There are three data points that are driving the business discussion around big data:
1. Only 1% of the world’s data was being analyzed (IDC); while at the same time, 100% of the data is costing companies CapEx and OpEx every day.
2. Consumers and businesses are beginning to recognize that the insights locked in data that reflects personal usage, location, profile and activity has a tangible market value. This is especially true when you apply the Power of Three principle to data sets.
3. As a result, 30% of businesses will monetize their data and information assets by 2016 (Gartner), up from today’s 10% baseline.
As big data management consultants and data scientists, working with lines of business, begin to address these drivers, we should expect the following solution to fundamentally change the we monetize our business (mostly through applications and people):
:: Companies will look to drive incremental revenue by placing their point-of-sale (POS), internal social, relationship-oriented, and other data online for business partners to subscribe
:: Companies will launch ventures that package and resell publicly available data (creating new data sets and insights), or using it to launch new information-based products
:: Information Resellers are arising to help organizations develop and execute data and information asset monetization strategies.
:: Information Product Managers to lead these efforts internally to identify, create, and make operational new services out of data.
:: New information architectures, focused on monetized data services (Quadrification of Big Data), will emerge since traditional business intelligence products and implementations are not well-suited to analyzing and sharing data in a subscription-based manner. This will transform platform companies that produce data into data insights companies that have platforms
This type of monetization strategy can can open new revenue doors without a significant change in existing platform and/or services investments. The nice thing about information product management is that it leverages most of the platform/service development to date. New immediate revenue can come through the sale and/or licensing of de-personalized data (loyalty, POS, social, etc.) to third parties.
Secondary revenue streams, which can come later in the implementation phase, comes from combining existing data sets with other third party data (transactional, social, etc.) in order to identify orthogonally conflated services (see the Power of Three). This capability would come at a marginal incremental cost and could be outsourced to cost competitive data science teams.
We are at a tipping point for the realization of value from data-oriented services (big data, data science, etc.). Those that see limited growth opportunities in traditional application and services development are already well underway in this data science transformation phase. For those that don’t see the need to monetize their data and information assets, it may be an Extinction Level Events (ELEs) that is competitively unavoidable.