The man who got rich on data - years before Google - Article Analysis

how data analysis developed into the booming industry it is today
 

The man who got rich on data - years before Google is a time-lined walk-through of how a man called Herman Hollerith came across a flawed process, that being the government’s ability to capture, sort and derive value from increasing amounts of census data, and came up with a solution that has changed the landscape of the modern economy forever.

In 1880 Hollerith developed the first tabulating machines which were first used in the 1890 census, saving millions of dollars and enabling the government to discover far more powerful insights from the information it was capturing.

The backbone of the story is based around the common and now frequently used saying in data related content: data is the new oil. Harford both agrees and disagrees with this statement. Data is like oil in that when it is crude and unrefined, it isn’t of much use to anyone. However, once it is refined, unlike oil, data can be used more than once to power whatever it is being used for.

He attributes this fact to the reason why tech companies like Alphabet, Alibaba, Amazon, Facebook and Tencent have grown to become 5 of the 10 biggest companies in the world, which was once dominated by oil companies. The way these companies have achieved success is dissimilar to that of Hollerith’s Tabulating Machine Company, which eventually went on the become IBM. This is because we now produce data in everything we do, meaning that compared to the 1890s and early 1900s where data was produced in much stricter and refinable formats, the most successful businesses are the ones who know and understand what data is valuable, and why.

Now we know this is much easier said than done, but is the reason we believe all companies who want to remain competitive over the next year and next decade need to carefully consider whether their data refining systems are producing outputs that drive effective decision making.

In essence, what’s the point of having a data strategy if the data strategy isn’t giving you outputs that create value for your business and customers?

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