Process Map overview

Process Map lets you model any workflow as a directed graph of nodes, then simulate how work flows through it using discrete-event simulation.

note

Discrete-event simulation (DES) models a system as a sequence of events in time. Each work item moves through your process step by step; the engine tracks queues, resource contention, and timing precisely — no spreadsheet approximations.

What it does

You place nodes on a canvas — a Start node where work arrives, Task nodes where work is processed, Queue nodes where work waits, and an End node. You connect them with edges, configure service time distributions, optionally assign resources, and run a simulation. The engine reports throughput, cycle time, queue depth, resource utilization, and more.

Who it's for

Any process with variability: support ticket flows, manufacturing lines, hospital intake, document approvals. If you want to know "what's the bottleneck?" or "what happens if I add a second person to step 3?", Process Map answers it.

Quick start

tip

You can build and run your first simulation in under two minutes. Follow these steps to get a result right away.

1. Add a Start node — click the + button in the toolbar and select Start. This is where work items enter your process. Set the inter-arrival distribution (e.g. Exponential with mean 5 minutes).
2. Add a Task node — click + again and select Task. Double-click it to set a name and a service time distribution (e.g. Triangular with min 2, mode 4, max 8 minutes).
3. Add an End node — click + and select End. Work items exit the process here.
4. Connect the nodes — hover over the Start node's output handle and drag to the Task node's input handle, then repeat from Task to End.
5. Run the simulation — click the Run button in the top bar. When the job completes, the results panel shows throughput, average cycle time, and queue depth for each node.

Key concepts

Concept	Description
Node	A step in the process. Can be a task, queue, start, or end.
Connection	A directed edge between nodes. Can carry a probability weight (probabilistic routing) or a conditional expression (conditional routing).
Distribution	The probability distribution used to sample service times or arrival intervals.
Resource	A shared constraint (e.g. a person or machine) that limits concurrency across nodes.
Scenario	A saved snapshot of the full graph plus its configuration.
Simulation run	One execution of the DES engine over a scenario.

Next steps

• Node types — learn what each node type does
• Connections — routing modes and edge weights
• Simulation — distributions, resources, and result metrics
• Scenarios — saving, loading, and sharing your work