The document outlines the rules and lessons from the Marshmallow Tower game, emphasizing teamwork and rapid prototyping. It discusses broader findings related to innovation, highlighting the high failure rate of new products and the ineffectiveness of current innovation strategies. Key insights include the importance of diverse skills, the need for emergent strategies, and learning through action to foster effective innovation processes.

1. Marshmallow Tower Game
Jay Rao
Professor
Babson

2. Game Rules
• Build the Tallest Freestanding Structure:
– Tallest structure measured from the table top surface to the top of the marshmallow.
– Structure cannot be suspended from a higher structure, like a chair, ceiling or chandelier.
– Do not search the internet for answers.
• The Entire Marshmallow Must be on Top:
– Cutting or eating part of the marshmallow disqualifies the team.
• Use as Much or as Little of the Kit – Spaghetti sticks, String and Tape:
– The team cannot use the paper bag or scissors as part of their structure.
• Break up the Spaghetti, String or Tape:
– Teams are free to break the spaghetti, cut up the tape and string to create new structures.
• The Challenge Lasts 18 minutes:
– Teams cannot hold on to the structure when the time runs out.
– Those touching or supporting the structure at the end of the exercise will be disqualified.

3. Game Summary

4. Source: Tom Wujec, Autodesk

5. Source: Tom Wujec, Autodesk

6. Source: Tom Wujec, Autodesk

7. Source: Tom Wujec, Autodesk

8. Source: Tom Wujec, Autodesk

9. Source: Tom Wujec, Autodesk

10. Who consistently performs poorly?
Source: Tom Wujec, Autodesk

11. Who consistently performs well?
Source: Tom Wujec, Autodesk

12. Why?
Source: Tom Wujec, Autodesk

13. Source: Tom Wujec, Autodesk

14. Source: Tom Wujec, Autodesk

15. Source: Tom Wujec, Autodesk

16. Source: Tom Wujec, Autodesk

17. Marshmallow Game Lessons
• Understanding known and unknown variables
• Rapid Prototyping uncovers hidden variables and their
relationships
– Fail Fast, Fail Cheap, Learn Quick, Refine and Repeat
• Diverse skills matter
• Specialized skills + Facilitation skills matters
• Incentives magnify outcomes
– Big Bang vs. Start Small
• Incentives without skills are useless
Source: Tom Wujec, Autodesk

18. Empirical findings about Innovations
75% of all new products launched
by established firms fail to make
profit. Most are yanked/killed
More than 90% of all without shaping & developing them
Innovations that were
successful started off in
Given more money & time,
the wrong direction
firms are known to pursue
the wrong strategies for a
longer period of time.
Most new innovations
are started with
access to no credit in Most of the great businesses today
good times and in bad started without a lot of VC funding or
any bank lending until 5-6 years
after they were up and running
Sources: Innosight; Amar Bhide; Barton

19. 2008 McKinsey Study Highlights
CEOs and Executives
are frustrated with their Overall dissatisfaction
efforts to jumpstart with dismal outcomes of
Innovation initiatives Innovation programs
Resources and Processes Unanimous agreement
that are applied are either (94%) that people and
underutilized or not achieving corporate culture are
scale to have a financial impact the most important
drivers of innovation
Mimicking and
Benchmarking best
practices have been
ineffective
Source: Leadership and Innovation, The McKinsey Quarterly, 2008 no. 1

20. Leading into the Future:
Managing Innovation Projects
Analytical and Emergent Strategies
(Prediction and Creation Logic)
20

21. “The Future ain’t what it used to be.”
“It is tough to make predictions, especially
about the future.”
Yogi Berra

23. Environmental Conditions
Normal Risk
• Steady and Stable
• Slowly changing, Predictable, Trends
are Evident
• Increasing Rate of Change with Some
Predictability, Foreseen Trends May Complicated Uncertainty
Appear
• Rapid Change, Little Predictability,
Many Surprises
• Chaotic & Unpredictable Complex Ambiguity
23

24. Nature of Innovation Projects
Unknown
Unknowns
Outcome
Known
Unknowns Ambiguity
Uncertainty
Known Risk
Knowns
Known Known Unknown
Knowns Unknowns Unknowns
Process

25. If you don't know where you are going, you
might wind up someplace else.
Yogi Berra

26. J. P. Guilford
(Convergent & Divergent Thinking)
Selecting the most suitable bomber pilot
candidates during WW II

27. How do you “sail” from Barcelona to
Mallorca?
27

28. Practice:
How do you “sail” from Barcelona to Barbados?

29. Environmental Conditions & Strategy
Normal Risk
• Steady and Stable
• Slowly changing, Predictable, Trends
are Evident
• Increasing Rate of Change with Some
Predictability, Foreseen Trends May Complicated Uncertainty
Appear
• Rapid Change, Little Predictability,
Many Surprises
• Chaotic & Unpredictable Complex Ambiguity
29

30. Emergent Strategy
Think Different
Think Big
Start Small
Start Several
Prototype Rapidly
Proof of Concept = Voice of Customer + Voice of Tech.
Fail Fast, Fail Cheap, Learn Quick
Pour Resources only after Proof of Concept
Celebrate Success & Celebrate Failure
30

31. Leading into the Future
Analytical Strategy Prediction Logic
• Steady and Stable Environmental Scanning
Predictive Models
Set Strategy
Project Planning
• Slowly changing, Predictable, Trends Budget & KPIs
Execution Plan
are Evident
• Increasing Rate of Change with Some
Predictability, Foreseen Trends May
Appear
• Rapid Change, Little Predictability,
Many Surprises Emergent Strategy
Think Big
Start Small
Start Several
• Chaotic & Unpredictable Prototype Rapidly
Fail Fast, Fail Cheap, Learn Quick
Pour Resources after POC
Creation Logic
31

32. How to create a firm that is good at
Emergent Strategy & Creative Logic?
• Learning by Doing
– Action vs. Analysis
• Take action to produce data and uncover variables
• Generate data vs. Using existing data
– Grounded in reality vs. Speculation
– Entrepreneurial Thought and Action
• Value Diversity and Inclusion
– Several functions and across layers
• Learn to Improvise
– Fluid and flexible processes
• Portfolio of Projects (Risky, Uncertain & Ambiguous)