Introduction to behavioral economics Nudging in IT From process architect to behavioral architect

1. Introduction to behavioral economics in IT
- When common sense isn’t enough
Christian F. Nissen, CFN Consult
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2. 2
Agenda
1. Introduction to behavioral economics
2. Nudging in IT
3. From process architect to behavioral architect
4. Conclusion
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Agenda

3. 3
Can we trust our intuition?
Intuitively, which of the black circles is the largest one?
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Behavioraleconomics

4. 4
Can we trust our intuition?
What colour do the middle fields have on the cube?
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Behavioraleconomics

5. 5
Can we trust our intuition?
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Behavioraleconomics
Which table is the longest?

6. Rational economics
Traditional (neo-classical) theories of
economic behavior assume that economic
agents apply rational thought to each and
every decision to achieve the maximization
of personal benefit (utility) or, in the case of
producers, the maximization of profits.
Rational man (Homo economicus)
The rational man or economic man (econ,
John Stuart Mill) acts to obtain the highest
possible well-being for him given available
information about opportunities and
constraints on his ability to achieve his
predetermined goals. He is fully informed of
all circumstances impinging on his
decisions and possesses unlimited (brain)
capacity to process the information when he
makes decisions.
Behavioral economics
A science that studies how individuals make
economic decisions in practice. Behavioral
economics attempts to understand the
effect of individual psychological processes,
including emotions, norms, and habits on
individual decision-making in a variety of
economic contexts.
Human
Unlike the rational man, humans sometimes
are irrational and predictably err
6
Rational vs behavioral economics
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Behavioraleconomics

7. 7
Behavioral economics
Selected titles:
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Behavioraleconomics

8. 8
We ask to be deceived. . .
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Behavioraleconomics

9. 9
Our intuition cheats on us
Intuitive and logical errors
When we must respond quickly, our intuition tends to take over and override
our logical thinking.
Example: In a lake, there is a patch of lily pads. Every day, the patch doubles
in size. If it takes 48 days for the patch to cover the entire lake, how long
would it take for the patch to cover half of the lake?
Neglect of probability
We overestimate the probabilities of unlikely events and underestimate
frequent events.
Example: In Denmark, the probability of being struck by lightning is many
times greater than that of being hit by terror.
Post rationalization
We have a well developed ability to find causes and explanations of
phenomena that actually are incidental.
Example: It turns out that over time luck has greater impact on the success of
an average business than the strategy and management team
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Behavioraleconomics

10. 10
Our intuition cheats on us
Loss aversion
Losses bite more than equivalent gains. The disutility of giving up an object is
greater than the utility associated with acquiring it.
Example: You are offered a gamble on the toss of a coin. If the coin show
tails, you loose € 1,000. If the coin shows heads, you win €1,500. Would you
accept the game?
Mental accounting
We may have multiple mental accounts for the same kind of resource
Example: We may not enter the time and gasoline we use to run after a
special offer on the same mental account as the offer itself.
Herd behavior
The tendency to do or believe things because many other people do or
believe the same.
Example: Fashion, likes, number of downloads, menu choice at the
restaurant
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Behavioraleconomics

11. 11
Our intuition cheats on us
Framing
We draw different conclusions from the same information, depending on how
that information is presented
Example: ”90% of the patients who have this operation, are alive after 10
years” versus ”Of 100 patients who have this operation, 10 are dead after 10
years”
Menu dependence
The choices we make are often highly dependent on the choices available in
a certain context, i.e. what alternatives a particular option is presented with.
Example: Ballots have to list candidates in some order. One study found that
a candidate whose name is listed first gains about 3.5 percent points in the
voting.
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Behavioraleconomics

12. 12
Our intuition cheats on us
Default bias
To avoid the discomfort of complex choices, we usually opt for the default
supplied to us.
Example: The rate of organ donation in a country is highly dependent on the
default option. The high-donation countries have an opt-out form. The low-
contribution countries have an opt-in form.
Availability
We overestimate available information and ignore absent information.
Including recent experience, access to information, clarity and convenience.
Example: A professor at UCLA asked different groups of students to list ways
to improve the course, and he varied the required number of improvements.
The students who listed more ways to improve the class rated it higher.
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Behavioraleconomics

