Five Things to Consider on the Road to Data Monetization

By   /  February 14, 2017  /  No Comments

Data is an asset, in more ways than one. Businesses want to monetize the data they create as much as they are interested in how they can take profitable advantage of the data that other companies may make available to them. It’s still an evolving world out there, though, when it comes to issues around offering information your company possesses to others and leveraging third-party data you license, as well as putting your data to use to improve internal business processes, and better support the products and services your customers want to buy. Data monetization strategies can help with this evolution.

That said, it’s an exciting time to explore new opportunities that are opening up around data monetization. In September, for example, Gartner analysts published a blog on research they conducted about helping organizations monetize their Internet of Thing (IoT) data as part of a strategy for outperforming competitors by using information to reinvent, digitalize or eliminate existing business processes and products. As for IoT data, they said that it,

“Contains incredible potential in terms of providing better insights about customers and behaviors, products and capabilities, and how customers interact with connected products and the world around them.”

And McKinsey & Co. recently honed in on car data monetization, explaining that the massive amount of data being generated in a world of increasingly connected cars could be used to create new products and services. “The overall revenue pool from car data monetization at a global scale might add up to USD 450 – 750 billion by 2030,” they said.

DATAVERSITY® recently explored some data monetization issues with Ramon Chen, CMO of Data Management and data-driven application vendor Reltio. (To learn more about its approach to Master Data Management, see the DATAVERSITY article here.) “Rather than looking at data gathering as an operating expense, it’s a natural course of business,” he says – and companies should use their human labor to further propel that course of business to value.

While a CRM system may list the basics – customer name, address, etc. – real data monetization value comes when employees can put such details into larger context. Salespeople, for instance, are the ones who become privy to information such as who is influential in this account, who really spends time with whom, and so on, he says. “Those are things that are the next wave of data as an asset,” both for your own organization and for others to tap into.

Here are some points to consider as your company explores paths to monetizing its own data and also looks for opportunities to put others’ data to work on its behalf:

  1. Clean Data is Useful Data.

Chen says the first step is to get your data house in order. That’s as true for the data you want to use to support your internal business efforts as it is for the data you’re considering making available to others.

In fact, a recent blog by Timocin Pervane, partner at Oliver Wyman Labs, assesses that “if you are already cleaning and analyzing the data for your own needs, it’s a marginal add-on investment to make it available to others” – either customers, suppliers or non-competitive companies. He points as an example to Yodlee Inc., which provides online finance tools to large banks, and the side business it started selling aggregate data it collects from credit- and debit-card transactions to investors and research firms who hope to gain insight into trends in consumer buying that can move stock prices.

Chen notes that data reliability and relevance are key to ensure that data will be an asset that a business can profit from directly or through relationships with outsiders interested in using its information. “You can’t sell it to anyone if it’s not pristine,” he says. Cleansing, matching, and merging data of any type and from any domain to contribute to its completeness and quality and further enrich information all matter here, he notes.

“The idea with a platform like Reltio is that Data Management happens,” but at a level where data specialists and scientists can spend less time combing through data and assembling it together themselves and more time “understanding and deriving value from data aspects.”

  1. There are New Data Asset Relationships to Explore

As companies think about the potential markets for their data, they should think about how they can leverage that as well as their vertical knowledge and best practices in new ways and in new relationships.

Plenty of vendors might want to sell data to promising startups in your industry, but why shouldn’t you be the one to pursue – and win – those deals, Chen asks. Leaders in their sectors likely have the most complete customer databases and know best what their industry goes through – what it takes to envision a product or service, create it and deliver it to market. A platform like Reltio lets companies combine their reliable data, relevant insights, and recommended actions into a single Cloud application delivering both analytical intelligence and operational execution.

“So, you could rapidly spin up a customer application that followed your business practices for a launch process, for example,” he says. “Why wouldn’t you want to think about supplying your processes and up-to-date data as an incubator for startups getting into your sector that you might someday acquire, so that they’re already indoctrinated into your way of thinking and processes?”

  1. Check Whether You Can Make it Easy to Monetize Your Data

Nuts-and-bolts Master Data Management is a critical part of the picture for data monetization activities, but Chen says it’s also important to consider the capabilities that Data-as-a-Service (DaaS) solutions like the one that Reltio offers provide. “The same DaaS that we provide to our customers so they can load data from third party sources like Dun and Bradstreet is usable by our customers to send data to other consuming parties,” he says.

Those parties could be another group in the internal organization, potentially in a charge-back situation so that the organization can practice monetizing data within its own ecosystem before it makes its move to the outside world, he says.

“We solve the Data Quality and MDM problem and extend from there to drive value – as other groups want to tap into the pool of data they can, and add more data as they go. DaaS allows everything to be fully connected and audited,” he says.

  1. Let Your Data Go.

With data monetization today, companies typically don’t completely let go of the data they make available to partners, suppliers, customers or others. “You have data aggregated, and you are monetizing relationships you know about in your customer base to make money,” he says.

For instance, a country club with a single view into high net-worth clients can monetize the knowledge it possesses about its members who are in the market for a timeshare. As it gets to the point where it is more hands off, though, its commitment is not to do marketing and promotion of its knowledge source to partners but just to keep the information refreshed and valuable. “That’s the purest form of data monetization,” Chen says.

  1. Put Some Thinking into a World of “Sticky Wicket” Issues

Besides the reliability and relevancy factors, the state of data monetization today requires you to consider data privacy and ownership baggage. Chen poses this question, for instance:

“When does data become your asset if it was generated by a consumer who didn’t give you his consent to use it?”

Or perhaps your business wants to make use of third-party data to help drive its own process or product improvements to grow revenue. “If you are licensing access to data from someone else who monetizes it and sells it to you, what happens when you introduce changes to it?” he asks. Your business might learn, for instance, that a piece of consumer data it has licensed from another party is incorrect and alters the information – does that data now become yours or is it still the property of the data provider?

Chen doesn’t pretend to have the answers to such a question and he doesn’t think anyone does yet.

“But key here, and a reason we are in business in addition to mastering data and cleaning it up, is that we are able to granularly track who updated what part of data and when, and its present image compared to when it was sourced from a supplier,” he says.

That will be important once regulations are in place around data ownership issues or in legal disputes concerning them.

 

About the author

Jennifer Zaino is a New York-based freelance writer specializing in business and technology journalism. She has been an executive editor at leading technology publications, including InformationWeek, where she spearheaded an award-winning news section, and Network Computing, where she helped develop online content strategies including review exclusives and analyst reports. Her freelance credentials include being a regular contributor of original content to The Semantic Web Blog; acting as a contributing writer to RFID Journal; and serving as executive editor at the Smart Architect Smart Enterprise Exchange group. Her work also has appeared in publications and on web sites including EdTech (K-12 and Higher Ed), Ingram Micro Channel Advisor, The CMO Site, and Federal Computer Week.

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