Alternative Futures
for Strategic
Foresight
Olaf J Groth, PhD
Global Professor
Management, Strategy, Innovation & Economics
Discipline Lead
Strategy, Innovation & Economics
Founding Director
Center for Disruptive Innovation
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A future of change
http://www.youtube.com/watch?v=2OZ0F7qpy0E
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Why worry about the future? (cont’d)
“500 dollars? And no keyboard?
Business people won’t like it.”
– Steve Balmer about the impending
iPhone launch, 2007
http://www.youtube.com/watch?v=eywi0h_Y5_U
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Why worry about the future? (cont’d)
“Anyone who thinks the
ANC is going to run South
Africa is living in cloud
cuckoo land.”
– Margaret Thatcher, 1987
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Why worry about the future?
“There is no reason for
any individual to have a
computer in their home.”
– Ken Olsen, President of
DEC, 1977
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The expert problem
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Things coming out of left field is becoming the new normal
US Oil Drilling Forecasts 1980-1990 by Major Oilfield
Equipment Group
Active Rigs
Forecast I
8000
7000
Forecast II
6000
Forecast III
5000
4000
3000
2000
Actual
1000
1978 ‘79 ‘80
‘81 ‘82
‘83 ‘84
‘85
‘86
‘87
‘88 ‘89 ‘90
Year
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Can the future be
assessed by looking
at historical data?
What will the global economy be like in 5 years?
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Absent data, our brains fill in the gaps
Actor-observer bias / Ambiguity effect / Anchoring / Attentional bias / Availability cascade / Availability
heuristic / Bandwagon effect / Base rate fallacy / Beneffectance / Bias blind spot / Capability bias /
Choice-supportive bias / Clustering illusion / Confirmation bias / Congruence bias / Conjunction fallacy
/ Consistency bias / Contrast effect / Cryptomnesia / Déformation professionnelle / Distinction bias /
Dunning-Kruger effect / Egocentric bias / Endowment effect / Extreme aversion / False consensus
effect / False memory / Focusing effect / Forer effect / Frame blindness / Framing / Fundamental
attribution error / Gambler's fallacy / Halo effect / Hawthorne effect / Herd instinct / Hindsight bias /
Hyperbolic discounting / Illusion of asymmetric insight / Illusion of control / Illusion of transparency /
Illusory correlation / Impact bias / Information bias / Ingroup bias / Irrational escalation / Just-world
phenomenon / Lake Wobegon effect / Loss aversion / Ludic fallacy / Mere exposure effect / Moral
credential effect / Need for closure / Neglect of prior base rates effect / Neglect of probability /
Notational bias / Observer-expectancy effect / Omission bias / Optimism bias / Outcome bias /
Outgroup homogeneity bias / Overconfidence effect / Planning fallacy / Positive outcome bias / Postpurchase rationalization / Primacy effect / Projection bias / Pseudocertainty effect / Reactance / Recency
effect / Regression toward the mean disregarded / Reminiscence bump / Rosy retrospection / Selection
bias / Selective perception / Self-fulfilling prophecy / Self-serving bias / Status quo bias / Stereotyping /
Subadditivity effect / Subjective validation / Suggestibility / System justification / Telescoping effect /
Texas sharpshooter fallacy / Trait ascription bias / Unit bias / Von Restorff effect / Zero-risk bias
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.
.
…
…
…
…
…
…
…
…
Biases are preferences or tendencies
that determine
how we look at the future by
influencing
our approach and its outcomes.
anchoring
anthropic bias
attributional bias
Barnum effect
base rate neglect
behavioral confirmation
belief perseverance
bias blind spot
clustering illusion
confirmation bias
conjunction fallacy
contrast effect
cultural bias
dilution effect
disconfirmation bias
egocentric bias
endowment effect
expectancy effect
experimenter's regress
false consensus effect
framing effect
fundamental attribution error
gambler's fallacy
group-serving bias
group attribution error
halo effect
hindsight bias
hostile media effect
hyperbolic discounting
illusion of control
illusion of validity
illusory correlation
impact bias
infrastructure bias
ingroup bias
just-world phenomenon
Kuleshov effect
Lake Wobegon effect
logical fallacy
loss aversion
media bias
memory bias
mere exposure effect
misinformation effect
negativity effect
negative perception of the color
black
notational bias
outgroup homogeneity bias
overconfidence effect
pathetic fallacy
peak-end rule
physical attractiveness stereotype
planning fallacy
picture superiority effect
positivity effect
preference reversal
primacy effect
priming
projection bias
pseudocertainty effect
pseudo-opinion
publication bias
recency effect
regression fallacy
reporting bias
risk-aversion
rosy retrospection
sample bias
selection bias
selective perception
self-deception
self-serving bias
spacing effect
statistical bias
status quo bias
sunk cost effects
tunnel vision
trait ascription bias
valence effect
Von Restorff effect
wishful thinking
worse-than-average effect
Zeigarnik effect
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EXERCISE: Identifying biases (cont’d)
Which country will be the third
largest in the world by 2050?
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Identifying biases (cont’d)
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Identifying biases (cont’d)
Pew Research:
India, it is projected, will secure global demographic primacy by 2050. The population
of India is expected to increase by more than 400 million from 2010 to 2050, to 1.6
billion.