13. 13
Our intuition cheats on us
Anchoring and adjustment
We start with an anchor, e.g. a number we know, and adjust in the direction
we think is appropriate. The bias occurs because the adjustments are
typically insufficient.
Example: The subjective difference between €99,900 and €100,000 is
perceived less than between €100 and €200.
Confirmation bias
We tend to search for, interpret, focus on and remember information in a way
that confirms our preconceptions
Example: An employer who believes that a job applicant is highly intelligent
may pay attention to only information that is consistent with the belief that the
job applicant is highly intelligent
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Behavioraleconomics

14. 14
Our intuition cheats on us
Optimism bias
The tendency to be over-optimistic, overestimating favorable and pleasing
outcomes
Example: Planning fallacy. We view the world in a more positive light than is
justifiable, we overestimate our own abilities, and we consider the goals we
set, easier to achieve than they probably are. We are often driven by the
desire to get our plans approved, and therefore our estimates are closer to a
best-case scenario than to a realistic assessment
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Behavioraleconomics

15. 15
Our intuition cheats on us
MINDSPACE
The UK Institute for Government has summarized our biases in the
abbreviation MINDSPACE:
Messenger: We are heavily influenced by who communicates information
Incentives: Our responses to incentives are shaped by predictable mental
shortcuts, such as strongly avoiding losses
Norms: We are strongly influenced by what others do.
Defaults: We ‘go with the flow’ of pre-set options
Salience : Our attention is drawn to what is novel and seems relevant to us
Priming: Our acts are often influenced by subconscious cues
Affect: Our emotional associations can powerfully shape our actions
Commitments: We seek to be consistent with our public promises, and
reciprocate acts
Ego: We act in ways that make us feel better about ourselves
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Behavioraleconomics

16. 16
And much more cognitive biases . . .
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Behavioraleconomics
Source: https://en.wikipedia.org/wiki/List_of_cognitive_biases

17. The intuitive/automatic system
 Uncontrolled
 Effortless
 Associative (similarity, proximity,
causality)
 Fast
 Unconscious
 Skilled
The rational/reflective system
 (Self)Controlled
 Effortful
 Deductive
 Slow
 Self-aware
 Rule-following
17
Two systems
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Behavioraleconomics
We are predictably irrational
When we are faced with incomplete information, when consequences are
uncertain and when we have to make fast decisions, we fall back on simple rules
of thumb (heuristics) and educated guesses.
They are essential to prevent mental meltdown, but they also regularly leads to
systematic errors.

18. 18
Influencing behavior
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Behavioraleconomics
The rational
system
(slow)
The intuitive
system
(fast)
Rational
behavior
Instinctive
and trained
behavior
Education
Knowledge / information / data
Nudge
Training
Disruptions
Convince / Post rationalize
Manipulate / Stimulate

19. 19
Difference natures of practice
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Behavioraleconomics
David Snowden, 2002, 2007, 2014
Disorder_
Complex
Probe
Sense
Respond
Emergent practice .
Complicated
Sense
Analyze
Respond
Good practice
Chaotic
Act
Sense
Respond
Novel practice
Simple/obvious
Sense
Categorize
Respond
Best practice
Complacency
Relationship between
cause and effect is
obvious.
Predictability, routine,
established practice,
entrained thinking.
Encourage
simplification.
Relationship between
cause and effect
requires investigation
and analysis.
Unique, non-repeated,
multiple right answers,
experience/expertise.
Encourage analysis.
Relationship between
cause and effect is
impossible to
determine.
Unpredictability,
turbulence, trial and
error, responsiveness.
Encourage action
Relationship between
cause and effect can
only be perceived in
retrospect.
Unpredictability, flux,
emergence, creativity.
Encourage
experimentation

20. 20
Different natures of practice
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Behavioraleconomics
The rational
system
(slow)
The intuitive
system
(fast)
Rational
behavior
Instinctive
and trained
behavior
Education
Knowledge / information / data
Nudge
Training
Disruptions
Convince / Post rationalize
Manipulate / Stimulate
Complex practice
Simple practice
Complicated practice

