strategic thinking in a complex environment · 8/18/2020 · strategic thinking in a complex...
TRANSCRIPT
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Strategic ThinkingIn a Complex Environment
NASMScott E Page
John Seely Brown (JSB)
Distinguished University Professor
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Music Education
Encouraging CreativityTeaching TechniqueEvaluating PerformanceHumanistic EducationCultural PluralismPublic Outreach
Ideas, Policy, and Education in Music, Foundation for the Advancement of Education in Music.
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A Moment
Known Outcomes
Known Distribution of Outcomes
Alternative Scenarios Each With Different Distributions
Partially Known Scenarios, Distributions Uncertain
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A Moment
Known Outcomes
Known Distribution of Outcomes
Alternative Scenarios Each With Different Distributions
Partially Known Scenarios, Distributions Uncertain: Complex
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Rob Lempert
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Complexity: BOAR
Between Ordered and Random
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Four Classes of Behavior
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8/17/20, 11)22 AMIMG_2711.jpg
Page 1 of 1https://mail.google.com/mail/u/0/
Design Unbound: Ann Pendleton-Jullian & John Seely Brown
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Strategic Thinking During High Complexity
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Hundreds of Studies: Algorithms (Simple Rules) vs “Gut”
Algorithms Win Big: 50%
Kahneman, Rosenfield, Gandhi, Blaser, ``How to Overcome the High Hidden Cost of Biased Decision Making,’’Harvard Business Review, 2016
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Hundreds of Studies: Algorithms (Simple Rules) vs “Gut”
Algorithms Win Big: 50%
Approximately the Same: 50%
Kahneman, Rosenfield, Gandhi, Blaser, ``How to Overcome the High Hidden Cost of Biased Decision Making,’’Harvard Business Review, 2016
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Human Biases
Escalation of CommitmentAnchoringFramingAvailabilityOverconfidence
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Gut vs Analtyics
AnalyticsFew Distinct OptionsLots of DataNovelVoice and Consensus Matter
GutExperienceTrack RecordCommon SituationFast Moving
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Goals
Better Decisions During Complex Period
Risk & Opportunity Awareness
Collective Intelligence
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Goals
Better Decisions During Complex Period
Risk & Opportunity Awareness
Collective Intelligence
Bonus: Sense of Community & Richer Self Understanding
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Part 1: Strategic Tools With Your Community
Qualitative Decision Theory
Multi-Criterion Decision Making
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Part 2: Conceptual Models
Dancing Landscapes
Multi-Armed Bandit: Value of Information
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Decision Theory
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New Program
Do Not
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Decision Theory: Certainty
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New Program
Do Not
0
$200,000, 50 students, Space, Reputation
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Decision Theory: Uncertainty
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New Program
Do Not
0
$200,000, 50 students, Space, Reputation
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Qualitative Decision Theory: Complexity
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New Program
Do Not
0
Big Outbreak
Clustered
Other?
? Regional
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New Program
Do Not
0
Big Outbreak
Clustered
Other?
? Regional
Send Home
Quarantine
Contact Trace
?
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New Program
Do Not
0
Big Outbreak
Clustered
Other?
? Regional
Send Home
Quarantine
Contact Trace
?
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Look to Your Community for Scenarios
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Possible Scenarios:Alternative Uses Test
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100,000 Straws
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16
95
1617
31
1620
1720
A B C D E F G H I J
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16
95
1617
31
1620
1720
A B C D E F G H I J
108
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Community Generated Scenarios
Quarantine All
Essential Workers
Gatherings of Fewer than X people
Tests at Cost $C
Contact Tracing Protocols
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Generate then Evaluate
Give everyone an opportunity to think of scenarios
Anonymously rank (vote up or down)
Discuss relative likelihood
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Determine Outcomes:Delphi Method
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Four Step Process
Step 1: Describe what you think could happen under each scenario
Step 2: Have someone synthesize, collect reasons
Step 3: Have people rewrite or rank reasons
Step 4: Create new synthesis
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Best, Most Likely, Worst
For each decision, consider the best case, most likely case, and the worst case.
