I’m stuck on a problem that I don’t think enough people talk about. When you’re comparing ROI between, say, staying on Camunda versus switching to something else, how do you actually build the comparison model?
Here’s my situation: we have existing Camunda workflows. Switching means:
Rebuilding workflows (cost and time)
Training the team on new platform (cost and time)
Short-term productivity hit during migration
But the upside is:
Lower licensing costs (maybe)
Faster time to build new workflows (maybe)
Access to capabilities we don’t have now (like easier AI integration)
The problem is quantifying the “maybe” parts. How do you estimate time savings from a better workflow builder? How do you value the ability to prototype faster?
I’ve seen some colleagues try to model this with spreadsheets, but it always feels like we’re just tweaking assumptions until we get the answer we want. I’m looking for a more grounded approach. Has anyone built a realistic ROI model that actually held up after implementation?
The mistake most teams make is trying to model the full three-year ROI upfront. You can’t. Too many variables are unknowns.
What we did instead was focus on year-one migration costs as a hard number, then measure year-one operational costs against current-state costs. The real ROI emerges in years two and three when you’re no longer paying the migration debt.
For the “maybe” items, we didn’t try to estimate them. Instead, we ran a small pilot on the new platform with a subset of workflows and measured actual lift. We compared how long it took our team to build and iterate on workflows in both systems. That gave us real data, not assumptions.
The pilot cost us a few weeks and some eng time, but it was way better than guessing at a spreadsheet for months.
One metric that actually works well is cost per workflow per month. Calculate what you’re paying now to maintain and operate your current workflows, divide by the number of workflows, then compare that to the new platform.
This forces you to think about the full cost, not just licensing. It includes dev time, maintenance, incidents, and vendor support. When you break it down to cost per workflow, the comparison becomes much clearer and less hand-wavy.
Most ROI models fail because they don’t account for sunk costs properly. You have Camunda expertise in your organization right now. Switching means losing some of that value. That’s a real cost. But here’s the thing: if the new platform is genuinely faster or cheaper to operate, that cost is recovered in months, not years. Try modeling it this way: Year one is rough (migration cost + learning curve). Years two and three, you’re faster and cheaper. Calculate when the cumulative savings exceed the first-year investment. If it’s under 18 months, the switch makes financial sense.
The right way to model this is through a small POC that measures actual velocity on the new platform versus your current baseline. Don’t estimate time savings—measure them. Have your team build the same three to five workflows on both systems and track hours. That’s your velocity multiplier. Then apply that to your full roadmap. This grounds your ROI in real data instead of optimistic assumptions, and it also de-risks the decision because you’ve proven the benefit before full migration.
Year 1: count migration cost + learning overhead. Year 2-3: measure actual savings per workflow, multiply by pipeline. ROI happens when cumulative savings exceed year-one cost.
We had the same problem, and what changed it for us was running a real pilot where we used our AI Copilot to generate workflows from plain English descriptions. We compared that to how long our team spent building the same workflows in the old system—there was no comparison. The AI-generated workflows cut our build time in half, and because we’re on a single-subscription model, we didn’t have to worry about licensing cost surprises when we scaled up.
For ROI modeling, I’d say: baseline your current cost per workflow (licensing + dev time), then run a one-week pilot where you build new workflows using AI assistance. You’ll see immediately whether the time savings justify the switch. The financial model becomes obvious once you have real numbers.