Learning Objective 4 Know how to choose which products to produce when there are capacity constraints
We now examine how the concept of relevance applies to product-mix decisions, the decisions managers make about which products to sell and in what quantities. These decisions usually have only a short-run focus because they typically arise in the context of capacity constraints that can be relaxed in the long run. In the short run, for example, BMW, the German car manufacturer, continually adapts the mix of its different models of cars (for example, 328i, 528i, and 750i) to fluctuations in selling prices and demand.
To determine product mix, managers maximize operating income, subject to constraints such as capacity and demand. Throughout this section, we assume that as short-run changes in product mix occur, the only costs that change are costs that are variable with the number of units produced (and sold). Under this assumption, the analysis of individual product contribution margins provides insight into the product mix that maximizes operating income. The same basic concepts apply in the more general cases except that we then need to consider contribution margins based on variable costs at different levels of the cost hierarchy.
In terms of contribution margin per unit and contribution-margin percentage, the data in Example 4 shows that boat engines are more profitable than snowmobile engines. Should Power Recreation produce and sell boat engines? Not necessarily. The following table shows that managers should choose the product with the highest contribution margin per unit of the constraining resource (factor). That’s the resource that restricts or limits the production or sale of products.

The table depicts contribution margin information for snowmobile and boat engines. The details of the table are as follows:
1. Contribution margin per unit
2. Machine-hours required to assemble one unit
3. Contribution margin per machine-hour
4. Total contribution margin for 600 machine-hours
The number of machine-hours is the constraining resource in this example, and snowmobile engines earn more contribution margin per machine-hour compared with boat engines Therefore, choosing to produce and sell snowmobile engines maximizes total contribution margin ($72,000 vs. $45,000 from producing and selling boat engines) and operating income. Other constraints in manufacturing settings can be the availability of direct materials, components, or skilled labor, as well as financial and sales factors. In a retail department store, the constraining resource may be linear feet of display space. Regardless of the specific constraining resource, managers will maximize total contribution margin by choosing products with the highest contribution margin per unit of the constraining resource.
In many cases, a manufacturer or retailer has the challenge of trying to maximize total operating income for a variety of products, each with more than one constraining resource. Some constraints may require a manufacturer or retailer to stock minimum quantities of products even if these products are not very profitable. For example, supermarkets must stock less-profitable products, such as paper towels and toilet paper, because customers will only shop at supermarkets that carry a wide range of products. To determine the most profitable product mix, the manufacturer or retailer must maximize total contribution margin in the face of many constraints. Optimization techniques, such as linear programming, discussed in the appendix to this chapter, help solve these more complex problems.
At the same time, managers work to relieve the bottleneck constraint to increase output and contribution margin. Can the available machine-hours for assembling engines be increased beyond 600, for example, by reducing idle time? Can the time needed to assemble each snowmobile engine (2 machine-hours) or each boat engine (5 machine-hours) be reduced, for example, by reducing setup time and processing time of assembly? Can some of the assembly operations be outsourced to allow more engines to be built? We address these questions in the following section.