• Caroline Carruthers

Why Your Data Strategy Should be Based on the Stone Age

Data is nothing new. Many often think of it as a part of the wider digital transformation process that we hear so much about, but the act of storing and analysing data can actually be traced back as far as 18,000 BC, when paleolithic tribespeople would mark notches into sticks to keep track of their tribes’ supplies. It’s a far cry from the big data we know today, but the core reasoning behind why we collect, store and analyse data still remains pretty much the same as it has done for several millennia.

So, what can we learn from history about data, and how can it help us to develop our own modern data strategies?

When you think about it, humans have always strived to collect more data. Whether it was the invention of the abacus to tally food stock and taxes or the emergence of the first “data centres” (what we know today as libraries), advances and innovation have always been marked by improved methods of storing, collecting and analysing information. In fact, our modern move from paper to virtual based data collection arguably wasn’t the most innovative transformation in data storage – The move in ancient Egypt from carving information onto stone or wood to papyrus-based documentation arguably had a far greater impact on human history.

The paleolithic age and the dawn of libraries all sound like an impressively long time ago, but for a slightly more topical example of data in history we should look at the work of John Graunt in the 17th century. Known as the founder of demography and perhaps the first epidemiologist, Graunt carried out the first recorded experiment in statistical data analysis all the way back in 1663. Then, as now, the UK was struggling with an outbreak of a deadly disease (in this case, the bubonic plague), and government officials were struggling to come up with ways to stem its effects. Graunt, who had several years earlier produced and distributed the first Life Table (which gave information on mortality and the probability of dying based on age and location), had an idea: In his work The Bills of Morality, he recorded information about mortality during the plague and designed an early warning system for areas across Europe based on the location and severity of local outbreaks.

The familiar images of international case comparison graphs, R-rates and the infamous Covid curve can all be traced back to John Graunt’s 17th century health data analysis. The core purpose of Graunt’s data analysis was the same as our own COVID data analysis today – To understand and contextualise what is going on whilst helping us to plan for the future.

Away from public health, that core purpose is true for organisations looking to utilise their data for business purposes. The phrase “Business Intelligence” was first coined by Richard Millar Devens in 1865 to describe how Sir Henry Furnese, a banker, was able to get the better of his competitors by gathering and acting on relevant financial information. Devens was building on the idea that data is useful both for getting the “lay of the land” and forecasting what might happen in the future to plan accordingly. His work, over 160 years ago, lay the foundations for modern data driven business transformations.

Our modern data strategies are built on thousands of years of human history. From those paleolithic sticks and the grand libraries of the classical world through to the demographic analysis of 17th century plagues and the first theories of business intelligence, humanity has a rich history of collecting, storing and analysing data. It would be remiss of me not to mention that, in the past two years, we have created more data than the entirety of the rest of human history put together, but in a way that mass collection of information has led to us losing a bit of the meaning behind data collection – The Great Library at Alexandria is fabled to have sorted the collective knowledge of the world’s nations within its walls, a pinnacle of human achievement. Will we ever consider the information we are currently storing in the same way? Have we forgotten the core purpose behind holding all of this information?

Humanity has utilised data over several millennia to understand and contextualise the world around us whilst helping us to plan for the future. No matter the size of our own data journeys, whether it’s to help a small start-up business get off of the ground or understand the latest trends in the current pandemic, every data strategy has to be built with that original, stone age purpose firmly in mind.

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