What it means
Capacity is simply how much a business can produce or serve in a period, and it is set by people, equipment, space and time. Aggregate planning deliberately blurs the detail: instead of forecasting 400 blue widgets and 300 red ones, it forecasts 700 widget-equivalents and asks whether the plant can make 700.
That coarser view is what makes medium-term decisions possible before the detail is knowable. The reason this matters commercially is that capacity decisions are slow and expensive to reverse.
Hiring and training a technician takes months, a new production line takes a year, and a signed lease on a warehouse takes five. If you wait until demand actually arrives, you have already lost the sale.
There are three broad strategies. A level strategy keeps output steady and absorbs demand swings with stock or backlogs; a chase strategy flexes headcount and hours to follow demand closely; and a mixed strategy, which most businesses actually use, combines a stable core team with overtime, temporary staff and outsourcing at the peaks.
Applying it means converting demand into a single capacity unit, comparing that with available capacity, and costing each way of closing the gap. Overtime is fast but expensive per unit; subcontracting protects service but hands margin to someone else; building stock ahead of a peak ties up cash and risks obsolescence.
Laying these options side by side in dollars is the whole exercise. The nuance people miss is that theoretical capacity is never available capacity.
Machine downtime, holidays, absence, changeovers and training all shave real hours off the calendar, and a plan built on the theoretical number will be wrong every single time.
In practice
Real-world examples.
Example
A commercial bakery knows December volumes run 60% above the annual average. It hires twelve seasonal staff from late October, builds frozen stock through November and books two extra delivery vans, all decided in August when the aggregate plan was set.
Example
A managed IT services firm measures capacity in consultant days. Its aggregate plan shows 2,400 available days next quarter against a pipeline needing 2,750, so it starts recruiting two consultants and lines up a contractor partner for the balance.
Example
A vaccine packing facility deliberately runs a level strategy, keeping output flat all year and holding finished stock, because the validation cost of turning a line on and off is far higher than the cost of holding inventory.
Formula
Calculation
Available capacity = number of resources x hours available per resource, capacity in units = available hours / hours per unit, and utilisation = required output / capacity.
A components plant runs 40 production staff, each available 160 hours a month after holidays and planned maintenance. Available labour hours are 40 x 160 = 6,400 hours a month. Each unit takes 4 labour hours, so monthly capacity is 6,400 / 4 = 1,600 units.
The sales forecast for the coming month is 1,850 units. Required utilisation is 1,850 / 1,600 = 1.156, or 115.6% of capacity, so the plant is short by 1,850 - 1,600 = 250 units. Those 250 units need 250 x 4 = 1,000 extra labour hours.
The operations manager compares two ways of finding the hours. Overtime costs $45 an hour, so 1,000 x $45 = $45,000. Subcontracting costs $210 a unit against an internal cost of $120, so 250 x ($210 - $120) = 250 x $90 = $22,500. Subcontracting is cheaper here by $45,000 - $22,500 = $22,500, and the plan is written accordingly.Case study
Seen in the real world.
Ambervale Furnishings is an illustrative, fictional manufacturer of flat-pack office furniture that had grown from one site to three without ever building a formal capacity plan. Each plant manager forecast their own month and reacted with overtime when the orders arrived.
A new operations director introduced a single aggregate plan measured in standard assembly hours. The exercise showed the group had 18,000 standard hours a month of genuinely available capacity against forecast demand of 21,500 hours in the autumn peak, a shortfall of 3,500 hours. It also showed that one plant was running at 72% utilisation in the same months another was paying weekend rates.
The fix was mostly reallocation rather than expansion. Ambervale moved two product families to the underused site, covered 1,200 of the remaining hours with a temporary shift and outsourced one low-margin line entirely. In this fictional example the peak was met without a single new machine, and overtime spend for the quarter fell by roughly 40% against the prior year.
Watch out
Common mistakes.
- Planning against theoretical capacity rather than realistically available capacity. Holidays, absence, maintenance and changeovers routinely remove 15% to 25% of the hours on the calendar.
- Treating aggregate planning as a production topic with no finance involvement. Every option for closing a capacity gap has a different cost and cash profile, so it is a joint decision.
- Running a pure chase strategy in a business with skilled staff. Constantly flexing headcount destroys experience, raises recruitment costs and usually costs more than it saves.
Questions
People also ask.
What time horizon does aggregate capacity management cover?
Typically six to eighteen months, which sits between long-term facility investment and short-term weekly scheduling.
How do you compare capacity across different products?
Convert everything into one common unit such as standard labour hours or machine hours, so a mixed order book can be measured against a single number.
Does it apply to service businesses?
Yes, and it is often more important there, because a service cannot be stockpiled and unused capacity in a consulting or clinical team is lost the moment the day ends.
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