Meanwhile, the population of China may increase by only 25 million, remaining at
about 1.4 billion. In 2050, India alone may be home to nearly as many people as China
and the U.S. combined. The U.S. is projected to add 89 million residents by 2050.
However, the U.S. is likely to be displaced by Nigeria as the third most
populous country. All in all, Nigeria’s population is projected to grow about 176
percent, moving it from the seventh-most-populous country in the world to the
third.
By 2050, 25 percent of the world’s population will live in Africa, up from 15 percent in
2010.
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EXERCISE: Identifying biases (cont’d)
http://www.youtube.com/watch?v=vJG698U2Mvo
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EXERCISE: Identifying biases (cont’d)
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The risks of not recognizing biases
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Why worry about biases for enterprise decisions?
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So, what do we do?
Comfortable,
yes.
Comfortable,
yes. For a short time.
For a short time.
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A good thing.
A good
And probably
notthing. Probably not enough.
enough.
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The “typical” strategy planning process
Make Initial
Hypothesis
Gather a
Known Set of Revise and
IndustryNarrow Your
Specific Data Hypothesis
Gather
Narrower Set of
Data to Validate
Hypothesis
Update
Model
Make
Recommendation
Dismiss Outliers and
Anomalies
Often based on same data everyone else has; hard to find truly differentiated source of
advantage.
Usually assumes incremental or linear changes in the market model; 10-20% variations.
New ideas are constrained by historical experience and knowledge.
Contextual changes are usually ignored.
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A more future – robust front end
Scan for anomalies.
Explore STEEPLE
uncertainties.
Look for analogies
outside the known
Gather a
Known Set of industry domain.
IndustrySpecific Data
Create Multiple,
New
Hypotheses and
Models
Research and
Discussion of
Directional
Implications
Develop a
Portfolio of
Recommendation
s
Less
constrained
observation
and analysis
Validation
of Specific
Strategy &
implementa
tion plan
Develop logic of multiple hypotheses before over-investing in research and modeling one
Don’t limit yourself to what everyone else knows or is already looking at.
Create a space for a new ideas in the discussion, or else you won’t discover or recognize it if
and when it happens.
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Seeing emerging patterns
Time
1 year
20 years
Scenario
Planning
Scenario A
Scenario C
Observed
Trends and Events
The trends and events that signal how an industry is
evolving can be overwhelming, seemingly
conflicting, and even paralyzing, when taken on
one-by-one.
Scenario B
Scenarios help relate and cluster these trends and events together
into broad patterns, organizing them into logical, higher-level
frameworks. These frameworks allow an organization to
understand and address change more comprehensively—at the
sources of the change—and align the perspectives of key
decision-makers.
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Principle 1: Explore and
gather a diverse range of
views
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Principle 2:
Take the long
view
Principle 2: Take the long view
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Principle 3: Connect the dots
“The most important failure
was one of imagination.”
– 9/11 Commission
Report Executive
Summary, p. 9
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Use interviews to gather multiple perspectives
Principle 4: Avoid organizational myopia
Contextual
Environment
Industry
Organization
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Principle 5: Examine through a caleidoscope
Legal &
Ethical
STEEPLE
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Principle 6: Look beyond the obvious
headlines
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Principle 7: Understand systems of systems
Driving forces: not obvious, more remote
forces in the wider macro-environment.
 The fundamental sources of future change
 Causes vs. articulation of change.
Examples:
• Weather systems and ocean currents
• Economic systems and oil prices.
What would cause a shift in oil
prices? …And what would be the
cause of that cause in turn?
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Davos MBA summit 2015
Sample driving forces for the future of work
Zero
marginal cost
society
Industrial &
econ dev
policies
Economic resources
for IT investment
Faith-based
initiatives
Capital’s
share of
income
Academic
humanism
Labor standards
& cost
Population
demographics
Reservation wage
AI v. brain science
advances
Digital natives v.
digital divide
Consumer preferences for
man-made & human touch
Role of labor
unions
Status of work in
society
Safety and eco
regulations
Education
reforms
Leisure
offerings &
affordability
Craft Renaissance /
DIY
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Take stock of the team’s perceptions
Exercise
• Think about What kind of innovation
economy will emerge in China by 2025?
• If you get there quickly, stretch yourself with 5-7
more
• As individuals and a group, brainstorm a
minimum of 20 driving forces for your scenario
focal question
• Invoke recent readings, experiences, and insights
• Consider drivers of drivers
• Remember that difference is an ally, not an
enemy
• Be critical of your own ideas, but go easy on
others
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Debrief: Identifying driving forces
Take stock of the team’s perceptions (cont’d)
Debrief

