Think about how technology is transforming the health care industry. With telemedicine, people can now get a medical diagnosis by just logging onto their laptop and having a video consultation with a doctor. And trials also are underway for a cancer-spotting breathalyzer that uses an app on your mobile device.

As the industry rapidly embraces advances in technology, it’s becoming increasingly important that brokers get up to speed on using Big Data and predictive analytics. Brokers need to be able to analyze all types of data to help clients spot trends emerging under the radar and gain insights to make better informed business decisions. Imagine if you could accurately estimate how many of your clients’ healthy employees will suffer a chronic illness in the coming year.  That’s using Big Data to make smart decisions!

While dipping your toes into the pool of Big Data may seem intimidating at first, the value it can add in helping clients and prospects understand possible future business outcomes is enormous.

If you’re unsure where to start, here are a few tips.

Go big or go home. You need to aggregate vast amounts of internal and external data to get the context needed to see the complete picture that data can provide. The first step?  Make sure your clients are collecting and standardizing their internal information across all parts of their business so they can measure and compare it companywide.

Next, leverage external data. While many brokers already collect data from benefits carriers and the U.S. Census, go beyond benefits and explore things like industry turnover rates and pay trends. This external data can help your clients benchmark their performance against industry peers so they can see how they stack up to the competition. Are they offering the benefits options needed to attract and retain top talent?

Lastly, ask your clients for permission to access their HCM and payroll data so you can help them identify patterns and make suggestions in real-time. Survey data can often be outdated. You want to make recommendations based on living data that’s changing with employees’ wants and needs.

Analysis doesn’t take a PhD. Collecting data is one thing; without analysis, your data means nothing. Analysis helps you tell a story and start asking questions such as, “Why are claims unusually high this year?” or “Why aren’t employees using their preventive health benefits?”

By digging deeper into data, you’ll be able to identify areas where clients may want to consider making changes. For example, a company may think employees want a high-deductible plan with certain options, but the data may uncover that only boomers are using the plan as intended. Upon closer examination, you may learn that millennials, who now only make up 30 percent of the company’s workforce, require different health care options and that segment is growing by 10 percent a year. Armed with this data, you can consult with your client and make plan recommendations that will better serve their multi-generational employee population in the years to come. Not only will you help them avoid unnecessary costs, but you’ll help them keep employees engaged by offering plans people will actually find beneficial and are more likely to use.

While showing clients how to reduce their medical costs is a huge differentiator, you can add further value by analyzing everything from absenteeism to overtime pay and compensation rates. For example, if your client is based in Peoria, Illinois, but is opening an office in New York City, you can help analyze industry benchmarks to show the best types of benefits plans being chosen by different segments of the population in New York City and show clients what competitors in the area are paying for that specific role.

Embrace the power of predictive analytics. According to the Mercer® 2017 Global Talent Trends study, few senior executives and HR professionals are able to translate human capital management data into predictive insights, and nearly 1 in 5 is generating only basic descriptive reporting and historical trend analyses.

This is where brokers can add value. How great would it be if you could show clients how employee turnover is impacting productivity or how more paid time off could lessen employee sick days?

While predictive analytics do not literally make predictions, they do show what is likely to happen given historical patterns and data analysis. Predictive models provide insights that can spark conversations to help determine whether action is needed. Consider employee turnover. Predictive models can help identify potential flight risks within a company so HR leaders can then take action and develop retention plans, or possibly encourage coaching to managers who may have high turnover levels in their department. The insight gained from the analytics helps lead to interventions so companies can address likely problem areas before they impact the entire organization.

Having the right insights available at the right time is critical to workforce management. Research from Deloitte® shows that “companies that build capabilities in people analytics outperform their peers in quality of hire, retention and leadership capabilities and are generally higher ranked in their employment brand.”

As the broker community shifts from a commission to fee-for-service model, brokers who wrap analytics services into their cost structure will not only be seen as more strategic consultants on “all things HCM,” but they will help clients unlock hidden value by gaining invaluable insights.

Bruce Whittredge is Vice President of Broker Strategy at ADP®.

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