Understanding how military groups make decisions is obviously
important&endash;it can cost lives to one side or the other, or both.
As such, it is a legitimate and indeed important subject for
study.
Surprisingly, how we humans make decisions is remarkably poorly
understood. Exploring how the military approach the issue in
relatively well-defined situations which they have, in the past,
faced might help us understand how things work - or don't work! And,
perhaps, we can apply any new knowledge to less extreme situations! A
sort of intellectual "swords into plough shares"!
The Nature of Decisions
Decision:-
"...a choice between options..."
Utility Theory proposes that we make decisions to maximize
utility or usefulness
Statistical, Catastrophe and Chaos Theories indicate future
may be predictable/unpredictable as weather
long-term stable but short-term unstable, according to
climate
How can we choose between options in dynamic situations if the
future is unknowable?
Can we/should we avoid making decisions if the future is
unknowable?
How do we go about making decisions anyway?
Decision-makers' Biases
It seems that humans, complex as ever, are prey to a wide variety
of behavioural influences and
pressures when they make decisions. Ian White has identified some
of the biases which affect decisions:-
Adjustment & Anchoring. Decision Maker selects a
Datum and fits other data to it improperly
Availability. Uses only freely-available data. An event
is believed to occur frequently if it is easy to recall similar
events
Conservatism. Failure to revise estimates as frequently
as necessary
Data Saturation. Reaching premature decisions on too
small a sample and then ignoring further data
Self-fulfilling Prophecy. Values certain outcomes and
acquires and analyses only data that supports that outcome
Attribution Error. Associates success with inherent
personal ability and failure with bad luck. "When you are wrong,
you screwed up, when I'm wrong it was just bad luck"
Gambler's Fallacy. Assumes the occurrence of one set of
events enhances the probability of an event that has not yet
occurred. "I have smoked for 10 years without getting
cancer&endash;clearly I am immune, so I can go on smoking
Habit. Familiarity with one rule results in its
excessive use
Law of Small Numbers. Confidence in predictions based
on small samples with non-discomforting evidence, than in
predictions based on large samples with discomforting evidence
Order Effects. Order of information presentation
affects retention and weighting
Outcome Irrelevant Learning. Use of an inferior rule leads to
belief in results because of inability to evaluate choices not
selected
Panic. Under stress, facing many options which cannot
be evaluated, either selects at random or fails to act at all
What is a "Good" Decision?
The Causal Loop Model above shows the
dilemma of judging whether a decision can be deemed good or not. It
really all depends on your viewpoint. You can take either of two
viewpoints:-
A decision is "good" if the decision maker has taken account
of all the relevant data, has weighed up the pros and cons, and
has developed a balanced judgment
A decision is "good" of the out-turn is that which the
decision-maker intended
For instance, is a good gun one made of the best metals, finely
made, with a well machined bore and a smooth, well-oiled breech?
OR
Is a good gun one which puts the shell on the target?
Put more succinctly, is the quality of a decision in the process
or in the outcome?
For my part, I have to fall down on the side of outcome. However,
the current paradigm in Command & Control thinking centres on
process.
The C2 Decision Circle
Classically, decisions are reached by a repeated sequential
process, shown above. Start at Assess Situation, and follow the
arrows. Since the Action taken changes the situation, Assess
Situation is necessary after the change, and so the process continues
ad infinitum.
Another way of looking at this process, one which omits the cyclic
nature, is shown above. This model is employed in:-
The Estimate-a formal decision-making process in wide use by
various militaries around the world
The process shown above has a distinguishing characteristic. The
decision-maker(s) try to consider all the possible options, and to
trade-off between them in order to find the preferred option. While
this might seem logical, it is not necessarily how human's evolved to
make decisions under pressure.
For instance, who considers all the options when the tiger is only
five steps behind you?
We evolved an innately-human ability to make fast decisions under
fight-or-flight pressures. If we had not, we would not have evolved
as a species. Under such conditions, we do not consider and weigh up
all the options - that would be naive. Instead, we use our experience
of what has worked before in similar situations. We might mentally
generate options, but we will stop doing so as soon as we identify
and option that will serve the purpose. At that point we will go with
the selected option.
This process is called "satisficing".
The figure shows satisficing. Note the iteration indicated by the
feedback from "initiate" to "recognize situation cues". The initial
satisficing decision might have been wide of the mark, even for an
expert decision-maker - he or she may have read the cues wrong.
