There are two reasons why I tend to be skeptical of statistics or anything else, until I have good reason to believe.
Firstly, I am not a very trusting person in my nature. My patron saint is really St John the Evangelist but some people think it should be St Thomas the Doubter. Well, that is fair enough, because, like Thomas, I am usually skeptical, but am open to being convinced by reason and evidence. (Remember that Thomas eventually believed in the Resurrection when he had seen the risen Christ with his own eyes).
Secondly, I have spent many years in Internal Audit and also many years dealing with liability claims. I have come across many frauds, scams, and dishonest claims. Wherever there is an opportunity to make a dishonest penny, or several, there is always someone there to make the most of it: and if every claim I have seen for tripping on the pavement was true, you ought to see someone fall down nearly every time you go out!
However, I do not distrust statistics in particular. Dishonest people use anything they can: facts, words, pictures, quotes, the Bible, and of course statistics. There are also many people who use statistics lazily and mislead others without intending to be dishonest, because they do not think clearly about what they really mean, or they have misled themselves into jumping to conclusions which the facts do not really support.
Yet all these things can be used rightly and in a way that informs rather than misleads. The Victorian Prime Minister, Benjamin Disraeli is supposed to have said there were “Lies, damned lies and statistics”, but the writer Andrew Lang said of someone “he uses statistics as a drunken man uses a lamp-post: for support rather than illumination”, thus blaming the user rather than the “lamp-post”. Well, I want us all to gain illumination as we use statistics whether in Risk Management or in anything else. They can help us to:
gain a sense of proportion
identify the most important issues
find what works and what does not.
If any group of people should be grateful for statistics being used correctly, that group is women!
I can remember a time when very few women drove cars, and very few drivers were women. You did not need to look at any statistics to notice that. In those days most men thought women were definitely inferior to men as drivers, whatever else they might be good at. Insurance companies accepted this as received wisdom, and charged women higher premiums than men. Nearly all comedians had a stock list of woman-driver jokes, generally about women being easily distracted by such trivia as sales adverts in shop windows, not knowing right from left, and thinking the car’s mirror was for checking their make-up. Some men thought that allowing women to drive was even more irresponsible than given them the vote. Ironically, one woman who did not drive was especially unpopular with most male motorists: the Minister of Transport in the mid-1960′s, Barbara Castle.
The cause of women’s equality was not helped by an unfortunate and highly publicised incident. There was a bus-conductress in Yorkshire, Bradford I think. (For the benefit of younger readers, I had better explain that a bus-conductor, or if female conductress, was someone who collected fares, issued tickets and maintained order on busses. Nowadays bus-drivers are expected to do all the foregoing duties as well as driving the vehicle. The change was made in the name of efficiency.) This woman was determined to become a bus-driver, and managed to get her employers to give her all the necessary training. There was then a lot of controversy as most of her male colleagues objected, putting management in a dilemma. After much debate, they let her drive. She then had three accidents in the first three days she was on the road. Whether this was due to her lack of ability, to the stress she was under with all the controversy, or just bad luck, I do not know. I do know that this single example was quoted frequently, as if conclusive proof that women should not be allowed to drive. You will observe that a single incident, or three, hardly counts as significant statistically.
Eventually women’s self-esteem was rescued, making the comedians seek other targets, by an unlikely band of champions: insurance underwriters! These unsung heroes actually knew how to collect, analyse and interpret statistics correctly. They discovered the fact that women generally had fewer accidents than men. This information led to lower premiums being charged to women-drivers, to the amazement of most men. I will not speculate as to the reasons for this difference, I merely state a fact.
Statistics have also helped the broader movement for women’s equality, by providing factual information as to the numbers of women employed in various organisations, and their levels of pay. This has provided almost conclusive proof of the existence of the “glass ceiling” in many occupations, as well as of the unequal pay for the same or similar work in certain industries. This information has not always led to the immediate rectification of the injustices, but it has at least forced Society to face the facts and stop being in denial. You may think I have just ignored the issue of multiple factors influencing human behaviour. I acknowledge that there may be causes other than discrimination to explain some of the apparent inequalities, such as women choosing to avoid certain occupations, or disabilities genuinely preventing some people doing certain jobs. However, the statistical evidence has forced employers to accept that there is a case to answer, and that it must be answered properly, not with unsubstantiated excuses.