Warehouse Throughput Bottleneck
Find which step in your warehouse flow is the real constraint and how much throughput you’d gain by relieving it.
Relieving Picking up to the next step's capacity would gain 150 units/day.
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Based on your results, these related decisions are available.
How this works
A warehouse flow's overall throughput is set by its slowest step, not the average of all steps. This engine compares two or three named process steps by capacity, identifies the constraint, and reports how much throughput would gain if that step were relieved up to the next-tightest step's capacity, since improving it further just moves the constraint elsewhere. It also flags when actual measured throughput falls short of even the theoretical bottleneck capacity, a sign of labor or downtime loss beyond the bottleneck.
Assumptions
- Steps run in series as one shared flow
- Capacities are steady daily rates
Limitations
- Two or three steps only
- Does not model buffers or WIP between steps
Sources
Follows Theory of Constraints (Goldratt, The Goal), the same family as Contribution Margin per Constraint Hour.
Worked example
Receiving handles 400 units/day, Picking 250, and Packing 500. Picking is the constraint at 250 units/day. Relieving Picking up to Packing's 500-unit capacity is unrealistic since Receiving would bind first at 400, so the real achievable gain from fixing Picking is 150 units/day, up to Receiving's level, not the full 250-unit gap to Packing.
Common use cases
- Deciding which warehouse process step to invest in first
- Sizing the realistic throughput gain from a specific fix
- Separating a capacity problem from a labor or downtime efficiency problem