However, this is a cyclic process. As the action unfolds, the
decision-maker has expectations which can be verified by the merging
cues. If the cues are as expected, fine. If, on the other hand, the
cues are out of line with expectations, then the expert
decision-maker will reevaluate the situation and satisfice again.
So, satisficing is a decision-making process employed
instinctively by an expert under time pressure, and it "homes in" on
a final solution (as opposed to making a "big-bang" "this is the only
way" choice and sticking to it in the face of mounting contrary
evidence).
Decision Paradigm Clash
On occasions, these two styles of decision-making can come into
conflict, as shown above.
At left, naive decision-making might be undertaken by a group
of staff officers in an HQ, and they might take anything up to 24
hours or more to go round the circle - referred to as the planning
cycle.
At right, the "boss" is briefed, sometimes using CCTV, so
placing him or her under psychological pressure to make
on-the-spot decisions in full view of many subordinates. The boss
is, therefore, likely to "satisfice" or employ Recognition-primed
Decision-making as Gary Klein calls it.
The result?
disagreement, of course
the boss, using his experience may reject the advice of the
staffs and select a particular course of action. the boss
probably also decides that his staff are not doing too well.
the staff, having spent 24 intensive hours coming up with a
recommendation, feel rejected and undervalued
These military situations would find their counterparts in
boardrooms around the country, with MDs and CEOs corresponding to
bosses
Decisions and Synthetic Environments (SE)
Great potential
until now, C2 systems designed by engineers to meet what
they believe are operators needs
operators not sure what they need, unable to describe it
effectively in writing, engineers have different viewpoint...
C2 technology based on Naive Decision-Making Model
each process supported by technology as though it were
alone
i.e. no concept of system, team or learning in the design
SE/VR. (Virtual Reality)
New concept.
Engineers create SE within which operators may form teams,
employ synthetic "technology", tackle variety of situations
Result. Operators:-
a) design own, team-based systems
b) develop/train cohesive operational team
Decision-making - Man or Machine?
For set-pieces, prescribed decisions are feasible:-
area air defence, known incoming weapon systems
saturation bombing, non-retaliating enemy
In volatile situations, short time horizons of predictability,
chain from cause to effect unclear
less amenable to machine decision
In the following 3 examples, all derived from, or based on,
newspaper accounts of Desert Storm, are decisions best suited to
man or machine (i.e. software algorithm)?
This diagram shows how different parties to a conflict might
represent the same potential target. So, a military target of Roads
and Bridges might be intended to deny the enemy freedom of action
and/or weapon replenishment. Enemy propaganda could easily, even
perhaps justifiably, represent attacks on Roads and Bridges as an
attack on refugees, bullied innocents who would be unable to flee the
conflict. With CNN listening for every opportunity, that sort of
propaganda can wreak havoc with military strategies and tactics.
This figure shows how military planners might try to reconcile the
issue of politically, or environmentally, sensitive sites which are
also military targets. In particular the approach might consider the
employment of precision weapons with little or no collateral damage
risk.
Finally, in this group of three, we have a classic decision tree.
This one compares the value of standoff Precision Guided Munitions
(PGMs) i.e. laser-guided bombs launched at a distance, with old-style
iron bombs delivered from close to the target. The comparison starts
with establishing a comparative outcome measure in the right hand
column of boxes.
For instance, the worst outcome, -100, arises when a PGM
equipped aircraft is lost having failed to reach the target. This
is a total lose-lose of an expensive asset.
The next worst outcome, -95 is for an iron bomb aircraft lost
to enemy fire. This is also lose-lose, but of a less expensive
asset - hence the slightly better score
The top score, 50, is for a successful attack by an iron-bomb
- win-win using the cheapest weapon
In this simple example, for which I made up the numbers of course,
the outcome is strongly in favour of standoff PGMs - surprise! (What
use is a complex method of 'deciding' what you already knew? and, on
what basis would you select the numbers to put in the right-hand
column boxes?))
So, have you made your choice?
Which of the three decision-making methods is best suited to
humans, and which to machines?
Come to that which, if any, is valuable, or would you rate
them suspect?
And that is one of the main issues with decision-methods
Individuals and groups make decisions differently
Experts make decisions differently from naive beginners
Experts make decisions in different ways according to the
urgency
Experts under pressure "satisfice"
Homo sapiens evolved by satisficing&endash;remember, who
trades off options when the tiger is five steps behind?
We do not understand
yet how we comprehend and make decisions