21. 21
Different natures of knowledge transfer
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Behavioraleconomics
Tacit
knowledge
Tacit
knowledge
Tacit
knowledge Socialisation Externalisation
Explicit
knowledge
Tacit
knowledge
Internalisation Combination
Explicit
knowledge
Explicit
knowledge
Explicit
knowledge
Ikujiro Nonaka & Hirotaka Takeuchi, The Knowledge Creating Company, 1995

22. 22
Different natures of knowledge transfer
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Behavioraleconomics
The rational
system
(slow)
The intuitive
system
(fast)
Rational
behavior
Instinctive
and trained
behavior
Education
Knowledge / information / data
Nudge
Training
Disruptions
Convince / Post rationalize
Manipulate / Stimulate
Socialization
Internalization
Externalization
Combination

23. 23
The limited human
The modern workplace has sent the rational system on
overtime, leading to stress:
 We are not rational
 We don’t have a strong will
 We do not have infinite cognitive capacity
 We are not self-managed
Humans, unlike Econs, need interventions to make good
decisions, and there are informed and un-intrusive ways to
provide that help (libertarian paternalism).
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Nudging

24. 24
Nudging
Sometimes a nudge is needed
Nudging explained by Richard H. Thaler
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Nudging

25. 25
Nudging
The concept nudge comes from elephants crossing the savannah. If one of
the baby elephants heads in the wrong direction, it gets a friendly nudge of
the older elephants, to help it in the right direction. Nudge can thus be
described as a friendly push in the right direction.
A definition
 Any aspect of the choice architecture that alters people’s behavior in a
predictable way without forbidding any options or significantly changing
their economic incentives. To count as a mere nudge, the intervention
must be easy and cheap to avoid. Nudges are not mandates.
Good nudges must
 be transparent and never misleading
 be easy and cheap to avoid
 improve the welfare of those who are being nudged
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Nudging

26. 26
A good and a more questionable example
The World's Deepest Bin
Social ad deters pedestrians from crossing at red lights
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Nudging

27. 27
Nudges – ITSM examples
Neglect of probability
 State how many times a trivial change resulted in adverse incidents over
the past 12 months
Begin with end mind
 Gather all stakeholders and celebrate the completion of a release with
cake
Loss aversion
 Introduce levels of authority in the ITSM tool, that may be lost if your
quality decreases
Mental accounting
 Introduce an artificial currency for estimation and resource management
- for example checkers, function points or story points
 Divide resources in pools (e.g. development, maintenance, error
correction). When a pool is empty, there are no more resources for that
specific type of task without management approval
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Nudging

28. 28
Nudges – ITSM examples
Herd behavior
 Indicate how many times a knowledge article has been used
 Number of ’likes’ on workarounds
 Inform what x other / x% typically have done in a similar situation
Framing
 Use alarms / notifications from real life (traffic lights, stop signs, etc.)
 Make physical changes when the work situation changes (rooms, draw a
circle, physical staging, war room, standing meetings, daily morning
meetings, kaizen meetings, coffee tables, etc.)
 Use Kanban boards (signaling)
 Introduce a baton for major incidents - the person with the baton is
accountable for the management of the major incident
 Show a picture of the person who will receive the case after you, to
make you more diligent with the details
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Nudging
Remind the participants what is a Nudge for good:
It is a smart and simple initiative that influences consumers’ behaviour in order to help them
achieve their own goals
It is ethically designed (means-end goal / legitimate originator)
It acts in favour of people’s own interest and that of the community (or the planet)
It preserves freedom of choice and existing options
It is based on observational insights of individuals, recorded in their local environment and
community
It leverages unconventional factors revealed by Behavioural Economics, neuroscience and
cognitive psychology, along with more conventional concepts (education, information,
marketing, communication…)
It uses a creative re-design of some situations and interaction points (including branded
touchpoints)
It doesn’t activate any economic incentive: you shouldn’t pay people to change their
behaviours, although you may offer them a symbolic reward
The output here is to pinpoint which ideas are potential Golden/Revolution Nudges!
NUDGING FO R GO O D
9

29. 29
Nudges – ITSM examples
Menu dependence
 Consciously order of the services or categories, you have to assign to a
case – e.g. by placing the services or categories that are often neglected
at the top
 Use the "frequency of use", "likes", "added date”, "last updated" etc. as
sort criteria in ITSM tool lists rather than alphabetical order
Default
 Priority is by default set to 3 
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Nudging

