(US and Canada) Zoher Karu, VP, Chief Data and Analytics Officer at Blue Shield of California, speaks with Jake Dreier, Director, Strategy and Growth at Hilabs, about organizational challenges from a change management perspective, building a team with required skills, and transitions in health care.

Karu discusses the challenges organizations face from the change management perspective. He says that data is a strategic asset, and it is critical to understand its varied uses.

The mindset required to drive change is that data is everyone’s job, he adds. It’s not an exclusive, one-team responsibility. 

He cites eBay as an example. They offer personalized customer service and support services through a call center. The information is used at multiple levels to meet the needs of highly valued customers. Hence, getting a version of information that can be used at the enterprise level is better.

While data scientists are essential, solving problems holistically requires a different skill set. He believes the interface or translator roles on a data analytics team are vital. Their job is to translate the business problem analytically through predictive modeling.

He says that a team also needs course specialists, statisticians, tableau designers, data scientists coding algorithms, and an analytics person to deconstruct the problem. A chief marketing officer and a data-analytics person can converse if each understands the other’s domain. If a statistician meets with the business provider, it will bear adverse outcomes.

As part of the health care industry’s evolution, Blue Shield of California — formerly a data warehouse – is transforming into a data engine, Karu says. An organization is data driven if it has evolved from data checking the decisions to data making the decisions.

He emphasizes driving the data democratization agenda to put information at people’s fingertips across the enterprise. A well-built dashboard makes it easy, Karu notes. He maintains there are multiple ways to project data, but the art is building it so that the answers are just a click away.

Karu measures data democratization’s success by usage. He says that if people are not using the dashboard, it is because it is difficult or lacks information. The dashboard must be easy to understand to encourage data-driven decision-making. In conclusion, he suggests that the best approach is automating, democratizing the easy problems and specializing in the more difficult ones.