What Benefits Data Options Do Employers, Consultants, and Brokers Face?

Benefit teams, whether in-house at a self-insured employer or acting as a consultant, always manage to have a full calendar. The problem many organizations face is trying to figure out what to do with mountains of benefits information they’ve collected over the years. They recognize data is essential, but it's just one of the many items to tackle on their agenda. And the choices are endless. Do you leave the analysis up to the experts? Do you evaluate all the data yourself?

Here are a few options to consider when approaching benefits data.

Do Nothing.

While doing nothing is an option (and a choice some teams make), you’re missing out of a goldmine of information. And that's because your data is the key to streamlining and professionalizing program evaluation, keeping an eye on employee engagement, and addressing the high costs of benefits. Data is also a powerful tool in helping organizations manage population health and detecting healthcare overspending more quickly and efficiently. Data analytics is the wave of the future in the benefits space. If you’re not using it, you might be falling behind.

DIY.

You might be tempted to gather, organize and analyze benefits data the old-fashioned way: in-house using spreadsheets and visualization tools, many of which aren't built specifically for benefits data. But that can cost you time and energy that your team doesn’t have. Doing it yourself means you need to gather data feeds from multiple vendors, comb through hundreds or thousands of rows in a spreadsheet, and crunch numbers. And without expertise or an active data analytic partner, you might also be drawing conclusions in your data that are not there. If you’re looking for surface-level information on spending to project future costs, this might work. But if you need to tackle wasted spending or justify new programs, DIY might not be the best option for your population. It doesn't give you the holistic view that's essential to truly understanding your population and taking action on the insights you find.

Traditional Data Warehouse.

Traditional data warehouses store information and allow analyses to help benefits teams make data-driven decisions. While some are more robust than others, they tend to have some drawbacks:

• Outdated tools and technology
• Slow queries when you need fast answers
• Difficulty “cross-walking,” or looking across data feeds for a holistic view
• Lack of support for users, and a steep learning curve
• “Nickel and dime” approach to custom analytical needs

Employer benefits teams often choose a traditional data warehouse and work with a consultant or their broker to conduct analyses in the software. This approach can work, but there’s a better option.  

Modern Data Solution.

A modern data solution gathers all of your data into one location and provides a holistic view across various data feeds, making it easier to tell stories, find fast answers, share insights, store resources, and take action.

Not only should you be able to perform cross-walking functions like this, but you should be able to do so quickly without requiring a professional service engagement that will take weeks and potentially incur additional costs.

A true data partner can help you see where you are and get where you're going with your benefits strategy, and should offer great product support and analytical expertise as well.

Here at Artemis, we believe that a great data solution should be designed to be used by both novices and experts, so we want our customer to have a tool that provides fast answers and enables an action plan. We know that finding ways to approach your data can be a big undertaking for your organization and Artemis understands the hurdles you face. For employers, brokers, and consultants struggling to make the most of their benefits data, Artemis Health can help.