One of the mainstays of the data-centric culture is to drop biases. Look for the data, and derive correlations from there. Or, ask not what you can do for your data, but what your data can do for you.
Data-Centric Companies Think Long Term
Data-centric companies find way to perpetuate lifetime value through the acquisition of new, multi-generational customers. Remember: the data you have now only shows a current snapshot of your environment. Thinking data-centric is thinking long-term. It’s looking for patterns in the data to see where your company is, sure, but more important to look at where it’s going, and then developing a plan to work towards getting there.
To data-centric companies, thinking long-term means thinking about customer engagement. They maintain a high brand-to-customer focus, where the brand itself is largely defined by the customer’s sentiment and influence. For the customer, the relationship to the brand is a connection assembled through experience. This, for example, is why I buy books from Amazon (for practicality and selection), but I spend weekend days curled up at Barnes and Nobles flipping through stacks of books and sipping coffee—it’s an experience.
Data-Centric Companies Take Action
Finally, data-centric companies act on analytics. Data without action holds no value on its own: it’s the action that drives the business value. Acting on analytics isn’t a one-time thing either, but instead a continuous process of experimentation and improvement. Improving analytic models is as important as the data underneath is continually changing, too.
For a quick example, refer back to my earlier comment on the untapped value of the weather app. At a recent client event in Reno, Nevada we asked attendees how many weather apps they had on their smartphones. Many—at least a quarter of the room—noted they had more than one. The rub: having multiple analytic engines drives competition, and competition drives improvement.
Lastly: Data-Centric Companies Don’t Forget About Mobile
Becoming a data-centric company requires an inevitable cultural change to achieve competitive advantage. Through competing on analytic abilities, companies can build deeper understandings of customers and relationships. Think about the data you collect today—and then realize that the activity you capture today (probably) isn’t enough. Being data-centric means going the extra mile in the way you interact with your data.
And, think mobile—and think about mobility as a way to instrument customers, too. Today, through mobile apps, customer’s “public personas” are available through APIs. And, mobile is a “me” phenomenon: it’s a direct line to a customer’s most selfish desires—what they like, what they hate, what they want, and what they’re willing to say about it all. This social data tells us exactly who our customers are, and the best ways to make them happy. Remember, too, that mobile is a two-way phenomenon: companies think about pushing information and services to customers, but they also need to think (selfishly) about how to pull data back and learn from customer activity.
Lindy Ryan, who will be a featured speaker at DBTA’s Data Summit, is the Research Director for Radiant Advisor’s Data Discovery and Visualization practice and leads research and analyst activities in the confluence of data discovery, visualization, and data science from a business needs perspective. You can follow Lindy on Twitter @lindy_ryan or email her at lindy.ryan@radiantadvisors.com.
Data Summit is your guide to the future of data management and analysis and how it is transforming the business world as we know it today. Providing an intensive 2-day immersion into critical technologies for becoming a data-driven enterprise, IT practitioners and business stakeholders alike will benefit from Data Summit. You have until April 11 to take advantage of special pricing for DBTA’s Data Summit, which will take place at the New York Hilton Midtown, from May 12 to May 14.