4 ways big data is affecting benefits administration
The Internet of Things (IoT) is an increasingly popular topic of conversation across all industries. The byproduct of all of this connected stuff is a goldmine of data to be analyzed. In fact, a recent study by EMC found that 1.7 megabytes of new information will be created every second for every human being on the planet by 2020. From a 10,000 foot perspective, that information represents the ability to identify patterns that could have the potential to unlock previously unknown insights valuable to delivering new products and services.
One industry that certainly stands to gain from all of this data is benefits administration – think “smart benefits.” So, what does that mean? Data from employees who are enrolled in benefits plans can be analyzed, providing insights around patterns of what is working, what isn’t working and where there are holes in coverage. Very broadly, big data should continue to push employers to be smarter and ultimately solution-oriented about their benefits offering.
Let’s break this down and look more specifically at the areas where data analysis will, and in some cases already is, impacting benefits administration.
1. Better informed recommendation engines. Benefit recommendation tools are already using data to suggest specific plans to employees based on their disclosed information. However, imagine how intelligently we could suggest benefits if we had insights – backed up by large data sets, into risk tolerance, budget concern (or lack thereof) and healthcare history among other factors – and were able to break down those insights by different demographics. This information would aid in the recommendation of benefits to new users that come into a network given the ability to match that user’s profile to thousands of other users that have comparable attributes and suggest similar offerings that have proven to be successful with these like-groups.
2. More educated benefit decisions. HR and benefits managers increasingly are asked to back up their benefits recommendations to company executives with data and analytics. Benefits platforms already offer real-time data reporting on their employees’ benefits choices, but that only provides face-value insights. The next generation of data analysis will look at patterns of benefits offering successes within many employer groups and match those patterns to the demographics of individual employers, giving HR and benefits managers more insight and confidence in their recommendations.
3. New benefits products. New products will be more easily placed where there are identified needs based on data analysis. As employers seek to exercise empathy through the benefits they offer, with the larger goal of attracting and retaining employees, understanding where the needs are will become that much more important. We’ve already seen this happening with the push towards offering student loan repayment as a benefit. Companies are recognizing that employees’ well-being and relative productivity is being affected by their mounds of debt and financial stress, and as a result are seeking to help alleviate that burden through empathic benefits offerings.
4. Well-informed user interface (UI) and user experience (UX) in benefits selection. UI and UX are quintessential aspects of our business, and it’s our job to help employers engage their employees in the process of selecting benefits critically and effectively. Data insights into behavior around selection will allow us to understand which UI and UX interfaces are the most effective, and we’ll be able to cut that data by various demographics to understand how we can customize selection to various employee groups.