Three Paths to External Data Monetization
A sea change is occurring on the data monetization front, as companies begin realizing data is as an asset that can generate profits rather than just a liability that brings risk. Data clearly has value from an internal data science perspective. But other opportunities for data monetization exist outside your company that you should be aware of.
“The way that we’re looking at data now is shifting,” says Traci Gusher, the principal of E&Y’s data and analytics business in the Americas. “For a long time, data was viewed as, for lack of a better term, a burden. People just thought of data as this stuff I need to use to get into reports and it’s always wrong or it’s always low quality or I can’t utilize it well.”
But that mindset has changed over the past three to five years to the point where data is a net positive, she says. “Organizations are starting to look at data not as a burden of something they need to deal with, but are looking at it as an asset,” she says. “And the best companies are looking at it as a revenue generating stream.”
External data monetization is also gaining steam. Here are three ways that companies are monetizing their data from an external standpoint.
1. Participate in Data Ecosystems
One way that companies can monetize their data is by combining their data with other companies’ data. This data ecosystem approach can generate data that is especially unique and valuable, Gusher says.
“I’ll take a subset of my data and you, a different company, take a subset of your data, and you another company, take a subset of your data, and let’s bring just those subsets of data together in order to create a specific data set, or a specific insight, that is unique because of our unique datasets,” Gusher says.
“Me monetizing just my data on an open market isn’t worth as much as if I combined it with other datasets that can create something that is truly unique and impossible to otherwise get,” she continues. “And those data ecosystems I think are starting to emerge pretty heavily.”
This data ecosystem approach works best with companies that are within the same sector, but not direct competitors. There’s no value in sharing data or insights with your competitors, Gusher says, but staying within a general industry sector can be quite beneficial.
“The bigger value is in looking outside of your direct competitive landscape, but staying within sector,” she says.
2. Spin Out Your Data Group
In some cases, your company’s data may be worth more than the company itself. This was the unfortunate realization that American Airlines came to in the early days of COVID-19, when it was applying for a CARES Act loan from the federal government to keep its business afloat.
As collateral for the loan, the U.S. portion of the airline’s AAdvantage mileage program was valued between $19.5 billion and $31.5 billion. However, the stock market at the time valued the entire company at $5.9 billion. That meant that all the airplanes and gate entitlements had negative worth, and data was the only real asset of value for the company.
American Airlines so far has resisted calls to spin out AAdvantage, but other companies have made the move. Kroger spun out its data group into 84.51, so called for the degrees west that its Cincinnati, Ohio offices sit from Greenwich, England. There is also Optum, which was spun out of UnitedHealth Group. The list goes on.
“It seems like every day you’re seeing, particularly in the large organization landscape, separate revenue streams and business units or unique business being stood up or spinoff spun off and their mission is data monetization,” Gusher says.
“I think this is all what we knew was going to happen, that we’ve been thinking about,” she adds. “But now we’re actually seeing it come to fruition and there’s a lot of organizations that are reaping the benefits of it.”
3. Outside Funding for Data Monetization
Many companies already realize the value of their data. That is what’s driving 53% of senior executives to identify data and analytics as their top investment priority over the next two years, according to E&Y’s recent Tech Horizon Survey.
But not every company has the resources to invest what they would like into data and analytics. That’s giving private equity (PE) firms an opportunity to step in and make strategic investments in data on behalf of companies, in exchange for a stake or a fee.
“There are some PEs jumping in to say, hey, let’s look at how we can give an influx of capital for you to invest in this, and what our generated value out of it would be once it’s monetized,” Gusher says.
E&Y is working with individual companies to help them harness their data, Gusher says, but it’s also working with PE firms to help them devise strategies for investing in the data and analytic projects at other companies.
There is a lot of potential for new lines of business and business strategies to emerge from data and analytics. That’s true at the individual company level, and it’s also true at the macro level, where companies pool their data in ecosystems.
Gusher also sees the potential for investment firms to begin using the pooled data of their portfolio companies in a strategic manner. Most of these firms stick to specific industrial pockets, she says, so the data sets would likely be highly complementary.
“We just are not seeing a lot of PE companies do this yet,” she says. “I don’t think that they have a defined path and resources thinking about beyond an individual port-co, how you would take the data from multiple portfolio companies and drive some type of insight that would benefit all those portfolio companies, or at least complement them.”