30. 30
Nudges – ITSM examples
Availability
 When creating a new change, highlight the last 10 changes that went
really wrong
 Traverse the configuration management system to draw attention to
possible impacts
 Every employee from respectively 1st and 2nd level must minimum twice
every week contact the other function with minimum one positive
feedback and minimum improvement item. 1st level keeps records
 Support with statistics and artificial intelligence – e.g. this change is
similar to these five previously implemented changes
 Automatically notify if there is no attachment to a mail containing the
word ’enclosed', 'attachment' etc.
 Ease the access to help: "If you are in doubt about how this field is to be
filled, then call 12 34 56 78" or "Watch this video on how to fill the field"
 Set up the best coffee machines where you want people to meet
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Nudging

31. 31
Nudges – ITSM examples
Anchoring and adjustment
 The completion of one field can prime the user in filling in a subsequent
field
 "The average development estimate for similar changes is nnn hours"
Status quo
 First month is free, then you pay a monthly subscription unless you
cancel your subscription
Rules of thumb
 "You need to estimate the same amount of time for testing and training,
as for the design, development and deployment”
Representativeness
 "Have you checked these similar cases: # 1, # 2, # 3”
Confirmation bias
 "Before you assign the incident to the network department, we want you
to consider once again whether there is another department, that might
be more obvious"
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Nudging

32. 32
Nudges – ITSM examples
Reward long-term gain
 Give more and more freedom in the tools, the more experienced a
person gets
Social contracts
 "Dear Colleague: If you register your change here, we take full
responsibility from here." Applies both to technicians and customers
 "Avoid extra work: Be aware that you avoid ??? if you have ???" or "Be
aware that you are prompted for ??? if you have not ???"
 "I hereby declare that I have attached the following documents: a, b”
 "You now only have eight fields left" (The implication: Hold on and
continue to work carefully)
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Nudging

33. 33
Nudges – ITSM examples
Gamification
 Use of gaming elements: Point, badges, scoreboards, progress
indicators, levels, rewards, challenges, etc.
 Assign points for contacts with the user during the lifecycle of a case
 Earn points through work (e.g. number of cases weighted by complexity)
 Credits for the number cases you have related to other cases in Service
Desk
 Rating of cases you receive from other groups
 User satisfaction team score boards
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Nudging

34. 34
Nudges – ITSM examples
DataCenter 2000
 The physical work was arranged into four zones:
 Customer zone
 Support zone
 Operations zone
 Maintenance zone
Each zone had its own unique office environment. A workplace in
DataCenter 2000 was not a place you owned, but a place you had to move
to for a certain type of work. The surroundings supported the work method
of the individual zone. In the support zone, as we see here, all workplaces
for example supported rotation. Furthermore, there was big screens were
mounted to give a status the of operations and support situation. The
workplaces were designed to encouraged dialogue and knowledge sharing.
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Nudging

35. 35
Nudging
Use 5 minutes with your neighbor to suggest
additional examples of IT service management
nudges
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Nudging

36. 36
Bureaucracy
”Because adherence to standard operating procedures is
difficult to second-guess, decision makers who expect to have
their decisions scrutinized with hindsight are driven to
bureaucratic solutions – and to an extreme reluctance to take
risks.”
Kahnemann
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Fromprocesstobehavioralarchitect

37. 37
When to nudge?
People will need nudges for decisions that are difficult and rare, for
which they do not get prompt feedback, and when they have
trouble translating aspects of the situation into terms that they can
easily understand.
Situations where people are least likely to make good choices:
 benefits now - costs later (situations that test my capacity for
self-control)
 degree of difficulty
 frequency - first time
 no or bad feedback
 not knowing what you like
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Fromprocesstobehavioralarchitect

38. 38
How to nudge?
iNcentives
 While humans respond to nudges, they also respond to incentives. Make sure users have the
right incentives. Make the incentives salient (or prominent) so that people don’t miss them
Understand mappings
 People make better choices when they have help in understanding what the various choices
means in terms of their welfare (health, satisfaction, happiness, and well being)
Defaults – Padding the paths of least resistance
 Every choice situation has a default choice, whether it is made explicit or not. The default is
what you get when you choose nothing
Give feedback
 The best way to help Humans improve their performance is to provide feedback. Well-designed
systems tell people when they are doing well and when they are making mistakes.
Expect error
 Humans makes mistakes. A well-designed system expects its users to err and is as forgiving as
possible.
Structure complex choices
 When people need to choose one item from a long list and evaluate each item by another long
list of criteria, people need structuring of choices, e.g. elimination by aspects
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Fromprocesstobehavioralarchitect

