The allure of statistics

One of the reasons I started J2 Research is because of our focus on qualitative methods. I have trained in both quantitative and qualitative methods and actually enjoy them both. They do different things. Quantitative methods are great for big picture understanding. For example, how many people in a country, how many of different ethnicities, religions, or ages. Or in the workplace, quantitative methods can quickly tell us how many people hired, fired, or retired. All very interesting numbers that can quickly tell us something. And this is their appeal, their quickness, their appearance of certainty, and perhaps of the aura of math and science and objectivity.

Meat (qualitative) and bones (quantitative)

But they don't always do such a good job at telling us the whys, the hows, the feelings and the thoughts of the individuals behind the statistics.  I conceptualize this as the quantitative methods provide the bones while the qualitative methods provide the meat. They provide that deeper, richer, more substantial material about a subject.

Interestingly, even the New Scientist, a weekly science magazine, in their 12 February issue, wrote an editorial about statistics and cautioned, "see any percentage in a headline and you should start asking questions." In the same issue, there is an article by the editors of an online mathematics magazine, Plus, that takes medical statistics to task. Freiberger and Thomas note, "Statistics can be notoriously slippery, easily misused by the unscrupulous or misinterpreted by the wary."

I couldn't agree more! It is so easy to be bamboozled by numbers! Statistics are the output of a process full of choices and decisions made by humans. So, let's say, we are interested in how happy workers are, we would start by thinking about happiness. What is 'happy'? How would we measure it? Is it how many times a person smiles? How do we tell the difference between nervous smiles, polite smiles, and happy smiles? What if we asked a person to rank how happy they are with the work? Should we ask what aspects of their job they are happy with? Happy with their colleagues, physical environment, control over tasks etc? The level of detail and the way in which the questions are asked, the way answers are structured and then the way in which the statistics are compiled and reported can all affect the outcome. It can make the statistics useful or useless.

Business is full of statistics and these can be useful. Looking beyond the allure of statistics though, it is always good practice to ask how terms were defined, how categories are constructed, and how the results are presented. It is also good practice to ask whether there is more to know and whether different methods, such as the ones we use, might be better able to get at it. Usually, qualitative methods are able to give a deeper, more detailed picture of culture and individuals than the big picture statistics provide. As we like to say, better information for better business decisions.

--- Judith

back to J2 Research