Three Paths to External Data Monetization
A sea change is occurring on the data monetization front, as businesses begin to realize that data is an asset that can generate profits rather than just a liability that carries risk. The data clearly has value from an internal data science perspective. But there are other data monetization opportunities outside of your business that you should be aware of.
“The way we look at data is changing,” says Traci Gusher, director of E&Ydata and analytics business in the Americas. “For a long time, data has been seen, for lack of a better term, as a burden. People just looked at the data as what I have to use to go into the reports and it’s always wrong or it’s always low quality or I can’t use it well.
But that mindset has changed over the past three to five years to the point where the data is a net positive, she says. “Organizations are starting to see data not as a burden they have to manage, but as an asset,” she says. “And the best companies view it as a revenue-generating stream.”
Monetization of external data is also gaining momentum. Here are three ways businesses are monetizing their data from an external perspective.
1. Participate in data ecosystems
One of the ways companies can monetize their data is by combining their data with data from other companies. This data ecosystem approach can generate particularly unique and valuable data, says Gusher.
“I’m going to 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 only bring together those subsets of data in order to create a specific dataset, or a specific insight, that is unique because of our unique datasets,” says Gusher.
“To me monetizing just my data in an open marketplace isn’t worth as much as combining it with other data sets that can create something truly unique and otherwise unobtainable,” she continues. “And those data ecosystems, I think, are starting to emerge quite strongly.”
This data ecosystem approach works best with companies in the same industry, but not direct competitors. There’s no value in sharing data or information with your competitors, Gusher says, but sticking to a general industry sector can be very beneficial.
“The greatest value is looking outside of your direct competitive landscape, but staying within the industry,” she says.
2. Rotate your dataset
In some cases, your company’s data may be worth more than the company itself. This is the sad realization American Airlines came to at the start of COVID-19, when it applied for a CARES Act loan from the federal government to keep its business afloat.
As security for the loan, the US portion of the airline’s AAdvantage miles program was valued at between $19.5 billion and $31.5 billion. However, the stock market at the time valued the entire company at $5.9 billion. This meant that all planes and boarding rights had a negative value, and data was the only real asset of value to the business.
So far, American Airlines has resisted calls to create AAdvantage, but other companies have followed suit. Kroger has transformed its data pool into 84.51, so called for degrees west that its Cincinnati, Ohio offices are located from Greenwich, England. There is also Optimum, which was spun off from UnitedHealth Group. The list continues.
“It seems like every day you see, especially in the landscape of large organizations, separate revenue streams and business units or unique companies being created or spun off and their mission is data monetization,” Gusher says.
“I think that’s all we knew was going to happen, that we thought about,” she adds. “But now we are seeing it come to fruition and many organizations are reaping the benefits.”
3. External funding for data monetization
Many companies are already realizing the value of their data. This is what drives 53% of senior executives to identify data and analytics as their top investment priority over the next two years, according to the recent E&Y report. Tech Horizon Survey.
But not all companies have the resources to invest what they want in data and analytics. This gives private equity (PE) firms the ability to step in and make strategic investments in data on behalf of companies, in return for equity or compensation.
“Some PEs are rushing to say, hey, let’s look at how we can give you an influx of capital to invest in this, and what our value would be generated once it’s monetized,” Gusher says.
E&Y works with individual companies to help them leverage their data, Gusher says, but it also works with private equity firms to help design data investment strategies and analytics projects at other companies. .
There is a lot of potential for new industries and business strategies to emerge from data and analytics. This is true at the individual company level, and it is also true at the macro level, where companies aggregate their data into ecosystems.
Gusher also sees an opportunity for investment firms to start using aggregated data from their portfolio companies strategically. Most of these companies stick to specific industrial pockets, she says, so the datasets would likely be very complementary.
“We just don’t see a lot of private equity firms doing that yet,” she says. “I don’t think they have a defined path and resources in thinking beyond an individual port-co, how you would take data from multiple portfolio companies and generate some type of information that would benefit all these portfolio companies, or at least supplement them. »
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