May care more about minimizing regret than expected value
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Logic/Power of Diversity
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Portfolio: Average
8 12
4
-8
µ=5
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Average = 1,197
Average = 1,197
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Average = 1,197
Average = 1,197
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Crowd Error = Average Error - Diversity
Diversity Prediction Theorem
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Crowd Error = Average Error - Diversity
Diversity Prediction Theorem
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Crowd Error = Average Error – Diversity
2 = 5410 – 5408
Galton’s Steer
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Crowd Error = Average Error – Diversity
= BIG
Why on Complex Problems?
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Crowd Error = Average Error – Diversity
= BIG
Why on Complex Problems?
small
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Crowd Error = Average Error – Diversity
= BIG – BIG
Why on Complex Problems?
small
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Economic Forecasts 1969-2009
28,000 forecasts by professional economists6 economic indicators
Crowd mean 21% better than average economist
Mannes, A. E., Soll, J. B., & Larrick, R. P. (2014). ``The wisdom of select crowds.’’ Journal of Personality and Social Psychology, 107, 276-299.
THE WISDOM OF SMALL CROWDS 43
Figure 2. Performance of judgment strategies for the economic data in Study 1. The y-axis is
error relative to the average judge, so lower values indicate better performance. The
performance of best members is illustrated at k = 1. Curves are shown for selecting judges at
random (RAND), based on last period’s performance only (SC-R), and based on cumulative
performance (SC-C). The performance of the entire panel’s mean (AVG), trimmed mean
(TAVG), or median (MED) forecasts are shown as dashed lines.
0.70
0.75
0.80
0.85
0.90
0.95
1.00
BEST 2 3 4 5 6 7 8 9 10
MAD
of S
trat
egy
/ MAD
of A
vera
ge Ju
dge
Number of judges, k
RAND SC-R SC-C AVG TAVG MED
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Portfolio: Average
8 12
4
-8
µ=5
Predictors: Bonus
9% 9% 8%
Crowd = 22%
10%
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Multi-Criterion Decision Making
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Multi-Criterion Decision Making: Certainty
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Continue a Program?
Known Criteria:
QualityImportanceAttendanceStudent Involvement……
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One on One Tutoring: Zoom or In Person?
Criteria?
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One on One Tutoring: Zoom or In Person?
EvaluationSafetySoundTechniqueCommunity……
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Allow Community to Weight Importance
Very Important (irreparable)Moderately Important (reparable)
EvaluationSafetySoundTechniqueCommunity……
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Voice
Safety: ZOOM ++Sound: Person +Technique: Person +Community: Person +……
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Piano
Safety: ZOOM +Sound: Person +Technique: Person ++Community: Person +……
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Part 2: Conceptual Models
Dancing Landscapes
Multi-Armed Bandit: Value of Information
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Definitions
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Definitions
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Local Optima
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Dancing Landscape
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Fixed Versus Dancing Landscape
Fixed DancingLocate Global Peak Constantly Adapt
Coordinated Allow ExperimentationPast Information Useful Emphasize Newest
Peak Tweaking All Roads up from TroughKnow Yourself Community Knowledge
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Part 2: Conceptual Models
Dancing Landscapes
Multi-Armed Bandit: Value of Information
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Multi Armed Bandit
A BClose New
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Multi Armed Bandit
A B
Safe Risky
Close New
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Information Gain
A B
None High
Close New
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Growth Mind Set
B
High
New
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Takeaway #1
Within high complexity, you cannot make decisions like you did in the past.
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Takeaway #2
You have less certainty about options, how world will unfold, and implications
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Takeaway #3
Lean on your community – you need DIVERSITY – during complex periods
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Takeaway #4
Complex means perpetual novel – monitor, think, experiment
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Takeaway #5
New actions build new skills and capabilities – be biased towards action.
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Questions?