COMPLEX PROBLEMS
CLASS 3
Heuristics to the Rescue
Alternatives to Purely Analytical
Problem-Solving Methods
Heuristics as a Problem
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Cognitive Biases -- “Implicit Heuristics”
» Most of the early work on heuristics focused on
showing poorly understood use of heuristics when
thinking/using analytical methods (Kahneman &
Tversky) -– Strong Priors
– Unwarranted Analogies
– Representative Bias
– Myopia
– Control ...
Heuristics as a Problem-Solving Tool
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“Heuristic”
» helping to discover or learn; a method of education [learning] or
computer programming in which the pupil or machine proceeds
along empirical lines, using rules of thumb, to find solutions or
answers (New World Dictionary, 2nd Ed.)
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In this broad & positive sense, heuristics are problemsolving methods using mental shortcuts, trial & error, ...
» Rules of Thumb
» Empirical Searches & exploratory experiments (Trial & Error)
» Intuition & experience
Non-analytic Based Disciplines
Does not imply lack of intelligent
thought or complete absence of
analytical methods, just not the core of
problem solving
 Significant Heuristic Content or Method

» Biomedicine
» Cognitive Psychology
» Computer Science, Engineering, Stats,
Math ...
Contrasting Analytical & Heuristic
Methods

Math Example
» Find point where y = 2x2 - 10x reaches a minimum
– Analytical: Find derivative, set equal to zero and solve for x
(dy/dx = 2x - 10); (0 = 2x - 10); (x = 5)
– Heuristic: Numerical Search (trial & error): plug-in values for x until you
find the minimum point
» in case above, analytical approach more efficient
» if equation not easily solved with analytics, numerical
search more efficient or may be only possible
Heuristics in Analytics
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Prior Class Analytical Toolkit
» Analogy
» Solving in parts
» Backward-Forward
» Transforming into known problem
» Generalizing from specific solution
Although now integral part of analytical problemsolving techniques, these are really rules of thumb
(heuristics) that people tried over time; they
became widely known because they worked
Experimental Evidence on
Heuristics

Bargaining & Ultimatum Game:
» Fixed sum to split between Player A & Player B ; A makes offer, if B
rejects, game ends-no deal; if B accepts, deal made
» Analytics: A offer minimum, B accept
» Experiments:
– Few offers below 75:25 split, if made, rejected
– Reasons: fear rejection, fairness so use “heuristics” (intuition …)
» Extensions: time limits,multiple rounds, …
– people who quickly agreed on 50:50 did the best
– people who tried for very uneven results or bickered over small
differences did the worst

Bottom Line?
» Where “norms” are involved that are not easily model in analytics, using
“intuition” can improve on pure analytics
Experimental Economics
Evidence on Heuristics

“Focal Points” -- rule of thumb (heuristic) solutions to
difficult strategic decisions
» Divide the cities (location game): Harvard & Stanford MBA
student pairs separately choose from list of cities with certain
limitations; score bigger when less overlap
» Results?
– Geographic (East-West) focal points
» Where to Meet in NYC?
– Thomas Schelling experiments found GST focal point
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Bottom Line?
» “Intuition” can be a useful heuristic
Biomedical Examples

Rules of Thumb & Intuition
» Patient presents with sore throat & upper respiratory symptoms
– common cold virus
» Infant presents with intestinal discomfort
– gas
» Patient presents with shortness of breath and fatigue
– asthma

Search
» Patient presents with fever severe sore throat, fatigue -- no other
– “Rapid” Strep Test;
– Symptoms recur frequently -- “overnight” strep culture
– Lack of resolution -- blood tests (C-reactive protein; white blood cells …)
» Start from low cost/most common and proceed
Decisions

Heuristics that you employ or have seen others employ
in everyday personal decisions
» Rules of Thumb?
» Searches?
Take 15 minutes and write down list of heuristics from both
personal and business experiences + rank by the ones that
work well and not so well; indicate why

In general, these kinds of examples from are often
called “Satisficing”
Limits of Intuition

