What it means
The starting point is a production schedule, usually the output of a materials requirements planning system that has already worked out what to make and when. Capacity requirements planning takes that schedule and asks a different question: can the factory physically do it?
Each planned item is multiplied by its standard hours to give the load on every machine, cell or work centre. Available capacity is then calculated for the same periods.
That means counting the number of usable machines or people, the hours per shift, the number of shifts and the working days, then discounting for maintenance, changeovers, absence and normal inefficiency. The result is effective capacity rather than the theoretical maximum.
Comparing load against effective capacity produces a capacity profile, typically shown week by week. Peaks above 100% are overloads that will cause late deliveries; troughs well below are idle time that still costs money.
Because load rarely arrives evenly, the usual output of the exercise is a picture of a few severe bottleneck weeks rather than a uniform shortage. Once the gaps are visible, there are two families of response.
Adjust the demand side by rescheduling orders, moving work earlier into an idle week, or subcontracting; or adjust the supply side by adding overtime, a temporary shift, hired equipment or additional staff. Each option has a cost, so the planning exercise usually ends with a comparison of the cheapest way to close each gap.
The same logic applies well outside factories. Professional services firms run the identical calculation on billable hours, hospitals run it on theatre time and staffing, and contact centres run it on agent hours against forecast call volumes.
In every case the discipline is the same: translate the plan into hours, compare with what exists, and resolve the difference before the period starts.
In practice
Real-world examples.
Example
A furniture maker wins a contract for 900 units due in eight weeks. Capacity requirements planning shows the spray booth, not the assembly line, is the constraint at 118% load, so two weeks of work are subcontracted to a nearby finisher.
Example
An accounting firm maps its January to March audit schedule against available senior hours and finds a 400-hour shortfall in February. Partners move three non-statutory jobs into April rather than hire contractors at short notice.
Example
A vaccine manufacturer runs capacity planning on its filling lines and finds utilisation at 96% for six consecutive months. With no headroom for breakdowns, it approves a second line rather than risk a single failure halting all supply.
Formula
Calculation
Required capacity (hours) = Units planned x Standard hours per unit
Available capacity (hours) = Work centres x Hours per day x Working days
Utilisation = Required capacity / Available capacity
A machining department plans to produce 4,000 units next month, each requiring 0.75 standard hours. The department has 10 work centres running 15 hours a day across 25 working days.
Required capacity = 4,000 x 0.75 = 3,000 hours.
Available capacity = 10 x 15 x 25 = 3,750 hours.
Utilisation = 3,000 / 3,750 = 80%.
The month looks comfortable. Now a customer adds a second product line requiring a further 1,000 hours in the same month.
New required capacity = 3,000 + 1,000 = 4,000 hours.
Utilisation = 4,000 / 3,750 = 106.7%, an overload of 250 hours.
Closing that gap with overtime at $45 an hour costs 250 x $45 = $11,250. If the planner instead applies a 90% efficiency factor, effective capacity is only 3,750 x 0.90 = 3,375 hours, and the true shortfall is 625 hours, which changes the answer from overtime to subcontracting.Case study
Seen in the real world.
Kestrel Marine Fittings is an invented manufacturer used for this illustrative example. It made brass fittings across four departments and had always planned capacity in aggregate, dividing total planned hours by total available hours across the whole plant. On that basis the plant ran at a comfortable 82% and management saw no problem.
Deliveries were nonetheless late roughly a third of the time. When a new operations manager built a capacity profile by work centre rather than for the plant as a whole, the reason was immediate: the polishing cell was loaded at 121% in most weeks while the packing area sat at 54%. The aggregate figure had been averaging away a severe bottleneck.
The response in this fictional scenario cost far less than the capital request that had been drafted. Kestrel added a second polishing shift two days a week at about $96,000 a year, moved simple polishing work to a subcontractor, and rescheduled three product families to spread their polishing demand across the month. On-time delivery rose from 67% to 94% within a quarter, with no new machinery bought.
Watch out
Common mistakes.
- Planning capacity at the plant level rather than by work centre. Aggregate numbers hide bottlenecks, and a plant averaging 80% can still have a cell running at 120%.
- Using theoretical hours as available capacity. Ignoring maintenance, changeovers, absence and normal inefficiency produces a plan that looks feasible and is not.
- Forgetting that people are capacity too. A factory can have spare machine hours and still be constrained by the number of trained operators or inspectors available.
Questions
People also ask.
How is capacity requirements planning different from rough-cut capacity planning?
Rough-cut is a quick sanity check on the master schedule using key resources only, while capacity requirements planning works from detailed order routings across every work centre.
What utilisation figure should a business aim for?
Most operations target somewhere between 80% and 90%, because running consistently above that leaves no room to absorb breakdowns, rework or urgent orders.
Does this only apply to manufacturing?
No, the same method is used for billable staff hours, hospital theatre time, call centre agents and any operation where demand must be matched to a finite supply of hours.
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