Idle Capacity Variance
Idle capacity variance, also known as unabsorbed overhead variance or fixed overhead volume variance, is a concept used in cost accounting and management accounting. It measures the difference between the budgeted fixed overheads and the actual fixed overheads absorbed during a specific period.
This variance arises when a company’s actual level of production or activity differs from the expected or budgeted level. When actual production is lower than what was budgeted, the company may not absorb all of its fixed overhead costs, leading to an unfavorable idle capacity variance. If production is higher than expected, the variance could be favorable.
Example of Idle Capacity Variance
Suppose a company, XYZ Ltd., manufactures widgets. The budgeted production for a given period is 20,000 units, and the budgeted fixed overhead costs for the same period are $200,000. This gives a budgeted overhead rate of $10 per unit ($200,000 / 20,000 units).
However, due to some unforeseen circumstances, the actual production volume falls short and the company is only able to produce 18,000 units during this period. Even though the production volume was lower, the fixed overheads remained the same, as these costs do not change with the level of output.
So, the actual absorbed overhead cost rate becomes $11.11 per unit ($200,000 / 18,000 units).
The idle capacity variance here would be calculated as:
(Budgeted units – Actual units) * Budgeted overhead rate
So, it’s (20,000 units – 18,000 units) * $10/unit = $20,000
This $20,000 is an unfavorable idle capacity variance. It signifies that XYZ Ltd. produced fewer units than it budgeted for, so it was unable to absorb all of its fixed overheads, leading to an under-absorption of $20,000.
This information can be very valuable to the management of XYZ Ltd. as it shows there is unused capacity in the production process. Management can then investigate the causes and try to address them. Perhaps there’s a problem in the supply chain, or maybe the demand for the widgets is not as high as expected. In either case, understanding the variance can help the company make more informed decisions.
