Strategic cost analysis helps companies identify, analyze, and use strategically important resources for continuing success and growth of the business

Applying strategic cost analysis concepts to capacity decisions: strategic cost analysis helps companies identify, analyze, and use strategically important resources for continuing success and growth of the business

Paul Juras

EXECUTIVE SUMMARY The product with the highest unit profit may not be the product with the highest profit per unit of resource consumed. The Theory of Constraints (TOC), with its emphasis on throughput costing, offers one possible approach to profitability analysis, but it is focused on the short term. The authors discuss why throughput costing, in combination with ABC, is a better option to guide long-term, strategic decision making.

In the fall of 2005, Ford Motor Company announced a nearly 50% reduction in the number of suppliers it would use in the future. Soon after, Delphi Corp., the largest U.S. automotive parts manufacturer, announced its move into Chapter 11 bankruptcy. In the first quarter of 2006, Dana Corp., another large auto parts manufacturer, also resorted to bankruptcy.

Why were such major players in the automotive industry toppling like bowling pins? These events resulted from the mounting costing pressures on companies in the automotive supply chain. In the auto industry, as in any other highly competitive environment, cost management can be crucial. An organization’s cost information can turn out to be a strength or a weakness, so the value of cost information depends on how it is used. In this article, we discuss ways that companies can use their cost information strategically.


An organization creates a competitive advantage through the use of resources to provide features demanded by customers. The resources consumed to create these attributes are not free, and the effective use of the resources is critical in any competitive environment. The value of a cost management system comes from the way management uses it to support decision making, including decisions about long-term strategy.

Having reliable cost information on the various aspects of their business allows management to make decisions such as whether to charge different prices for different attributes, how much demand various processes place on resources, and which products or services to promote. In effect, the cost system becomes a strategic support system. The primary benefit of a strategic cost system is that it takes a long-term view of the organization. The system can provide valuable insights into the firm’s operations, which can be used to formulate or assess overall business strategies and plans.

The strategic plan should include a clear picture of the organization’s current and future position and offer a map for moving from the current to the future position. Any move an organization makes toward a desired future state requires the effective and efficient use of strategically important resources. A properly designed cost system can help identify and monitor the use of strategic resources.

With this focus in mind, we present a general strategic cost analysis (SCA) approach to managing capacity and apply it to the specific situation faced by Custom Paint Shop (CPS), a fictitious privately held custom painter of automotive components for original equipment manufacturers (OEM) and Tier 1 and Tier 2 suppliers. We introduced our readers to CPS in our article “Cost Management by Customer Choice,” which appeared in the Spring 2005 issue of Management Accounting Quarterly. (1) That article contained a detailed scenario explaining the job complexity caused by the wide variety of coatings the company offered and the company’s lack of a customer strategy. This lack of a strategy led the company to bid on any job that came their way, without regard for the demand that such jobs would put on important resources.

In the 2005 article, CPS needed to develop a customer strategy. A critical element in any customer-related competitive strategy is knowing which services provide a competitive advantage and which provide the most profit. Determining profitability may not be straightforward because profit can be defined in a number of ways. The product with the highest unit profit may not be the product with the highest profit per unit of resource consumed.

Eliyahu M. Goldratt’s Theory of Constraints (TOC) offers one possible approach to profitability analysis. TOC directs management’s attention to the resources that represent production constraints. These scarce resources are known as “bottlenecks.” TOC promotes focusing on the throughput per unit of scarce resource, defined as revenue less material costs. This costing method, known as throughput costing, is focused on the short term.

Activity-based costing (ABC) analysis is a better option to guide long-term decision making. We will show how management can use the activity and cost information obtained from the ABC process to make decisions related to capacity. ABC is not without its own limitations, however. We propose that management combine TOC and ABC information to help make capacity-utilization decisions regarding strategic resources.

With the goal of helping management make informed decisions regarding orders or types of bids they should pursue, CPS assessed the financial profitability of its various product families (applications of a series of paint coatings and finishes). CPS used ABC analysis to identify the impact each product would have on company profits. The conclusion of the analysis was that an activity-based approach to costing provided a better understanding of costs and, therefore, a possibility for improving company profitability.

