SUPSupply & productionStop 5 of 12
Rough-cut capacity check
Testing whether the production plan fits the bottleneck resources before anyone commits to it.
Read atChange any time
A plan can look fine on paper and still be impossible on the shop floor. Rough-cut capacity planning (RCCP) is the quick check that catches this early. It doesn’t look at every machine; it looks at the few critical resources, the bottleneck lines, scarce skills or a key supplier, and asks whether the plan fits.
Say the plan calls for 50,000 units next month, and every unit passes through a filling line that can make 40,000. RCCP shows a 10,000-unit gap before anything is released. Management then chooses how to close it:
- overtime or an extra shift,
- moving some volume to another plant or a co-packer,
- building stock in an earlier month with spare capacity,
- changing the plan itself, by delaying, reducing or shaping demand.
The important nuance: RCCP finds the gap; it doesn’t solve it. Choosing the cheapest fix is a separate planning or optimization decision.
RCCP has a more detailed cousin. Capacity requirements planning (CRP) runs after MRP and checks the load on every work centre, using the actual planned orders and routings. RCCP is fast and approximate, used on the MPS; CRP is detailed and used closer to execution.
Words to use
- Critical resource
- A line, skill or supplier whose capacity limits total output.
- Capacity gap
- Planned load minus available capacity on a critical resource.
- CRP
- Capacity requirements planning: detailed load checking for every work centre after MRP.
Bills of capacity
RCCP needs, for each product family, the time it takes on each critical resource: a bill of capacity (or resource profile). Multiply the plan by those times and compare the load with the capacity available.
Every 1,000 units need 5 hours on the filling line, including an average share of changeovers. The line runs one 8-hour shift on 25 days a month: 200 hours, or 50 hours a week, enough for 10,000 units a week.
| Week | 1 | 2 | 3 | 4 | Month |
|---|---|---|---|---|---|
| Plan (units) | 12,000 | 14,000 | 12,000 | 12,000 | 50,000 |
| Load (hours) | 60 | 70 | 60 | 60 | 250 |
| Available (hours) | 50 | 50 | 50 | 50 | 200 |
| Gap (hours) | −10 | −20 | −10 | −10 | −50 |
The month is 50 hours short: 10,000 units, with the worst week second. Options: Saturday overtime, a second shift on some days, moving volume to a co-packer, building ahead in the previous month if it had spare hours, or changing the plan.
Three common methods, in rising accuracy: overall factors (total hours split across resources by historical shares), bills of capacity (hours per unit by resource, as above) and resource profiles (bills of capacity spread over the lead time, so load lands in the right week).
RCCP versus CRP
| RCCP | CRP | |
|---|---|---|
| Runs on | Master production schedule | MRP planned and released orders |
| Uses | Bills of capacity | Detailed routings |
| Resources | Critical ones only | Every work centre |
| When | Before releasing the MPS | Closer to execution |
| Purpose | Is the plan feasible on the bottlenecks? | Is each work centre’s load feasible week by week? |
Which capacity number?
- Nameplate (design) capacity: what the equipment could do under ideal conditions.
- Effective capacity: after planned stops such as changeovers, maintenance and breaks.
- Demonstrated capacity: what the line has actually produced over recent weeks.
Plans built on nameplate capacity are systematically infeasible. Demonstrated capacity, adjusted for any real improvements, is the honest basis for RCCP.
Why planning to 100% is a trap
Queueing theory explains why a resource loaded close to 100% creates long waits. In Kingman’s approximation, waiting time grows with , where is utilization. At 80% that factor is 4; at 90% it is 9; at 95% it is 19. Pushing a bottleneck from 90% to 95% roughly doubles the queue in front of it, and with it the lead time and the work in process. That is why sensible plans leave some headroom on the bottleneck, especially when arrivals and processing times vary.
Choosing critical resources
Critical resources are those that limit output or are hard to expand quickly:
- bottleneck machines or lines,
- scarce skills, such as certified welders or quality approvers,
- key suppliers with limited capacity,
- storage space, cold rooms or dock doors in peak season.
Keep the list short (a handful per plant) and review it when the product mix changes, because a mix shift can move the bottleneck.
Capacity decisions are trade-offs
RCCP finds the gap; closing it is an economic choice. Overtime costs a premium, subcontracting costs margin and control, building ahead costs inventory, and changing the plan costs sales or service. These options usually go to the supply review in S&OP with their costs, where they are compared and decided.
Interview kit
Practise it out loud
Answer each question yourself before opening the model answer.
Rough-cut capacity planning checks whether the master schedule is feasible against critical or bottleneck resources before it’s released. If a plan needs 50,000 units and the bottleneck can do 40,000, RCCP flags the 10,000-unit gap, and then planning decides how to close it through overtime, other plants, co-packers, pre-building stock or changing the plan. It identifies the gap; it doesn’t solve it.
A company plans 50,000 units but its bottleneck line can only make 40,000. What concept flags this, and what can it do?
Rough-cut capacity planning flags the 10,000-unit gap. Options include overtime or extra shifts, moving volume to another plant or a co-manufacturer, producing earlier and holding stock, investing in capacity, or adjusting the plan. The choice depends on cost, lead time and service impact.
How is RCCP different from CRP?
RCCP is an approximate check of the MPS against a few critical resources, done early. CRP is a detailed check of every work centre using MRP’s planned orders and routings, done closer to execution.
Connected stops
Where this idea feeds in, or gets its inputs from.
Sources and further reading
- Silver, E. A., Pyke, D. F. & Thomas, D. J. (2017). Inventory and Production Management in Supply Chains (4th ed.). CRC Press.
- Chopra, S. & Meindl, P. Supply Chain Management: Strategy, Planning, and Operation. Pearson.
- Hopp, W. J., & Spearman, M. L. (2008). Factory Physics (3rd ed.). McGraw-Hill.
- Kingman, J. F. C. (1961). The single server queue in heavy traffic. Mathematical Proceedings of the Cambridge Philosophical Society, 57(4), 902–904.