Data fatigue started entering the vocabulary sometime around late 2012, for a few years before that data was to be a be-all, end all buzzword. Not of course for people who knew the limits of data-based or (evidence based) decision making, and they were, and continue to be a-plenty.
The challenge around big data is largely one of context. Any data is as useful and important as the insight it can bring to an area of investigation. As a large amount of data (in the parlance of data science it is scale) is captured it has to be standardised, defined, normalised, and clustered. This is important if the data is to be at this scale, a useful lens with which to look at the world. There are use cases where this approach is the one to use and it works such as detecting frauds in banking transactions, the spread of Covid (alas! it is still around) etc. You get the picture.
There is however a problem with this kind of data, it lacks context, depth, and story, and if done badly has no meaning. Try opening the portal to the madness that is your smartphone and the weird datum it collects. The solution?
Enter tech-ethnographer Tricia Wang who wrote a very interesting article first published in Ethnography Matters in 2013. Which has since been republished on her Medium blog. The blog introduces the concept of Thick Data. Thick Data is the insight gleaned from a small sample but it has more context, meaning, and depth. It uses qualitative, and quantitative methods in order to glean an insight into the stories, thoughts, and a snapshot of the mental model of the people at the heart of the investigation.
Data has to help us navigate the conundrum of the knowledge quadrant below. The real tricky bit is when we have to make decisions about the future that we do not have enough information on and are not sure how to process. See the image below (hopefully, helpful!)
Data is the most useful of the canonical tools employed to make hard decisions. However, even with the presence of data in all the forms it can take, there is a growing level of scepticism around it. The mask mandate fights come to mind. The constant barrage of misleading information that we see thrust upon us through different mediums is another.
I have been reliably informed about the state of economy of my country four times this week already. Not once have I come across the same data twice, so we must really be doing something. At the heart of this is the problem of data fatigue, but also a diminishing trust in the public institutions the world over. The United States has been a leader in measuring trust. It has been constantly declining. See the graph below by Pew Research. Declining trust in institutions is not unique to the Unites States, it has been reported from many other countries.
Partly the decline of trust could be an inability by the government to persuade the citizenry of its intent, and action. Yes, this is not the only reason, but it is more and more clear that the way we marshal our statistical facts, often creates more problems than it solves. Try getting into the debate about economic growth. It often boils down to my facts are more factual than your facts (I am only half joking!)
Perhaps taking a look at how during the first Crimean war, using data, statistical analysis, and empathetic story-telling a small group led by a redoubtable leader managed to have a lasting impact.
During the middle of first Crimean war (1853-55) sometime in 1854, a 34 year old n proposed to the army that she along with 38 nurses would like to go and help the hospitals at the front lines.
That is how Florence Nightingale found herself working 20 hours a day to turn around the squalor of the battle field hospitals. She got people to send clean linen, saw that the dressings were changed on time, and hygiene standards be put in place. She ensured that the food given to the soldiers was not rancid, or mouldy.
It helped that she was a statistics enthusiast (19th century speak for nerd) and collected data throughout. By the time the war ended she had turned the hospital system on the battlefield around. Lowering the casualty rate of injured soldiers by a significant margin. She returned to her country as a much loved icon. For a lot of us that would have been it. Not her.
She realised that the changes she had brought about on the battlefield needed to stick. This is where she had an uphill battle, to convince change averse top leadership that the changes she was advocating would be useful and must stick.
This is where she used both the tools of persuasion logos (cold logical argument) her friend William Farr a noted physician and statistical enthusiast had written a fairly cogent report on the subject, armed with data she made convincing arguments. She wrote with conviction on the numbers. However she knew that by themselves the numbers are not always convincing, therefore she chose what is today a common practice measuring in small, equal baskets.
Instead of reporting large numbers such as 600 deaths per 1,000 troops (those are actual numbers) she chose to report it as 3 soldiers out of 5 would die. The strategy she chose to employ was to have a basket size. It made analogies stick in the mind of people who were reading it.
The other method that Florence Nightingale found, and development organisations use till today is to have a comparative emotional story. Instead of dry numbers to invoke an emotion, that makes the story stick longer in the minds of people for whom it was intended.
Florence Nightingale communicated her data she had painstakingly collected in a manner that was vivid, passionate, and dramatic. It was done to ensure that the systemic problems she had measured made it to the top brass, and general public alike. This was the other tool she could use communicating research with passion and to seek the trust of the people. Win the trust she did. In a way she pioneered data visualisation but through words. Something tells me she would have gotten along with Hans Rosling. For the late great Professor Rosling made a huge difference through his work on data, and public health by combining research with impeccable story telling.
Florence Nightingale managed to convince a large bureaucratic organisation to change, In the process she also managed to change a specialised body of knowledge's (doctors/surgeons) perception on something integral to their work. Florence Nightingale and her illustrious successors including Prof. Rosling have been able to break the divide of logos, and pathos. They have a robust and rigorous data collection process, which leads to numbers that can be trusted. They ensure that these numbers are useful for inducing action and build trust. How do they do that?
Florence used emotion to communicate her findings, and to seek the changes she desired. However, she chose to eschew personal emotion, she did not tell her personal story. Today in this emotion laden world of ours often people use their emotions to convince others of their ways and it ends up backfiring on their credibility. Look at the number of bad TED talks or multiple other platforms where personal story telling sometime back fires.
Florence used an interesting psychological trick called transferred emotion, Instead of making fresh appeals to emotion, she found by employing a language that evoked a sense of tragedy which existed in the imagination of her audience she could make them take notice of something that was easy to overlook. To quote Chip Heath & Karla Starr she targeted “pre-existing pools of emotion”. Even now good communicators do this, but they come up against the attention divide.
With the advent of personalised internet it becomes more urgent and important to communicate not just a number but our feelings towards that number. In a world where the opportunity cost is extremely high if we are not invested in the outcomes, and the alternatives we will not have the resilience to pursue it.
So collect data, tell a truthful, but an emotional story, and follow through on the resistance. That would be a perfect homage to the lady with the lamp.
Thank you for reading, THE BEHAVIOURAL REVIEW!