While our 2005 article showed that product mix drives costs, it did not define any customer strategy. Essentially, CPS was taking a reactive, short-term approach to pricing and cost management.

In an effort to show how companies can proactively develop a customer strategy, we will revisit CPS to look at costing the capacity of one of its strategic resources. We will draw on strategic cost analysis concepts to help companies identify, analyze, and use strategically important resources optimally for continuing success and growth of the business.

CPS is basically a job shop. Raw metal parts are received from the customer, finished with the desired application(s) of paint, and shipped back to the customer. The parts include bumpers, luggage racks, window sashes, tailgates, hoods, and body moldings.


Most customers need their parts to be coated in accordance with OEM paint specifications but lack the expertise, start-up capital, or desire to face the business and financial risks associated with “tooling up” to perform the painting function. CPS, therefore, markets itself as a “headache relief” option.

The immense number of combinations of coatings and colors makes CPS’s jobs complex, however. In addition to the different colors of the paint products, the type of coating applied over the paint also varies. Customers can choose enamel topcoat, high gloss (HG) or low gloss (LG), base coat, clear coat, and whether or not a primer is added at the beginning of the paint process. The complexity is further increased by the variation in the size and shape of the parts to be coated. Thus, four variables–coating, color, shape, and size–determine the mix of activities required and the difficulty of each job.

Figure 1 illustrates the flow of parts through the workplace. Notice that after pretreatment and E-coating (a process by which negatively charged paint in a large vat attaches to the positively charged parts that are dragged through the vat), each part travels through four paint booths–even though all four booths may not be required for every type of part. For example, when parts requiring a low-gloss coating are being painted, the painters (employees) manning booths 3 and 4 are idle, and the spray guns for those booths are turned off.


At the end of the process, the paint coating is cured in an oven. Then, in the unload/load area, each part is date-stamped, unracked onto a monorail floor conveyor line, inspected, unloaded, and packaged. The monorail conveyor line transports the parts through the whole paint process. The conveyor moves at line speeds of between 10 and 18 feet per minute, depending on the complexity of the job. The total paint cycle time is about 2.5 hours, and setup between jobs take five minutes.


The industry dictates the need for quality at nearly a 100% perfection level. The nature of the painting process, however, lends itself to a certain level of defects. Dirt and dust in the manual hand sprayers and CPS’s old equipment add to the defect rate. Some defects can be corrected by finessing, which is a labor-intensive process of buffing out the defects. The finessing process eliminates the need for complete reprocessing. Approximately 5% of all bumpers come out with a defective paint job, but most are saved by finessing.

Historically, CPS accepted most of the work assignments it was offered, but, at one point, demand started to increase significantly, especially for the higher-grade coatings. Such paint jobs were thought to be profitable, but after doing an ABC analysis, management found that some of those jobs were not as profitable as originally thought.

Table 1 shows a dramatic change in profit margins for many different kinds of parts, implying that a change in how CPS determines the cost of the paint jobs may alter the bidding strategy and overall profitability. The profit for each part under the old absorption-costing method was compared to the profit under the new ABC system. The parts with the largest change in profit margin were the low-production-volume parts, meaning that these parts had been assigned a disproportionate level of production costs.

For example, the reported profit of the Darama XJ-G part changed from a 19% loss under the absorption costing method of accounting to 55% profit under the ABC method, and the MT Xrail part went from an 11% loss to a 29% profit. Given this data, management’s logical conclusion was to seek out jobs coating parts with high profit margins.


As competitive pressures mount, companies must become more customer focused. This means finding out what the customer wants and is willing to pay, as well as understanding what it costs to provide the product or service. To help understand costs, CPS has devoted significant resources to developing an effective ABC system. The key is to use the costing system to generate information that will not only help management better understand the costs of different finishes but will also help with strategic decision making.

An ABC analysis draws attention to the cost of production. While this analysis indicates the cost and related profitability of products, the results of the analysis may cause management to move in the wrong direction by trying to attract paint jobs that are profitable at the per unit level but place a high demand on production capacity. The result is that a profitable job that requires a large amount of conveyor time and space can severely limit the potential total profit that can be earned by reducing the available capacity for other paint jobs.

