When you hear the phrase “data monetization,” you might think of selling data to a third party – along with the many ethical and privacy issues that go with it. While this practice plays a significant role in our modern economy, there is another type of data monetization that receives less buzz but is equally lucrative: using internal data to gain insights, make better decisions, and improve business performance. In his presentation at a recent Data Governance & Information Quality Conference, Sunil Soares argued that it is critical to learn how to quantify and communicate the value of this so-called first-party data.
Soares, the CEO of YDC Data Economics, argues that a rich ocean of data lies untapped, largely because many data professionals – from Data Governance specialists to chief data officers (CDOs) – remain unconvinced about the value of data. “What is the challenge here?” Soares asked his audience. “If you look at the S&P 500, excluding FANG (Facebook, Amazon, Netflix, Google), that’s about $32 trillion, and 2% of this is unrecognized value around the data.”
According to Soares, data managers can effectively be won over by looking at data through a new set of lenses.
The Hidden Value of Data
The ROI of data is frequently obscured when critical data points fail to form a bigger picture, said Soares. For example, a modest profit from a particular business asset might not be tracked against a long-enough timescale to warrant its initial price tag.
To illustrate how data can be monetized by thinking outside of the box, Soares pointed to a paradigm shift that unfolded among airline companies. In the summer of 2020, when the uncertainties of COVID were keeping planes on the tarmac and government relief initiatives were still up in the air, the major carriers in the U.S. – American, United, Delta – were rapidly exhausting their liquid assets. In a bold move, these companies pledged their loyalty mileage programs as data assets. United, for example, realized that its customer data was worth roughly 20–40% of the total value of its loyalty program. “That’s about $4.3–$8.6 billion,” Soares marveled. “Lo and behold, the value of the customer data was more than the value of United itself at the height of COVID.”
But even with successes like the one mentioned above, CDOs still have a hard time seeing past the seemingly prohibitive cost of data. To put things in perspective, worldwide IT spending is projected to reach $4.9 trillion in 2023. Meanwhile, the average budget of a CDO of a major corporation with at least $10 billion in revenue comes to roughly $30 million. “This is the statistic that everyone is focused on,” said Soares. “CDOs must be able to demonstrate the ROI for the data in a manner that’s really compelling so we can get away from this thinking of Data Management as a cost center.”
Data Management: Getting a Grasp on Intangibles
Although data has been providing value for decades now, many executives still find it counterintuitive to see data as an asset simply because putting it on a balance sheet can be tricky. As opposed to physical stock or infrastructure, data falls under the category of “intangibles.”
“A tangible asset is something you can touch, like furniture, automobiles, machinery,” explained Soares. “Intangible assets are things you can’t touch, like goodwill, brand reputation, or innovation.”
Yet while intangible assets currently command an overwhelming 80% of the market cap of the S&P 500 index, accounting standards rarely reflect this reality due to data’s vulnerability to manipulation. As a result, most companies focus on tangible assets. If business leaders focused instead on converting data into “data products,” said Soares, they could increase enterprise value.
How is it possible to change business culture to recognize the true value of data? Soares suggested that there is an ultimately simple way to begin benchmarking across companies to assign data value without resorting to “voodoo economics.”
“The value of a company’s data divided by the value of the company is what we call a data monetization index,” noted Soares. “And we have another metric called intangible asset index.” Data-related intangibles include customer data, employee data, reference data, reports, critical data elements, and more.
How does one identify a critical data element? Soares estimates that roughly 10% of corporate data would fall under this category, though this number is contextual: What may be critical for one application may not be critical for another. “If you think about it,” he said, “when you’re investing so much money around a capital adequacy program, if you’re a bank or a pharma company, you’re spending so much money around a specific regulation that you can devolve that down to what’s the value of a critical data element.”
Putting It All Together: A Case Study
To take these ideas out of the hypothetical realm, Soares looked at iRobot, a company that furnishes automated devices for home cleaning. While these Space Age domestic gadgets are interesting as a product, “they are vacuums not just for dust, but for data,” joked Soares. To wit, as the automated devices rove around an entire house, they also harvest the floorplans of the consumers who use them. So, when Amazon recently made a bid to acquire the product line, the FTC halted the deal because Amazon was already too powerful and ubiquitous to acquire this trove of consumer data that it valued at over $1.5 billion. How did the FTC arrive at such a figure?
For this sort of value assessment, one can perform a comparable analysis through either a bottom-up or top-down model. In the case of iRobot, Soares looked at another sale of another product with the ability to track user movement: Fitbit, the exercise tracking line purchased by Google. Taking the price it paid for Fitbit and dividing it by the total of Fitbit users, Google calculated that it had paid a mere $60 a user. This figure proved to be a solid ROI, and as a consequence, Google decided to invest half a billion dollars in the home security company ADT under the expectation that it would provide a similar wealth of user data.
“I’m not opining on whether it’s good or bad,” Soares conceded. “This is just a way of putting a number on it.”
It’s the tangibility of such a number that can convince business stakeholders to ultimately invest in data.
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Here is the video of the DGIQ presentation:
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