(US and Canada) Zoher Karu, VP, Chief Data and Analytics Officer, Blue Shield of California, speaks with Jake Dreier, Director, Strategy and Growth, at Hilabs Inc., about using data analytics to lower costs while enhancing quality, exploring and prioritizing solutions, and challenges related to the changing data landscape.

Karu describes reducing cost while maintaining quality as a balancing act. It’s a two-step process that requires understanding cost reduction by looking at significant averages and the philosophy of variability opportunity.

He adds that the trick is to uncover the value in the cost of health care through the philosophy of variability and opportunity. Every provider and hospital is different, he says. Thus, it is critical to understand the outliers, such as why the average cost of an essential service MRI varies from place to place. He emphasizes it is crucial to pinpoint the outliers that might lead to actions.

Karu maintains that a data analytics professional should be curious and proactive in discovering opportunities and driving business outcomes. He states that an analytic person should know what needs to be done at work even if there are no emails or calls to respond to. Karu adds that it is critical to free up mental space to think and solve problems, which is accomplished through automation, data democratization, etc.

He notes that one of the biggest problems in data analytics is prioritization. There are many methods and approaches toward solutions, but prioritization needs to come through continuous dialogue with all business stakeholders.

Referring to Blue Shield of California in this context, Karu states that the organization can do many things but not at the same time. He adds that it is essential to understand what to prioritize and what will move the business needle.

The goal is to accelerate plans and work backward from there, says Karu. He mentions AI and ML as the methodology to get to the goals. He analogizes machine learning using the brake pedal while driving a car. Karu says there are no written rules for it, but the brain takes massive inputs and directs accordingly.

Likewise, machine learning in health care can process massive amounts of data and detect patterns to drive the right outcomes. Karu states that understanding people at an individual level is the backbone of these actions.

Karu affirms that the challenges in the business world have not changed entirely, but the ways to address them have evolved. With the increased velocity and an end-to-end view of the supply chain, he says, businesses are becoming more productive over time.

In conclusion, he states that data analytics is a gold mine — or the “new oil,” as termed by many. However, he considers it the “new sand” because, like sand, data acquires meaning o after it is refined and turned into something else.