39. 39
How to nudge?
1. Map
 Describe the desired behavior. Be specific, both in terms of desired behavior and expected
results. Use the 'video test'!
 Observe and describe current behavior. How does it differ specifically from the desired behavior
and what are the consequences?
 Describe the involved actors. Who is closest to the desired behavior and who is furthest from?
Are there actors who try to achieve the desired behavior, but do not achieve it? Are there
patterns (persona / archetypes)?
 Describe the desired behavioral change. Describe both the desired change and how it can be
measured.
2. Analyze
 Identify the nature of irrational behavior (biases). What is the reason for the undesired behavior?
 Identify barriers (physical, mental and social) for the desired behavior and triggers of irrational
behavior. Ask and observe.
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Fromprocesstobehavioralarchitect

40. 40
How to nudge?
3. Design
 Brainstorm on specific nudges. How can the desired behavior be activated? Start with the nature
of irrational behavior. Take advantage of your knowledge about bias, barriers and triggers.
 Identify any ethical challenges of the identified nudges
 Select the most promising nudges with the least unwanted side effects (risk)
4. Evaluate
 Test for effect and unwanted side effects. Use prototypes, test on different subjects, test in the
'laboratory’ as wells as in the field. Compare achieved behavior (test group) with current
behavior (control group). Optimize if possible.
5. Implement
 Deploy
 Monitor and follow-up
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Fromprocesstobehavioralarchitect

41. 41
How to nudge?
© 2018
Fromprocesstobehavioralarchitect
1. Map
2.Analyze
3. Design
4.Evaluate–5.Implement

42. 42
The 21 drivers of influence
© 2018
Fromprocesstobehavioralarchitect
THE 21 DRIVERS O F INFLUENCE
RANSMITTERT
ABITSH
GOE
EFAULTD
ECIPROCITYR
NCENTIVESI
ALUEV
MOTIONE
EWARDSR
ALIENCES
Choose the right messenger to
reinforce the message
Promote the development of new habits
through new triggers and appropriate rewards
Give value to the action by rewarding
with recognition
Encourage a behaviour with
money, goodies or social reward
Create a default choice sequence that
leads to the desired behaviour
Engage in a logic of reciprocity by
creating a social debt
Generate an emotional response
through images, visuals and
embodied stories
Highlight the scope of work realised
to justify the price
Reward with positive feedback
Attract attention by making an
item salient
O
RAMINGF
MMEDIACY
I
OSTALGIAN
AIRNESSF
OSSAVERSIONL
PPER/ LOWER
ANCHORINGU
ASINESSE
ORMSN
OMPARTMENTALIZEC
NGAGEMENTE
Create a choice context that
encourages the desired
behaviour
Make the task seem easier
by going on step at time
Generate favourable associations
and reference points
Activate the feeling of
nostalgia
Show the fairness of the
targeted behaviour
Mention the loss provoked
by not adopting the desired
behaviour
Encourage the need for
conformity
Simplify the desired behaviour
Postpone constraints and efforts
in the future while immediately
providing advantages
Materialise invisible flows (like
efforts, expenses) with objects
you can visually handle
Generate commitments to promote
consistency
NESTEPATA
TIME
7
Eric Singler, Nudge Marketing – Winning a behavioral change, 2015

43. 43
Conclusion
© 2018
“Don’t build a machine and expect it to behave
with any intelligence or creativity.
Don’t employ people and then try and make
them behave like machines.”
- Rob England
Conclusion

44. Questions and comments
44
Conclusion
© 2018

45. Contact
45
Christian F. Nissen
cfn@cfnconsult.dk
+45 40 19 41 45
CFN Consult ApS
Linde Allé 1
DK-2600 Glostrup
CVR: 39 36 47 86
© 2018

46. 46
Appendix
© 2018