Methods of Data Monetization

Video produced by Steve Nathans-Kelly

Infonomics author Doug Laney discussed the seven methods of monetizing data within the Infonomics paradigm in his keynote at Data Summit Connect Fall 2020.

There are a variety of steps to monetizing data, said Laney. "There's kind of a simple look at it. We have a more complex, more sophisticated methodology to data monetization, but basically what you want to do is follow any kind of product management approach." According to Laney, data monetization is really about applying traditional ideas related to the monetization, management, and measurement of traditional assets and applying that in the context of information in ways that it's never been done before.

"There are a few kinds of nuances here. One thing in step two is that you want to inventory your available information assets and, by available information assets, we're perhaps thinking outside of the business as well. There's our enterprise or our operational data, there's our dark data that maybe we've forgotten about and archived. There's this world of data externally that we can integrate with our own data or repackage in ways to monetize it from open data."

Looking at the possibilities, Laney said, "There are 10 million estimated open datasets published throughout the world. There are billions of websites that can be harvested. There's your partner data or data from your customers or other structure-extended business ecosystem, there's social media data that can be harvested—billions and trillions of posts. And then there's syndicated data from data brokers and others that can be leveraged in a monetizeable way, at least internally, if not externally."

The other thing to consider, said Laney, is that you want to identify ways that others have generated value from data, not just internally and not just within your industry, but looking at how other industries have monetized data, and think about how to perhaps adapt those to your own business. One great example of that, he said, is the LA police force which identified that they could adapt seismic prediction algorithms to predict where crimes were going to occur and where they applied that technique, they were able to reduce violent crimes by 30%. "So, look at the ways that others, and other industries, are leveraging data and analytics and think about how to apply that in your, in your own market."

Videos of full presentations from Data Summit Connect Fall 2020, a 3-day series of data management and analytics webinars presented by DBTA and Big Data Quarterly, are also now available for on-demand viewing on the DBTA YouTube channel.