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.
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:
However, unless you’re measuring the impact data is having on these internal benefits, it may be difficult to claim you’re monetizingit.
Direct data monetization methods are less common and all too often overlooked. Various studies from Gartner, Forrester, McKinsey, MIT’s Center for Information Systems Research and others indicate that only about one-third of companies today have even begun dabbling in generating external benefits from available data. These various forms of direct data monetization include the following:
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.
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”.
