With traditional business income streams drying up or in long-term jeopardy due to the pandemic-spawned economic crisis, organizations need to identify new sources of value such as from the surfeit of available data. Getting this right is a challenge that CIOs and chief data officers (CDOs) in particular must master.
Monetizing data about much more than simply selling it outright. Data has economic properties that enable it to be leveraged in ways other assets cannot—especially oil, to which it often is erroneously compared. Data can be used simultaneously for multiple purposes. It is what economists call a non-rivalrous, non-depleting and regenerative asset. When you consume data it doesn’t get used up, and when you do use data it often generates yet more data. Moreover, information assets have relatively low inventory carrying costs and transit costs compared with other assets, making monetizing them a high-margin venture.
Businesses should monetize data in any and all ways in which it can generate measurable economic value, internally or externally. Due to its protean nature, data can assume infinite forms and therefore be monetized in endless ways.
Methods for Monetizing Data
Data monetization methods are classiﬁed into two broad groups: direct and indirect monetization. With direct monetization data generates explicitly attributable economic beneﬁts. With indirect monetization data contributes to economic beneﬁts more obliquely. Direct data monetization generally is in the form of a transaction, whereas indirect data monetization involves affecting one or more of your own business processes. Indirect data monetization methods include many of the your organization already is leveraging data, such as:
Licensing Data or Insights to Others
The most obvious method to monetize data is to sell it, or rather to license rights to it, instead of exchanging sole custody of it. Few organizations are sufficiently set up to offer data as a product or service in addition to their traditional products or services. This is where data marketplaces or exchanges like Dawex, Demyst, EagleAlpha, Quandl, or a growing number of industry-specific data aggregators come in. They handle the marketing, sales, sharing of sample data and access to data sets or APIs, along with the licensing transactions.
Often however, consumers of what’s called “external” or “alternative” data don’t really want raw data; they want insights, including ones that are specific to their business such as benchmarks or recommendations. Various industry-specific market research organizations such as ACNielsen, IHS-Market and Gartner monetize data (or content) in this manner.
In some cases, however, organizations desire solutions in which others’ data is integrated with their own data or into their own applications. This is where consultants specializing in data monetization solutions can assist CIOs and CDOs.
Bartering or Trading with Data
Exchanging data in return for goods and services is more common than you might imagine. Consider the grocery store transaction in which you scan your loyalty card. You receive what’s called a “discount”. But what’s really happening? You are exchanging data about you and what’s in your shopping cart in return for free food.
Similar opportunities abound in the B2B world in which discounts or favorable contract terms can be negotiated in return for sharing information about sales, forecasts or supply. Moreover, the liquidity and regulatory reporting conspicuousness of money can make data a preferable form of currency. Hint: discounts received are not taxed as income, selling data outright is.
Enhancing Existing Products or Services with Data
Data and insights don’t have to be sold or exchanged directly. Sometimes baking data or analytics into one of your existing products or services instead can bolster their competitiveness, benefits, and a price premium . For example, a forecasting tool that has access to external datasets such as open data, syndicated data, social media streams and web content, and can automatically generate leading indicators of business performance, will set itself apart from stand-alone “dumb” forecasting tools that consider only a company’s own transaction history.
Another good example are IoT-enabled automobile components that continually integrate data collected from other automobiles and drivers, and which can tune their own performance and/or prolong its lifespan.
Digitalizing Existing Products or Services
Rather than merely infusing existing products or services with data, go a step further and digitalize them altogether. For example, Kaiser Permanente implemented secure messaging, image sharing, video consultations and mobile apps, and now has more virtual patient visits than in-person doctor visits in some geographies. In addition, it and can get patients with specialists quicker than ever, and 90 percent of physicians say this digitalization has allowed them to provide higher-quality care for their patients. Digitalizing solutions often requires the wholesale redesign of products, services, processes and customer journeys to integrate and take advantage of data.
Inverted Data Monetization
In light of privacy regulations such as the GDPR, CCPA and HIPAA many business leaders, IT executives and general counsels mistakenly contend that their customer data cannot be monetized. This unidirectional way of thinking about the flow of data is limiting. Although you may not be able to share your customer data with others, there are no restrictions on sharing information about others’ products and services with your customers in return for a referral fee or commission.
Scrutinize your extended business ecosystem to identify related solutions your customers may need or desire. For example a hospital could introduce at-home glucose monitoring kits, healthy meal plans or exercise plans to its diabetes patients. Or a bank that knows its customers’ purchases, lifestyle, demographics and financial situation could refer its customers to particular insurance products or non-financial services that meet their profile.
Indeed, direct data monetization requires more than just an internal analytics project. Rather, it should be treated as a new product line, with a full product management function and dedicated marketing, sales and support functions. The benefits can be real and significant, such as those from a healthcare industry company that recently identified $100 million of new direct value from a $3 million data monetization initiative. This was from data they were collecting already and using only for basic internal operational purposes, then archiving.
Data monetization comes in assorted flavors. Many of the foremost companies in their sector simultaneously investigate and implement several methods. However, a essential degree of leadership awakening is required. As Cardinal Health’s VP and global head of data, Ranjana Young observes: “Once a company’s business leaders realize that one company’s trash is another company’s treasure, new data-driven value streams start to materialize.”