3 Capacity Planning

Purpose of capacity planning

Capacity planning connects demand forecasts to decisions about equipment, facilities, labor, operating hours, and process design. Because capacity choices can require substantial investment and take time to change, organizations plan for both near-term operations and longer-term demand.

When demand exceeds capacity, an organization may face lost sales and delays. When capacity exceeds demand, it may incur unnecessary costs.

Measuring capacity and performance

Choose measurement units that reflect the operation, such as customers served per hour, beds available, labor hours, or products per shift. For multiple products, measure output by product or use a shared input such as machine hours so that unlike outputs are not treated as interchangeable.

Design capacity is the maximum theoretical output under specified conditions. Effective capacity is the output realistically achievable after allowing for planned maintenance, product mix, breaks, setup time, and other operating limits. Actual output is what the process produces in practice.

Utilization and efficiency compare actual output with different capacity benchmarks:

For example, a plant with design capacity of $1{,}000$ units per day, effective capacity of $800$ units, and actual output of $720$ units has utilization of $72\%$ and efficiency of $90\%$. Utilization compares output with the theoretical ceiling; efficiency compares it with a realistic operating target.

Constraints and bottlenecks

A constraint is any resource or condition that limits an operation’s output. Examples include machine time, staffing, workspace, materials, or a policy. In a sequence of dependent steps, the step with the lowest capacity is usually the bottleneck and limits the throughput of the whole process.

Faster upstream steps cannot make the system deliver more than the bottleneck can handle. They may instead create queues and excess work in process. For example, if each order must pass through three steps capable of handling $50$, $30$, and $40$ orders per hour, the process capacity is at most $30$ orders per hour. Increasing the first step from $50$ to $60$ orders per hour does not raise total capacity.

Managers should first identify and make good use of the constraint, then consider adding capacity there. Reducing changeover time or adding a trained worker are possible ways to improve the bottleneck and may increase throughput. Once a bottleneck is relieved, a different step may become the new bottleneck.

Matching capacity to demand

Capacity planning compares forecast demand with effective capacity over the relevant time period. If expected demand exceeds capacity, managers can consider overtime, additional shifts, cross-training, process improvements, subcontracting, or investment in equipment and facilities. If capacity exceeds demand, they might reduce shifts, reassign resources, build inventory when feasible, or defer expansion.

Each option has trade-offs involving cost, flexibility, quality, lead time, and service. Capacity changes can also depend on suppliers, transportation, staffing, and regulatory requirements.

Timing capacity changes

Organizations commonly use three approaches to the timing of capacity changes:

• Leading capacity: Add capacity before demand is expected to rise. This can protect service and support growth, but risks idle resources if the forecast is too high.

• Following capacity: Wait until demand increases before expanding. This limits early investment, but may cause delays or lost sales while the organization catches up.

• Tracking capacity: Add capacity in smaller increments as demand develops. This can balance responsiveness and investment, though repeated adjustments may be costly or difficult.

These approaches differ in when capacity is added and in their associated costs and risks. The appropriate choice depends on how managers weigh responsiveness against the risk and cost of excess capacity.

Planning and adjustment

A sound capacity plan begins by forecasting demand for an appropriate horizon, checking current effective capacity, and identifying gaps and constraints. Managers then compare alternatives, including their financial costs and practical effects, select a response, and monitor actual demand and output so the plan can be adjusted.

Demand is uncertain, so a plan should account for variation rather than assume a single forecast is guaranteed. Capacity planning therefore links a forecast to a response while allowing for monitoring and adjustment.