I gave this talk at the Budapest University of Technology and Economics to psychology students about the philosophies we use to build and improve a workplace. I covered a wide range of topics (Taylor, Kanban, staff liquidity, cynefin, etc.)

1. Philosophies of Building
the Workplace
@ZsoltFabok
by
Zsolt Fabok
2015.04.16 !
http://zsoltfabok.com/

2. Intro

3. book: http://www.libri.hu/konyv/empowerment-a-felelosseg-hatalma.html

4. book: http://www.triballeadership.net/book

5. image: https://technologybubbles.files.wordpress.com/2012/06/screen-shot-2012-06-28-at-12-21-22-pm.png

6. Processes

7. Frederick Taylor
more info: http://en.wikipedia.org/wiki/Scientific_management

8. Henri Fayol
more info: http://hu.wikipedia.org/wiki/Henri_Fayol

9. Max Weber
more info: http://hu.wikipedia.org/wiki/Max_Weber

10. Let’s jump forward in time

11. book: http://www.amazon.com/Toyota-Production-System-Beyond-Large-Scale/dp/0915299143

12. more info: http://zsoltfabok.com/blog/2012/08/waste-in-software-development/

13. book: http://www.amazon.co.uk/This-Lean-Resolving-Efficiency-Paradox/dp/919803930X

54. source: https://innovation.internews.org/pilots/agile-methodology-human-development

55. source: http://www.mountaingoatsoftware.com/agile/scrum/overview

56. more info: http://edu.leankanban.com/ http://www.zsoltfabok.com/blog/tag/kanban/

57. Small incremental
evolutionary changes
(continuous improvement)

58. The Pull System

59. If you understand the purpose of small
incremental evolutionary changes and the
pull system, you’ll do fine with the Kanban
Method, because you can easily deduce
the rest.
(helping questions:Am I improving? Am I pulling the work?)

60. It is hard to improve the invisible, so
we have to see what we have at our
hands.

61. Meet the team

62. Value Stream Mapping
Start with what you do now
(possibly end to end)

63. Car manufacturing
vs
software engineering
“The gemba walk”
(Unfortunately, you won’t see much at a
software engineering workplace)
(http://zsoltfabok.com/blog/2013/06/gemba-walk-has-low-value/)

64. Value Stream Mapping

65. Design
Implementation
Delivery
Test information
work item
http://zsoltfabok.com/blog/2012/04/see-the-whole-flow-exercise/

66. Design
Implementation
Delivery
Test

67. Ready Design Implementation Test Delivery Live

68. This board was a “traditional” board,
how about a less “traditional” one?

69. Courtesy of Prezi.com

70. We decided that we are going to discover
our value stream (flow) on the go.

71. Ready Design Implementation Test Delivery Live
Flow (Stream)
The flow ([value] stream) starts at the left side,
and ends at the right side of the board.

72. The Flow is different in a typical
enterprise and start-up environment.

73. Typical enterprise flow
Flow (Stream)

74. Typical start-up flow
Flow
Flow
Flow

75. Now we can see the previously unseen,
but we need to start pulling work items
otherwise they won’t get delivered.

76. Ready Design Implementation Test Delivery Live
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77. Ready Design Implementation Test Delivery Live
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78. Ready Design Implementation Test Delivery Live
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79. Ready Design Implementation Test Delivery Live
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80. The pull system itself does not guarantee
that work items get to be delivered.

81. That’s when the Work In Progress (WIP)
limit comes into the picture.

82. Ready Design Implementation Test Delivery Live
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1 2 1 3
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83. How to set the WIP limit
at the beginning?

84. # ~
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work done
staff liquidity + internal queue

85. Too low WIP limit creates unnecessary
bottleneck, too high WIP limit encourages
multitasking and/or longer lead time.

86. Yes, the WIP limit can
change over time.

87. # ~
~ ~
work done
week 1 week 2 week 3 week 4

88. Car manufacturing
vs
software engineering
“The inventory”
(AtToyota the inventory is finite, however in
software engineering it is infinite, therefore we
cannot approach it with the same attitude)

89. And now, back to the queues.

90. There is another kind of queue: the
infinite queue.

91. 2
1
Visible
Invisible
2 3
Infinite queues

92. Now the work items are getting delivered,
it is time to improve the system.
!
Improvement requires measurement.

93. The lead time

94. The lead time
Ready Design Implementation Test Delivery Live
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commitment

95. Distribution of lead times
days
count
0
2
4
6
8
10
12
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 22 28 33 56
average
median*
*Calculation of medians is a popular technique in summary statistics and
summarizing statistical data, since it is simple to understand and easy to calculate,
while also giving a measure that is more robust in the presence of outlier values
Courtesy of Digital Natives

96. Car manufacturing
vs
software engineering
“The takt time”
(In software engineering the demand is not
quantitive, therefore it doesn’t matter how
much time we spend between two features)

