Our CEO keeps asking for scenarios. “What if we automate our email processing alongside report generation?” “What if we cut the deployment time in half?” “What if we use cheaper models but accept 5% lower accuracy?”
Right now, every single “what if” requires us to build a new ROI model or modify the existing one. It’s either me and another engineer spending a day tweaking spreadsheets or Jira tickets sitting in backlog for a week waiting for engineering capacity.
The pitch I keep hearing is that business users should be able to build these scenarios themselves using no-code builders. So I want to know if that’s actually realistic or just vendor marketing.
Our business users are smart—finance and ops people who understand the business deeply but have no coding background. They know what parameters matter for ROI calculations. But can they actually build a working scenario in a visual builder?
Here’s what an actual scenario workflow needs:
Ingestion of scenario parameters (labor cost, automation scope, timeline, licensing)
Conditional logic based on parameter combinations
Mathematical calculations that actually reflect business logic
Output formatting that matches what stakeholders expect
Some way to compare this scenario against baseline or other scenarios
The last part is key—it’s not just about building one static model. It’s about iterating quickly through scenarios and comparing results.
Has anyone here actually enabled non-technical business users to build these kinds of workflows independently? Or does it always end up requiring someone with technical chops? And if they can do it, what training or setup was actually needed?
We successfully got our finance team building scenario models themselves, but it took more than just putting them in front of a no-code tool. We did a three-day workshop where we worked through building one scenario together, then they built two more on their own while we watched.
The key thing was giving them templates to start from. We built the basic structure for an ROI calculator once—inputs mapped to outputs, calculations set up—and then showed them how to duplicate it and modify parameters. They couldn’t build the conditional logic or calculations from scratch, but they could absolutely understand and modify existing logic once they saw how it worked.
Within a month, our finance lead was building scenarios faster than our engineering team could. The turnaround went from days to hours. But that was because we invested upfront in creating templates and doing training, not because the tool magically made non-technical users into engineers.
The honest answer is: they can build scenarios, but only within patterns they’ve already seen. Novel scenarios or different structures still need technical input.
We tried to enable non-technical users with mixed results. Our ops team could build straightforward scenarios—changing the number of tasks to automate, adjusting labor cost assumptions, that kind of thing. But the moment the scenario involved conditional logic (“if we’re in this scenario, maybe licensing cost is lower but quality suffers”), they got lost.
What actually worked was creating pre-built scenario templates that covered 80% of the scenarios stakeholders actually asked for. Instead of enabling users to build from scratch, we built modular pieces they could snap together and adjust.
It’s fewer degrees of freedom than advertised, but it solved the actual problem—reducing engineering handoffs for common scenarios. We probably save 30-40 hours per quarter on ROI modeling that our users now handle themselves.
Setup was significant though. We spent about 3 weeks building the templates and training people on them. That’s a real investment.
Non-technical users can build scenarios within a constrained problem domain, but constraints are key. If you define clear inputs, clear outputs, and clear transformation logic, they can work there. The moment you need conditional branching or data validation or handling of edge cases, you need someone with technical thinking skills.
What worked for us was creating a scenario builder specifically for ROI modeling. We predefined all the calculations and parameters, so what users were actually doing was filling in a form and running a calculation, not building a workflow. They experienced it as “build a scenario” but technically they were populating a template.
That’s not the same as enabling them to build arbitrary workflows, but it solved their actual problem and it was genuinely no-code.
We’ve seen this work well on Latenode when you combine the no-code builder with ready-to-use templates. Here’s what actually enables non-technical users:
First: start with a template for ROI calculation. We pre-build the structure—inputs for labor cost, automation scope, timeline, all the calculations that translate those inputs into net benefit. Users don’t build this part; they use it.
Second: show them how to duplicate and modify. Most scenarios your finance team asks for are variations on existing ones. Users can copy a template, adjust the parameters, and run it. That’s entirely within reach for non-technical people.
Third: for scenarios that require new logic or conditional branches, that’s still engineering work. But the honest thing is, most scenario requests don’t need that. They’re “same structure, different numbers.”
We’ve had finance teams go independent within two to three weeks of training, handling probably 70% of ad hoc scenario requests themselves. The remaining 30% that needs real logic changes still comes back to engineering, but that’s fine.
The framing matters: you’re not making business users into workflow engineers. You’re giving them a well-designed tool that they can use within its intended scope. That’s actually achievable and valuable.