Automating Workday Benefits - how are you handling decision support?
Hey all,
Wanted to pick some brains here because i feel like we've been banging our heads against this for a while.
So we have Workday handling our core benefits admin - enrollment, life events, the usual. And it does that fine. But there's this whole layer on top that Workday just... doesn't really do? Like the actual decision support piece. Every open enrollment our HR team turns into a help desk answering the same 50 questions about plan differences, what's in-network, cost comparisons, etc. And then throughout the year it's the same thing - "does my plan cover this?" "what's my copay for a specialist?" over and over.
We also had this annoying manual gap where enrollment data needed to get synced and follow-ups tracked, and honestly nobody on the team had bandwidth for it. We were basically automating workday benefits on the transactional side but still doing everything else by hand.
We ended up layering Healthee on top of Workday a few months ago - they have this AI assistant (Zoe) that handles the benefits Q&A stuff 24/7 and does plan comparison/recommendation. It's cut down on the volume of questions hitting our benefits team pretty significantly, which was the main thing we needed. The decision support piece during OE was actually better than i expected - employees could get personalized plan recs without waiting for someone on our team to walk them through it.
That said I'm curious what others are doing here. I saw that older thread about AI decision making tools for OE and it seemed like people were mostly still figuring this out. Are you:
- Just eating the manual burden every OE and hoping for the best?
- Using something like Nayya or Jellyvision for the decision support side?
- Built something custom with the API?
- Or does your Workday config actually handle more of this than I'm giving it credit for?
I know someone's going to say "just put the plan docs in ChatGPT" lol - we tried that, it was... not great for anything specific.
Would love to hear what's actually working for people, especially at orgs with 500+ employees where this stuff really starts to scale badly.