For a long time, we have all been used to the need for ever more information about everything.  It is certainly true in Risk Management, as we try to assess risks and evaluate the effectiveness of control measures.

We all know that to make sense of data we need to reduce it to a digital form so as to be able to measure and analyse it.  Looking at individual cases is often described, generally disparagingly, as an old-fashioned, anecdotal approach.  And if there is one thing you must never be it is old-fashioned. Data must be quantitative rather than qualitative.

I found it pleasantly refreshing, therefore, to hear, at a Risk Management seminar, that some experts are now challenging the prevailing thinking in this respect.

What is wrong with digitising your data?

By definition, to digitise information means to express it in mumerical form.  But the things we are interested in are not just numbers.  All accidents, complaints, customers, or whatever, are different.  Of course, we can break them into categories, by cause, type, location and so on, and thus be able to analyse the data as well as count it.  The trouble is that we tend to lose sight of the uniqueness of each item and treat all customers of a certain age and class, for instance, as the same.  Or we assume all accidents of a certain cause as being caused by exactly the same circumstances.  This way a lot of useful information gets overlooked.  People are dehumanised.

What can we do about it?

One answer is to look in depth at, at least a sample of, your data: accident reports, letters of complaint, or whatever.   Of course many of us do that.  Or say we do.  Let us be honest.  How much time do we spend on that compared with that spent looking at statistical reports?

We also need to challenge the IT people about ways of capturing qualitative information as well as quantitative.  Are not computers getting more intelligent all the time?

I now think this is another chapter I should have included in my book: “How to avoid being misled by statistics”.

Go to:  https://www.createspace.com/4767398

Or http://www.amazon.com/How-Avoid-Being-Misled-Statistics/dp/1499190484/

I must include it in my next one.

 Any suggestions on this would be welcome.