Adam Gordon on Quality Industry Foresight

1. Generating Quality
Industry & Policy Foresight
for Emerging Markets
Adam Gordon

2. 1. Quality in
foresight, a
half-dozen
thoughts
2. Emerging
markets,
SA 2030

4. Forecast failure
“Before man reaches
the moon your mail
will be delivered
within hours from
New York to Australia
by guided missiles. We
stand on the threshold
of rocket mail” ‐‐
Arthur Summerfield,
U.S. Postmaster
General, 1959

5. Housing market 2004-2013
 “Robust demand will require producLon
of 2 million new housing units a year.
 “The naLonal homeownership rate will
exceed 70 percent by 2013.
 “Home price appreciaLon will average
5% a year 2004‐2013.
 “Mortgage originaLons are projected to
average nearly $3 trillion per year.”
The Next Decade for Housing and Mortgage Finance (2004‐2013)
Homeownership Alliance: www.homeownership.com Report available at
www.freddiemac.com/news/pdf/

8. The cost of poor foresight:
Poor decisions:
business, economy, public policy
environment, defense, etc.

10. ‘Levels’ view of future uncertainty
1 2
1. Low uncertainty. Clear
view of the future. A
Dependable outcome
B
2. Limited set of possible
C
future outcomes, one
of which will occur
3 4
3. Outcomes
indeterminate, but
bounded in a range ?
4. A limitless range of
possible outcomes.
HUGH COURTNEY ET Al; 2020 FORESIGHT, HBS PRESS, 2001

11. Chapter 1. Forecast Intentions
Chapter 2. Quality of Information
Chapter 3. Bias Traps
Chapter 4. Zeitgeist & Perception
Chapter 5. User Utility
Chapter 6. A DEFT View of Trends
Chapter 7. Limits of Quantitative Forecasting
Chapter 8. A Systems Perspective
Chapter 9. Anticipating Alternative Outcomes
Chapter 10. Case Studies
Chapter 11. Quality in Foresight ‘Cheat Sheet’

12. 1. The limits of sector experts
Chapter 3

13. 2. Customer is king of the future
‘Tech push vs. Chapter 5
Consumer pull’

14. 3. Limits of trend extrapolaYon:
Chapter 6
underesLmate
overesLmate
‘

15. 4. Extrapolate the trend,
disbelieve the outcome
Turners &
Driver
FricYon
Outcome 1
Blockers
Driver Enablers Trend Outcome 2
Driver Outcome 3

16. 5. Limits of quant forecasYng:
The turkey problem
Chapter 7
TALEB: THE FOURTH QUADRANT: A MAP OF THE LIMITS OF STATISTICS [Edge, 2008]

17. “History doesn’t walk, it jumps.”

18. Game Changers (wild cards, black swans)

19. ‘Well Behaved’ vs. ‘Badly Behaved’ change
‘Predictable’ environment,  Uncertain tech evoluLon
steady evoluLon from the
present:  Uncertain demand for new
products & services
 InformaLon rich
 Uncertain evoluLon of
 Not prone to tech upheavals
legislaLve environment
 Stable regulatory environment
 Unstable macro‐economic
 ell established markets
W condiLons: inflaLon, interest
rates, currency
 Stable players. High barriers
 Shihing social values, mores,
 Consistent demand
preferences, orientaLons
 No great social pressure
No steady evoluLon

20. ‘

21. Chapter 9
Point predicYon
Scenarios
ANALYSIS

22. Exploring the cone of plausible uncertainty
?
present
Adam Gordon

23. A testbed for decision‐makers:
Stress‐tesYng decisions
The Sixth Sense
Vd HEIJDEN ET Al; THE SIXTH SENSE, WILEY, 2002

24. Not a scenario set

25. 6. The limits of future‐advocacy
AdapLve vs Visionary foresight
(Future aligning vs. Future influencing)
MetLife, Aids 2025
Arup, Ecoresorts Tanzania 2025

26. ImplicaYons for emerging markets,
views of SA 2030
1. Expect badly‐behaved change
2. PracLce quality in foresight. No head‐in‐the‐sand, but
severe limits on predicLon (incl. limits of experts)
3. Respect consumers/adopters, they determine the future.
4. Disrespect trend extrapolaLon. Apply DEFT
5. Respect limits of quant modelling. Don’t be the turkey
6. Know when we can influence vs. when we must adapt.

27. Adam Gordon
adam.gordon@futuresavvy.net
hop://futuresavvy.net
c. 083‐745‐4580