The Cost of Falling Behind: Why Big Data investments can't be measured in simple ROI

ROI, ROI, ROI: when convincing executives to embrace Big Data, it may seem that the bottom line is all that matters—and for good reason. But building Big Data infrastructure is a long-term investment, and it’s very difficult to measure with simple ROI.

It’s not that businesses won’t see a return. In fact, although the costs of building infrastructure and hiring a skilled team to manage it are significant, the effort will pay off. Still, there are two major reasons that judging data investments by short-term ROI is not particularly useful. 

First, ROI for Big Data is notoriously difficult to calculate. You can determine the ROI of individual experiments, but Big Data is a long-term investment.

Enterprises using Big Data tools must understand that several smaller insights are more valuable to them than one major discovery. Big Data is still a brave new world, and teams need to have an experimental mindset to succeed. This approach may not translate to immediate ROI, but it’s the smarter long-term strategy.

Secondly, Big Data is so critical that businesses can’t afford not to invest. If the competition’s already made the investment, they must weigh the cost of doing nothing—and falling permanently behind.

Consider the story of Blockbuster and Netflix. Blockbuster was doing well, but failed to make the investment in data and customer preferences that Netflix did. Years later, they paid the price.

The bottom line? Big Data puts your business in a position to succeed, even as customers and preferences shift. Though it’s difficult to measure the short-term ROI of a data investment, it’s a choice you can’t afford not to make.

Visit Brillio at Booth #1434 at Strata + Hadoop World to help you succeed in your Big Data Journey