Teaching Cases

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• Teaching Cases
• Decision Behavior Teaching Conference
• August 3-5, 2005
• George Wu
• University of Chicago
• gsbww.uchicago.edu/fac/george.wu/teaching/decision
  /

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Some Background

• Managerial Decision Making at University of
  Chicago Graduate School of Business
• Hastie, Hsee, Thaler, Wu (following Einhorn,
  Hogarth, Russo, Schoemaker, etc.)
• Core Class Regular MBA curriculum
• 1 of 4 possible classes to satisfy Managerial and
  Organizational Behavior requirement
• ? 12 sections of 40-65 students annually
• Required Class Executive MBA program
• ? 3 sections of 85 students annually

• Course content
• Classic Lecture
• Discussion (cases, caselets, interactive lecture,
  etc.) 50

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Why Cases?

• Why not JDMs greatest hits instead?
• Not always sufficient for material to be
  intrinsically interesting
• Demonstrations often seen as stupid human tricks

• What do cases demonstrate?
• Descriptive that judgment and decision making
  errors can be extremely costly in the real world
• Prescriptive that awareness of these errors can
  lead to profit opportunities or better decisions

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What is a Case?

• The case method is built around the concepts of
  metaphors and simulation. Each case is a
  description of a real business situation and
  serves as a metaphor for a particular set of
  problems. The situations which you face as a
  manager may differ from the metaphors we have
  chosen here, but taken together, the cases
  provide a useful and relevant set of metaphors
  for marketing situations. The cases were
  selected to include a wide variety of products
  and company types so that at least some of them
  would be relevant to almost all marketing
  management situations.
• The case method of management instruction is
  based upon the belief that management is a skill
  rather than a collection of techniques or
  concepts. Because it is impractical to have the
  student manager a company, the case provides a
  vehicle for simulation.
• Benjamin Shapiro (1984), An Introduction to
  Cases

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Cases Dimensions, etc.

• Characteristics
• Engaging and Interactive
• students defend their ideas, argue, question,
  etc.
• Action-oriented
• Facilitation
• Retention
• Recall (pattern recognition)
• Motivating Devices
• Relevant issues (decision processes components
  John Brown)
• Specific issues (Toro)
• Parables (AOL)
• When the rubber hits the road
• What are you going to do? Necessity of
  tradeoffs
• Psychological Engineering

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Cases Types, etc.

• Professional Cases
• Business
• Harvard Business School Publishing
  www.hbsp.harvard.edu
• Other Schools (Stanford, INSEAD, University of
  Western Ontario Ivey School, etc.)
• Other Professional Schools
• Journalistic Accounts
• Need not necessarily be domain-relevant
• Into Thin Air (Jon Krakauer)
• John Brown
• Cases vs. Caselets
• Caselet unveiled real-time
• Students prepare case in advance

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First, a Caselet
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Case Example America Online I

• Pricing Change
• On 12/1/96, AOL to introduce a new flat-rate
  charge 19.95/month for unlimited access
• AOL has been charging 19.95/month for 20 hours
  of service, or 9.95/month for five hours (plus
  2.95/additional hour)

What are the critical uncertainties?
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Case Example America Online II

• What decisions are tied to these uncertainties?

What information would you collect?
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Case Example America Online III

• What would you do?

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America Online What Happened

• AOL Planning
• Began bracing for the expected usage surge in
  September, adding 12,000 new modems (to 260,000
  existing modems) in November (along with more
  phone lines and computer servers).
• Steve Case AOL would really be challenged to
  meet that demand and try to avoid busy signals
  and system sluggishness.
• David Gang, VP marketing Were going into
  territory that nobody on the face of the planet
  has ever been before.

•  What happened
• Peak hour logins skyrocketed from 140,000 in
  early October to 236,000 the week before
  Christmas.
• Average time spent online by AOL subscriber
  doubled since September, rising to 32 minutes
  from 14 minutes.
• Case urged AOL members who also subscribe to
  other Internet services to use them as back doors
  into the AOL system.

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America Online Epilogue

• Bob Pittman, President of AOL
• Forecasts are fairly reliable if you have a
  historical precedent in any business or
  opportunity. They get tricky if you have no
  historical precedent. No one has ever been our
  size before in this business. There is nothing
  else in the world like AOL and there never has
  been. Who would have thought usage would double.
  I mean, thats like saying the ratings of a
  radio station or a TV station doubled in one
  month.

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Debriefing AOL case

• What works
• Demonstrates value of following a particular
  decision process
• Process helps generate a specific prescription
• Demonstrates the role of confidence judgments
• Distinguishes between Primary and Secondary
  Knowledge
• Demonstrates some costs of having narrow
  confidence intervals (overconfidence)

• Why does this case work?
• Case versus caselets Latter requires no
  advanced prep
• Students thrown into decision situation
• Exploits hindsight bias

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Now, a Case
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Toro
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The S'No Risk Promotion
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So What Would You Do?
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Survey Should Toro repeat the program?
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Survey Provide some reasons..
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Was the program a success?
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Survey Was S'No Risk a success?
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Survey justification for success rating
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Options

• Is there anything else we could do?
• Give dealers a choice (dealer allowance or SNo
  Risk)
• Use selectively (regionally)
• Use in the future (jumpstart after poor years)
• Modify program
• Change dates
• Change refund schedule
• Apply only to high-end products

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Consumer Decision Making Process

• Who is the marginal consumer?
• What keeps the marginal consumer on the fence?
• What does SNo Risk do to convert marginal
  consumer?

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SNo Risk eliminates Regret
Without SNo Risk
With SNo Risk
?
?
?
?
?
Wheres the sleight-of-hand?
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Other Psychological Biases Exploited

• Are there other psychological biases at play?
• Mental Accounting
• Prospect theory
• Overweighting of small probabilities
• Heuristics and biases
• Anchoring ? Overestimating chance of winning

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Chicago Annual Snowfall
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Improving Promotion?
Is there any way to improve the promotion?
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Chances of Collecting
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Improving Promotion?
Is there any way to improve the promotion?
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40
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Other Cases

• John Brown (Harvard case)
• AOL (Caselet)
• National Demographics Lifestyle (Harvard case)
• Kodak in China (Chicago case available on
  website)
• Eureka Ranch (Inc. Magazine)
• Jump Start your Business (May 1997)
• Dave Armstrong (Harvard case)
• Toro (Harvard case)
• Into Thin Air (Outside Magazine)
• http//outside.away.com/outside/destinations/1996
  09/199609_into_thin_air_1.html
• Smithkline Beecham (Harvard Business Review)

www.hbsp.harvard.edu