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Most companies know the impact that data — and, more significantly, a keen analysis of that data — can have on business strategy. Far fewer understand how to successfully convert the results of data efforts into monetary value.
There is a clear distinction between creating value from data and realizing that value in the form of some type of financial gain, according to a new research briefing by researchers Barbara H. Wixom, Cynthia M. Beath, and Leslie Owens, who are affiliated with MIT’s Center for Information Systems Research.
Data monetization is also the subject of the researchers’ new book, “Data Is Everybody’s Business: The Fundamentals of Data Monetization.”
Most organizations approach data monetization either too narrowly — such as simply selling their datasets — or too broadly, with an eye toward creating benefits from data use, according to the research briefing.
The key is making a proper distinction between value creation and value realization. Creating value from data means using it to fix processes or to provide services, which in turn delivers improved efficiency, productivity, and time to market, and even customer and employee satisfaction benefits. While companies regularly create value with their data, far fewer successfully monetize that data by measuring whether the value contributes to the overall bottom line.
“An organization that is adept at creating value from data might look and feel like a high-performing moneymaking machine, but it’s a mistake to assume that benefits flow inexorably to the bottom line,” the researchers write. “It’s the act of transforming the value created by data initiatives into real money — by bringing more money in or putting less money out — that makes data monetization real.”
For example, airlines regularly create value from data by leveraging weather forecasts to predict flight delays and then automatically adjust flight schedules and passenger travel itineraries as required. While those benefits are significant, monetization comes into play when a data-powered rebooking process translates into measurable gains, such as a reduction in overtime pay and customer refunds, or a boost in ticket sales thanks to higher customer satisfaction.
Three moneymaking data strategies
The authors outline three ways to monetize data: improving work, wrapping products, and selling information offerings.
Value realization from improving. This approach involves using data to make work better, faster, or less expensive and then turning those benefits into financial gain. Consider an effort to give financial analysts new tools to analyze data to aid in the sales process. While the new tools significantly streamline the data-gathering process, monetization is achieved only if those financial analysts use that spare time to work directly with partners to boost sales.
Inevitably, there are hurdles to realizing financial benefits, including process owners who aren’t motivated to cut costs or time savings that are redirected to minimize other workloads. “Ultimately, if an improvement is supposed to reduce costs or budgets and those don’t change, data is not monetized,” the authors write.
Value realization from wrapping. This data monetization strategy involves enhancing a product with something customers value — for example, a health device that sends tailored alerts to users’ phones. Yet in order to realize that value, the product must be sold at a higher price, or the organization needs to boost sales.
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To succeed with this approach, organizations must have a full understanding of the enhanced value as well as customers’ willingness to pay more. Product owners might be reluctant to take this step, depending on their performance metrics, and cross-functional collaboration is essential for translating efficiencies into bottom-line results. Removing slack — the resources an organization has available that exceed what it needs to sustain routine operations — can be political. “That’s why everybody in the organization must be inspired to participate in data monetization,” the authors write.
Value realization from selling. This is when some form of data is exchanged for money, whether it is retail point-of-sale data or insights that can help partners grow their businesses. These information offerings hinge on price structure, so there must be a careful analysis of how much value they create and how much customers will be willing to pay.
No matter how value is achieved, data monetization is an essential part of any company’s data journey. “It would be irresponsible for an organization not to exploit its mounting, costly data investments for financial gain,” the authors write. “That would be akin to underutilizing its talent, facilities, or equipment.”
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