Florence Nightingale and Data Visualization

Florence Nightingale and Data Visualization

Florence Nightingale and Data Visualization

The Web has long been awash with articles on Big Data, each  with a story to tell, full of catchphrases and figures to prove the factual importance of information analysis.

In a world where information has become the greatest asset, it is easy to demonstrate the strength of this solution. Nevertheless, we are far from truly understanding the instrument we need to use, which is still perceived as obscure, a black box with no user manual ─ the enabling instrument is perhaps what scares us most.
Big Data is something different, though: first and foremost, it is a philosophy, an approach to data, a method. This is indeed the gap we maybe need to fill and very few articles have tackled it.
We spend too long wondering whether any of this is really useful or if it is just the product of a well-thought-out marketing campaign, while those who have already changed their way of thinking are gaining competitive advantage that will be harder and harder to catch up on, given its outcomes.

 

Then let us learn about Florence’s story and how Big Data paved her road to victory.

Florence Nightingale was born in Florence, hence her first name. Florence also had an elder sister, Parthenope, whose name was chosen because she was born in Naples. How their parents chose their names is surely funny, but it is not the subject matter of this post. Young Florence knew her vocation from an early age, deciding to become a nurse. Her passion was much more than a simple job, we might even call it an innate need to help others, especially the downtrodden, like the poor or war victims.
That is how Florence got to Barrack hospital in Scutari, Turkey. The first thing that impressed Florence was the lack of sanitation in the hospital. At a time when they were short of staff and the war did not even leave the time to stock up on supplies, it was obvious that even the most basic rules had been forgotten. Unfortunately, the mortality rate was too high, around 42%.
When Florence first arrived, she had been joined by 48 collaborators. A year later, only 12 of them were still alive. The mortality rate outnumbered the war victim population by far.

Today, numbers like these would be enough to shake the public and catch the attention of the whole world, but in such a faraway country  nobody cared. After all, a war was being waged and obviously wars bring death. Florence was not the type of person that just lets things go, though.
Unfortunately, the factual, almost visible, data, like filth in the corridors, the lack of proper air circulation and even the gurneys scattered haphazardly along the corridors, were not enough to prove that they were the true causes of the high mortality rate. So Florence decided to approach the problem like a data scientist, collecting more and more data that could prove her theories beyond any doubt. Partly thanks to the role of Nursing Corps Superintendent awarded to her by Her Majesty’s government, her theories managed to catch the attention of her higher-ups.
Being used to performing her tasks with efficiency and effectiveness, Florence personally applied statistical models to the collected data, something that had never been done before in a hospital.

The result were hundreds of pages of detailed analysis of the situation. By then, no one could ignore her anymore. The evidence was unquestionable, as were her results: the mortality rate dropped to 2%, which obviously happened after proper hospital renovations.

 

How much would a Big Data solution have helped Florence?
How quicker would have been her report drafting if the right technology had been available to her?
How many more lives would have been spared?
But that happened during the Crimean War and it was only 1858.

What seems even more surprising is that Florence did not only understand the importance of data collecting and processing, but even how its correct representation could be leveraged to gain insights that, otherwise, would have been much more difficult to recognise. (Or, even worse, the implicit unwillingness   to accept obvious data, as this story tells us.) 

This is why a Big Data solution always needs to be accompanied by the right front-end instrument (when it is not integrated in the solution proposed by the vendor); an instrument that does not only efficiently represent data and process them with no need for complex technical skills, but that also makes them easily usable and searchable, needing short development periods and making them always ready to tackle the many challenges that still await us.

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Author: 

Alessia Civita
Consultant
Visual & Search Analytics

SDG Consulting Italy

10/Apr/15