ABC attempts to measure the consumption of the activities known as “cost drivers,” which are part of each paint job’s production process. The capacity of every resource to perform activities is limited, and the demands on the most constrained resource can have strategic implications for an organization. ABC analysis does not explicitly consider that the quantity of resources demanded may not equal the capacity of resources supplied. Management should consider the potential profit from each product’s use of a resource to help promote effectiveness and efficiency to maximize value.

Take the product mix decision as an example. The ABC costing process indicates that bumpers are one of the most profitable parts to coat, so CPS’s management will try to gain more business coating bumpers. The problem is that the size of the bumpers limits the number that can be put on the rails that hold them on the conveyor line. Because there is a limit on the number of rails that can move the parts through the paint process in a given time, the rails and conveyor are a limiting factor, also known as a scarce resource.

Pursuing high-margin products may not be a practical course of action, therefore, because the ABC profit levels do not explicitly consider the demand that the products put on the strategic resources. Through proper analysis and strategic decision making, management can proactively manage the demands on a constraint and help improve their organization’s chances of financial success.

An effective costing system will help identify the products or processes that provide the greatest return within the given production environment. It can also identify the specific areas that the firm should progressively shift resources toward or away from through capital investment and restructuring of the production process. We will focus on exploiting the existing resources within the current operating structure as CPS moves in the intended direction. This is accomplished through the use of strategic cost analysis.


Strategic cost analysis is a process of developing cost information that helps managers make strategic choices with an emphasis on maximizing the use of strategic resources in the future. The SCA process examines the relationships between the cost of providing a product or service and the value delivered. SCA relies on a good understanding of the underlying causes of costs. Undertaking an ABC analysis, as CPS has already done, provides an understanding of causal factors and relationships.

SCA looks at two types of cost drivers–structural and executional. Structural cost drivers relate to the scale, scope, and technology of the production environment. Decisions that create the structural cost drivers pertain to capital equipment investment, hiring of employees of certain skill levels, and pay rates.

Given that CPS has been in business for more than a decade, management has already made decisions on what the production environment (structural cost drivers) looks like. Structural cost drivers can be changed, but only with a fundamental modification in the way the organization chooses to compete. For our discussion, we take the structural drivers as a given for CPS and focus on the second component of a company’s total cost structure–the executional cost drivers. Executional cost drivers relate to the way management utilizes the operating and production resources to provide the attributes customers demand. These cost drivers include such factors as product and process design, quality control, and capacity management (see Figure 2).



Our 2005 article focused on understanding the cost of providing the service by looking at past results. The lack of customer strategy identified in that article meant that CPS may not have been properly matching the customers’ perceived added value of the paint process to the cost of providing the service.

No organization, CPS included, wants to have its resources committed to a path with limited profit potential by simply accepting whatever work comes along and not considering the limits an order may put on potential profits. Some jobs may require the use of a strategic resource that restricts the ability to accept more profitable work requiring the same resource. This is an issue only if there is a resource that lacks sufficient capacity to keep up with demand–also known as a “bottleneck” or “production constraint.” For CPS, the paint line does not sit idle due to a lack of jobs. In fact, the conveyor line is the bottleneck.

The conveyor line is the key strategic resource, so good communication with the customer is needed to manage the products produced on the line. For example, what kinds of concessions are you and the customer willing to make regarding lead times and delivery schedules, which have an impact on managing the resources consumed to make the product? One strategy would be to attract jobs that do not use the bottleneck resource (conveyor), but there are no paint jobs that CPS could perform without using the conveyor.


Drawing on concepts from TOC, efforts should focus on increasing the capacity of a constrained resource, such as reducing the already short setup time (five minutes) or reducing the number of setups needed. Another possibility is to hire temporary workers, but there is already idle labor when some paint jobs are run, so temporary workers will not help solve the problem.

