How to Prove Your Process Recommendations Work Before Implementing Them
The Problem Every Consultant Faces
Have you ever spent weeks mapping a client’s process, identified inefficiencies, spotted bottlenecks, and developed a solid recommendation for how to improve things, and then your client asks the question that stops you cold: "How do you know this will actually work?"
It's a reasonable ask. Implementing process changes costs money, disrupts operations, and carries real risk. Your client isn't going to bet their business on your gut feel, no matter how experienced you are. They want proof.
But how do you actually prove that your recommendation will deliver the results you're claiming?
The Traditional Approach (and Why It Falls Short)
Most consultants reach for one of a few familiar options:
Option one: The spreadsheet model. You build a static Excel file that shows "if we staff differently, throughput goes up by X percent." It's better than nothing, but it's also disconnected from your actual process diagram. Your client sees numbers, but they can't visualize how the change flows through the real work. Plus, static models assume perfect conditions with no variability, no unexpected delays, no real-world messiness. Reality is messier than a spreadsheet.
Option two: The pilot program. You convince the client to test your recommendation on a small scale. This works, but it's slow, expensive, and risky if the pilot goes sideways. You're learning through real implementation, not through analysis.
Option three: Hope and credibility. You lean on your track record and experience. "I've done this before, and it worked." This can work if you have deep relationships, but it's not scalable, and newer consultants are at a disadvantage.
What If You Could Show Them First?
Simulation can show the performance of a process and test assumptions. You can use data-driven simulation to test your recommendations before your client implements them. And it doesn’t need to be fancy or complicated.
Here's how it works in practice:
You take the process diagram you've already built which shows the current state and future state and you convert it into a simulation model. The simulation runs your process thousands of times, accounting for variability in how long tasks actually take, how resources are allocated, what demand looks like on different days. It gives you back numbers: throughput, cycle time, resource utilization, costs, bottleneck identification.
Then you test your recommendation. "What if we add one more person to this step?" Run the simulation again. Compare the results side by side. "What if we prioritize orders differently?" Run another scenario. Each time, you get concrete numbers showing the impact.
Now when your client asks "Will this work?", you can show them. You pull up your comparison and say: "Here's the baseline. Here's the recommendation. Here's the projected improvement, accounting for real-world variability." That's proof.
This approach does three things for you as a consultant:
One: It builds client confidence. They're seeing data, not opinions. They understand the logic because they can see it play out across multiple scenarios.
Two: It de-risks the implementation. You've already tested it. You know where the real bottlenecks are, where staffing changes matter most, what actually drives the improvement. That means better execution on the client side.
Three: It strengthens your credibility. You're proving instead of recommending. That's a different level of consulting and clients remember that.
The catch has always been that simulation requires separate tools, separate data setup, separate exports. Your process lives in one tool, your simulation lives in another and that other tool might have a learning curve.
What if simulation lived right where your process diagram is?
That's where Quodsi comes in. Quodsi brings embedded simulation directly into your diagramming tools so you can test and prove your recommendations without leaving the platform you're already using. Quodsi for Lucidchart is available now, giving you one-click conversion, scenario comparison and results dashboards all inside Lucidchart so you do not have to switch tools.
No exporting and reimporting. No disconnect between your visual process and your data analysis.
For consultants, that means less friction and more time proving recommendations instead of wrestling with software.
The Bottom Line
Process improvement recommendations are only as good as the confidence your client has in them. Simulation doesn't replace your expertise but it sure does amplifies it. It turns your analysis from an educated guess into data-backed proof.
And when your client sees that proof, implementation becomes easier. They understand the why and they're aligned on the expected outcomes.
