The approach
See the process clearly, then prove what to fix
A supply chain is only as fast as its tightest constraint, and that constraint shifts as volume and variability change. With ProcessModel you build a working model of the flow, from inbound through warehouse and out to delivery, with finite capacity, queues, travel time, and variability all in play. Run a discrete event simulation to see throughput and bottlenecks under realistic conditions, then test distribution process improvement ideas safely before you commit trucks, space, or people. It is the same modeling that drives bottleneck analysis and continuous improvement on the floor, applied across the chain.
What you can model
What you can model in logistics
A working model of the work, run as a real simulation, so the real constraint is obvious.
Supply chain and distribution
Model the flow from inbound to delivery with real capacity, queues, and variability, and see how the network behaves before you change it.
Warehouse and fulfillment flow
Lay out receiving, putaway, picking, and shipping, then run it with real volumes to find where work and orders pile up.
Transportation and routing
Test carriers with finite carrying capacity, travel time, and routing rules, and measure the effect on throughput and cost.
Throughput and bottlenecks
Rank every step by the time it adds with Impact Analysis, so the real constraint in the chain stops hiding behind the obvious one.
Inventory and replenishment
Model stock, multiple SKUs, reorder levels, and replenishment, and test the policy that holds service levels without overstocking.
Ready to run
Start from a demo model
4 ready-to-run models for logistics come with ProcessModel. Open one from File, Demo Models, run it straight away, then change it to fit your process.
Cold Chain FEFO
Good product spoils waiting in the cooler. Release by expiry and waste drops to zero.
Miss the Truck
Orders outrun the packing crew before the truck leaves. Staff the cutoff and late orders vanish.
Fill Rate Safety Stock
Orders go unfilled as the shelf runs dry. Staff the receiving dock, not the shelf, and fill rate recovers.
Held for the Last Line Item
Two pick zones sit idle while orders wait on the one slow bulk zone. Add a picker there, not at packing, and late orders vanish.
Case studies
Proven in logistics
Real projects where a team mapped the process, ran the simulation, and proved the result.
87%shorter sales cycle
Cutting a nine-month sales cycle to 35 days
A maker of reflective, high-visibility safety garments
Read the project$40.5Mcapital expansion avoided
Avoiding a $40.5M plant expansion
A road-paving equipment manufacturer with more than 30 years in business, building machines 45 to 60 feet long and weighing 50,000 to 100,000 pounds
Read the projectSee it in action
Build it, run it, find the bottleneck
The same workflow powers every industry. Build the model, or let your own AI app work in it through PM AI Bridge. Run a real discrete event simulation, find the constraint with Impact Analysis, and compare the fix against the current state. See the canvas, the live run, and the reports on the product page.
Explore the product- 01
Build the model
Lay the process out on the canvas, or turn on PM AI Bridge and let your own AI app work in it, and review the model before anything changes.
- 02
Run the simulation
Watch the work move through your process with real resources, queues, and variability.
- 03
Find the constraint
Rank every step by the time and cost it adds, then start with the one that matters most.
- 04
Prove the fix
Compare current state against future state and see the result before you commit.
Customer stories
Teams that model first, change once
ProcessModel support delivers tailor-made solutions that drive efficiency, improve productivity, and greatly increase process performance, whether modeling complex production processes or optimizing supply chain operations.
See your logistics process clearly, then prove the fix
Build the model, run the simulation, find the constraint, and show the improvement before you change a thing.