Risk versus Uncertainty in Forecasting

Summary : Risk is when an outcome’s probability is known. Uncertainty is when an outcome’s probability is unknown. Know which is which before you weigh your decisions

 

Risk is when an outcome’s probability is known.  Uncertainty is when an outcome’s probability is unknown.  Know which is which before you weigh your decisions

 

Timing is one of the most difficult problems of decision making.  Wait too long to get all the facts together and opportunity is lost, as it escapes to those who beat you to the punch.  Move too early and what seemed to be an opportunity may be a mirage.  The finer your ability to resolve risk from uncertainty and the better your ability to grade the facts at hand, the better will be your ability to time your decisions.  Andy Grove once said that he never regretted making a decision; he only regretted not making them earlier.  That is the paradox of decision making.  No matter how good you get, once you know a decision must be made – it always could have been made earlier.  But you couldn’t have known to make it without the information.  This is why Andy is such a legend in decision making: his timing was as good as it gets.

 

The first principle is to weigh the facts at hand: what are facts, what are probabilities, and what are faiths (remember you can’t have faith if you know).  Facts have no assigned probability.  Information that you can assign a probability is a step down in quality.  For example, today’s weather is a fact.  As for tomorrow’s, there may or may not be an assignable probability.  But once tomorrow is over, it will be a fact.  An investment is when you know the odds favor you.  A gamble is when the odds don’t favor you.  Information is actionable.  Data is not.  Once information becomes known, it ceases to be information and becomes data.  For example, if you knew which stocks would rise tomorrow . . . that would be information, as you can act by buying these stocks.  But once tomorrow passes, this information will be known by everyone – making it data to be used in search of more information.  Uncertainty is where no probability can be assigned.  This is where faith comes into the decision-making process.  Faith is based on beliefs that come from either experience or are passed down from others you respect.

 

For example, we can assign a specific probability to flipping a coin.  We cannot assign a probability to the continuance of Moore’s Law or Murphy’s Law as there are parts to the underlying mechanism for their continuance that we cannot comprehend with certainty.

 

Let’s look at Intel and how it has institutionalized its decision making process as an example of a great success formula.  They have faith in both Moore’s and Murphy’s Laws.  Murphy’s Law drives how they approach manufacturing.  They never know where Murphy will strike, but by mistake-proofing their operations, they systematically eliminate the potential for Murphy to raise his head.  As for Moore’s Law, the odds are high that it will continue because it has always continued.  The known facts, first documented in Gordon’s paper, are that it is made possible by shrinking critical dimensions.  Faith comes in where one must believe in the continuing ingenuity of the engineers and scientists in our industry to make this possible and then the ingenuity of the designers to use the added transistors in a way that will appeal to those who buy ICs and ultimately, electronics.  It is a general rule that Faith turns to information and information turns to data.  Seldom do things flow the other way.  Intel applies this rigorously.  So when they do have surprises, they are able to quickly align an organization of thousands around a systematic vision based on their deep understanding of decision making.

 

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