178.307 markets, firms and consumers lecture 5- investment
TRANSCRIPT
178.307 Markets, Firms and Consumers
Lecture 5- Investment
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Prediction
Prediction is difficult,
especially of the future.
Neils Bohr
Danish Physicist and
Nobel Prize Winner
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Introduction
Scenario Planning involves two common elements:
– First- it is based on a heterodox view of risk and uncertainty.
– Second- it is a management approach to deal with uncertainties.
It is an approach that increases manager’s awareness of uncertainty.
– It can minimise the costs of adverse surprises.
– It can allow managers to take advantage of opportunities, otherwise not foreseen.
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Scenario Planning
Stems from two distinct pressures:
– The failure of orthodox planning and forecasting techniques in many instances.
– The recognition that human systems are complex, not simple.
Three core issues are:– Describing or predicting future
events.– Developing management or
strategic responses to these.– Limited capacity to forecast or
manage future events.
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Predicting FutureGNP per capita ($US)
Year
1960 1970 1980 1990 2000
GN
P $
US
0
5000
10000
15000
20000
25000
30000
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Predicting Singapore’s GNP
Growth path of Singapore seems largely smooth
How easy is it to predict the GNP for Singapore?
Consider the following graph
GNP per capita ($US)
Year
1960 1970 1980 1990 2000
GN
P $
0
5000
10000
15000
20000
25000
30000
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Singapore GNP- Analysis
On average, my predictions are 92.9% accurate.
BUT– I did not predict the 1985
recession– I under-estimated growth
during the 1990s– I did not predict the 1997
Asian crisis– I over-estimated growth
since then.
GNP Growth Rate (%)
Year
1960 1970 1980 1990 2000
Ann
ual C
hang
e
-20
-10
0
10
20
30
40
50
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Complex systems can’t easily be predicted
Annual Changes in GNP show big swings
Changes are largely unpredictable
Achieving a ‘smooth’ rate of change is difficult.
Sustaining high growth rates is challenging- especially as GNP grows.
Complex systems don’t follow straight lines.
They are characterised by:– Unpredictable turning points– Sudden shifts– Feedbacks– Spillovers– Gaming behaviour
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A Complex System
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Investment Failure
““The greatest danger in The greatest danger in times of turbulence is times of turbulence is not the turbulence; it is not the turbulence; it is to act with yesterday’s to act with yesterday’s logic”logic”– Peter DruckerPeter Drucker
Why did US Car Manufacturer’s “fail” in the 70-80s?
– Market share was lost to Japanese automobile manufacturers
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Firm Failures
Why did US Car Manufacturer’s “fail” in the 70-80s?– Market share was lost to Japanese automobile
manufacturers– Losses were huge- Chrysler obtained a
Government bail-out.– Prototypes failed to make it to production.– Consumer dissatisfaction with product.
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US Car Industry
Background- US Market in 60s was
dominated by oligopoly of 3 firms:
– General Motors (GM)– Ford– Chrysler
Foreign competition had little impact.
Fuel prices low.
External Factors – Steady economic
growth, stable demand.– Insulated from
competition– Low oil prices, biasing
production and design towards large cars.
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Other Factors
Corporate culture uninterested in Japanese technology.
– Inefficient management (concealed by steady growth in industry).
– High wages- a Union ‘monopoly’ sharing ‘dividends’
Ignored Factors– Demand for small cars– Production-efficiency of
Japanese manufacturing-plants.
– Tight oil-market– Middle-East instability.
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What went wrong?
– Oil prices rose in response to the two oil-shocks of the 70s.
– Consumer demand switched away from large-cars to small-cars.
– This move reinforced by US new environmental regulations.
Lack of prototypes limited reaction by US car-manufacturers.
Oil-shock seen as temporary– Oligopolies were
traditionally seen as unstable.
Market dominance considered unassailable.
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US Car Industry
How many uncertainties did US Car manufacturers ignore?
– Possibility of oil-shock– Response of consumer
demand to oil-shocks.– Demand for small cars– Competitor’s response to
new situation– New regulatory
environment
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Internal Factors
Senior Managers– Uncertainty is a complex
problem.– People adopt simplifying
procedures.– Procedures that are
successful are reused.– Poor procedures tend to
be dropped.
…many managers developed their skills in the 1950s and 1960s, an era characterized by an unusually high level of economic predictability…it was considered incompetent or unprofessional to say, ”Things could go this way – or that.”
Pierre Wack, 1985.
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Senior Managers
Adopt similar strategies that ‘worked’ in the past.
Look for similarities to past, discount differences.
Result- poor performing investments
– E.g. Ford’s large engine plant.
Anticipating surprises facing a firm is hindered by ‘perceptions of stability’.
Internal coalitions can prevent timely responses.
The longer a period of stability, the more likely a shift will occur.
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Scenario Planning
Makes managers more aware of uncertainties.
Challenges perceptions of stability. Identifies signals of a forthcoming switch. As a corporate activity, can help bring about
agreement on need for change. Scenario planning is prudent- not timid.
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Risk and Uncertainty
Many formal planning tools are based on orthodox economic theory.
Risky events are those that:– Occur with predictable
frequency– Similar to historical events– Can be assigned
probabilities.
Risk and Uncertainty distinguished by Knight.
Uncertain events occur:– Infrequently– May be completely novel– Impact is varied- dissimilar
to historical events.– Probabilities difficult to
assign- E.g. insuring space rockets against accidental destruction.
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Conventional Planning
The core problem is that conventional planning has led to managers making expensive mistakes.
Example:– Mexican Debt Crisis
Unlike the 70s, most forecaster's predicted that oil prices would rise through the eighties
Some forecasters (Club of Rome, Global 2000) extrapolated exhaustion of oil reserves.
