In the last post (Benefits as a Strategy (How Plan Design and Behavior Create Outcomes)), we talked about benefits as strategy and where tradeoffs get made.
Now we shift from decisions to execution. Once a plan is defined, something has to carry those rules into the real world. Data. But before data can move, a system has to be configured to move it correctly.
Configuration comes before everything
Early in my career as a benefits consultant, I was too busy learning the job to think about what happened to the benefits after we helped a client define their plan design. It never crossed my mind that there was another whole part of this process, one that involved systems and configuration. That gap in my understanding didn’t close until much later.
Once a plan is designed, someone has to translate that design into a system so participants can actually enroll. That means configuring eligibility rules. Is the employee eligible on day one, or after 30 days? It means configuring classes. Different employee classes within an organization may have access to different benefits, and the system has to know which class an employee falls into and tie the right plans to it. It means configuring divisions, and sometimes even zip codes, because some plans are geographically specific.
All of that configuration determines what an employee sees when they go to enroll and whether they’re enrolling in the right plans to begin with. This step is easy to underestimate. But if configuration is off, everything that follows is off.
How the data actually moves
Once enrollment happens, data has to travel from the enrollment system to the carriers. How it travels depends on what’s been set up. Some organizations still move data through spreadsheets. Many use EDI (electronic data interchange) file formats. The most common EDI is the 834 file, a HIPAA mandated enrollment transfer file that has been an industry standard for decades. Increasingly and in a positive way, systems are moving towards API (application programming interface) integrations, which are designed to pass data back and forth in something closer to real time. Designed to. Whether they actually do is a different conversation.
Regardless of the method, the file tells the carrier who the employee is, which dependents are covered, which plans were elected, and when coverage starts and ends. The file simply reflects the configuration it was built on.
And this is where the AI conversation starts to get interesting. Existing systems check if a file can pass through using standard EDI programming. What’s emerging will be the use of AI to flag and reconcile an incoming file against the specific plan design sold to that client.
Where complexity and errors begin
Problems usually start earlier than people think. If the system was configured incorrectly, the data passed will be incorrect. If the file was never tested, those errors travel forward undetected. And testing is where things quietly break down. The person sending the file needs to test it. The carrier receiving it needs to test it on their end to confirm they’re seeing what they should. When neither side tests, data gets loaded into carrier systems incorrectly. And the first time anyone finds out is when an employee goes to get care and runs into an access issue.
This is when the issues become highly visible and escalated. But it started as a configuration and testing problem.
Technology executes what it receives
This is the same point from the last post in the series. Technology doesn’t define the plan, it executes it. If eligibility logic is wrong, the file will be wrong. If configuration is misaligned, the carrier will administer it that way. If data is incomplete, automation will scale the incompleteness. AI won’t fix flawed inputs. It will just process them faster.
Before we can talk about intelligent systems, we have to understand the foundation. AI can flag anomalies, predict enrollment patterns, identify high-risk populations, and surface inconsistencies, but it can only reason on the data it’s given. If upstream configuration is unclear or inconsistently applied, AI becomes another layer operating on noise.
You can have the best plan design in the world. But if the system isn’t configured correctly and the files aren’t tested, none of it reaches the employee the right way. That’s where it either works or it doesn’t.
Question for you
When something goes wrong in your benefits process, do you dig into the root cause, or do you jump in to fix it quickly? Honestly, both must happen, or the same issue will keep recurring.
Next Up
Post 9: Where Errors Multiply: The most common breakdown points in benefits ecosystems, and why troubleshooting often starts in the wrong place.
