The Untapped Potential of Benefits Data Analytics

Woodruff Sawyer’s “Mission to More” series leads you through today’s Benefits news and serves as a guide for everything from competitive programs to compliance. In this blog post, Hector Jaramillo shares the power of using data analytics and expertise to keep companies thriving.

What’s Your Data Experience Level?

Employers recognize that they need healthcare data to better manage benefits costs but are at three different levels when collecting, managing, or interpreting that data.

One study indicated that 97% of employers want more data, but more data isn't necessarily better unless you know how to create and apply insights. Understanding where you are on your data analytics journey is the first step in deploying a well-defined data analytics strategy.

Regardless of where your organization falls, it’s likely that you are looking to do more to achieve your employee benefits goals. Getting there will require clarity on what your mission is and what you will need to achieve it.

Building a Case for Data Analytics

HR and Finance leaders must have a clear purpose for using healthcare data to garner support across the organization for their program. Once such programs are endorsed, companies find unique ways to use employee healthcare data to help them control costs, become more competitive, and attract employees in a tight job market. Here are some examples of ways that data analytics help to improve your benefits programs and strategies:

Build an equitable benefits program: A recent study showed employees want expanded benefits that meet basic needs (including housing and transportation); are easy to understand, access, and use; and support a workplace culture that destigmatizes receiving care. In addition, the study showed that Black, Hispanic, Latino, Asian, and LGBTQ+ people were less likely to get the care they needed and more likely to consider switching employers for better benefits. Employers can use this kind of survey data to expand or evolve their benefits program offering to meet the needs of their workforce demographics.

Understand costs and cost drivers: Annual premium hikes, confusing claims experience, and rising prescription costs can leave employers feeling helpless. Data analytics show employers detailed costs and who and what drives those costs. The Pareto principle is common, where 20% of the people drive 80% of the cost. Focusing on that 20% can lead to significant reductions, helping employers redirect resources to other strategic priorities. Examples include examining outcomes for specific employee populations and chronic conditions that result in care gaps. In addition, understanding business unit or geographic differences helps employers deploy specific initiatives to lower costs.

Identify funding alternatives: Reviewing claims experience, large claims, and employee demographics reveals if companies are financially ready for self-funding, captive programs or an Individual Coverage HRA (ICHRA). This data opens doors to funding alternatives that employers had not considered but that may be excellent strategic fits.

Improve M&A data economies of scale: Companies expect to save money in a merger by consolidating benefit plans. But it is hard to find those savings unless data from all business units are combined to reveal hidden issues, cost savings, and opportunities to serve employees better. These insights will align benefits programs, reveal inconsistencies between business units, identify the financial impact of consolidation, and support a common platform for plan performance.

Support a culture of healthy employees: The CDC cites studies that show healthy employees are less likely to call in sick or use vacation time. As employers use data to dive into benefits usage and costs, they can drive better health outcomes for employees while benefitting from improved productivity, lower costs, and increased satisfaction. Furthermore, monitoring wellness program utilization with data helps employers evaluate their investment.

These tangible benefits are a great reason to adopt or enhance data analytics usage. However, true success comes from aligning data analytics to strategic initiatives, including improved profits, DEI and employee engagement, and competitive standing. Strategic alignment unleashes the untapped potential of analytics, revealing new opportunities to save money, serve employees, and stay competitive.

Best Practices from Best-in-Class Companies

Best-in-class companies start with clear organizational goals for their benefit programs, backed by workforce demographics, detailed healthcare costs, and claims experience. In addition, companies need advanced tools and expertise to manage and disseminate data.

As firms expand their use of analytics, they find new insights. But there is no substitute for experience, as leading companies have learned how to collect, analyze, and apply insights. These leaders are in tune with data patterns and scenarios, driving strategic decisions. But they also are nimble, learning from mistakes while they keep moving forward.

One study examined data from 13 large companies that leveraged data, questioning 26,000 employees. As a result, they identified individuals with at-risk health conditions based on claims experience, biometrics, and related data. Employees received communications that offered a nurse-led coaching session. This initiative resulted in a 10.3% reduction in medical costs and a 5-to-1 ROI for employer health plans and wellness programs.

In addition, biometric data screening identified employees with chronic conditions like high blood pressure, followed by an uptick in associated prescriptions a month later. New tools help HR identify employees needing assistance while avoiding future complications.

Leaders understand that data collection is not a one-time event but an ongoing pursuit of improving employee health while meeting strategic goals. HR dashboards and advanced tools alert employers to immediate issues so that they can follow up with appropriate action.

As companies gather more data, they are also obligated to improve data security and maintain a secure IT architecture. These systems manage the most sensitive employee data, and firms must have the resources and foundation to keep that information safe.

Finally, best-in-class companies recognize the human component of data analytics. While data reveals trends, the people in the organization must act upon them. As empathy, connection, and equity become standards in today's business, data will continue to drive decisions but cannot replace human actions.

Using Data and Analytics: Next Steps for Employers

Data analytics becomes a well-honed practice for those who know how to embrace it, learn from it, and use it to their strategic advantage. By combining people, data, and insights, you'll learn to unleash the true potential hidden in your employee benefits program.