For years, using more data to make better decisions has been the holy grail for global companies, and most of them aim to treat data as a strategic asset. But new research from the MIT Center for Information Systems Research (CISR) has found that future-ready companies have greater ambition regarding their data. These organizations strive to maximize their data monetization outcomes by pervasively improving processes to do things better, cheaper, and faster; wrapping products with analytics features and experiences; and selling new, innovative information solutions.
To monetize data, companies must first transform it 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, which we define as “the ease of data asset reuse and recombination.”
Preparing strategic data assets for reuse and recombination
Data liquidity is a continuum, not a binary condition. It is a function of the ability to convert data for use, which means that a particular data asset may be more liquid or less liquid than another. Many companies’ data has low liquidity — it may be trapped in local business processes, locked in closed platforms, or replicated in multiple locations, for example — or it may be inaccessible simply because it’s incomplete, inaccurate, or poorly classified or defined.
Much managerial attention focuses on liberating data from silos and applying it to a new, specific use, such as calculating customer churn or spotting supply chain breaks. This is a good exercise, but not a strategic one. Sure, an initiative on customer churn or supply chain will realize new value for the company. But companies that continue to pursue only a linear value creation cycle are leaving money on the table.