The rise of Data Driven Organizations.

“Data is the new oil” – Clive Humby, 2006. An ideology that holds weight in today’s world, but honestly who would have thought? The world we live in has always been full of information or data – from our smartphones, banking transactions, organisations’ HR departments, etc. Data has always been there, but I guess as widely available data has been, it’s always been about how you interpret it and make it useful.

If data is said to have existed for centuries, how was it utilised? What milestones were achieved? How effective was it for society and the economy?

The history of data dates back to 19 000 B.C Paleolithic era, the days of the Great Baboon.  People during these ages never knew much about data or its importance. The age of 3 000 B.C was when people started writing on clay tablets, hieroglyphs, a system of writing that used picture symbols. This form of writing was used to record important information such as trade transactions, laws, and stories. The real breakthrough came around the 16 00’s when John Graunt figured out a process on how to utilise data; he did this by noticing patterns in the data he studied, like birth rates and death rates of London. This was a significant milestone, as it helped people understand how populations grew and how diseases spread; in essence, one would conclude that he has revolutionised how we use medical data to the present day. Fast forward to the age of the 1940s; computers were born. These machines were capable of calculating complex calculations, making them a power tool for scientists, engineers, and businesses for solving large problems from calculating numbers to processing data; the birth of the computer shaped the digital world we live in today.

Now that we know the history of data and how it has advanced, one would conclude that the transformation of how data was used from the early centuries has evolved mainly because of technological advances. Fast forward to the 21st century: the growth of data has influenced how we live, how we work and our careers. The significant development of supercomputers, AI models and careers such as data scientists and big data engineers is a clear indicator of how much data exists and the need to translate this data. This is also an indicator setting the direction of where the future is heading towards.

So now that we have gone through the timeline of data, let’s dive into crude oil, which is a global commodity.

Crude oil or oil, is a raw natural resource which is extracted from the earth’s core and refined into petroleum products. Oil is a global driver for world trade, positioning it as an in-demand commodity. For any country’s GDP to thrive in world trade, owning oil is crucial. Oil is the primary source of energy production; it is widely used in the plastic manufacturing, automotive and air transport sectors, so you can just imagine how important it is.

The history of oil dates back in 1837 in Baku. This  is when the first commercially viable oil refinery was established; this oil was used to distil oil into paraffin. In 1846 was the first modern well, which reached a depth of 21 metres. Around this time an oil field in Baku accounted for 90% of the world’s oil production. From 1854 to 1859, regions such as Bobrka, Poland; Bucharest, Romania; Ontario, Canada; and Pennsylvania, USA, experienced a “black gold” rush. Pennsylvania was the winner in this race, producing at least half of the world’s oil. As oil production expanded between the USA and Russia in the 1800s, oil prices fell globally from $2.56 a barrel to $0.56. In 1896 Germany and the U.S. launched their first commercial car; this was a technological revolution which would fuel the demand for oil. In 2003. Oil experienced uncertainty because of the US invasion of Iraq. Meanwhile, the Asian demand was increasing, which influenced the price to rise from $23.38 in July 2000 to $146.02 in July 2008.

The origins and evolution of oil clearly show us how much of a valuable commodity oil is; it is by no means arguable that industries rely on oil and countries rely on oil, making it a valuable commodity for trade. From the past to the present day, there’s a clear pattern in the fluctuating prices of oil, and those influences are region and economics, supply and demand and technological advancements. I mean, at the end of the day, that’s what global trade is all about: supply and demand.

Now that we have dissected the history of data and oil and how technological advancements have influenced these to the modern world that we live in, let’s dive into 2025 and the significance of the saying “Data is the new oil.”

From this article we can clearly distinguish the milestones between oil and data and the role these milestones contributed to the economy and society; With Data: it was when John Graunt was able to interpret the birth and death rate of London; this type of data became important to the government so they could track the growth and decline of the country’s population. This type of data revolutionised the medical industry. To this day, it is how countries like China were able to tell whether they were becoming overpopulated, which then brought the law: each family should have a maximum of one child (1979-2015). With the significant growth in technology and career paths within data, data has become more valuable than ever to the government and society. Businesses are now able to make data-driven decisions by tracking customer spendings, location Ads, social media interactions, etc. Data has globally become the backbone of every corporation.

Oil on the other hand has had its Milestone when the first vehicle was invented, this meant the demand of oil would steadily increase. Fast forward to 2025: oil still is not outdated, as it is the backbone of global trade. Every country needs oil to support its industries so its GDP thrives and competes globally. In essence, no country can survive without oil.

Therefore, one would argue or conclude that in the digital day we live in, data just like oil, is far more important than we think. With the growth of A.I, all industries rely on data. The mere fact that A.I is now being regulated proves the growth and impact of data, which now can be referred to as ‘Big Data’. We refer to it as ‘Big Data’ because the data has become so large that no ordinary human can be able to make use of it, which explains the implementation of A.I models like supercomputers. Whether you are in Africa where the A.I implementation is quite blurry or in developed countries were the A.I has rapid growth the fundamentals of business growth have been reconstructed- Business growth has become parallel with data, they coexist and so the mandate is clear; implement data analysis in your organization to make informative decisions.