Outsourcing some of the work is not an option because the physical painting is CPS’s value proposition. Outsourcing to another paint vendor would simply support a direct competitor. If we accept that CPS has reached its capacity limit, the objective is to optimize the use of the constrained conveyor resource by maximizing the profit generated by the paint jobs that demand some of the resource’s capacity.

As mentioned earlier, four factors–shape, size, coatings, and color–determine job complexity, and job complexity drives up the demand for line capacity. Large parts, for example, take up more space on racks, meaning that more racks are needed and that fewer parts can be painted simultaneously. The shape of a part determines loading and unloading times.

The size of the parts on a rack affects the number of parts that can fit on the rack and on the conveyor belt. A bumper, for example, is easier to paint than a luggage rack because there is more uniform surface area and because the bumper takes up less square footage on the conveyor line. Some colors are easier to work with than others, which impacts line speed, which impacts capacity demanded. Also, the parts with the LG finish have fewer defects than the parts with the HG finish, meaning that LG parts have a higher first-pass yield rate. A company can optimize profits by marketing certain finishes more proactively or by only accepting customers that request coating for a limited number of parts–but profitability must still be determined in advance.


As mentioned previously, TOC promotes focusing on the throughput per unit of scarce resource. This approach to managing a constrained resource uses a short-term, day-to-day view to develop a long-term customer strategy. As noted earlier, the production environment (structural cost drivers) of CPS is not expected to change in the short term, and the goal is to create a customer strategy to satisfy customer needs given the production environment that management has put into place.

While throughput costing may seem to be the obvious approach to use, it ignores the cost of capacity utilization that must be covered over the long term. The use of throughput costing to make all bidding and customer-related decisions would result in a continuous series of decisions made with a strictly short-term, day-to-day emphasis. No organization can survive in the long run if it continually ignores the costs of production other than material costs.

ABC is an alternative costing approach that does factor in the cost of all resources consumed during production. Although it offers a rational assignment of costs, ABC mixes fixed and variable costs in the assignment, which can lead to decisions that are not optimal. Figure 3 helps illustrate this point.


In the figure, a particular cost actually behaves in a step function, meaning that additional costs are incurred in lump sum amounts as certain driver activity levels are reached. Each step represents an additional investment in capacity to handle the added demand for activity. The main issue is the selection of the denominator in the formula (total cost/unit activity) used to calculate the fixed cost per unit. Some argue that practical capacity of the resources rather than actual demand on the resources should be used in the denominator.

The advantage of using practical capacity is that the ABC cost per cost driver unit remains constant irrespective of the actual or estimated demand placed on a resource by other products. Keep in mind, however, that operating at practical capacity may mean some qualitative factors of production or customer service may suffer, as described by Gilbert Y. Yang, former CFO of UFO Group, Ltd., and Roger C. Wu, former controller of Diamond Entertainment. (2) In their article, Yang and Wu note that a customer’s wait time before a call center operator answers a phone is an element of customer service that is strategically important. Although, from a practical capacity point of view, a phone can be constantly in use 24 hours a day, they recommend planning to have more phones in use in order to reduce the amount of time a customer must spend on hold.

We condone following this recommendation and suggest using strategic capacity, which is usually less than practical capacity, in the denominator. As Figure 3 shows, the use of strategic capacity in the denominator raises the cost per driver unit because strategic capacity is less than practical capacity. The use of strategic capacity also reduces the cost assigned to excess capacity, which is the distance between the sloped cost-per-unit line and the step representing the cost of capacity acquired.

Management should attempt to price a product as if the company were operating at the strategic capacity level. It is then up to the management team to find ways to actually operate at that capacity level through various strategic decisions. Management also must remember that a reduction in fixed resource demand does not translate into more profit for the organization unless the now idle capacity is either eliminated or redeployed.

As noted previously, the simple profit information that the ABC process generates is not enough, but it is still relevant. The ABC information has already served two purposes: directing management’s attention to the varying demand that products place on various resources and providing a refined calculation of the profit that each paint job generates.

We propose combining the TOC and ABC information into a format similar to the template in Figure 4. The calculation contained in the figure shows that the costs of capacity used to produce or support a product can be explicitly considered. Regardless of the costing method used, the information must be utilized in order to make strategic decisions.


