The promise of big data has existed now for over 30 years, but in my experience, many companies are only now starting to figure out how to capitalize on this strategic asset.  Many well-known use case studies on the value of data like Netflix, Amazon, and Google exist. But what has changed recently that’s enabling more companies to start monetizing their data, and what common obstacles still exist?

As Dr. Barbara Wixom points out in this MIT Sloan Management Review article on Data Monetization, “companies must first transform data so that it can be reused and recombined to enable new value creation. The easier the reuse and recombination, the higher the data’s liquidity”.

What we see in the industry is a classic chicken-and-egg problem between the business and technology departments.  Many businesses wait for the technology teams to demonstrate the art of the possible. Yet, the business doesn’t want to invest in data re-platforming initiatives that enable data monetization without a strong business case, leaving the business with data siloes and a lot of dark data.

We are already starting to see a number of companies separate themselves from their competition, by strategically investing in data re-platforming. In doing so they are creating long-term data assets to enable data monetization capabilities. With initiatives such as these, companies are priming their data sets for re-use. By following a well-defined enterprise data taxonomy, different data owners within the business can contribute their own data sets and create a central repository of data assets for the business. 

With a carefully curated set of data assets, users can now select, combine, and reuse data sets to address current business case requirements and have the capability to address new business use cases that aren’t yet defined.  As a result, companies that invest in data transformation are finally starting to realize the promise and value of big data.