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One of the messy facts of life about facts (bad pun intended) is that they are hard to work with.   There are many reasons why facts do not reveal everything you want to know about consumer tastes, price trends and anything else that success in business depends on.  These problems will not shrink in the future as Big Data takes hold and as smart buildings throw out so much information in real time.

Fortunately, a simple idea shows how to deal with much of the messiness.  All facts matter but not all facts are equally important: different sources of facts imply different weights for a fact.  I will focus on facts as numbers since, except for the added slipperiness of facts as words, as conversations, as rumours and as written reports, the same concepts applies.

Several different perspectives reveal why attaching weights to facts reduces the confusion.  In a series of posts, I will talk about weighting and context, weighting and precision of data, weighting and trade off and weighting and communication.  Here is the first:


Facts have meaning because facts are not isolated; there is no magic bullet and no secret key which reveals everything.  They exist in a context which helps to distinguish between more important facts, less important facts and other kinds of facts.

I think that many people find facts confusing because they have listened to too many debates amongst forecasters: Esteemed Mr. X says that prices will go up next year and, looking at the same sources of facts, Successful Ms. Y says that prices will go down next year.  When I listen to an analyst or forecaster, I give 0 weight to their predictions.  Instead, I listen for the story they tell, to learn about the context they are thinking of.  Do their stories reveal something that I forgot?

Sometimes, the existing facts cannot distinguish between many possible contexts.  For example, it is obvious that the high price of residential property and land could be caused by a high demand curve from consumers.  It is also possible that the high price is caused by a low supply curve.  In this case, little weight should be given to the fact of a “high price” and high weight should be given to any fact which can distinguish two contexts (e.g. facts which reveal excess demand).

Context also reveals omissions.  Omitting a relevant fact means giving it an excessively low weight of 0.  Therefore, recognizing when others omit a fact is a great opportunity for you.

Surprising facts are more important.  It can be tempting to ignore them, since explaining a surprise creates work.  Facts which explain surprises should be given a big weight because they prove how badly you misunderstood something.

It is easy to assign a weight if you already know the answer but do not fall into that trap because, if you already know the right answer then you would not need any facts.