Questions, answered.

A process map shows you the design of a process, the steps, the decision points, who does what. A process simulation shows you the performance of that process, how it actually behaves over time, under real volume, with real variability in how long things take and how busy people get. A map can tell a client what the new process will look like. A simulation can tell them what will actually happen when it runs: where the bottlenecks show up, how long things take on average versus on a bad day, and whether the redesign holds up once real numbers get thrown at it. Quodsi exists because most process improvement work stops at the map, even though the decision being made, commit budget, commit headcount, commit to change, depends on the second question.

Discrete event simulation, usually shortened to DES, is a modeling technique that plays out a process step by step over simulated time, using realistic variation in how long each step takes and how often work arrives. Instead of a single average-case estimate, it produces a distribution of outcomes, the way a process actually behaves across a thousand different days rather than one idealized one. For process improvement work, that matters because averages hide the problems clients actually experience. A process can look fine on paper and excel, and still fall apart during a volume spike, and DES is the tool that surfaces that before it happens in production instead of after.

Yes, that's specifically what Quodsi is built to do. If you've already mapped a process in Lucidchart or draw.io, Quodsi layers simulation parameters onto that same diagram, arrival rates, activity durations, resource capacities and costs, rather than asking you to rebuild the process from scratch in separate simulation software. The diagramming work you've already done becomes the starting point for the analysis, not a throwaway step before the "real" modeling begins.

Quodsi is a discrete event simulation tool, which is one of the technologies that gets grouped under the broader "digital twin" umbrella. The distinction that matters practically: a digital twin is usually a live, continuously updated model connected to real-time data from an operating system. Quodsi is built for a different moment, before a process exists or before a change is made, to answer "what would happen if," not to mirror something that's already running. It's the tool for the decision, not the tool for ongoing monitoring afterward.

The honest answer is that you don't, until you can see how the new process behaves under realistic volume and variability, and most organizations are being asked to commit budget on the strength of a diagram and a set of assumptions rather than that evidence. Simulation closes that gap by modeling the proposed process before anything is built: how work flows once a step is automated, where capacity actually gets freed up, and what the cost and throughput numbers look like once you account for real variation rather than best-case estimates. It turns "we think this will save money" into a testable claim with a number attached, before the investment is made rather than after.

By simulating the redesigned process with the automation or AI step built in, and comparing key metrics against the current-state process, cost per transaction, cycle time, throughput, resource utilization, under the same volume assumptions. That comparison is what turns an ROI estimate from a spreadsheet guess into a defensible number, because it accounts for queuing effects and variability that a static before-and-after cost comparison misses entirely. It also surfaces the less obvious findings early, like a case where adding automation capacity matters far more than adding headcount, which is exactly the kind of counterintuitive result a client needs to see modeled before they'll believe it.

Build a simulation of the process as it would run with the automation in place, and run it against realistic demand rather than a single average scenario. A one-time cost comparison tells you what automation costs. A simulation tells you what actually happens to wait times, throughput, and total cost once that automation is handling real, variable volume, including the volume spikes and edge cases that a static estimate glosses over. That's the difference between a plausible business case and one that survives the first hard question in the room.

Because a process map is a design artifact, not a performance forecast. It shows the intended steps and flow, but it can't account for how those steps behave under real conditions, variability in how long tasks take, uneven arrival of work, resources being shared across competing activities. Two processes can look identical on a map and perform completely differently in practice. Clients committing budget to a redesign are really asking about performance, and a map alone can't answer that question, which is the exact moment simulation earns its place in the conversation.

Quodsi is discrete event simulation software embedded directly in the diagramming tools process improvement consultants already use, Lucidchart and draw.io. It turns an existing process map into a working simulation model, so consultants can show clients how a redesigned process will actually perform, under realistic conditions, before anyone commits to implementing it.

Quodsi is built primarily for process improvement consultants, the people whose engagements live or die on whether a client believes a recommendation will actually work. It's also useful for internal business process improvement practitioners and industrial engineers who need to validate a redesign before it goes to leadership for sign-off. The common thread is someone who has already done the process mapping work and needs a faster way to prove the recommendation holds up, without learning traditional simulation software from scratch.

Yes. Quodsi is embedded directly in Lucidchart, so simulation parameters, arrival rates, task durations, resource capacity and cost, attach to the same diagram you're already building, rather than requiring you to export the process into separate modeling software. draw.io is also supported.

No. Quodsi is built specifically for process improvement consultants and business analysts who understand process mapping but have never used traditional discrete event simulation software like Arena, and don't have the time or need to become simulation specialists. The parameters you add are the ones you'd already be gathering for a process improvement engagement, how long things take, how often work arrives, what resources are involved, not the statistical modeling knowledge that traditional simulation tools assume.

The questions clients actually ask before they'll commit to a change: where will the bottleneck show up once volume increases, how long will things really take on average and on a bad day, is the new resource plan enough or is it overbuilt, and what does the cost per transaction look like once the process is running at realistic scale. Comparison studies, running two or three versions of a redesign side by side, like different staffing or capacity levels, are where the counterintuitive findings tend to surface, and those are often the most persuasive part of a recommendation.

Traditional discrete event simulation tools are powerful but built for full-time simulation specialists, with a learning curve that puts them out of reach for most process improvement consulting engagements. Quodsi is built to embed inside the diagramming tools consultants already use for process mapping, so the simulation model grows out of work they're doing anyway rather than requiring a separate specialist tool and a separate skill set. The trade-off is scope: Quodsi is built for the process improvement use case specifically, not for the full range of applications traditional simulation software covers.

Self-serve pricing and product access are coming to quodsi.com. Until then, contact Quodsi directly to get access to the free version.

Contact Quodsi directly to get access to the free version while self-serve pricing and product access are being added to quodsi.com. From there, you can see how Quodsi turns a process map into a working simulation using an example close to your own work.