Capacity utilisation rate (CUR)

Capacity is the amount of output or work that a resource can produce within a defined period. A machine may be capable of 40 widgets an hour, while a factory may offer 10,000 machine-hours in a 40-hour week. The capacity utilisation rate (CUR) shows how much of that productive potential is actually being used and helps an organisation assess the return on investments in equipment, people and processes.

When to use it

• Use CUR to answer: “To what extent are we using our practical production or work potential?”
• Place the measure within the operational-processes and supply-chain perspective.
• Define capacity, data sources, calculation and reporting frequency before comparing periods.
• Interpret the result against relevant targets, internal trends and like-for-like benchmarks.

Origins

Capacity utilisation developed in industrial economics and production management as a comparison between actual output and defined productive potential. During the twentieth century, factories used related measures for line and equipment planning while statistical agencies began publishing industry-wide utilisation series. The US Federal Reserve, for example, defines capacity in terms of sustainable maximum output under a realistic work schedule and normal downtime. No denominator is universal: design maximum, practical capacity and sustainable output describe different things and produce different rates.

What it is

Perspective: Operational processes and supply chain perspective.

Key performance question: To what extent are we leveraging our full production/work potential?

CUR expresses actual output as a proportion of the output that installed resources could reasonably deliver. It is commonly associated with manufacturing assets but applies equally to services: a department might have practical capacity for three projects a month or a clinic for 15 consultations a day.

A low rate can reveal slack, weak demand, a process constraint or avoidable loss. A rate of 70% per cent suggests theoretical headroom before new machines, facilities or people are required, but it does not prove that the remaining thirty per cent is usable. Product mix, maintenance, skills, scheduling and bottlenecks elsewhere may prevent output from rising to the denominator. Conversely, a very high rate can indicate strong asset use or insufficient resilience.

How to use it

Measurement