. Incremental Analysis
Managers must take advantage of opportunities that will improve the organization’s profitability in the short run. An opportunity that arises must be evaluated to determine its potential profitability and whether its implementation supports the organization’s long term objectives. When a manager is presented with an opportunity to increase profitability by accepting a special order, for example, she must quantitatively and qualitatively evaluate the proposal. A qualitative analysis would include research on whether the special order is within the scope of the organization’s long term strategic business objectives and whether the company’s culture would support fulfilling the special order. The quantitative analysis would include identifying the relevant costs and the proposed revenue associated with accepting the special order.
Managers must gather information and communicate results when evaluating short run decisions. When preparing reports associated with short run decisions, managers apply incremental analysis.
The first step in incremental analysis is to determine the costs and revenues that are relevant and irrelevant. If a cost changes as a result of implementing the decision, then it is relevant. If a cost remains the same as a result of implementing the decision, then it is irrelevant. Usually fixed costs are irrelevant because they do not change as a result of implementing the decision. However, if implementing the decision results in a new relevant range for the fixed costs, then the change in fixed costs would be relevant.
For example, assume a special order for custom baseball bats is received by a baseball bat manufacturer. The budgeted fixed costs for the baseball bat plant are calculated in a relevant range of up to 20,000 baseball bats manufactured. However, because the plant is not operating at capacity (due to demand) the plant capacity could support the manufacturing of 10,000 more baseball bats if another shift was added. Therefore, the plant has capacity to manufacture 30,000 baseball bats but the fixed costs associated with manufacturing are calculated using 20,000 baseball bats. If a special order was accepted, there would be plant capacity, but fixed costs would become a relevant cost because another shift manager, whose salary and benefits is a fixed cost, would have to be hired.
One type of irrelevant cost is a sunk cost. A sunk cost is a cost that was previously incurred that cannot be recovered. Since the new decision will not recover the cost, the sunk cost is irrelevant to the decision at hand.
For example, assume that special software was purchased to manufacture a special order. The special order was successful, so management would like to obtain another similar special order. Since the software was previously purchased, the cost has already been incurred and is irrelevant to the new decision. If management does find another special order in which the software is applicable, then potential for even higher profit on the special order is possible since the cost of the software does not have to be considered.
Opportunity costs are another type of cost that is irrelevant to the quantitative analysis for the decision, but may affect the qualitative analysis. For example, when one decision eliminates the possibility of another decision, then an opportunity was lost. Assume that the baseball bat manufacturer accepts the special order and begins operating at full capacity to fulfill the order. The opportunity to manufacture another special order at a higher profit is gone. If, at the time the special order decision is made, it is known that there might be another special order available, then an opportunity cost is incurred when the first special order is taken.
II. Models for Incremental Analysis
Incremental analysis is most often used for decisions involving outsourcing, special orders, segment profitability, and sales mix. It can be used for any decision that involves costs and revenues that change as a result of a decision.
Let’s go through an example of applying incremental analysis for the quantitative support in an outsourcing decision. Outsourcing is the use of suppliers outside the organization to perform services or produce goods that could be performed or produced internally.
Assume that Box Company has been outsourcing the manufacturing of packing cartons for several years. The company that manufactures Box Company’s packing cartons has informed Box Company that there will be a price increase from $1.25 per carton to $1.50 per carton. Since Box Company has idle machinery and capacity in the plant that could be upgraded to manufacture the packing cartons, they must decide if it is cost effective to continue outsourcing the manufacturing of packing cartons after the price increase.
Other data includes:
•Annual production and usage would be 20,000 cartons.
•Estimated cost of direct materials is $.84 per carton.
•Workers earn $8.00 per hour and can process 20 cartons per hour ($.40 per carton).
•Cost of variable overhead will be $4 per direct labor hour and 1,000 direct labor hours will be required.
•Fixed overhead per year includes $4,000 of depreciation and $6,000 of other fixed costs.
•There is space to produce the cartons and the machines will remain idle if the cartons are purchased.
Our first step is to determine the relevant and irrelevant costs. Direct materials are relevant because they would not be incurred if Box Company continued to outsource. Direct labor is also relevant as these workers would not be manufacturing the packing cartons if Box Company continued to outsource. Variable overhead is relevant as it pertains to the direct labor. Fixed overhead and depreciation are irrelevant because these costs are incurred whether or not Box Company outsources.
Using incremental analysis, management can support manufacturing their own packing cartons by proving the cost savings of $1,200. Shown in the illustration to the left.
Now let’s look at a segment profitability example of using incremental analysis. Segment profitability analysis is used for determining if business divisions, product lines, or supplemental services are actually profitable. Breaking down the relevant costs associated with the segment is the first step.
In segment analysis, there are two types of fixed costs. There are fixed costs associated with the segment that are relevant, and fixed costs that are common to the entire company that are irrelevant to the segment.
