Analyse & Improve

Process Simulation

Monte Carlo simulation for data-backed process planning

Overview

Process Simulation brings Monte Carlo methods to value stream mapping. Define variability ranges for cycle times, staffing levels, and demand volumes, then run thousands of simulated iterations to understand the probability distribution of your process outcomes. See confidence intervals for lead time, throughput, and resource utilisation. Model what happens when demand spikes, staff call in sick, or equipment fails. Make capacity planning and improvement decisions backed by statistical evidence rather than single-point estimates.

Why Process Simulation?

Three reasons teams choose this tool

Thousands of Scenarios

Run Monte Carlo simulations in seconds. Model more scenarios in a minute than you could test in a year.

Statistical Confidence

Confidence intervals at 50th, 75th, 90th, and 95th percentiles. Replace guesswork with probability.

Risk Made Visible

See what happens when demand spikes, staff call in sick, or equipment fails. Plan for reality, not best case.

How It Works

Get started in four steps

1

Set Variability Ranges

Define min, max, and distribution for cycle times, staffing, and demand volumes.

2

Run Simulations

The Monte Carlo engine runs thousands of iterations modelling your process under uncertainty.

3

Review Distributions

See confidence intervals for lead time, throughput, and resource utilisation.

4

Make Decisions

Compare configurations side by side. Plan capacity with statistical evidence.

Applications

Real-world use cases

1

Capacity planning for seasonal demand variation in manufacturing

2

Staffing optimisation for service delivery processes

3

Risk analysis for process changes before implementation

4

Building evidence-based business cases for resource investment

Capabilities

Everything included

Monte Carlo simulation engine running thousands of process iterations
Staffing variation modelling — test different headcount scenarios
Demand fluctuation analysis with seasonal and random variation
Confidence interval reporting (50th, 75th, 90th, 95th percentiles)
Resource utilisation heatmaps across simulated scenarios
Bottleneck probability analysis — which step is most likely to constrain
Export simulation results as PDF reports with charts and tables
Compare multiple simulation configurations side by side

Preview

See it in action

app.mapvs.com/process-simulation

Availability

Plan Access

Free
Starter
Pro Recommended
Team
Enterprise

Ready to try Process Simulation?

Available on the Pro plan and above. Start with a free account and upgrade when you are ready.