Fooled by Randomness (Taleb, 2002): Experiments show that people
using simple observation (heuristic), repeatedly see patterns to
outcomes where none exist
60
50
40
30
20
10
0
90
91
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93
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Robert Lucas on Limits of Simple
Searches & Observations
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Since the mid 1980s, companies like Microsoft, FedEx, Staples, MCI and many
others have shown tremendous growth in earnings, market share, employment
and other performance measures. With such a range of experience, why do we
need theoretical models? Why can’t a company just send a fact-finding team to
Staples, find out the strategies and structures which made them successful, and
then go home and get their own company to do the same? This sounds easy
enough, but it is not really operational ... Firms are just too complex -- there are
too many things going on at once -- for getting all the facts to be either possible
or useful. Faced with so much data, an observer who is unequipped with a
theory sees what he wants to see, or what the successful company or
management guru wants to show him. One needs some principles for deciding
which facts are central and which are peripheral. This is exactly the purpose of
to isolate some very limited aspects of a situation and focus on them to the
exclusion of all others ... We need to make some hard choices about what to
emphasize and what to leave out before we can think in an organized way at
all.How do economies or companies succeed?
»
Adapted from Robert Lucas, 1994 Nobel Prize Winner to European Econometrics
Society (Extension of science philosopher, Karl Popper)
Limits of Heuristics:
Examples

Biomedical
» Jerome Groopman -- Harvard Hematologist-Oncologist Second
Opinions: Stories of Intuition and Choice from the Changing
World of Medicine (2001)
» Pediatrician’s rule of thumb > Infant has gas
– Reality > Obstructed Bowel
» Primary Physician rule of thumb > Woman has asthma
– Reality > Leukemia

Production
» Carnegie-Mellon Bicycle Production Example
General Lessons about
Using Heursitics

Heuristics Most Successful Where
» Outcomes conform to “typical” situations
– Heuristics fail where nuances present
» Causal relationships simple (e.g. virus-disease)
– Heuristic approach in biomedicine not as successful in multifactor problems, e.g. Neurological problems
» Problem of a nature so that computational power can
overwhelm the search problem by brute force,
– e.g. Human Genome project; finding a numerical solution
through searches;
» Problem is time-sensitive
» Problem beyond analytical limits
The Tradeoffs: analytics v. heuristics

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Analytics -- “High Cost/Low Error”
» Precise, Logical,
» Costly in terms of time/mental demands;
flexibility
Heuristics -- “Low Cost/High Error”
» Low cost in terms of time/mental demands,
flexibility
» Difficult to assess; Subject to unclear biases…
– CS: “Heuristics are bug ridden by definition. If they
weren’t, they would be algorithms”
Analytical Heuristics: an oxymoron?

Methods different but the same?
» rules of thumb & intuitive searches sometimes
imitate analytical results (Day, AER)

Analytical Heuristics
» Not all search random are led by intuition alone
» Search can be guided by analytics & prior
knowledge
– Wright Brothers & entrepreneurship
Development of Flight:
Bradshaw & Lienert (1991)
WRIGHT BROTHERS &
ENTREPRENUERSHIP


One meaning of entrepreneurship: innovating and
improving through combining or mutating
products, processes …
Wright Brothers (See Related Websites & First Flight)
»
»
»
»
Did not just go through trial & error or use just intuition
Serious research on past efforts
Analytical reasoning regarding physics
Then Search through Experimentation in wind tunnels
and full-scale
Critical Lessons
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Effective use of heuristics will make you a better
manager
Overuse of heuristics will create mistakes -- sometimes
devastating mistakes
Employ heuristics when best suited to the situation -- not
as a crutch to alleviate the need to think analytically
What is the decision environment
» Time sensitivity, analytical tractability and completeness, search
power, analytics guiding heuristics possible

Remember the implicit biases apply to heuristics too!
Mini-Assignment

Identify and be able to explain 2
examples of the use of heuristics to solve
problems in a workplace setting involving
rules of thumb, simple search, or the
overlap of analytics & heuristics.
Evaluate how well the heuristic seems to
work and the reasons it does or does not
seem to work very well.