Looking at the example below, Home State Bank, we see a segmented income statement that shows the safe deposit box service is not profitable. In the right column of the segmented income statement we see the common fixed costs of $12,000 that would continue to be incurred even if the safe deposit box service were eliminated. Therefore, the common fixed costs have been identified and removed for the segment analysis report to determine if the safe deposit box service really is unprofitable.
Now, looking at the second report that supports the decision to remove the safe deposit box division, we see that profitability will increase by $9,000 for Home State Bank if they discontinue the Safe Deposit Box Division. The segmented profitability decision report shows in the left column a contribution margin income statement that combines both divisions. In the middle column, the Safe Deposit division is discontinued and the column shows only the operating profit of the Bank Operations division. In other words, the left column shows both divisions combined and the middle column shows only the Bank Operations division. Notice that both the left and the middle columns contain the common fixed costs of $12,000. Since the common fixed costs are relevant to the company as a whole, they must be considered in both columns.
III. The Sales Mix Decision
We will look at one more example that is similar to our critical thinking assignment for this module, a sales mix decision.
When a company manufactures more than one product or offers more than one service it is likely that one product or service is more profitable for the company. If the company utilizes the same equipment to manufacture the different products, or the same people to provide the multiple services then it becomes imperative that the optimum sales mix is determined to accomplish maximum profitability. The limited ability to produce products or provide services is called a resource constraint. In other words, the company only has resources to provide a set number of products or services, so they had better optimize the resource to provide the most profitable.
Using the Home State Bank as our example again, let’s assume that they have three loan products, auto loans, home loans, and commercial loans. They currently have available enough resources and people to provide 100,000 hours of loan processing time. Each of these three types of loans takes a different amount of time to process with home loans taking the longest amount of time to process. The consumer demand for each of these types of loans is relevant data as well as the fees received for each of these types of loans.
Commercial Loans
Auto Loans
Home Loans
Current loan application demand
20,000
30,000
18,000
Processing hours per loan application
2
1
2.5
Loan origination fee
$24.00
$18.00
$32.00
Variable processing costs
$12.50
$10.00
$18.75
Variable selling costs
$6.50
$5.00
$6.25
Our first step is to prepare a contribution margin for each of the loan products. We will start with the loan origination fee as our sales figure and then subtract the variable costs given above.
Commercial Loans
Auto Loans
Home Loans
Sales
Variable processing
Variable selling
$24.00
– 12.50
– 6.50
$18.00
– 10.00
– 5.00
$32.00
– 18.75
– 6.25
Contribution Margin
$5.00
$3.00
$7.00
Once the contribution margin is determined for each product or service, then the resource constraint can be applied. Each contribution margin is divided by its resource use. The commercial loans take 2 hours to process, so the $5.00 contribution margin is divided by 2 hours to find the contribution margin per processing hour.
Now we have determined that auto loans at $3.00 are the most profitable loan product for Home State Bank. Since Auto loans are the most profitable, the bank should seek to process as many auto loans as possible.
Remember there is demand for 30,000 auto loans, so further calculations must be made to find the optimum mix for sales of all three loan products. If total demand does not exceed the capacity, then optimum sales mix will equal demand for that product.
If though, the capacity is lower than the total demand, then an optimum mix must be calculated. Recall that Home State Bank’s capacity is 100,000 hours. If we multiply and sum the demand for each product, we find that total demand exceeds the capacity of 100,000 processing hours.
Loan Type
Current Demand
Commercial
Auto
Home
40,000
30,000
+ 45,000
processing hours (20,000 loans x 2 processing hours)
processing hours (30,000 loans x 1 processing hour)
processing hours (18,000 loans x 2.5 processing hours)
115,000
Total processing hours
Since auto loans are the most profitable, we will start by using the entire demand of 30,000 auto loans against our 100,000 processing hours.
100,000
total processing hours available
-30,000
hours used for auto loans
70,000
hours remaining for home loans and commercial loans
Our next most profitable product was home loans at $2.80, so let’s apply that product next. The demand for home loans is 18,000 loans and the time for processing is 2.5 hours utilizing 45,000 hours of the constrained resource of processing hours.
70,000
hours remaining after auto loans
-45,000
home loans
25,000
hours remaining for commercial loans
Now we have determined that the best use of the processing hours is 30,000 for auto loans, 45,000 for home loans, and 25,000 for commercial loans. Let’s see how that plays out for calculating the contribution margin by applying the contribution margins we calculated above.
Auto loans (30,000 loans x $3.00 per loan)
$
90,000
Home loans (18,000 loans x $7.00 per loan)
126,000
Commercial loans (12,500 loans x $5.00 per loan)
62,500
Total contribution margin
278,500
Now Home State Bank has found their optimum sales mix for the three loan products.