97. Car manufacturing
vs
software engineering
“The throughput”
(In software engineering we don’t have to deliver 10
features, we have to deliverTHE feature, therefore
the number of delivered feature doesn’t help us, but
it is a good “secondary” measure)

98. Car manufacturing
vs
software engineering
“The throughput”
(In software engineering we don’t have to deliver 10
features, we have to deliverTHE feature, therefore
the number of delivered feature doesn’t help us, but
it is a good “secondary” measure to see how we react
to changes, or how good we are at forecasting)

99. 0
2
4
5
7
week 1 week 2 week 3 week 4
incoming
outgoing
The throughput

100. The throughput (output) is helpful, if
and only if it is compared to the
demand (input).

101. 1 2 1 3
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2
4
5
7
w 1 w 2 w 3 w 4
6

102. The goal is to have a stable system
(first target) because improvement on
a stable system will have a long term
effect (second target).

103. 1 2 1 3
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2
4
5
7
w 1 w 2 w 3 w 4
7
It is Monday on Week 5...
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104. 1 2 1 3
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2
4
5
7
w 1 w 2 w 3 w 4
7
It is Monday on Week 5...
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Aging item

105. The aging items mess up your forecasting.

106. 0
2
4
5
7
w 1 w 2 w 3 w 4
throughput
*This argument is so weak that a decent philosopher stops thinking about
philosophy and looks for another profession every time one reads it up
“We get N items a week”
“We deliver N items a week”
!
“Therefore we can deliver an
item in a week”
“We deliver an item in a week”
!
Therefore our lead time is the
length of the week which is 5
days)”*

107. days
count
0
2
4
6
8
10
12
1 2 3 4 5 6 7 8 9
But in reality you are actually here:
5 != [6,9]

108. Protect the bottleneck and don’t punish the
phase before the bottleneck.
(with Theory of Constraints)

109. 3 3 4 2
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Bottleneck

110. 3 3 4 2
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It hurts here...
...because the work items queue up here.
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111. 3 3 4
2
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2
Now the bottleneck is better protected...
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...and the phase before the bottleneck doesn’t suffer.

112. Cost of delay flavored Kanban

113. Courtesy of Prezi.com

114. time
impact
Level 1
The original idea comes from Thomas Jeffrey: http://bit.ly/exBGNo

115. time
impact
cost of delay
Level 1

116. time
impact
Level 2

117. t1
cost of delay
time
impact
Level 2

118. time
impact
t2
Level 2 will eventually turn into Level 1

119. time
impact
Level 3

120. time
impact
t1
no cost of delay
Level 3

121. time
impact
t2
Level 3 will eventually turn into Level 2

122. time
impact
And, Level 2 will turn into Level 1

123. time
impact
Improvement, technical debts. You know those
we always talk about, but never actually do

124. Courtesy of Prezi.com

125. 0
3
6
9
12
week 1 week 2 week 3 week 4
incoming
outgoing
Real data will come after finishing this experiment!

126. If you understand the purpose of small
incremental evolutionary changes and the
pull system, you’ll do fine in Kanban land,
because you can easily deduce the rest.
And be skeptical about the practices that come from the
manufacturing world (context matters).

127. source: [

128. source: http://bbrt.org/

129. People

130. Definition:
!
The time spent on any item of the agenda will be
inverse proportion to the sum involved.

135. The good thing about science is that
it's true whether or not you believe in it

139. by
Prof. Dr. Martin Seligman (1967)
The dog experiment
image: http://bit.ly/14axX5J

140. Learned helplessness
Is a technical term that refers to the condition of
a human or animal that has learned to behave
helplessly, failing to respond even though there
are opportunities for it to help itself by avoiding
unpleasant circumstances or by gaining positive
rewards.

141. by
Robert Rosenthal and Lenore Jacobson (1968)
The class room experiment
image: http://bit.ly/12IiNzR

142. Pygmalion Effect
People will perform to the level of
expectations you set for them.

143. image: http://bit.ly/1cwnw2l

144. by
Elton Mayo (1927)
The Hawthorne experiments
image: http://bit.ly/PEucyR

145. Hawthorne Effect
The phenomenon in which subjects in
behavioral studies change their performance
in response to being observed.

146. by
Lee Ross, David Green, Pamela House (1977)
The False-consensus Effect
image: http://bit.ly/9n66nj

147. False-consensus Effect
There is a tendency for people to assume that
their own opinions, beliefs, preferences, values
and habits are 'normal' and that others also think
the same way that they do. This tends to lead to
the perception of a consensus that does not exist,
a 'false consensus'.

148. by
Edmund Gettier (1963)
The Gettier Problem
(campus clock version)
The Gettier Problem is a philosophical thought experiment that
has nothing to do with social sciences, yet it is important image: http://bit.ly/MG8Kbn

149. Gettier Problems
The problems are actual or possible situations in
which someone has a belief that is both true and
well supported by evidence, yet which — according
to almost all epistemologists — fails to be
knowledge.

151. Thank you very much for your attention!
@ZsoltFabokhttp://zsoltfabok.com/