Businessolver Blog

Why it’s Important to Personalize Benefits Based on Real Data

Why it’s Important to Personalize Benefits Based on Real Data
Posted on Monday, April 26, 2021 by Rae Shanahan
Share:

People love choice, but they really don’t like making choices. As humans, we get overwhelmed and even experience psychological stress when faced with too many decisions.

MicrosoftTeams-image (4)

This applies to everything from routine trips to the grocery store to employee benefits elections. According to a recent study, just over a quarter of employees would rather give up their favorite food than go through benefits enrollment, and 93% simply pick the same options year after year.

This inertia and avoidance aren’t because employees don’t appreciate their benefits package. In fact, the opposite is true: Almost three-quarters of employees believe their benefits are extremely or very important to their financial well-being.

However, benefits decision-making can represent some pretty advanced number-crunching, which can make it challenging. With core health and welfare coverage alone, making the best decision means employees need to calculate potential total costs—including their contributions, out-of-pocket spending and maximum limits, plus any FSA, HSA or HRA dollars. This is something HR and benefits professionals likely can do in their sleep; but for many employees, the easiest choice may often be seen as the best one.

In this third year of Businessolver’s annual MyChoice® Recommendation Engine Benefits Insights Report, we look specifically at the impact of COVID-19 on three factors influencing employee decision-making that we’ve been tracking since 2019. To dive into the importance of this data and why personalization and digitalization of benefits enrollment can help boost employee productivity and overall consumer intelligence, our Head of Benefits Innovation Mike Meyerring and SVP of Innovation and Strategy Sherri Bockhorst discuss the report in the video below. 

Video Transcript

Mike Meyerring:

Hello. My name is Mike Meyerring. I lead our benefits innovation group here at Businessolver. We’re a team within Businessolver that’s really focused on connecting our customers to the most innovative products, services, and solutions in the industry. And today we’re going to be talking about one of those really innovative products and services, which is our MyChoice Recommendation Engine, but more specifically the important data that we continue to gather from the individuals that use the MyChoice Recommendation Engine.

                         We provide the support for our customers so that they can start to gain better insights in what’s going on in their population, their employees. What are we seeing as it relates to benefit adoption and enrollment? How does this tie to individual’s emotional, financial and physical wellbeing, and how can employers take this information and think about it strategically in designing their benefits programs? But I’ll be facilitating the conversation today. More importantly, I’ve brought a friend and a coworker with me who is an expert to share some background more specifically around this. Sherri Bockhorst is with me. Sherri, would you like to introduce herself?

Sherri Bockhorst:

Sure. Thanks, Mike, and hi everyone. My name is Sherri Bockhorst. I help lead innovation and strategy here at Businessolver, and I am intimately involved with the MyChoice Recommendation Engine. This is the third year that we’ve provided the Insights Report. We’ve actually had the Recommendation Engine quite longer than that, but we were finding the data so valuable in our discussions internally about how to drive our products and our solutions, and our clients were finding the data so valuable regarding the management of their own benefits programs that we decided to really turn this into a report to share those findings more broadly. So, excited to share some of those insights with you today. Thanks, Mike.

Mike Meyerring:

Fantastic. Well, as we mentioned, the MyChoice Recommendation Engine Benefits Insight report is a report that we’ve been working on so that we can provide some of the data. I think what’s really interesting, Sherri, as everyone knows, 2020 was just definitely a unique year, to say the least. But when you’re looking at the data and you’re thinking about the MyChoice Recommendation Engine and how individuals interacted with our platform, were there any big surprises for you from the insights or trends that you were seeing?

Sherri Bockhorst:

Yeah. So, maybe before I dive into the surprise, just some key overview statistics or findings that I think might be valuable. One is that because we’ve been doing the report for a number of years, one of the things that we noticed, benefits literacy has always been incredibly low. It’s still frustrating to me. I remember way back in my consulting career, we were trying to deal with helping employees learn what a co-pay was or a deductible. People still don’t know what a co-pay or a deductible are. Benefits literacy is still really low. We did see that really plummet over the summer. So, where we had clients with mid-year plan enrollments, we saw it plummet. And then it sort of came back up to the regular low, if you will. The other thing that we saw is that COVID-19 really affected employees’ risk tolerance.

Sherri Bockhorst:

So, not surprising that when you’re in the middle of a pandemic, your concerns about your health, your safety, your job security, all of that is more concerning. And so we did see that there was an increase in loss aversion, right? So, people were much more concerned about that and continue to be one. Of the other things that I thought was interesting, and this is where it gets into more of your question about what did I find surprising, is that one of the findings was that we saw savings across the board. We saw more people put more of their paycheck in a savings to help support them during emergencies. Upon reflection, because when I first saw that, that surprised me, upon reflection, it’s actually not all that surprising in some ways.

