dung-beetles have right of way…
CC-BY-NC-SA arthur_chapman via Flickr

195. Something to
think about,
perhaps?
CC-BY-ND-SA ores2k via Flickr

196. “What’s the
Thank you!

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)