I used to cringe when I’d hear people say, data is the new oil. Like any of these phrases that get tossed around and often misused, it just bugged me.
But then I thought about it some more. Maybe this metaphor works better than I originally thought.
The first discoveries of oil were almost accidental. How it would be used was not immediately apparent. Then someone got a bright idea and applied it, making initial products that had some value. For example, oil was discovered in 1858 a place in Ontario, Canada called, fittingly, Oil Springs. Later additional discoveries were made around a town that came to be called Petrolia.
Initial discoveries were by chance and they were noted in the Geological Surveys of the time. The oil was close to the surface, not like the wells of today. And the wells were dug by hand.
Remember, this was before the first gas powered automobile, made by Karl Benz in 1885 – so the oil was refined by some pretty primitive processes and used for kerosine for lamps. It was a smaller industry than what we know today, but if fulfilled a real need.
It wasn’t until the gas fired automobile came into existence in the 1890’s that the real demand for petroleum began in a big way and oil discoveries led to untold wealth. By that time, the “easy” discoveries were made. If you wanted to find oil sufficient to be part of the new automobile and industrial demand, you had to invest what would be today, hundreds of millions of dollars. And there was a risk. You could do the planning, the development and invest all that money – and have little or nothing to show for it.
Actually this sounds a lot more like data exploration than I thought.
The value of data is unquestionable – at least to those of us who deal with data. The reality is that many company’s analytics programs underperform, in large part because they don’t understand their data.