Srinivasan Sankar, Enterprise Data and Analytics Leader, The Hanover Insurance Group, speaks with Robert Lutton, Vice President, Sandhill Consultants, about the ideal approach to data literacy and the need for business involvement in all data projects.

Sankar has been in the field of data and analytics for 25 years. He says that the topic can be dissected in several different ways and could eventually have various meanings for others.

A professional, he looks at current data and analytics platforms as ensuring access to the right data at the right time and right quality for all the business users. It also includes self-service, self-sustained, scalable performance, and accessibility aspects. 

“It’s available without too much engineering or management. I’m not advocating that everything has to be completely black-boxed, and we don’t need engineers. It is more of a self-service analytics data information access with a consumer-friendly approach,” Sankar explains.

He shares how he established such a program at Hanover. When he joined the company seven years ago, business users at the organization didn’t have easy access to data.  Data users at Hanover flagged the issue, noticing how it took three to six months to access reporting dashboards and scorecards after submitting a request to IT.

Against this backdrop, Sankar highlights another aspect of modern data and analytics — data democratization and opening data up with proper security, privacy, and access controls.

“I found an opportunity at just the right time to put all dashboards, score cards, and report development in the hands of the user. It’s been five years since the organization went to the self-service BI and analytics platform.”

Data literacy training is not limited to data people or IT. A successful data leader needs expertise in data and analytics, he says. A CEO or CFO needs to have data literacy.

Next, Sankar shares his insights regarding the best way to engage the business and explain how IT delivers. He recalls his early days as a data professional when data initiatives were identified as business intelligence projects.