Data is all around us. It’s ever-growing, and as we know, it’s a powerful commodity, and the underlying factor for many of the world’s most successful businesses. We can say, data is the new currency. Armed with it, some companies are disrupting established industries, and traditional businesses are transforming the way they operate. Not all organizations are equally adept at translating data into business(and eventually money), but their ability to play, churn and get value out of the data is impacting their ability to compete. With larger-than-ever volumes of data now being captured and stored, coupled with cheaper and improved computer infrastructure and processing power, there has never been a better time to make data commercialization, a part of org-wide corporate strategy. ‘Data commercialization’ or ‘data monetisation’ is ‘the next frontier in digital transformation’.
Data-rich businesses like banks, retail outlets, malls etc which do not commercialise data in an effective way to provide new services to customers or create new propositions will fall behind the competition and the new disruptors in the marketplace. Most organizations realize they have a wealth of data -but not all of them are able to realize its potential value because of technological and cultural challenges often stand in the way. Even though more lines of business are better at leveraging their data for their own purposes than they once were, the value of the data from an enterprise perspective may not yet be fully realized. In my opinion, the reasons for this could be Data quality, disintegrated systems, lack of understanding of data driven decision making in leadership teams, budget allocation for innovative business offerings, compliance, privacy, and security issues may limit the ways in which the data can be used.
Data commercialization can be a source of competitive advantage, which can be achieved by: 1. Analysing the data to create new products or services which enhance the customer relationship 2. Applying insights for building internal efficiencies 3. Generating new revenue streams by studying trends and patterns from all data sources in your organisation