This is a summary of the big data presentation by Andrew McAfee at the Oracle CIO summit. McAfee is the principal research scientist at MIT’s Center for Digital Business.
Antonie Philips van Leeuwenhoek, the inventor of the microscope, could very well be the patron saint of big data. Through his invention, we have been able to see deeper into things. Because of that, we have also been able to measure things better. With better measurement comes deeper understanding, or even a completely different understanding. In other words, by inventing the microscope, Leeuwenhoek opened up a whole new perspective for mankind.
What Leeuwenhoek did for the world in the eighteenth century, big data is doing today. By giving us a better insight into the world, big data magnifies our ability to measure and understand all the things we truly care about.
Take the case of the bar code, for instance. This relic of old technology helped us know what was being bought, how fast it was being bought, and when it was being bought. But there was a blind spot to the bar code. It did not tell you what else the buyer looked at but did not buy. What did the buyer already pick up but did not bring to the cashier for checkout? How did the buyers respond to our coupons? Without these information, you are basing business decisions on a grossly incomplete picture. Big data completes that picture, so we are better able to measure and understand customer behavior, and thus we can improve our marketing strategies and sales.
The good news is that these days, data is plentiful. In fact, the problem is no longer data scarcity, but data explosion. There is so much data around, it’s hard to sift through it or even just keep up with it.
How much data is around, anyway?
In little more than a decade, our computers have gone from kilobytes to megabytes to gigabytes to terabytes. Now we are looking at petabytes, exabytes, and pretty soon, zetabytes. If we are to believe Moore’s law (and we do), the day is not far off when we will run out of prefixes to “bytes” and we’ll have to invent new prefixes to be able to describe the amount of data we are accumulating and receiving day by day.
But that’s a good thing, because big data can help us make decisions and predictions with an accuracy we’ve never seen before. Take, for instance, the Google self-driving car. It’s an amazing product made possible by big data. Although it may be unnerving at first to ride in a car that moves without a driver, it only takes a few minutes into the ride for you to realize that this car is in fact a better driver than most humans you’ve ever met (including yourself). Thanks to the car’s sensors and its access to a vast information database, it is able to slow down, speed up, stop, go, and turn exactly when and where it should.
Imagine the implications if we use big data technology to drive companies instead of cars: Performance gaps among companies will grow. Research has shown that companies that base their decision-making on the opinion of the highest paid person in the room consistently lose to companies whose decisions are data driven. The highest performers are pulling away from the low performers.
Therefore, it is high time for us to be more scientific about our decision-making process. We need to use data to shape our predictions and interventions, instead of merely using it to support our premade decisions. We need to ask the right questions that will point us to the right data, from the vast sea of data available. We need to get people who know what problems need to be fixed, what questions to ask; then we need bring these people together with those who know how to find the answers using big data.
When we are able to form a team like that, only then can we compete and succeed in the big data driven future we’re heading into.