We will now focus on the profit analysis of a single type of paint job and use the ABC and capacity demand information to help direct management’s attention toward appropriate long-term actions. The emphasis will be on dealing with a part of a certain size and how to best manage operations and pricing decisions for that type of part.

To illustrate, we will now present information for two hypothetical bumpers, one requiring a low-gloss coating and the other a high-gloss coating. As Table 2 shows, high-gloss and low-gloss finishes have different requirements.

The HG finishes have higher reject rates and require additional painters, more colors, more inspections and maintenance costs, and slower line speed. Also, the HG products are treated as they pass through stations 3 and 4, but products requiring LG finishes simply pass through those booths untreated. As some of the costs related to the resource capacity of booths 3 and 4 are fixed costs, throughput costing does not capture the additional cost of capacity demanded.

Table 3 presents a method for factoring the various elements into the demand for conveyor capacity. Continuing to use bumpers as an example, consider the quality issue. The greater the percentage of defects in a finish, the lower the yield rate (YR) for a production run. The yield rate refers to the number of parts that have gone through the coating process without any defects. More complex shapes and finishes have lower yield rates than less complex shapes and finishes. In the following example, the LG bumper will have a higher YR than the HG bumper.

As noted earlier, defective products can be recovered through in-house finessing. The recovery rate (RR) runs at about 5% for bumpers, which means that about 5% of all bumpers painted are recovered through the finesse process, which, when added to the first pass yield rate (YR) yields a value less than or equal to 100%. Because the recovered bumpers are brought up to an acceptable quality level, they contribute toward meeting customer demand and put no further demand on the conveyor capacity.

The YR and RR can be combined to determine how many parts must be processed on the conveyor to generate one unit of acceptable quality. We call this concept the “run factor” (RF). The computation to determine the run factor is 1/(YR+RR). If the yield rate plus the recovery rate equals an RF of 1, then only one unit must be put on the conveyor to yield one unit of acceptable quality. The RF for an LG bumper is lower than the RF for an HG bumper.

The next production factor relates to line speed. Line speed can vary from 10 to 18 feet per minute, depending upon the size, shape, and required coating of the product, all of which are elements affecting the complexity of the painting process. As these three elements can be combined in a number of ways, we attempt to capture the various combinations in the form of a complexity factor (CF). We consider 18 minutes to be the standard time unit for the conveyor line. A complexity factor ranging between 1 (for fastest line speed) and 1.8 (for slowest speed) can be determined for each group of parts and included in the calculation of demand.

The CF is computed by dividing the standard line speed of 18 feet per minute by the line speed required for the specific product, so a faster line speed results in a lower CF. When the CF is multiplied by the RF, the result is a total demand factor (DF). This demand factor helps managers recognize the relative demand that each paint job puts on the capacity of the paint conveyor. In the initial comparison shown in Table 3, the line speeds for the LG and HG bumpers differ. The line speed of 12 feet per minute for the HG bumper is slower than the 15 feet per minute for the LG bumper because of the complexity of applying an HG finish.


Parts can vary in shape and size, so we needed a standard unit of measure to compare the total demand that each part places on the conveyor. Because it is the surface area of each part that is coated, square footage of each part is a logical measurement unit. As a result, the DF described above is actually a demand placed on the conveyor per unit of finished good of a particular part type, such as bumpers or luggage racks.

When the DF is divided by the total square footage of a particular part (e.g., a bumper), the end result is a demand factor per square foot of a particular size, shape, and finish, which we call the bottleneck demand factor (BDF). The ABC profit level per square foot can now be divided by the BDF to yield the profit per throughput unit (PTU) on the conveyor line.

The initial product comparison in Table 3 shows that while the profit per throughput unit of finished good is higher for the HG bumper, the PTU on the LG bumper is higher, so these bumpers should be targeted for increased sales. Keeping in mind that demand for certain types of coatings varies and that there is insufficient demand for any one product to fully utilize the line, planning profitability now depends on the mix of products and their respective PTUs. The approach we suggest gives management valuable information to help them decide which coatings to promote.

