Understanding forecasting and realising its limitations is a key task in planning new strategies

1. Forecasting
Creating and Presenting Strategic Plans

2. Forecasting
Difficult
Vital
Approaches
Numbers Descriptive Adaptive Models

3. Forecasting
Numbers

4. Numbers
Precise estimates
http://www.worldbank.org/en/publication/global-economic-prospects/summary-table

5. Numbers
February 2015
There are considerable uncertainties surrounding the projections of GDP growth and CPI inflation published in the Inflation Report. This
uncertainty is reflected by the presentation of projections as fan charts. The fan charts are derived from the MPC's projected probability
distributions for the annual rate of CPI inflation and four-quarter growth rate of GDP.
Estimates with probabilities
http://www.bankofengland.co.uk/publications/Pages/inflationreport/irprobab.aspx
6%

6. What’s to be done?
…The MPC’s recent forecast performance has been noticeably worse than prior to the crisis,
and marginally worse than that of outside forecasters. The forecast errors of the MPC have
been characterized by persistent over-prediction of output growth and persistent under-
prediction of CPI inflation…
….The central model used by staff for processing news and judgments .. is a Dynamic
Stochastic General Equilibrium (DSGE) model with a relatively parsimonious 16 variables at
its core…
…there may be too few incentives and opportunities for staff to seriously challenge the MPC
…Some former MPC members… reported that they encountered difficulties getting divergent
points of view to be seriously considered in the forecasting process.
Report on Monetary Policy Committee’s Forecasting Capability, 2012
Source: REVIEW OF THE MONETARY POLICY COMMITTEE’S FORECASTING CAPABILITY Report by David Stockton
http://www.bankofengland.co.uk/publications/Documents/news/2012/cr3stockton.pdf

7. The ECB record
Date Event ECB Forecast
9 August
2007
BNP Paribas ceases trading in 3
US hedge funds specialising in
US mortgage debt
‘The outlook for the external environment…remains
favourable’
15
September
2008
US Government allows Lehman
Brothers to go bankrupt
‘…..growth in the world economy is expected to remain
relatively resilient.’
2 April 2009
G20 Summit agrees $5tn fiscal
expansion of $1.1tn to help IMF
‘….However, the risks to global activity appear to be broadly
balanced.’
9 May 2010
Governments declared insolvent:
Financial aid to Greece debt
crises
‘Global economic prospects remain subject to high levels of
uncertainty. On the one hand, there are concerns that the
financial market turmoil could have a greater impact on the
real economy, as well as fears that protectionist pressures
could intensify ….On the other hand, there may be stronger
than anticipated positive effects due to the decrease in
commodity prices…
5 August
2011
America’s debt loses triple A
status
Looking ahead, the expected gradual retreat of some adverse
transitory factors should support world economic activity in
the second half of the year.…. In emerging economies, the
growth outlook remains buoyant…’
https://www.ecb.europa.eu/pub/economic-bulletin/mb/html/index.en.htmlSource:

8. Forecasting: An astonishing record of complete failure
2001: The accuracy of economic forecasts in the 1990s
1. All much the same: IMF, World Bank and private forecasters.
2. The predictive record of economists was terrible.
“The record of failure to predict recessions is virtually unblemished.”
An astonishing record – of complete failure By Tim Harford:
Source http://www.ft.com/cms/s/2/14e323ee-e602-11e3-aeef-00144feabdc0.html
The accuracy of economic forecasts from 2007
2008: no recessions in 2009: most of world.
2011 Spring: no recessions in 2012:15 occurred.

9. Conclusion on Forecasting Numbers
Dreadful

10. Forecasting
Descriptive

11. Why?
‘If you know all possible conditions of a physical system you can, in theory, project its
behavior into the future. But this only concerns inanimate objects. We hit a stumbling block
when social matters are involved. It is another matter to project a future when humans are
involved if you consider living beings and endowed with free will. …However. if you believe
in free will you can’t truly believe in social sciences and economic projection. You cannot
predict how people will act….
… In orthodox economics, rationality became a straitjacket. Platonified economists ignored
the fact that people might prefer to do something other than maximise their economic
interests. This led to mathematical techniques such as ‘maximization’ or ‘Optimization’ on
which Paul Samuelson built much of his work. I would not be the first to say that this
optimisation set back social science by reducing it from the intellectual and reflective
discipline that it was becoming an attempt be an ‘exact science’. By ‘exact science’ I mean
a second rate engineering problem for those who want to pretend that they are in the
physics department - so-called physics envy. In other words an intellectual fraud.’
Source: Taleb, N. N. (2007), The Black Swan: The Impact of the Highly Improbable, Penguin books.
2007: Published: Before the banking crisis
Seismic Shocks

12. What’s to be done?
‘As a result of demographics, the Soviet Union thus faces internal problems for which
communism has no answers. It will have to retrench either industrially or militarily, or it
will have to reform the collective farm, which can hardly be done without political
convulsion. It cannot escape the rising tensions between the populations of a
developed European Russia and the fast-growing populations of an Asian Russia.
Within the next twenty five years, the Soviet Union will be faced with the same kind of
racial, ethnic, religious and cultural tensions that have split apart all other nineteenth
century empires since World War II.’
Drucker, P., (1980), Managing in Turbulent Times, p. 90 Heinemann, London.
1980: 11 years before the end of the Soviet Union December 1991

13. Process and structure
Process: listening to people
No figures or mathematical models
Unfairness: Poverty, food, religion, regions, race

14. Forecasting
Adaptive Models

15. Adaptive models
Adapt to change
Build ‘What if’ scenarios
Discussion before numbers
Disruptive change

16. Stage 1: Descriptive
Just words
Scenarios
Those involved
Group diversity
Listening

17. Sales 201X to 201Z
By Product
By Territory
By Customer
Stage 2: Adaptive Model
Sales 201X to 201Z
By Product
By Territory
By Customer
Ratios
Profitability
Assets
Liquidity
Leverage
Income Statement
For Firm
Balance Sheet
For Firm
Cash Flows
For Firm
Sales 201X to 201Z
By Product
By Territory
By Customer
Discussion
leading
to this
Expected
Best
Worst

18. For each scenario
A commentary on risk

19. The end