Sometimes the best example is an unlikely one
As someone who works in both data analytics and experience design, I’m forever coming across quantitative v qualitative research debates. By now we should all know that it takes a combination of research approaches, and more importantly the right balance that best suits the questions you want answered. However we still see this polarising debate and the continuous display of data visualisations and statistics set against the understanding of the voices of real people. Well, I think I’ve found an example that will make both sides finally happy.
My colleague James Richardson wrote a great piece over on our work blog about the famous John Snow cholera map. It’s a fantastic look at how the story we hear told about the map and John Snow’s use of data visualisation has been twisted by narrators over the years. Often you hear the story that John Snow used the map (the data visualisation) to convince the Board of Guardians of St. James parish to remove the pump handle at Broad Street, thus stopping the cholera outbreak. Or even that it was the map alone that gave him the insight which enabled him to spot the source of the outbreak. However as James points out, that was not actually the case, and the map as we know it was in fact produced after the event. It was created specifically to help tell the ‘story’ of his findings to the Epidemiological Society of London. So what does this darling of the data visualisation community have to do with the quantitative v qualitative research debate?
John Snow was a doctor, he made house calls, he walked the streets in the area — he was in the field. Reading around the events you get a much better feel for how much of his ‘data’ was from talking with people and teasing out those important insights. Yes the quantitative ‘death rate’ and ‘infection rate’ when mapped geospatially helped hint towards to outbreak’s source, but it was the qualitative conversations that added the depth and real insight.
In fact much of the clues to the source came from things that aren’t even shown on the map. They are, in some cases implied, and in others recorded in the the tabular logs of the outbreak, but the understanding for all of them came through conversation. For instance there are the ‘outlier’ deaths of the widow and her niece which are not on the map. As the fabulous site John Snow site by UCLA explains:
Dr Snow rode up to Hampstead to interview the widow’s son. He discovered from him that the widow had once lived in Broad Street, and that she had liked the taste of the well-water there so much that she had sent her servant down to Soho every day to bring back a large bottle of it for her by cart.
It took probing and questioning to get the full picture that enabled him to pin point the source. Whether that was to understand the outliers or to find out why there were less deaths, in the case of the Poland Street workhouse (with 500 residents) or even none at all, in the case of the Broad Street Brewery. Both of which were situated near the pump, however the workhouse had it’s own well and the workers at the brewery had a daily beer quoted, thus never drank the water.
John Snow’s brilliance lies in his ability to keep asking why?, both through the data and by talking to the people directly affected. It took both the quantitative and the qualitative research to truly understand the problem.
So when faced with a quantitative v qualitative debate, reach for John Snow, because the good Dr knew a thing or two about research.
