Model capacity, bottlenecks, turnover and peak projection of your warehouse. Honeycomb, Little's Law, AI, 3 scenarios. Free.
Advanced simulator
How many months until my warehouse saturates?
Project when your warehouse fills up at the current pace, where the bottleneck sits, and which expansion is worth doing first.
Capacity & growth
Pallet positions, current inventory, demand growth and seasonal peak.
Throughput
Daily flow of pallets inbound, outbound and picking lines required.
Infrastructure
Docks, trucks and picking crew.
Costs
Rent, fixed labor, 3PL overflow and expansion potential.
Saved configurations
Fill in your data to see the report
This simulator only generates a diagnosis, charts and recommendations when it has your real business values. Fill the editor above and the report will appear automatically.
Required data
Total capacity (pallets)
Pallets currently occupied
Warehouse cost per month
Monthly growth (%)
Want to explore it first?
Load a realistic case to see how the report looks. You can edit any field afterwards.
Base, tough growth and optimized WMS. The simulator calculates your primary bottleneck and compares four routes to cover the peak.
Frequently asked questions
1What is the honeycomb effect and why does it matter?
In single-deep rack with SKU mix, above 85% utilization free positions get blocked by other pallets. Effective capacity drops quadratically — at 100% you can lose 22-35% of productivity. This simulator penalizes effective capacity above 85% so you do not plan with an unrealistic number.
2What is the difference between 'full' and 'saturated'?
Full (100%) means zero free positions. Saturated is 85-95%: you cannot receive pallets without reorganizing, you lose picking productivity and errors go up. Typical healthy target is 80-85% — above that, hidden operating cost grows faster than rent savings.
3How do I calculate my dock capacity?
Doors × trucks/door/day. A typical dock handles 25-35 trucks in a 2-shift day. The simulator assumes 20 pallets/truck — if you handle case-pick or LTL, adjust the daily inbound/outbound to reflect reality.
4When is 3PL overflow better than expanding the warehouse?
3PL overflow is variable: you pay only what you use, ideal for short seasonal peaks. Expanding is fixed: buys years of runway and lowers cost per pallet if growth is sustained. Rule of thumb: if you would use overflow more than 6 months a year, expanding is cheaper.
5What does reconfiguring the layout mean and how much does it help?
Switching from current rack to double-deep, very narrow aisle (VNA) or dynamic slotting. You reclaim 10-15% of capacity without civil work. Typical cost is a one-time investment of 2-4 months of rent. It is the first option to evaluate before expanding.
Pallet positions utilization 80-85%, cube utilization 75-85%. Above 85% pallet utilization picking productivity degrades exponentially from aisle congestion and interfering moves. Running at 95% is, in real operating cost, more expensive than paying for a second warehouse at 70% — the hidden cost sits in cycle time and productivity, not space.
2What is cube utilization?
Volumetric utilization = Volume occupied ÷ Total usable volume × 100. Different from floor utilization: a warehouse can sit at 70% floor yet only 50% cube if it wastes height. Improving cube utilization with higher rack, double-deep rack or mezzanine can add 15-30% pallet positions without expanding built square feet.
3What is warehouse slotting?
Slotting = assigning products to physical warehouse locations based on rotation, weight, volume and frequency. Class A SKUs (20% of SKUs that drive 80% of volume) go in forward pick near dispatch; classes B and C go in reserve or secondary zones. Optimized slotting cuts picker travel time 30-45%, which accounts for 50-60% of total order time.
4What is picking productivity?
Lines picked per hour per picker. Benchmarks: manual warehouse 75-120 lines/h; pick-to-light 150-250 lines/h; voice picking 130-180 lines/h; goods-to-person (AutoStore, Exotec) 200-400 lines/h. Productivity improves with slotting, wave picking (grouping orders by zone), and assistive technologies (RF scanner, voice, light).
5When do I need a WMS?
Over 3,000 active SKUs, over 500 lines/day, multiple locations inside the warehouse, or regulation requiring traceability (pharma, food, spirits). Without WMS, inventory errors run 8-15%; with a well-calibrated WMS they drop to 1-3%. Typical implementation ROI for 20k-100k sq ft operations: 6-14 months from error reduction, throughput improvement and elimination of manual capture.
6What is cross-docking?