What surprised you?

Were you able to get beyond the obvious? If so, how?

How did your team work together?

As a team, what didn’t you do that you should have?
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Prioritizing critical uncertainties
Focus on what matters most: critical
uncertainties
Identify driving forces with greatest impact and uncertainty by
categorizing them in terms of quadrants.
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Value your diversity
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2
3
4
5
6
7
8
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10
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13
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16
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Geographic Scope of Outbreak
Length of Time Period Until Outbreak
Pace of Pandemic Growth
Nature of Virus
Mortality Rate
Coordination Among Federal, Local, & Private Sectors
Effectiveness of Early Pandemic Detection Systems
Degree of Global Coordination & Collaboration
CDC Pandemic Influenza Preparedness Plan
Capacity of US Hospitals
Transportation, Energy & Distribution Infrastructure
Awareness/Education of Citizens
Fear or Perceived Seriousness of Threat
Public Attitude Toward Pharma
Compliance with Govt Containment Efforts
Insurance Coverage
Patients Willingness to Pay Out of Pocket
Overall Zeitgeist and Social Mood
Concurrent Shocks and Threats
Personal Mobility
Variability of Uncertainty
4.2
2
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3.7
8
14
3.2
18
2.7
13
16
20
15
11
4
3
5
1
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10
7
12
6
9
2.2
17
1.7
2.5
3.0
3.5
4.0
4.5
Importance of Uncertainty
5.0
5.5
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How we prioritize





Each team member selects by themselves
his / her most critical and impactful
uncertainties.
Each team member distributes a total of 25
points among the 80 driving forces, with no
more than 5 points allocated to any one
Use a marker to write your individual point
allocations up on the flip chart by the
selected drivers
Discuss as a team
Tabulate the combined vote totals for all
candidates, and draw a circle around the top
5 you identified as a group
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Alternative futures on energy innovation
for a client
“Middle Age”
High Concept and Thumbnail of this Future:
Nationally Centralized Synthetic Innovation
Scarce
Global Supply of
High Concept and Thumbnail of this Future:
Frugal Custom Innovation
“Jugaad Age”
Global Access to and Demand for Capital and Talent
Rudimentary,
Restricted &
centralized
“Colonial Age”
High Concept and Thumbnail of this Future:
Transnational Megaproject Innovation
Natural Resources
Sophisticated,
Free & Diffused
Abundant
High Concept and Thumbnail of this Future:
Massively Distributed Luxury Innovation
“Renaissances Age”
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Futures trajectories
Global ecoFragmented
Public resistance to trade agreements
Energy generation paradigm
Oil price skyrockets
Decentralized
nomic integration
Centralized
Unified
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Building the path with uncertainties
and pre-determineds
The narrative is told
as well as through
through the critical
the pre-
uncertainties that
define the
differences between
scenarios
determined
elements that are
common to each
scenario
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Determining what it means for the
business
What are the implications of the scenarios for the industry
What are the options for your client organization in response to the Strategic
Question?
FSWOT – Futurized SWOT
5FF – Futurized Five Forces
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What are the implications of the scenarios for your industry or domain?
Starting outside-in with our industry
How does your 5F change in each scenario?
What is the robust “futurized” 5F across all scenarios?
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… And inside-out with our organization
How does your SWOT change in each scenario?
What is the robust “futurized” SWOT across all scenarios?
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Crafting actionable moves to build
strategic optionality
Options portfolios should consist of options in different classes according to scenario
requirements for a more robust, “futurized” overall strategic options slate
Scenario
#1
Core/Sat
Core
Scenario
#2
Scenario
#3
Scenario
#4
Satellite
Bet
Robust
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Systematically building options ladders
with early indicator triggers
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What will
stop you?
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Thank you
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