“Hey, Alexa! Which benefits should I choose?”
We may not be that far from the day when artificial intelligence can assess an individual’s unique circumstances, stage in life, number of dependents, and past benefits utilization, and determine an optimal benefits package that is relevant to that person.
Or are we already there?
Selecting benefits is viewed as complicated, confusing, and frustrating for more than one in three employees, according to a recent survey by Aflac. So how can benefits communications leverage both technology and human support to help people make informed, smart decisions, all while removing the complexity and angst associated with it?
Let’s look at the factors that influence the process of making a benefits decision—and what roles technology and live support can play.
The intelligence of technology
Predictive analytics can help determine which benefits will be most valued by which employees, and even which employees will most likely gain value from certain benefits packages.
When it comes to communicating options and details about benefits, chatbots, apps, and web portals are effective in providing relevant information for the user at hand. Online tools can contain all the key points of different benefits packages. Today, it is easier than ever for employees to learn what the right benefits are for them.
And yet, it seems just as difficult to make selections, so much so that the default is often, “Stick with whatever I have”—or, “Can I just talk to a real person?”
The reassurance of human interaction
As people move closer to making a decision on any purchase, the overwhelming preference is often for human conversation. According to an article in Harvard Business Review, there are quite a few indicators of this:
- Voice communication is faster, easier, and more effective than typing messages back and forth.
- After doing research online, people are more likely to call when making a high-value purchase.
- According to a study by Google, 61% of mobile users call when they are in the purchase phase of the buying cycle.
- In “considered purchase categories” like insurance, finance, or healthcare, the likelihood of personal communication is even more acute.
Even many millennials, who have grown up in the digital age, have a strong preference for human interaction when seeking assistance.
Benefits concierge services can add that much-needed human touch to today’s digital solutions. These third-party services often provide telephonic access to experts who can walk employees through their options, while the technology provides details on which benefits may be most appropriate for that individual situation.
The tendency to inaction
Let’s assume the benefits program is designed well, the choices are clearly explained, and both technology and personal communication are used together. Still, employees will only change behavior if they can overcome their own natural biases.
Nudges are needed.
The most recent Nobel prize winner in economics, Richard Thaler, popularized the idea of subtle communication at the right time, in the right way, and in the right context being effective in moving people to better decisions. Rather than viewing ourselves as rational creatures always acting in our own best interests, Thaler posits that we are subject to several biases that get in the way.
Among the most common is the planner versus doer bias. At the start of a new year, for example, our planner self is full of good intentions—but our doer self does not always follow through. Different parts of the brain are responsible for planning and doing, and connecting them is often a challenge.
A second bias is loss aversion. We tend to experience the negative feelings of loss more strongly than the positive senses of gain. So, if changing benefits carries the risk of loss (from making the wrong choice or a more expensive choice), even when there is an equal possibility of making a better selection, the default will likely be to do nothing.
A third bias is the availability heuristic, which says decisions are made based on the most readily available or easiest-to-recall information. So, if a particular health plan is viewed more favorably than another (because of advertising, past experience, or word of mouth) employees may conclude it is the best choice even when another option is objectively better for their situation.
The lesson for employers seeing poor benefits engagement? Well-timed nudges, supported by the intelligence of predictive analytics and the support of human interaction, may be the ideal combination to help employees overcome natural tendencies toward inaction. Data-driven solutions with concierge-level assistance can simplify the benefits experience—for employers and employees alike—and pave the way for informed decisions.
So, in the future, when you ask Alexa which benefits package to choose, she may well respond with, “Here are three good options. Give your benefits concierge a call to help you with your decision.”