Cross-docking = products that enter the warehouse and leave in under 24h (typically <8h) without going through storage. Goods arrive, get consolidated by destination and dispatched. It eliminates storage cost and meaningfully reduces cycle time. Applied to high-rotation SKUs, short-cycle promotional products and perishable distribution. Requires tight synchronization between supplier, transport and customer.
7How do I handle seasonality in warehouse capacity?
Four strategies: (1) flex space contracted with neighboring 3PLs for 3-6 months (40-60% cheaper than sizing permanent to peak); (2) mobile racking deployed only at peak; (3) intensive cross-docking on high-rotation SKUs; (4) supplier consignment stock (stock held at supplier and billed on consumption). Sizing permanent capacity to peak destroys profitability the rest of the year.
What you'll see, what it prevents, and where you shouldn't trust it
Every simulator on Simúlalo ships with the same editorial structure: two hypothetical worked examples with numbers, the errors it helps you avoid, the model's declared limitations, and a visible financial disclaimer. The review is signed and dated.
Hypothetical case·Case A
A warehouse that thought it ran at 85% but was actually at 108%
A 4,200 m² distribution center with 3,800 locations reported 'utilization' at 85%. The simulator, with 22% honeycombing factor (free aisle, empty slot in shared racks), 78% picking efficiency, and 1:3 aisle ratio, recomputes effective utilization at 108%. The overfill causes slow rotation, picking errors at 3.4% (versus 1% target), and operator productivity loss. The decision: free 14% of long-tail SKUs to external cross-dock and bring effective utilization down to 92%.
Illustrative figures. Does not represent a real company or an investment recommendation.
Hypothetical case·Case B
A retailer that adds a mezzanine and postpones a new warehouse by 2 years
A retailer projects 28% growth in 18 months. Current capacity: 5,400 m², effective utilization 91%. The simulator compares four paths: new warehouse ($18M MXN, 6 months), mezzanine ($2.4M, 60 days), pick-to-light automation ($3.8M, 90 days), outsourcing slow movers ($85,000/mo recurring). The mezzanine IRR comes in at 38% over 24 months, versus 14% for the new warehouse. The decision: install the mezzanine and postpone the new warehouse until growth holds steady for 12 months.
Illustrative figures. Does not represent a real company or an investment recommendation.
Common mistakes it helps you avoid
Things a team or decision-maker might assume that this simulator forces you to verify before committing.
Reporting utilization by m² without subtracting aisle, dock, and pick zone — the number looks low but operations are saturated.
Mistaking static capacity for dynamic capacity: a warehouse that 'fits 100%' under doesn't rotate inventory and triggers obsolescence.
Ignoring seasonal peaks: sizing for the annual average leaves out the 2-3 high-demand months when operations collapse.
Comparing expansion options on initial cost only: the simulator forces a 24-month IRR so the comparison is clean.
Model limitations
What the simulator does not do, and where you need a professional or a specialized tool.
Does not simulate layouts. For slotting and rack design use specialized software (FlexSim, AnyLogic). The simulator works at aggregate capacity and cost level.
Assumes one or two shifts. For 24/7 operations with relays, adjust the productivity-per-hour assumptions.
Does not model a specific WMS or bin rules: it uses generic picking efficiency assumptions by operation type (B2C, B2B, mixed).
Expansion costs are reference values. For real budgeting, request quotes from integrators and contractors.
When NOT to use this simulator
If you're about to commit Capex above $5M MXN in physical infrastructure, do not use this simulator as the only piece of evidence. It is a pre-screening tool: it helps you discard the 2-3 weak options and focus deep analysis on viable ones. The final decision must be backed by formal quotes, soil mechanics studies if applicable, and financial analysis from your CFO.
Financial notice
Results are illustrative estimates and do not constitute financial, tax, accounting, or legal advice. Use the results as a reference point and validate important decisions with a certified professional.
Editorial review
Reviewed by the Simúlalo editorial team
This simulator was reviewed by the people listed below before being published. The review covers the declared formula, the model's assumptions, the explicit limitations, and the absence of unsupported financial claims.
They are part of the Simúlalo editorial team, focused on building financial tools that are clear, educational, and easy to interpret.
Last updated: ·We update this page when the methodology, sources used, or simulator structure change.
This tool uses standard financial formulas and user-supplied data. To explain concepts like rates, credit, risk, or cash flow we consult public and official sources (Banxico, SAT, CONDUSEF, CNBV, Banco de España, IFRS, BIS, among others). Simúlalo is not affiliated with, sponsored by, or endorsed by these institutions.