Chicken or the Egg? Data or Analytics?
I just saw an online discussion about the role of a chief data officer, whether it should be more about data or analytics. My initial response to that question is "neither." A chief data officer must represent the business first. And I had the same answer when such a title didn't even exist and CTOs or other types of executives covered that role in data-rich environments. As soon as an executive with a seemingly technical title starts representing the technology, that business is doomed. (Unless, of course, the business itself is about having fun with the technology. How nice!)
Nonetheless, if I really have to pick just one out of the two choices, I would definitely pick the analytics over data, as that is the key to providing answers to business questions. Data and databases must be supporting that critical role of analytics, not the other way around. Unfortunately, many organizations are completely backward about it, where analysts are confined within the limitations of database structures and affiliated technologies, and the business owners and decision-makers are dictated to by the analysts and analytical tool sets. It should be the business first, then the analytics. And all databases—especially marketing databases—should be optimized for analytical activities.
In my previous columns, I talked about the importance of marketing databases and statistical modeling in the age of Big Data; not all depositories of information are necessarily marketing databases, and statistical modeling is the best way to harness marketing answers out of mounds of accumulated data. That begs for the next question: Is your marketing database model-ready?
When I talk about the benefits of statistical modeling in data-rich environments (refer to my previous column titled "Why Model?"), I often encounter folks who list reasons why they do not employ modeling as part of their normal marketing activities. If I may share a few examples here:
Stephen H. Yu is a world-class database marketer. He has a proven track record in comprehensive strategic planning and tactical execution, effectively bridging the gap between the marketing and technology world with a balanced view obtained from more than 30 years of experience in best practices of database marketing. Currently, Yu is president and chief consultant at Willow Data Strategy. Previously, he was the head of analytics and insights at eClerx, and VP, Data Strategy & Analytics at Infogroup. Prior to that, Yu was the founding CTO of I-Behavior Inc., which pioneered the use of SKU-level behavioral data. “As a long-time data player with plenty of battle experiences, I would like to share my thoughts and knowledge that I obtained from being a bridge person between the marketing world and the technology world. In the end, data and analytics are just tools for decision-makers; let’s think about what we should be (or shouldn’t be) doing with them first. And the tools must be wielded properly to meet the goals, so let me share some useful tricks in database design, data refinement process and analytics.” Reach him at firstname.lastname@example.org.