Most children of the 70s and 80s remember the PC explosion very well, and in particular the Apple II, the Commodore 64, and the almighty IBM PC. Even though I was a child at the time (or maybe because I was a child at the time) it was immediately obvious how computers would eventually become ubiquitous. It just seemed so…..inevitable.
As always, however, there were naysayers who derided the idea of computers playing a central role in business as the fanciful imaginings of science fiction. In their minds these new gadgets were little more than replacements for the typewriter. It would have taken a lot of forward-looking vision and imagination to conceive of a world where they fit in a briefcase and almost everyone had one, and yet, that’s exactly what happened. These days few in their right mind would consider running a company without computers. It’s an accepted cost of doing business, the table stakes for getting into the game of commerce.
Fast forward a few decades and data analytics are the new PCs. Data are by no means new, companies have always had data, it’s just that now there are technologies that enable the storage and analysis of data on a scale and depth previously impossible.
Recently there’s been some backlash to the idea of analytics in business, which is probably a natural reaction to all the hype that preceded it. Some think the value is grossly overstated despite the success stories coming from early adopters, and there are those whose management styles demand that they downplay the importance of data to good decision making. “Gut decisions” rule in their world and they won’t be easily swayed, which harkens back to the old meme “My mind’s made up, don’t confuse me with the facts.”
But that backlash will fade away as more and more organizations crack the code on successful implementation and reap the rewards. Industry leading early adopters like UPS and Procter & Gamble have already reaped windfalls in additional revenue and/or cost savings, and once competitors figure out how to successfully implement similar methods the acquisition and analysis of data will eventually match the status of computers; it will become the table stakes for being in business. Refusal to use data heavily in the decision-making process will result in a lack of ability to compete, and we will eventually assume that everyone analyzes data and that’s just how business is conducted.
When will this happen? It’s hard to know for sure, but events unfold much faster now than they did in the early 80’s. And with the ever-increasing march toward the democratization of data science, I doubt it will be long.