Recall that in Chapter 16, Bayou Division was projected to produce and sell 100,000 units, but in fact only produced and sold 80,000. Suppose instead that Bayou had pro- duced 90,000 units, but still only sold 80,000. How would this affect our prior analysis, and what new information is useful for managers to consider as they evaluate operations? In this chapter we consider how the presence of inventory affects our earlier analysis of variances. We also consider some new variances that arise when firms are interested in evaluating shifts of market share, in industry growth rates, in the mix of products that customers purchase (for firms that sell a range of related products at different prices), and in the efficient use of a mix of inputs than can substitute for one another.
Note that the assumption that production was greater than sales has no effect on the sales activity variance because the master budget and flexible budget are based on sales volume. Thus, Columns (5), (6), and (7) of Exhibit 16.5 remain unchanged. In addition, the sales price variance is based on units sold, so Column (4) remains the same. Gener- ally, marketing and administrative costs are not affected by producing 90,000 instead of 80,000 units, so we assume that they do not change. This allows us to focus on Columns (1) and (2), which do change.
We assume that actual variable production manufacturing costs are $4.121 per unit (based on $329,680 ÷ 80,000 units as in Chapter 16) and actual fixed production costs are $195,500 for the period. This leaves the fixed production cost variance of $4,500 F un- changed. In addition to the $4,500 favorable fixed overhead price variance, there is now a $20,000 unfavorable production volume variance caused by producing 90,000 units when the budget called for production of 100,000 units [$20,000 = (90,000 — 100,000) × $2.00].
The general approach in variance analysis is to separate the variance into components based on a budgeting formula. For example, budget revenues can be expressed as: Budget revenues = SP × SQ. Where SP is the standard price of output and SQ is the master budget quantity (sales ac- tivity). Two components are used to estimate revenues, so two factors lead to a variance between actual revenues and budgeted revenues: either the actual price (AP) is different from standard price (SP) or actual sales quantity (AQ) is different from standard (bud- geted) sales quantity (SQ), or both.
We can extend this simple idea by asking, for example, how the estimate of sales activity was made. Many companies base an initial sales forecast on an estimate of sales activity in the industry as a whole and on an estimate of the company’s market share.
For example, Bayou Division’s marketing manager developed the estimated sales volume of 100,000 frames based on an estimated 400,000 frames being sold in Bayou’s market and the assumption that Bayou would maintain its historical market share of 25 percent (= 100,000 frames or 400,000 frames × 25% market share). There are two reasons that actual sales activity is different from budgeted sales activity: either actual industry volume was different from budget industry volume or actual market share was different from budgeted market share, or both. Extending our knowledge about variance analysis, we know that we can compute two variances, an industry volume variance and a market share variance.
The industry volume variance indicates how much of the sales activity variance is due to changes in industry volume. The market share variance represents how much of the activity variance is due to changes in market share. The market share variance is usu- ally more controllable by the marketing department and is a measure of its performance.
The volume in the metal frame industry increased from 400,000 units to 500,000 because favorable weather led to increased construction activity; Bayou’s market share, however, fell dramatically from 25 percent to 16 percent (= 80,000 frames ÷ 500,000 frames) as customers were concerned about whether Bayou would remain in business. Hence, the 20,000-unit unfavorable activity variance (the difference between the 80,000- unit actual sales and the 100,000-unit budgeted sales) can be broken down into an indus- try effect and a market share effect (see Exhibit 17.4).
The 20,000-unit decrease can be split as follows. Due to industry volume, Bayou would have sold 25,000 additional frames, which is 25 percent of the actual increase in industry volume. However, Bayou lost sales of 45,000 units as its market share fell from 25 percent to 16 percent. Multiplying each figure by the standard contribution margin gives the impact of these variances on operating profits. The sales activity variance of $106,000 is exactly the same sales activity variance we computed in Exhibit 16.4. By decomposing it into an industry volume and a market share variance, we have additional information that can be used to make operational improvements next period.
The use of the industry volume and market share variances enables management to separate that portion of the activity variance that coincides with changes in the overall industry from that which is specific to the company. Favorable market share variances indicate that the company is achieving better-than-industry-average volume changes. This can be very important information for marketing managers, who are constantly concerned about their products’ market share.
No comments:
Post a Comment