Leading health payer bolsters insights with NLG for business intelligence
By: Shawn Parks
Waiting is the hardest part
The chief data officer (CDO) was used to waiting, but that didn’t mean she liked it. Running a center of excellence is often a solution looking for a home. In her case, the parent organization did the initial vetting, so she was just waiting for her team to approve. She was very excited about the implementation of this new technology.
This was exactly the situation when one of the largest health insurance plans was looking for a group to engage in a natural language generation (NLG) project. The CDO in this division serves more than three million members in the Southern U.S. She was the one who raised her hand to be the guinea pig.
There were a number of concerns that led to the discovery and subsequent excitement.
First, improving data literacy. This is not a unique challenge; it’s a growing concern that many deal with. We have more data than we know what to do with, yet lack insight.
Next, the organization needed to cut down on manual reporting time for analysts and consultants within the commercial reporting group. Also like many others, the best solution was to throw time, people, and money to attack the problem with data literacy by brute force.
Finally, account managers needed assistance to deliver better insights to plan participants on a wide range of issues. This is more unique for health payers. There were concerns with macro topics, such as tracking metrics related to population health or helping companies realize savings by better understanding their premium utilization.
But, good things come to those who wait
The national organization found that it could innovate and begin to tell stories with its data. This discussion originated as a custom engagement. The team thought that what they needed was a uniquely built report. They believed that their underlying data was too complex to be automated by an out-of-the-box product. The robustness of the solution ultimately exceeded their expectations. Additionally, it provided the scale that could not be achieved with multiple custom projects.
After upgrading their Tableau license, the team gained access to the Extensions API. This supported additional integrations and this was the exact value-add they were looking for. Typical with data visualization deployments, there were more than a hundred dashboard builders and well over a thousand viewers. Nationally, this number exceeds 400,000. All who need a better way to quickly glean insights and make better decisions.
A solution finds a home
So after nearly a year, the CDO rolled out NLG for business intelligence to the team. The results are better understanding of their data, more time for in-depth analysis, and deeper insights to meet customer needs. With a new approach, she has one more tool to support data-driven decision-making. In hindsight, it was well worth the wait.
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