Become a superhero with the power of your company’s benefits data
Starbucks, data scientist John Thomas reports, spends more on its employee healthcare than it does on coffee beans.
That fact helps put in perspective just how much organizations spend on healthcare and other benefits for their workers. During an HR Tech Conference session Friday morning in Las Vegas, Thomas described a problem that he believes data analytics can help solve: The rising cost of employee benefits amid flat or falling budgets for benefits, increasing benefits costs and, of course, the COVID-induced changes in the labor market.
Putting these tools to work can help HR leaders better understand and help their organizations, in part because they have access to a broad range of data, said Thomas, chief data officer for Benefitfocus.
“So, I want to equip you with some information about how data analytics and technology can help us become superheroes—at least when it comes to benefits,” he said.
Descriptive and diagnostic analytics can help you see what’s going on and why it’s happening, respectively. For example, seeing a cost increase from year to year is descriptive, and slicing the numbers to find out that it happened because of more pregnancies is diagnostic.
Both of these can help HR leaders better plan for the future, he says. Recent examples include the 29% increase from 2019 to 2020 in the use of mental health benefits because of COVID. Knowing that, organizations can adjust their plans to meet anticipated needs next year.
Predictive analytics is using the data to predict the future, so an individual could use it to help choose the best health plan. Thomas used himself as an example of someone who’s “moderately intelligent” but really bad at making this choice each year.
Rather than closing his eyes and selecting either whatever he had last year or “the most expensive plan,” he could use analytics to run his claims from this year, with some customization if needed, through the new plans being offered next year to compare prices.
That means “I can make more informed decisions about what my total cost would be,” Thomas says.
Using similar scenarios can help organizations look at possible savings under new proposed healthcare plans, evaluate their ROI from different vendors and determine how to restructure their networks of service providers to reduce costs, Thomas says.
Prescriptive analytics takes data analysis a step further by recommending actions to manage care, either individually or for organizations. Ideally, Thomas says, that last piece is tied to technology and automation.
An organization trying to reduce its high and inefficient spending on prescription drugs, for example, can run an algorithm for similar drugs that health plan users might use for diabetes. If it finds a doctor has prescribed a more expensive name-brand drug, the program could email the doctor noting that the patient could save $900 a month on a generic drug.
If the doctor signs off on making a change, an API could change the prescription at the pharmacy for the patient. Companies that deploy this technology typically reduce their drug costs by 5-15% without doing any more work, Thomas says.
And that was just a short overview. “In the benefits space,” Thomas says, “there are tons and tons of examples where we can find ways to use data technology to drive efficiency.”