Monetizing enterprise data without running afoul of privacy laws is the next frontier. There may very well be data in your organization that is just sitting there unused, waiting to be put to good use. While a company might, for example, consider itself a manufacturing business that provides new products, or a telecommunications enterprise that offers services to other businesses, there’s another point of view that would put them in the data business.
As far as MIT Sloan Management Review is concerned, every enterprise in business today is a data company whether they realize it or not. “Most have access to an array of data on their supply chains, operations, strategic partners, customers, and competitors.”
However, MIT determined that only 1 out of 12 companies are now monetizing money to their full potential. The information itself is indeed valuable, but there is even more value to realize based on insights you generate from this data. “These insights can be used to direct activities as varied as customer segmentation, demand and churn prediction, pricing optimization, retention marketing, and cost management — and they can also command even greater margins when sold externally.”
You’ll see that there will be opportunities to monetize data in two main ways: leveraging it to improve internal operations and adding value to data for external use, selling it to partners and customers.
For companies that are realizing the benefits of turning their data into revenue, many have only recently begun to explore this new approach. McKinsey reported that such “efforts are fairly new. Of the 41 percent of respondents whose companies have begun to monetize data, a majority say they began doing so just in the past two years.”
About half of respondents to a McKinsey survey said that “data and analytics have significantly or fundamentally changed business practices in their sales and marketing functions, and more than one-third say the same about R&D.”
Building a Solid Base for Monetizing Enterprise Data
Chances are that if you aren’t already generating revenue from data in your enterprise, you’ll need to first set up a foundation for the system.
A foundation for turning data into revenue will be based on devising a strategy, putting the talent in place and organizing the employees, and getting buy-in and endorsement from your key stakeholders.
When it comes to strategic decisions, the majority of companies responding to McKinsey’s survey (61%) said they do not have a strategy for data and analytics. Part of the problem is that often it’s a lack of available talent to help companies in these endeavors. About 60% of respondents said they find it difficult to recruit individuals who are skilled technically and can demonstrate expertise in their domain, to serve as “translators” between departments.
Your leaders will need to demonstrate their commitment to the data monetization project. This will involve being consistent in leadership messaging to workers about the high priority you place on turning data into new sources of revenue.
Establishing a Data Platform
Forward-focused enterprises will determine that setting up a data platform is the essential next step in monetizing the information they’ve been generating and collecting.
Sisense raised the question: “What makes the world’s most innovative and successful companies different from the rest? One secret is constantly seeking new ways to develop their resources. And one of the biggest assets at any company’s fingertips is their data.”
It’s important to figure out where you will incubate the work that goes into turning data into revenue. You’ll also need to settle on who will be in charge. Charles Holive, Managing Director of Data Monetization and Strategy Consulting for Sisense, said that “My recommendation, and where I’ve seen it working really well in companies I’ve consulted with, is having the data chief reports to someone neutral, like a chief innovation officer or a chief financial or executive officer.”
Then, it’s time to decide whether to create a data analytics platform or buy one. You can determine the best course to follow by seeing if you would save money and time building an analytics system yourself, or if you would be better off using existing tools using pre-built solutions that you customize as needed. If you already have staff in place with the skills set to take on this challenge, it may be best to do it internally.
Examples of Monetizing Enterprise Data
To help spark discussions among your stakeholders on data monetization, it’s useful to consider examples of companies that have had some success in this area.
In telecommunications, companies such as Deutsche Telekom and Verizon are monetizing data to improve client services and operations. They are also leveraging this data by anonymizing and aggregating it to highlight use cases for business-to-business partners and clients.
Now, telecommunications enterprises can offer geotargeting and geofencing information to tourism companies and retailers. They supply fraud detection data to credit card businesses, and provide data on traffic density and flow to support new business planning for advertising companies, healthcare entities, and transportation businesses, according to MIT Sloan Management Review.
Another example comes from the agriculture sector. “John Deere is one company that has created a new source of revenue for itself and value for its farmer customers through data,” said MIT. “They did this through a partnership with Cornell University, using Ag-Analytics, Cornell’s data platform that syncs with John Deere’s operation center to access and analyze farm data.” Public data sources integrate details about weather and soil conditions. Farmers log into the platform for analytics, helping them to make better estimates for crop insurance as well as to forecast yields or manage risks.
Other enterprises which are digital natives have found new ways to harness their data too. Companies such as Airbnb, Amazon, and Netflix “monetize data internally by gaining an intimate understanding of their customers. They look at things such as demographics, special needs, historical purchases and interactions, shopping behaviors, and pivotal events, offering highly personalized products and services within an end-to-end experience,” per MIT.
Fueled by the ongoing data that they analyze, the companies extend their interactions with customers, such as prompting them to discover new products, engaging with them after purchases, and presenting new information to promote re-engagement.
Making the Most out of Your Data Internally and Externally
Depending on the nature of your company and industry, the new revenue you derive from monetizing data may come mostly through improving internal functions, making you more efficient and productive as well as assisting in meeting customer expectations. Or you may find yourself profiting by enhancing the data for sale to customers and partners.
For many companies, profits will come from using data internally and externally as they learn to harness the new streams of information and see the added value they can add. Time will tell whether new external sources of revenue will start to eclipse the value you derive from improving company processes and systems based on such data.
Are you monetizing enterprise data? How are you balancing privacy and information security considerations with the need to make money from data?