Interpreting the Production-Volume Variance

Lump-sum fixed costs represent the costs of acquiring capacity. These costs do not decrease automatically if the capacity needed turns out to be less than the capacity acquired. Sometimes costs are fixed for a specific time period for contractual reasons, such as an annual lease contract for equipment. At other times, costs are fixed because capacity has to be acquired or disposed of in fixed increments, or lumps. For example, suppose that acquiring a sewing machine gives Webb the ability to produce 1,000 jackets. If it is not possible to buy or lease a fraction of a machine, Webb can add capacity only in increments of 1,000 jackets. That is, Webb may choose capacity levels of 10,000, 11,000, or 12,000 jackets, but nothing in between.

What explains the $46,000 U production-volume variance? Why did this overcapacity occur? Why were 10,000 jackets produced instead of 12,000? Is demand weak? Should Webb reevaluate its product and marketing strategies? Is there a quality problem? Or did Webb make a strategic mistake by acquiring too much capacity? The causes of the $46,000 U production-volume variance will determine the actions Webb’s managers take in response to the variance.

In contrast, a favorable production-volume variance indicates an overallocation of fixed overhead costs. That is, the overhead costs allocated to the actual output produced exceed the budgeted fixed overhead costs of $276,000. The favorable production-volume variance represents fixed costs allocated in excess of $276,000.

Be careful when drawing conclusions about Webb’s capacity planning on the basis of an unfavorable production-volume variance. Consider why Webb sold only 10,000 jackets in April. Suppose a new competitor gained market share by pricing its jackets lower than Webb’s. To sell the budgeted 12,000 jackets, Webb might have had to reduce its own selling price on all 12,000 jackets. Suppose it decided that selling 10,000 jackets at a higher price yielded higher operating income than selling 12,000 jackets at a lower price. This would be a good decision even though it would mean Webb would not utilize all its capacity. The production-volume variance cannot take into account such information. We should not interpret the $46,000 U amount as the total economic cost of selling 2,000 jackets fewer than the 12,000 jackets budgeted.

Companies plan their plant capacity strategically on the basis of market information about how much capacity will be needed over some future time horizon. For 2020, Webb’s budgeted quantity of output is equal to the maximum capacity of the plant for that budget period. Actual demand (and quantity produced) turned out to be below the budgeted quantity of output, so Webb reports an unfavorable production-volume variance for April 2020. However, it would be incorrect to conclude that Webb’s management made a poor planning decision regarding its plant capacity. The demand for Webb’s jackets might be highly uncertain. Given this uncertainty and the cost of not having sufficient capacity to meet sudden demand surges (including lost contribution margins as well as reduced repeat business), Webb’s management may have made a wise capacity choice for 2020.

So what should Webb’s managers ultimately do about the unfavorable variance in April? Should they try to reduce capacity, increase sales, or do nothing? Suppose Webb’s managers anticipate they will not need 12,000 jackets of capacity in future years. They will then cancel leases on some machines but continue to maintain some excess capacity to accommodate unexpected surges in demand. Concepts in Action: Variance Analysis and Standard Costing Help Sandoz Manage Its Overhead Costs highlights another example of managers using variances to help guide their decisions.

We next describe journal entries to record fixed overhead costs using standard costing.

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Concepts in Action

Variance Analysis and Standard Costing Help Sandoz Manage Its Overhead Costs^*

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Sandoz, the $10.1 billion generics division of Swiss-based Novartis AG, is the world’s third largest generic drug manufacturer. As products lose patents, multiple manufacturers enter the market and prices drop. How much? Very significantly. In the United States, for example, 90% of all prescription drugs dispensed were generics, but they account for only 23% of total drug costs. To compete, generics companies must carefully control costs.

To manage overhead costs, Sandoz prepares an overhead budget based on a detailed production plan, planned overhead spending, and other factors. Sandoz uses activity-based costing to assign budgeted overhead costs to different work centers (for example, mixing, blending, tableting, testing, and packaging). Finally, overhead costs are assigned to products based on the activity levels required by each product at each work center.

Each month, Sandoz compares actual costs to the standard costs of products made to evaluate whether costs are in line with the budget. If not, reasons are examined and accountable managers are notified. Manufacturing overhead variances are examined at the work center level. These variances help determine when equipment is not running as expected so it can be repaired or replaced. Variances also help to identify inefficiencies in processing and setup and cleaning times, which leads to more efficient ways to use equipment. Sometimes, the manufacturing overhead variance analysis leads to the review and improvement of the standards themselves—a critical element in planning the level of plant capacity. Management also reviews current and future capacity on a monthly basis to identify constraints and future capital needs.