In our examples, we have focused only on demand for the conveyor line capacity. TOC tells us that it is possible to expand the capacity of a bottleneck to the point where the limiting constraint moves to a different resource. The ABC information can be combined with the capacity information for various resources to obtain a company-wide analysis of the cost of resources demanded. Given that there may be more than one capacity constraint, a linear programming model could possibly be developed to help identify ways to maximize the total profit.

The Solver function in Excel is a tool that can handle the computations of a linear programming model. (3)


Turning back to the hypothetical HG bumper, the current PTU is $7.76. If management sees or promotes a shift in customer demand toward this type of part, they should turn their attention to trying to improve the PTU. Table 3 provides the results of several types of actions management may take. We now consider each in turn.

In the first scenario, we look at increasing the yield and then at increasing the recovery rate. If changes can be made to the processes on the conveyor line to increase the YR from 92% to 93%, the RF and DF decrease. The decrease translates into an increase in the PTU of $0.08. If, instead, the recovery process is modified to increase the RR from the current 5% level to 6% and the conveyor line speed is unchanged, the end result is the same $0.08 increase in the PTU. Given these results, management would be advised to pursue the option that is least costly to implement.

It should be noted that the finesse process is labor intensive but requires very little in the way of materials. The Finesse department has excess capacity and is not a bottleneck resource. Throughput costing would only consider the minor incremental cost of materials used in the finesse process and would show little difference in the total profitability of the two options described in the previous paragraph. ABC, on the other hand, would show a much bigger difference between these options.

In the second scenario, the focus is on increasing line speed while holding the other factors constant. Again, changes would have to be made to the painting process to increase the line speed, but increasing the line speed to 13 feet per minute results in about an 8% increase in the PTU. Management then would have to decide if the necessary changes to attain the increase in the conveyor line speed are cost effective.

In the third scenario, the speed, YR, and RR are held constant, and the profit per unit of finished product is changed. Such a change may come from using the ABC information to identify ways to decrease resource consumption costs for the process and/or to look at increasing the price of the coating.

Management does not have to consider one change at a time, and trade-offs could be factored into an analysis. For example, increased speed may increase the defect rate (lower the YR), but there could be a coordinated effort to simultaneously increase the RR of defective units.

The fourth scenario shows that an increase in conveyor line speed to 13 feet per minute with a corresponding decrease in the YR to 88% actually increases the PTU. Management could prepare a matrix like the one in Table 4 to summarize the impact of various options and compare the benefits to the costs that would need to be incurred to bring about the change.

The resources of all organizations have limited productive capacity. An organization’s cost management systems should help guide management in making decisions on how to best use these limited resources strategically. In this article, we have attempted to illustrate the advantage of combining the constraint-focused view of throughput costing with the ABC approach of assigning resource costs to give management a more effective cost management tool.


(1) Eileen Peacock, “Cost Management by Customer Choice,” Management Accounting Quarterly, Spring 2005, pp. 28-36.

(2) Gilbert Y. Yang and Roger C. Wu, “Strategic Costing & ABC,” Management Accounting, May 1993, pp. 33-37.

(3) For more information on using Sover, see Sidney J. Baxendale, Mahesh Gupta, and P.S. Raju, “Profit Enhancement Using an ABC Model,” Management Accounting Quarterly, Winter 2005, pp. 11-21.

Paul Juras, Ph.D., CMA, CPA, is an associate professor at Wake Forest University. He can be reached at (336) 758-4836 or

Eileen Peacock, Ph.D., CMA, CPA, is a professor and dean at University of Massachusetts, Dartmouth. She can be reached at


