In our previous blog post, we looked at 4 ways that real-time, big data analytics can give your business a competitive advantage. One of them was that you could use real-time Big Data Analytics to make dynamic changes based on user behavior. This brings us to the realm of Predictive Analytics, which, as Eric Siegel says, gives you “the power to predict who will click, buy, lie or die”.
Let’s dig deeper. Think about it – one of the earliest instances of putting Predictive Analytics into use, was (like most of the other modern marvels) during World War 2, by Norbert Wiener. While he tried to predict the path of warplanes, the closest he could get was to tell where it would be in 1 second from now. You’d need at least 20 seconds to load the artillery and bring the plane down, so a 1-second head-start was nowhere near adequate. As fate would have it – it didn’t end up creating much of an impact, but surely laid the foundation to some of the successful use cases we see now, thanks to the emergence of big data and cloud computing capabilities.
If you’re still wondering if predictive analytics is just another fad, ask the Banks that successfully predict which of their credit card users are likely to default. Or ask the insurance companies who can predict the probability of a claim, better, by correlating lifestyles and diseases – and therefore price their policies better. Of course, there have been a few infamous ones as well.”How Target figured out a teen girl was pregnant before her father did” is, surely, a case in point!
Given these hits and misses, it becomes all the more important that a business picks up the right problem to solve and employ the right infrastructure and resources that help them get there, rather than taking up a me-too project that sounds like the next best thing since sliced bread.
As Gartner puts it, the most valuable Predictive Analysis solutions are those that are faster, more relevant to businesses and easier to use; while being increasingly focused on the prediction aspect rather than description or classification.
Here are a few commonly seen applications of Predictive Analytics:
All said and done, merely listing the use cases wouldn’t give you enough confidence to jump in and start treading the predictive analytics route.