Hall, R., N. P. Galambos and M. Karlsson.  1997.  Constraint-based profitability analysis: Stepping beyond the theory of constraints. Journal of Cost Management (July/August): 6-10.

Summary by Dennis Tichio
Master of Accountancy Program
University of South Florida, Fall 2001

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Introduction

Companies have determined the profitability of their products on an aggregate basis. Providing this information in the aggregate allows investors to make reasonable decisions, but provides no useful information for management. Management must determine profitability on an individual product basis.

Activity based management (ABM) has allowed companies to determine the costs associated with individual products. This technique provides useful information to the company.  However, this technique cannot be used alone when the company also experiences constraints. Constraints must be accounted for. Constraint-based profitability analysis (CBPA) is the technique of determining a company’s most profitable product mix with the use of ABM calculations, and constraints or bottlenecks.

What is CBPA?

CBPA is the process of identifying the most profitable product mix across certain capacity constraints, and then implementing a plan to obtain this higher profit at any given time. The first step of CBPA is to compute product profitability for each product in a company using ABM. The ABM profitability per unit will be used to determine the ABM profitability on an hourly basis across the constraint. 

The product with the highest profitability per hour shall be optimized until all of the demand for that product is met.  Next, the second most profitable item will be optimized to meet demands.  This process will continue until the constraint or bottleneck’s capacity is completely used. CBPA is best used to maximize the constraint for certain products, and allowing those products to be used in the future. CBPA is not sufficient for order-based products.

Management must not only rely on the numbers when determining the most profitable product mix.  Management should also consider qualitative factors.  Management may choose to produce a less profitable product for a major customer, or produce products that are new to the market, or early in the product’s life cycle.  Management must also consider the flexibility within a company to change product mix, and whether the company can alter its resource structure.  Management must also consider the market constraints, which will be uncontrollable by the company.

ABM as a component of CBPA

ABM provides valuable information for costing products. ABM is necessary for a successful CBPA analysis. Traditional costing systems favor low volume, highly complex products which are a result of traditional systems allocation of overhead costs. ABM focuses on those costs that are variable with production. ABM can better identify the resources and incremental costs associated with production.

ABM looks at costs on a long-term basis, which is consistent with CBPA. ABM also identifies costs on a more precise basis than just variable and fixed.  ABM identifies those costs that have an effect on production volumes and those costs management can change.  ABM also identifies excess capacity costs, and does not factor them into product costs. This results in more precise costs, and provides useful information to the company regarding these excess costs.

CBPA in practice

A simple example of CBPA can show the product producing the most profit on a per unit basis produces the least profit hourly.  A product with the least per unit profitability may produce the highest hourly profit.

A case study that implemented CBPA showed surprising results.  The case study was done on a steel manufacturer, and there ultimate constraint was machine hours on one particular machine.  First, the company needed to cost their products using ABM.  The product costing results from ABM provided different information regarding per pound profit compared to hourly profit.  Based on the bottleneck, an optimum product mix was developed.

The case also provided information in regards to the industry and customers of the company. Certain factors should be considered when developing an ultimate product mix.  By determining their hourly profits per product, the company was able to gauge their customers’ needs.  The company was able to enter into a contract that required their most profitable product. Determining the costs of some of their less profitable products provided the company with valuable information. The company determined outsourcing the product would be more beneficial to their operations.

The development of CBPA sometimes develops a related constraint based on the new product mix. The company must analyze the new constraint and determine changes that are necessary to increase profits. Again, in this case the company chose to maximize the most profitable product, and to outsource the product they would no longer be able to produce.  

A CBPA analysis becomes more complex as the number of constraints increases. To handle the added constraints, linear programming must be used.  Linear programming mathematically determines the optimal mix of certain variables based upon certain equations. There is a maximum or minimum equation (the objective function), followed by all the equations that identify capacity constraints. Linear programming is then capable of determining the optimal mix of products.

Conclusion

CBPA is a valuable technique for companies trying to maximize profits in light of capacity constraints.  CBPA allows companies to determine the optimal mix of products that will ultimately maximize the bottom line.