– Club of Rome- Oil reserves would be exhausted by 1992.
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Oil Demand
Mid-point case was oil averaging $50 a barrel in the 1990s.
Even low-price case had oil averaging around $35 per barrel.
Oil companies and governments responded with synthetic fuel factories.
This turned natural gas or coal into gasoline.
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Mexico
Mexico was a “special case”— A member of OPEC Used oil receipts to fund public
projects. Borrowing programme based
on projections of oil increases. Encouraged by low international
interest rates and favourable terms of trade in 70s.
Mexico's Debt
Year
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990
Ext
erna
l Deb
t $U
Sm
0.0
2.0e+4
4.0e+4
6.0e+4
8.0e+4
1.0e+5
1.2e+5
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Mexico
Unplanned Problems:
1) Recession in OECD in 1980-1
2) Faltering oil prices3) Rises in interest rates4) Fall in terms of trade5) Capital flight, requiring
more borrowing
By 1982, Mexico unable to sustain debt-repayments.
Debt-crisis began Exacerbated by the collapse
in oil prices by mid-1985. Trade policies limited ability
to earn foreign exchange.
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Shackle’s Critique
Defining set of all possible outcomes not feasible.
Addition of new events causes probabilities to be adjusted. Unsurprising events become ‘unlikely’.
We weight events that don’t occur in the decision.
Expected payoffs depend on winning on ‘average’.
BUT- some ‘losses’ may be so catastrophic, there is no chance to rebuild profitability.
Unanticipated events- or incorrect probabilities- will distort decisions.
Expected payoffs work best in stable- not turbulent environment.
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Theory of Surprise
Scenario Planning is derived from Shackle’s theory of surprise.
Shackle proposed a different metric for uncertain events.
This would be the level of surprise attached to a future event.
Key differences:– As you imagine more
events, the surprise attached to each event does not change.
– We keep ‘losses’ and ‘gains’ separate– rather than aggregating them as a net benefit.
– We don’t give events ‘probabilities’.
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Theory of Scenario Planning
A number of scenarios are proposed.
Scenarios may be generated in two ways:
– Experts can suggest a number of cases (Brainstorming).
– Surveys (and similar) can be used to generate events.
– These events are grouped into a number of scenarios.
Use of Experts– Experts have to be drawn
from a broad field.– Experts can still have blind
spots—– Shell failed to generate any
“Egalitarian” scenarios.– Out-maneuvered by
Greenpeace over the Brent Spar.
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Experts and Surveys
Can be efficient- captures a lot of pre-existing knowledge.
Can exclude other stake-holders. Harder to get others involved.
Can create elegant, elaborate and detailed scenarios– impenetrable to anyone…
Surveys– Self-interest can affect
responses.– It is biased in favour of
conservative standpoints.– Responses can be difficult
to verify.– Drop-outs can distort the
final conclusion.– Delphi method penalises
unorthodox answers.
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What are Scenarios?
Scenarios are not forecasts or predictions.
They are more like a story. Each story is in some sense
plausible. Because they are plausible,
no scenario is regarded as astonishing in prospect.
Catastropic scenarios are rarely considered.
E.g. an asteroid crashes into Earth, flattening Singapore’s CBD.
The scenario is plausible. The scenario would have a
dramatic effect on Singapore
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Catastrophes and Scenario Numbers
Planning options are very circumscribed.
– It is an event that is difficult to manage.
– Most organizations can do little to insulate themselves from the catastrophe.
– It is too small a probability to divert resources to deal with.
How Many Scenarios?– According to Miller’s
Rule, most people can only consider 7+/- 2 “things” at a time.
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Too few?
Some organisations have gone down to 2 or 3.
E.g. British Airways in mid-90s created 2 scenarios.
Generally this is not recommended.
What are the dangers of too few scenarios?
Two scenarios lend themselves to ‘optimistic’ and ‘pessimistic’ spins.
Depending on whether people who use scenarios are pessimists or optimists, one scenario ends up being treated as a forecast.
The other scenario is discounted- even though it is equally valid.
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Three or Four Scenarios?
The problem with three scenarios is one is one can be interpreted as the mid-point scenario.
This scenario then becomes (in the employer’s mind) the ‘forecast’ and the others are discounted as ‘outliers’.
Four scenarios have no natural mid-point.
Can be easily presented (e.g. graphs) and interpreted by people who use them.
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Scenarios
Scenarios are developed and described.
Both quantitative tools (mathematical models) and qualitative tools (logical arguments) used.
Scenario planning is less reliant on mathematical tools.
Exploratory scenarios are useful to alert people to uncertainties.
By challenging current perceptions, people can be more alert.
This lessens the surprise-effect of the future.
Some suggest this is the major benefit of scenario planning.
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Strategic Scenarios
Strategic scenarios integrate management decisions (strategies) with scenarios.
Strategies are identified that are appropriate for each scenario.
Strategies are then selected that meet two criteria.
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Robustness
A strategy is robust if it generates a satisfactory result in many scenarios.– For instance, Singapore’s high savings rate is a
robust macro-economic strategy.– It helps balance the current account.– It has (historically) permitted high growth rates.– It provides a buffer against shocks.
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Robustness
Robust strategies may not generate the best outcome.
They generate satisfactory outcomes in a wide range of circumstances.
This means they are prudent strategies- they are risk averse.
They are not timid.
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Adaptable
Adaptable strategies are ones that are easily switched.
If they are recognised as inappropriate, they can easily be reversed.
The flip to this is avoiding getting locked into costly courses of action.
Another aspect is contingency planning.