Choice Architectures

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Choice Architectures 1 Research and diagnostic series Bob Suh, Founder and CEO August 2014 © Private and confidential. All rights reserved. OnCorps 2014.

description

This presentation provides OnCorps' perspectives on critical research from Daniel Kahneman, AmosTversky, Richard Thaler and Cass Sunstein.

Transcript of Choice Architectures

Page 1: Choice Architectures

1

Choice Architectures

Research and diagnostic seriesBob Suh, Founder and CEO

August 2014

© Private and confidential. All rights reserved. OnCorps 2014.

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This presentation is derived from the theories developed by

Daniel Kahneman, AmosTversky, Richard Thaler and Cass Sunstein

© Private and confidential. All rights reserved. OnCorps 2014.

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When conditions change, default decisions can be mistakes

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Avoiding the certainty of releasing bad data can result in fraud

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Confusion over product differentiation causes products to lose

A&W third pounder fails because consumers think it is smaller than quarter pounder

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Decisions can be “nudged” to improve outcomes

1.Automatic

2.Reflective

2+2=?

32x11=?

Whenever multiplying by 11, add first 2 numbers and

insert sum between themRepeat insight

Lean back when you fear falling

Learn to lean forwardBalance retained

32x11=352

Repeat insight

Nudges

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We are piloting a series of heuristic algorithms

Belief Observation Reaction

ABC stock will go up 200%

ABC stock rises 210% Sell ABC

ABC stock declines 20% Switch to XYZ

Buy more ABC

All shares

Some shares

• How convicted are you in your beliefs?

• How do your beliefs influence what you observe?

• How does what you observe change your beliefs?

• How does what you observe change your actions?

• How does your action or inaction change your observed performance?

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Risk aversion drives many of our decisions

Value

GainsLosses

Take a risk on possible loss

versus accepting a certain loss

Choose certain cash

versus higher expected

value

Reference point or value function can change

They can also change the perception of gains and losses: for example, gaining $10,000 from nothing is much more significant than gaining $110,000 from $100,000

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Typical prospect theory behaviors

Value

GainsLosses

Short-term profit taking in favor of long-term investments

Not accepting a sunk cost or actual loss in favor of a delayed probable loss

Risk averse

Risk seeking

Hypothetical value function curve

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Prospect Analysis: Value Function

Value

GainsLosses

Mobile Q: at what level would you sell to cut losses?

Mobile Q: at what level would you sell to capture gains?

Mobile Q: What is your target price for IBM?• Group 1• Group 2• Group 3

Threshold for selling to

capture gains

Threshold for selling to cut losses

Bottom quartile

Top quartile

Median value

Bottom quartile

Top quartile

Median value

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Richard Thaler’s Nudges

1. Incentives: putting the right incentives on the right people.

2. Understanding mappings: helping customers understand the right categories and steps.

3. Defaults: helping customers avoid the “path of least resistance.”

4. Give feedback: provide customers data on how they are doing.

5. Expect error: anticipate common errors and make the process or product error-tolerant.

6. Structure complex choices: making complex choices easier to make through understandable structures.

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