Your organization has taken all of the right steps. It went all-in on big data. That is, it incorporated vast amounts of data from new sources, many of which lay outside of its control. It deployed Hadoop and encouraged employees to eschew their intuition and make data-based decisions.
And still it completely missed the boat on the viability of a new product, strategy, marketing campaign, direction or partnership. Think New Coke, Apple Maps and Microsoft Vista bad. Some pretty senior people at your organization aren't just scratching their heads. They're embarrassed and they're questioning the very idea of big data.
What happened? Was the choice bet on data – be it big or small – the wrong choice?
In this clearly hypothetical example, individual details certainly matter. At a high level, though, rare is the organization that uses data too much (although it certainly has happened).
Data-centrism is rare but it exists
For instance, in Marissa Mayer and the Fight to Save Yahoo!, Nicholas Carlson writes about the struggles of the iconic web company. It turns out that Mayer often relies a bit too much upon data when making decisions. For instance, while Mayer worked at Google, a designer quit because of her intense scrutiny toward details:
… a team at Google couldn’t decide between two blues, so they’re testing 41 shades between each blue to see which one performs better. I had a recent debate over whether a border should be 3, 4 or 5 pixels wide, and was asked to prove my case. I can’t operate in an environment like that. I’ve grown tired of debating such minuscule design decisions. There are more exciting design problems in this world to tackle.
Generally, however, Mayer's tale of data-centrism is the exception that proves the rule. (All of the data in the world isn't going to save Yahoo!, but I digress.) Most individuals, groups, departments and organizations make decisions based upon too little information, not too much.
Even organizations that predicate their businesses on data occasionally make mistakes. (Google+ is one case in point.) Many, if not most things, are only completely understood in hindsight. Big data and attendant tools can help, but they guarantee nothing.
This is a tough pill for many people to swallow. After all, doesn't linking traditional (internal) data sources with newer (external) ones lead to better information and, by extension, better business decisions?
There’s a good chance that business decisions based on analytics will sometimes miss their marks. That goes double for predictions.
Brass tacks: Nothing in business has ever been guaranteed. The era of analytics and big data doesn't change that one bit.
What say you?