By Cheryl SooHoo
How do you turn your company’s big data into big bucks? First think big and then bigger about the value of your data, says Russell Walker EMP 64, clinical associate professor of Managerial Economics & Decision Sciences at Kellogg.
“Your data doesn’t jump out and say, ‘Hey, I am worth hundreds of millions of dollars,” says Walker. “You must create unique data products that provide valuable solutions that answer business questions. Very few companies want to buy reams of raw data.”
LinkedIn, for instance, found gold in helping its users manage their own professional networks by selling premium services right back to them. Learning who has viewed your LinkedIn profile can lead to additional networking opportunities, but it comes with a price. Says Walker, “LinkedIn has taken data that’s essentially free to them and transformed it into products people are willing to purchase.”
Mining for nuggets of gold is just one of the key tenets of monetizing big data that Walker highlights in his new book, From Big Data to Big Profits: Success with Data and Analytics (Oxford University Press, 2015). In it, Walker cites the profitable business models of Apple, NetFlix, and Amazon, among others. These enterprises have successfully created new products and services by utilizing the massive amounts of information being produced in our increasingly connected and digitized world.
“Aside from the innovators and disruptors, a lot of companies are just now waking up to the idea of monetizing their data,” says Walker. “Many of them struggle with how to do it.”
Providing a roadmap for business leaders, Walker’s book offers a myriad of tips, including:
“The biggest challenge for companies is expecting results quickly,” says Walker, who consults with firms on the use of big data and analytics. “It takes a long-term commitment of people and time, and a healthy appetite for risk-taking. The value in big data will not be created overnight.”
This originally appeared in the Kellogg Executive MBA blog on September, 24, 2015.
Analytics, Asymmetric Information, Big Data, Big Data Analytics, Big Data to Big Profits, Data Analytics, Data Monetization, Data Science, Digital Platforms, Economic Sciences, Kellogg School of Management, Leadership, Location Based Services, Mobile, Oxford University Press