Making a buck with your big data

The high costs associated with big data projects will push more and more organisations to use their stores of data as a direct revenue source in the coming years.

The most obvious examples of companies turning a profit from their data stores are Google and Facebook, which have both found ways to convert their vast databases of information into dollars.

And according to Douglas Laney, a research vice president at Gartner, almost a third (30%) of businesses will have begun directly or indirectly monetising their own big data stores “via bartering or selling them outright” by 2016.

This is because, frankly, big data projects can be very costly, and organisations need to justify the expenses these projects incur.

“Most organisations already attempt to quantify the cost-benefit of business analytics, data warehouse and enterprise content management initiatives. However, calculating the bottom-line ROI for such initiatives can be more art than science,” Laney said.

“And with information itself still, remarkably, an unrecognised, off-balance-sheet asset according to accounting standards, historically there has been little regulatory impetus for businesses to formally value it.”

So, to justify these projects, organisations will look for more direct ways to make money from them - “outright monetising or productising” these information assets, in Laney’s words.

But not everyone is a Google or a Facebook; few big data projects result in information that’s directly worth big bucks to online advertisers.

“Several retailers are already generating millions of dollars per year in incremental revenue by placing online their point-of-sale and other data for business partners to subscribe to,” Laney said.

“Other enterprising individuals have launched ventures packaging and reselling publicly available data, or using it to launch new information-based products such as in the insurance and financial markets.”

We have the technology

Some organisations may find selling their data stores via subscription to be problematic - traditional database management systems and business intelligence solutions don’t play well with this idea of subscription-based data sharing, Laney said.

However, “New forms of technology are emerging that are focused on cloud-based implementations and also enabling subscriber-based and restricted access to segments of data,” he said.

He also predicts the rise of “information resellers” - companies that specialise in helping other organisations make a dollar from their big data projects.

Privacy concerns

This trend of companies looking to sell their accumulated data will lead manufacturers of internet-enabled products - smartphones, TVs, fridges, etc - to make sure their products collect as much usage, location and system data as possible, relaying it to home-base for future monetisation, Laney said.

While some consumers are already savvy enough to guard their personal information - which is valuable both intrinsically and as a tradable resource - many are not.

“Consumers should appreciate that their personal usage, location and profile data has tangible market value. Therefore, they should guard it and ensure that when they do share it they receive ample services, products or cash for it,” Laney said.

Image credit ©iStockphoto.com/David Gunn