The number of benefits decision-support tools available to HR teams has multiplied considerably over the past few years. It shouldn’t be surprising.
As benefits — particularly healthcare plans — become more complex, and employees have less and less time to consider their options, the market demands solutions that simplify and streamline the benefits enrollment process while guiding employees toward satisfying, cost-effective selections.
As an HR professional, you might be choosing a decision-support tool for the first time (excellent strategy!) or searching for a replacement after being let down by your current decision-support tool. Either way, you’re faced with dozens of options — and they are not all good.
Which tools live up to the hype, and which just throw a digital coat over the same old intrusive, confusing, and time-consuming open enrollment process most employees despise?
The following should help you narrow down your list. Here are five red flags to look for when shopping for a benefits decision-support tool:
Related: 5 Ways Flimp Decisions Helps You Contain Costs. Read it here →
1. A Lengthy User Experience
Every HR professional dreams of inspiring employees to give benefits decision-making the time and consideration it deserves. That dream seems to slip farther away with each passing year. Digital information overload is cratering attention spans throughout the working world.
A decision-support tool can be the perfect solution for communicating with distracted employees during open enrollment, but it must respect the many demands on their attention and time.
According to Aflac’s 2022-23 WorkForces Report (a definitive source for open enrollment statistics), nearly three out of five employees spend less than 30 minutes researching their benefits. Many workers dedicate even less time to open enrollment.
So, if your open-enrollment tool takes a half-hour or more to complete — as several do — you’re likely to see low levels of employee engagement. Data bears this out:
- Flimp Decisions, which usually requires five minutes or less to complete, sees typical engagement rates of 60% to 65% based on completion.
- A competing tool that requires 25 to 30 minutes to complete sees engagement rates of only 10% to 20% based on completion.
2. Invasive Questioning
The confidentiality of personal health and financial information during open enrollment isn’t just a question of HIPAA and other federal regulations (though it absolutely is that). An overwhelming majority of Americans believe their data is their own and their health status is between them and their doctors.
- Over 92% of patients say privacy is a right, according to a 2022 American Medical Association survey.
- 80% of patients want the ability to opt out of sharing some or all of their health data with companies.
- According to a Pew study, 79% of Americans are concerned about how companies use the personal data they collect.
Even the perception of privacy intrusions can deter users from a decision-support tool. Yet, some tools ask not only for health information but pry into other sensitive areas, such as annual income, savings, and risk tolerance.
However, Flimp Decisions and tools like it are designed to avoid asking for personally identifiable information (PHI) and comply with all HIPAA regulations. Answers are anonymous and never stored within the system, eliminating risk and potential liability for employers.
(How does Flimp Decisions forecast healthcare needs accurately and recommend plans without asking intrusive questions? As explained below, it’s all about the algorithm.)
3. Poor Forecasts and Unreliable Recommendations
Of course, the most essential aspect of any decision-support tool is how well it helps employees choose the right benefits. If employees can’t trust the tool to recommend the most affordable plans for their needs, they probably won’t use it.
So, when comparing decision-support tools, be sure to take a peek under the hood. What kind of engine drives the forecasts and recommendations?
Some decision-support tools generate results with a “calculator” model. This requires employees to enter detailed estimates of past and future medical services and prescription data for each family member. (Already, you can see how this violates both points above; it’s time-consuming and intrusive.)
Calculator tools estimate costs by multiplying units of services by applicable copay or average costs. Consequently, they tend to underestimate employee out-of-pocket costs and expenses for ancillary services such as diagnostics, anesthesia, therapy, and supplies.
Algorithmic tools like Flimp Decisions take a data-driven approach, requiring much less guesswork on the part of users. Using data from the Federal Actuarial Value Calculator and a database of over a quarter-billion claimants, Flimp Decisions maps users’ needs across 26 types of medical services (office visits, labs, prescriptions, and so on). The analytical engine matches each employee to a “lookalike” audience within that database to project premium and total expected out-of-pocket costs, less employer contributions, for each plan.
The results are more accurate than the calculator model, and the data-driven methodology provides a swifter, less invasive experience for employees.
4. Mobile Unfriendly Design
In 2022, the share of global internet traffic originating from mobile devices (primarily smartphones) was nearly 60%. People love their phones, and not just for sending texts and watching TikTok videos. Whether at work or home, your employees are more likely to pick up their phones than turn on their computers to complete digital tasks.
Researching and choosing benefits is no exception. Unfortunately, many decision-support tools have been designed solely for big-screen consumption.
The best digital-support tools feature responsive design, which automatically adapts the layout to render as well on mobile devices as on computer monitors — for example, removing clutter and enlarging the text for smaller screens.
Your employees are rarely more than an arm’s length away from their phones. Responsive design means your decision-support tool is available however and wherever employees choose to use it.
5. Biased Results
Sponsored results are everywhere these days. Online shopping and search sites are littered with ads masquerading as genuine recommendations — and for consumers, it can be highly dispiriting.
Your employees know how to spot a fake; they can tell when a decision-support tool is working on their behalf and when it is pushing the interests of plan providers and carriers.
The most trustworthy decision-support tools, such as Flimp Decisions, are 100% employee-centric. When presenting results, the only factors that matter are healthcare costs and plan features relevant to the user.
Unbiased results are good for your organization, too. After all, employers save money when employees save money.
Test Drive a Decision-Support Tool That Gets It Right
Eliminating all the time-consuming, invasive, inaccurate, poorly designed, and biased decision-support tools from your search will leave you with a much more manageable list of options. You could go through your checklist for each one. Or you could skip right to a tool that checks all the boxes.
Click here to experience Flimp Decisions for yourself with a free self-guided demo.