Mobile Edition
Print
Get the Mag
Weekly UpdatesEXECUTIVE SUMMARY
Identify opportunities for improvement by graphically analyzing the relative profitability of various segments of your business, The side-by-side comparison makes it easier to identify the most attractive areas for improvement, And the spreadsheet used to illustrate the analysis contains macros that make it possible to reflect what-if alternatives quickly.
**********
Companies continually try to improve their financial performance. Often, this takes the form of reviewing the relative contribution of product families, customer groups, market segments, or geographic areas. While the absolute contribution of each element of the business is important, more often the analysis involves a comparison of the relative contribution of each member of the group (i.e. the relative profit contribution of each product as compared with other products).
This analysis usually involves a first step of taking a macro view of the area to study, such as products or families of products. This first pass often identifies possibilities for improvement. Analyzing each possibility more closely helps to determine its true profit improvement potential. While there is no quick and easy answer to this type of analysis, some tools make the analysis faster and more systematic.
Analyzing the relative profit contribution for each product line or line of service is common practice among many companies. It is not always possible to allocate enough resources to make improvements in every product line; therefore, a practical approach is to allocate those resources in the areas of greatest need or opportunity. This article proposes a way to identify those areas of need or opportunity quickly.
One of the authors used the approach described below when he was the chief industrial engineer with a New York Stock Exchange electronics company He provided the comparative graphs to the vice president of manufacturing, who used this information in his review of annual plans with the division managers. While the example is for product line analysis, the same approach applies to an analysis of customer groups, market segments, or some other grouping. Figure 1 shows how the cost categories could change for different types of businesses. The number of cost elements could increase; however, too many will make the stacked bar graph more difficult to interpret.
Current situation
Figure 2 is a graphical representation of a company's current product line. There are five product families--A, B, C, D, and E. This analysis is not limited to products; the columns could be market segments of customer types or some other classification for which the results are available. The top section shows the dollar amounts of sales, costs--direct materials, direct labor, variable overhead, and fixed overhead--and gross profit. Subtracting selling, general, and administrative expenses (SG&A) from the gross profit yields net income before taxes (NIBT).
[FIGURE 2 OMITTED]
The middle portion of the spreadsheet converts the dollars to a percentage of the sales dollar for the same categories. The conditional formatting feature of the spreadsheet highlights those ceils that are above (worse) or below (better) than limits prescribed for cost elements.
The bottom portion graphically represents the percentages for each product. The horizontal axis shows sales volume as the width of the column for each product. The vertical axis shows each cost element as a percentage of the selling price, so that each column represents 100 percent of the sales price. The area within each bar is an indication of the total dollar value assigned to each cost or profit category
Vertical review
By looking at Figure 2, it is possible to observe the relative contribution of each product. Product A makes an NIBT of 20 percent, or $10,000 on sales of $50,000. The mix of cost elements looks similar to those shown in the Total column at the right of the diagram, so product A appears to be about as close to average as any of the products. Product B has a smaller NIBT than A, higher direct labor, and overhead costs, so perhaps it's an area of opportunity Product C has a large sales volume but shows a negative NIBT. The problem area appears to be the direct materials costs, which are 60 percent of the selling price. The direct labor and overhead costs appear to be in line, so the opportunity is in doing something about the direct materials costs. Product D is a real winner, at least for the present time. It contributes the highest NIBT of any product (in total dollars) as represented by the large area. Product E is a problem: It has a negative NIBT, a loss. The direct material costs are in line, but the direct labor and overhead costs are high (although in line relative to one another). Perhaps the opportunity is to increase the sales volume without increasing the cost dollars proportionally
As a result of this analysis, two actions appear to hold the greatest potential for improvement: Reduce the direct materials cost for product C and increase the sales volume for product E. If, after further analysis, neither is feasible, the company may consider discontinuing these product lines.
Horizontal review
Another way to look at the information is by cost element. This can be done by observing the values in Figure 1. However, it may be more meaningful to rearrange the data to see each cost and income element in a display that shows a side-by-side comparison of products. Figure 3 further displays this information.
[FIGURE 3 OMITTED]
Direct materials: Figure 3 shows the products arranged with the percentage of direct materials on the left. A look at direct materials confirms that product C, at 60 percent of the sales dollar, is out of line, at least compared with the other products. What may not be so obvious at first glance is that product D looks very good on direct materials at 30 percent of the sales dollar. How was this achieved? Is that level available with other products? If so, how? Further study is required.
Direct labor: Figure 3 also shows the products arranged with the percentage of direct labor. Direct labor has variations also. Again, products C and E look high. It may be helpful to look at the age of the products. Is it the process design for C? Is it the early stages of the product life cycle for E? Again, further study may be required, but at least there is a direction in which to pursue the analysis. Product B is more elusive. Direct labor costs may be high but so are variable and fixed overhead. Does a competitive market limit the selling price? Is there a need to redesign this product to improve quality and sell at a higher price or should we redesign to lower the cost?
Variable overhead: Following along to the right, Figure 3 shows the products arranged with the percentage of variable overhead. Product E has a high percentage of variable overhead costs, perhaps because it may be a new product. Product C has a low percentage. However, this could be because not enough indirect resources, such as engineering or automation, are being applied. Analyzing overhead costs requires a deeper look at the overhead components, such as with an activity-based cost approach.
Fixed overhead: Figure 3 continues, showing the products arranged with the percentage of fixed overhead. It is difficult to draw definite conclusions by looking at fixed overhead as a percentage of the sales dollar. Product C has low overhead costs as a percentage of the sales dollar. Is this good or a possible cause of the direct materials and direct labor problem? Should we add some engineering or purchasing resources to see what they can do about the direct costs? Can we reduce direct costs by adding some indirect costs? It is worth a closer look. The problem with Product E may be the need for further marketing effort to gain the added sales volume. Often, the marketing costs do not show as part of the product costs. Perhaps they should, so the resource allocation for all functional areas is visible.
Gross profit: In Figure 3, the products display a variety of gross profit percentages. Although products D and A may be acceptable, B, C, and E require attention.
SG&A expenses: Figure 3 also shows the products arranged with the percentage of SG&A expenses. Product E is highest; however, this is probably the result of its low sales volume, perhaps the result of startup efforts to generate higher sales. While product B and C have low SG&A expenses, this may result from a lack of resource support.
NIBT: Figure 3 concludes on the right with a comparison of NIBT for each product. Product A is the highest and product E is the lowest. Figure 3 shows that while product D has only the second highest percentage of NIBT, its sales volume makes it the highest dollar contributor of income. Its $30,000 of NIBT is 64 percent of the total income for all products.
Proposed changes
As a result of the analysis, it may be possible to develop some changes in the forecast. Suppose it is possible to make the following improvements. What will be the effect on the product profiles?
* Make an engineering change to substitute a lower-cost material in product C. This change will reduce the material costs by 25 percent, or $30,000 for the same level of sales, and will cost an additional $5,000 in fixed overhead to make the change. Figure 4 shows the effect of this change. While the percentage of direct materials for C is still the highest of all products, the product now shows a gross profit percentage of 13 percent. At its relatively high sales volume, it now has the second highest dollar volume ($25,000) of gross profit.
[FIGURE 4 OMITTED]
* The sales department acquires a second major customer for product E, doubling its sales. The direct materials, direct labor, and variable overhead remain at the same percentages of the sales dollar. However, the SG&A expenses increase by $5,000. Figure 4 shows the effect. With this change, product E now shows an NIBT of zero. While it is still marginal, it may have even greater potential for improved earnings.
FEED