One useful trick in dissecting a complex problem and performing
thorough analysis of it is what statisticians called

Factorial Experiment.

Intuitively, in analyzing an phenomenon, once
one identify some underlying key factors and their possible levels/values, one
can generate exhaustively all possible combinations of these factors and
values.

Often, with such a brute force exercise,
one finds some surprises of missing cases which have not been noticed
previously.

To appreciate what the techniques is, let us look at the smallest
examples when there are two factors with each taking possibly two distinct
levels/values. Thus, in total, they
constitute 2 by 2, or 4 cases.

Professor Daniel Kahneman has the following discussion of decision
makings with what he called “the

*fourfold
pattern*” in his book

Thinking,
Fast and Slow.

He noted two key
factors in making decisions with risks: one factor is the perceived value of
the outcome which can be

*gains* or

*losses*.

The second factor is the likelihood of the outcome which can be high or
low.

Four cases or patterns can thus be
identified:

- High probability of gains
- Low probability of gains
- High probability of losses
- Low probability of losses

Now, one can systematically analyze easily the behavior of
people when they are in each of these situations. I bet you would agree that people tend to be
risk-averse (i.e., prefer certainty) when in situation 1 and 4, and be
risk-seeking (i.e., prefer gambling or taking a chance) when in situation 2 and
3. Kahneman’s examples include: being
risk averse for case 1 and 4, the acceptance of unfavorable settlement when
there is a 95% to win $10,000 and 5% chance to lose $10,000, respectively. The formal is the reason why many settle a
law suits even when there is a chance to win much bigger and the latter is the
reason why insurance business exists and why people buy insurance even when it
is overpriced. And being risk seeking for
case 2 and 3, the rejection of favorable settlements, when there is a 5%
chances to win $10,000 or 95% chances to lose $10,000. The former is the reason why gambling
business exists and the latter is the reason why some people refuse to be
relocated during disasters or eminent domain cases.

I am sure you can relate or find more interesting examples
and observations using such fourfold pattern or factorial design trick. Here are two interesting ones to get you going.

Two decades back, I heard in a Broadband Networking Conference
what I thought was the best characterization of the difficult notion of “

*virtual*”.

At the early part of his keynote speech,

Bob Kahn, one of "

*the fathers of the Internet*" (along
with

Vint
Cerf), drew on a transparency a two by two grid.

In one dimension, he noted the factor of

*visibility* (of an object) which can be
visible, or invisible. And in the other dimension, he noted the factor of

*existence* which can be yes (is there),
or no (is not there).

While we are
familiar with the physical world where objects are visible and there,
networking researchers have created long ago a world of

*virtual* objects and resources which are

*visible* but

*not there*!

This is actually one fundamental reason why
Internet-based services can be inexpensive but more volatile.

Now I
think you can understand easily and intuitively what all these

*virtual xyz’s *(world, game, reality,…) you
have been hearing about are.

In closing, let me give you one more example of fourfold
pattern. In my previous life as a
manager, one report of mine related the following quiz to me during our annual
performance review discussion. He asked
“How would you rank order the following four types of employees?”

- Smart and hardworking
- Stupid and hardworking?
- Smart and lazy?
- Stupid and lazy?

His insight is that *stupid
and lazy* is preferable to *stupid and
hardworking* since the latter produces far greater negative impact and
rework to the team! Can you guess which
type of employees is he?

Talk to you soon!

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