Sherri Bockhorst:

If you’re in the middle of a pandemic, and if people are fearing loss more so than normal, it makes sense that they were stockpiling money while they could in order to save for that emergency. But even with that said, it’s still only about 33% on average of people are regularly putting money in the savings. And that doesn’t vary by generation. It varies by pay grade, right? So, at the higher level of the income scale, there’s more people saving. But across generations, there really wasn’t much of a difference between a Gen Z and an older generation type, from a savings percentage perspective.

Mike Meyerring:

That is very interesting, and not surprising, right? I think we’ve saw a number of people that had to furlough employees and there were layoffs as an outcome of the pandemic. And it was definitely turbulent times. When you think about the MyChoice Recommendations Engine, I know that behavioral economics is really an important key piece as we continue the development of my MyChoice Recommendation Engine and enhancing it. What do you think are the behavioral economics that come into play specifically with the Recommendation Engine and what was the outcome?

Sherri Bockhorst:

Yeah. I just talked about savings, right? And we saw overall savings went up. Again, these are people who are employed, obviously, because the Recommendation Engine is for those employees who are benefit-eligible employees and electing those benefits. So, these are people who retained employment, but their savings went up. But at the same time as their savings went up and it kind of makes sense, right? They’re concerned. They put more money in the savings, but they’re very protective of those savings. So, even at the higher income levels where the savings percentage was higher, their aversion to spending that money was also higher.

Sherri Bockhorst:

So, those people who save really want to hold onto those dollars that they’ve worked so hard to put into savings. And that’s where the loss aversion comes into play, because it’s actually the people who do have that wallet to be able to leverage in case of an emergency are the ones who really don’t want to spend what they put in that wallet for emergencies. And so that’s where, when you think about benefit selection, which benefit type is best for people who might have the savings, but really don’t want to spend it? So, there’s the emotional state versus the financial state which comes into play when we’re thinking about how the Recommendation Engine supports people in their choices.

Mike Meyerring:

You mentioned the selection process. In this year more than ever, we’ve had a huge increase in virtual enrollments and many employers that had offered benefit fairs to their employees onsite in the past moved to a virtual benefit fair leveraging some of our internal teams and resources. When you think about this, and I know you’re passionate about selection and making sure that people are enrolling in the right products, not all the products, with the enrollments up, do you think that the virtual piece made a significant difference for the enrollment process that we saw this year?

Sherri Bockhorst:

Yeah, so absolutely. When you think back to what we were talking about earlier with benefits literacy already being low, clients were really worried about how did they manage a benefits enrollment in a virtual environment when people already didn’t understand what they needed to do. And so one of the words that I used so often last year was the word pivot, right? Pivot was just part of my constant vocabulary, and it’s one of the places where we really saw employers have to pivot. So, Mike, you mentioned the virtual benefit fairs. We had a lot of employers that couldn’t do onsite fairs anymore, so they moved into a virtual environment with virtual benefit fairs. One of the things that I thought was interesting about the virtual benefit fairs that we did see, of those that engaged in it, they spent nearly nine minutes exploring those virtual benefit fair sites, which is great.

Sherri Bockhorst:

One of the other things that we saw is tools that were already previously available. So, virtual benefit fairs weren’t common in the past. The Recommendation Engine had been available in the past, but we saw a significant increase. It was like a 65% increase in the use of the Recommendation Engine. So, again, they couldn’t go sit down with HR or their benefits team. They use the tools that were available to them. The other thing that we saw that was really interesting is that during that enrollment timeframe, we saw a sizable increase in the percentage of people who downloaded the mobile app. So, we do have a mobile app available to people. It obviously can help support the enrollment decisions because they can ask questions through the mobile app through the chat.

Sherri Bockhorst:

They can obviously enroll on a mobile device, but it also is really great for us that they downloaded the app because it gets that year round engagement as well. So, again, with benefits literacy being low, not only do we want to help support people in selecting their benefits and making wise decisions at that point of selection, but by downloading the app, it also helps us get better access to them during the year to help them with that year-round engagement and activate their programs most appropriately.

Mike Meyerring:

You mentioned a couple of pieces there specifically around the app and utilization, and when I start to think about our platform and our Recommendation Engine, we have a number of data points. And you having an actuarial background, I know that data is very near and dear to everything that you do. But if you’re an employer that leverages Businessolver today, how can they use this data to help continue the innovation and evolution of their benefit programs or just their communication and/or their communication to the employees?