Table 1: A Comparison of Profit Margins: ABC and Absorption

Costing Systems

Profit under

Percent Profit Absorption

Product Family of Sales under ABC Costing

XY Hitchplate–G 0% -282% NA

XY QM150–G 0% 1% -1%

XYZ Metal GMT600, 2 pass–A 0% 14% NA

Data–A 0% 0% NA

Deli–G 0% -34% -29%

Other 0% -24% NA

NAO–G 0% 51% 33%

Samples 0% NA NA

XY UN150–G 1% 8% -14%

XY Service, Var 1% 38% NA

XYZ PN150–A 1% 4% 23%

Horne–A/G 1% 8% 19%

Dango–G 1% 40% NA

Darama XJ–G 2% 55% -19%

Window Sash–G 2% 16% 34%

MT Xrail–A 2% 29% -11%

MT Srail–A 2% 29% -11%

TMG 425–A 4% -29% -53%

Q3–A/G 4% 32% -7%

Data–G 4% 11% 9%

Dango–A 5% 17% 22%

XY QM 96, P131, UN93–G 7% 10% 16%

XY QM150–A 8% 5% 12%

Darama XJ–A 17% 25% -2%

XY QM 96–A 17% 9% 29%

XY UN150–A 20% 32% 46%

Total 100%

0% indicates less than 1%

Table 2: The Effect of High-Gloss and Low-Gloss Finishes

on Certain Variables

Rejection Number Batch

Rate of Colors Size

High Gloss Increases More required Smaller required

Low Gloss Decreases Fewer required Larger required

Number Line

of Painters Inspections Speed

High Gloss More required More required Slower

Low Gloss Fewer required Fewer required Faster

Table 3: Using Capacity Demand to Rank Profitability

Run Factor

Yield Recovery = 1 / Complexity

Product Rate Rate (YR + RR) Speed Factor



Bumper-LG 95% 5% 1.000 15 1.20

Bumper-HG 92% 5% 1.031 12 1.50


Bumper-HG 92% 5% 1.031 12 1.50

Increase YR 93% 5% 1.020 12 1.50

Increase RR 92% 6% 1.020 12 1.50


Bumper-HG 92% 5% 1.031 12 1.50

Increase speed 92% 5% 1.031 13 1.38


Bumper-HG 92% 5% 1.031 12 1.50

Increase profit 92% 5% 1.031 12 1.50


Bumper-HG 92% 5% 1.031 12 1.50

Change speed 88% 5% 1.075 13 1.38

and YR

Square Demand

Demand Feet Per Per Square

Factor Unit of Foot

Product = (RF 5 CF) Product = (DF / Sq. Ft.)



Bumper-LG 1.20 10 0.120

Bumper-HG 1.55 10 0.155


Bumper-HG 1.55 10 0.150

Increase YR 1.53 10 0.150

Increase RR 1.53 10 0.150


Bumper-HG 1.55 10 0.150

Increase speed 1.43 10 0.140


Bumper-HG 1.55 10 0.150

Increase profit 1.55 10 0.150


Bumper-HG 1.55 10 0.150

Change speed 1.49 10 0.150

and YR

Profit Per

Unit of



Product (In dollars) PTU *



Bumper-LG 10.00 8.33

Bumper-HG 12.00 7.76


Bumper-HG 12.00 7.76

Increase YR 12.00 7.84

Increase RR 12.00 7.84


Bumper-HG 12.00 7.76

Increase speed 12.00 8.41


Bumper-HG 12.00 7.76

Increase profit 12.60 8.15


Bumper-HG 12.00 7.76

Change speed 12.00 8.06

and YR

* Adjusted Product Profit Per Throughput Unit Profit Per Sq. Ft./BDF)

Bottleneck Demand Per Square Foot (BDF), Complexity Factor (CF),

Demand Factor (DF), Profit Per Throughput Unit (PTU), Recovery Rate

(RR), Run Factor (RF), Square Feet (Sq. Ft.), Yield Rate (YR).

Table 4: Summary of Effects of Production Changes on PTU

Change in Change

Change in YR Change in RR Line Speed ABC Profit to PTU

Increase to 76% Up .01

Increase to 6% Up .01

Increase to 13 Up .10

Increase Up .05

to $24

Decrease to 70% Increase to 13 Up .02

Figure 4: A Template for

Combining TOC and ABC

Costing Information

Product A Product B


– Materials

= Throughput

x Volume

= Total Throughput

– ABC costs

= Product margin

COPYRIGHT 2006 Institute of Management Accountants

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