Sherri Bockhorst:

Yeah. Great question. So, when I think about leveraging that’s available out of our system to help an employer from a strategic perspective, it is in those two buckets. It’s what products should they be offering to their employees? And then what’s the way that they deliver that information to their employees? So, on the product selection side, when you look at the questions within the enrollment flow and how we ask those questions, we’re getting at those concerns that are near and dear to the employee from a financial and health perspective, but also from a risk perspective. And so when you look at those responses and the generational aspects of those responses, I think what can be really helpful is it sort of allows the client some insight into how employees are feeling about what’s offered to them and how it can protect them. So, back to that loss aversion question. And that’s where we’ve seen a lot of employers start to take better advantage of voluntary benefit programs, as an example. Whether if it’s critical illness, accident, hospital, indemnity, ID theft, pet insurance, right?

Sherri Bockhorst:

So, all of those products where you can get down to the individual level and say, “What matters to you? What are you most concerned about and how we help you feel safer, more valued?” and have that member really value the benefit plans and programs that the employer offers. The other component of that is that I think annual enrollment is a really great time, because we do have the attention of the employee, to ensure that employees can start to also understand not just the program that employees elect, but when you think about some of the emotional concerns that come out through the Recommendation Engine questions. Think about how an EAP might be able to help with some of that. Look at the vast services that an EAP offers. People just forget that it’s there. So, how can we start to tie how somebody responded to the Recommendation Engine questions with the promotion of underlying programs that they may forget are even available to them, that they don’t have to pay for, that are already embedded in the value of working for you as an employer.

Sherri Bockhorst:

And that’s why I want to see that tie come together. So, that’s kind of on the product side, both electable and non-electable product. But the other perspective is, how are people interacting with us, right? I talked about the mobile utilization, but we see mobile utilization has skyrocketed. We see chat has skyrocketed. Chats on mobile is now up to almost 50% of all chats with our artificially intelligent virtual assistant Sophia. But Sophia continues to get smarter and smarter, but just look at how people interact with Sophia. Nearly 50% of those chats with Sophia were done from a mobile device. So, how are people interacting with us? And so then when you think about communicating with employees, you got to put on your employee hat. How are they seeking information? From what device? At what time of day? I think it’s about a third, it may be over a third now, of Sophia chats are at night and on weekends.

Sherri Bockhorst:

So, it’s not during regular business hours when member services is there to answer the phone. So, having that additional support on those off hours at night or on weekends. Because that is one thing. Back at the beginning you had asked me about surprising data. This isn’t Recommendation Engine related, but one of the things that was surprising… I’m one of those parents who got sent home, right? I used to travel a lot. My son got sent home from school and I would have thought, “Hey, I’m sitting at home instead of around my colleagues. I can now make these personal calls during the day.” You can’t, right? Because not only are you still doing your job, but now you’re homeschooling and all sorts of other things. So, a lot of those calls, we saw a big increase in nighttime and weekend chats during this time period as well. And I don’t think that’ll go back to what it used to be, either. It’s gone back to people got more comfortable with technology, and I think it’ll stay that way.

Mike Meyerring:

Well, we’ve had a [inaudible 00:17:47] of really about meeting people where they want to be met on our Omni Channel Communication program, and a lot of what you’re talking about is really taking some of this data and making it personal to that individual. Why do you think personalization is so important for benefit programs?

Sherri Bockhorst:

Yeah. So, it’s interesting. Just outside of the benefits space, we are all consumers. So, I know most of us walk around with our handheld device near and dear to us, right? When I needed a new gardening tool I got on Amazon. It’s probably is sitting at my house already. But that’s the speed at which we expect interactions. It’s the personalization that we expect from interactions and it’s in the channel that we expect our interactions. And so we need to apply that same consumer mentality to benefits. And that’s where I think that personalization becomes really important, and that’s where it really ties to the Recommendation Engine. Because the Recommendation Engine is taking that information from the member to create a portfolio of benefits available to them that are recommended based upon their personal preferences.

Sherri Bockhorst:

So, Mike, you and I have somewhat different family statuses, right? We’re both married and have kids, but I have one kid. You’ve got a plethora of kids. You’ve got all boys. So, probably an accident plan is more important to you than it is to me and how you answer those questions would be different than how I answer them. And I’m certainly far different than a single Gen Z who just graduated from college. So, it’s taking in those inputs and really personalizing that benefit selection to support that employee around, not just the plans that are subsidized by the employer, but those voluntary benefit plans becomes really important. And that’s where I think that the personalization really comes into play.

Mike Meyerring:

You mentioned Gen Z. I’m curious from the MyChoice Recommendation Engine, and you also mentioned earlier that there isn’t quite the disparity on utilization based on generation that maybe could be the stereotypical thought process. But how has Gen Z fared this year? They’re certainly a big focus for employers right now. They are a burgeoning workforce. Anything that you can share from an insight perspective, generationally?

Sherri Bockhorst:

Yeah. I mean our poor Gen Z-ers, right? Again, back to that benefits literacy issue. Benefits literacy is an issue across the board, but at least those of us that have been employed for some time, we’re sort of used to the annual enrollment process. We sort of understand that an employer pays for part of our benefits and we pay for part of our benefits. We sort of get how to interact with a health plan and use an ID card. For these, I’m going to call them kids. I probably shouldn’t call them kids. They seem like kids to me, though. But for these younger folks, these Gen Z-ers that are coming into the workforce too, it’s probably their first time buying benefits on their own. It’s their first time trying to understand, “What’s the difference between a medical plan and a dental plan? Why would I need vision or would I not need vision? I have no idea what an accident plan is. What does that do?” Right?

Sherri Bockhorst:

So, that benefits literacy. And when you look at the response on the benefits literacy through the Recommendation Engine that definitely showed through, right? It was something like 56% or 54% of Gen Z-ers knew nothing. They’re completely confused about benefits. So, not surprising, right? But you couple that, going back to the personalization question, they’re also the ones that want the deepest level of personalization. They want us to know everything about them already. They want everything instant, right? They want instant accessibility. They want immediacy of information. And so again, pairing the Recommendation Engine results and the tool itself and the benefit of using the tool to help drive that personalization from a recommendation perspective, but also making sure that it’s available in the media that they want it and being able to have that instant support on questions.

Sherri Bockhorst:

So, Sophia is a great example. Sophia sort of rides along that enrollment experience. So, if they have a question, they’re on the medical plan page and they’re like, “What’s a medical plan? What’s a deductible? What’s a co-pay?” Right back to those basics, but they can ask those questions right there in the enrollment flow. They don’t have to go get a glossary and then come back. So, we really try to put as much at the fingertips of the participant as we can along the way. I think that’s particularly useful for the Gen Z population, though, who it does show is overly confused about benefits and they want that instant and immediate response to their questions.

Mike Meyerring:

Yeah, that’s interesting. I think when I think about the MyChoice Recommendation Engine Benefits Insight Report, there’s a number of data points that we’re providing to our HR partners and the benefits community as a whole. I’m hearing that leveraging this data to continue to meet people where they want to be met, make it personal, unhinge ourselves from the stereotypes that is generationally biased. It’s really not. Virtual activity is absolutely real. And because of some of the things that happened this year, loss aversion is definitely a big point for the group to take away. What would be three key takeaways that you want our audience members to really walk away from and remember as they are getting ready to read and dive into the MyChoice Recommendation Engine Benefits Insight Report?

Sherri Bockhorst:

Yeah. Great question. So, I think first, I’ll just start with that personalization. Remember that people of all generations want that level of personalization. They want you to know who they are. They want to have a recommendation, particularly on this subject where benefits literacy is low. Meet people where they want to be met. It’s important to have somebody available to answer the phone if somebody wants to talk through a question. Clearly important.

Sherri Bockhorst:

We’re not saying that’s not important, but a lot of people are interacting with us at night or on weekends. They are leveraging Sophia to answer their questions. They want that instantaneous response. So, really think about that channel opportunity that you have to communicate the same information across multiple channels to meet different types of people in different types of scenarios. I think that’s really critical. And the third would be really take a look at your benefits program, just from a strategic planning perspective. Look at the needs of your population and how do you create a benefit program that meets those different needs so that different types of individuals with different needs can feel the value of the programs that you offer?

Sherri Bockhorst:

Maternity programs might be great for one population. An accident plan might be great for another, right? So, how do you create that diversity in your benefit plans to meet the needs of the individual? And then make sure to feed it back through what we just talked about, providing the support so that they know that it’s there, they have the awareness that it’s there, and the support to allow people to interact with those programs year-round, not just at time of enrollment.

Mike Meyerring:

Well, I appreciate the sneak peek and some of the highlights of the MyChoice Recommendation Engine Benefits Insights Report. Hopefully our audience is excited to grab this report and read through it and gain some of that knowledge. But thank you for the time today, Sherri, and some of the background on what we can expect when we all get our hands on the MyChoice Recommendation Engine Benefits Insight Report coming soon.

Sherri Bockhorst:

Great. Thank you, Mike. I appreciate it.

Get the full MyChoice Recommendation Engine Benefits Insights Report below. 

{{cta(‘1aca50fc-1970-44e3-bb65-14cfd8e5a5fd’)}}