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Profit driver management: when you review all the factors involved in creating and selling a product, you plan a better operation. Make sure you're seeing the whole picture.

Business leaders are compelled to intensify their efforts to reach profitability targets by ever increasing market pressure. Identifying new opportunities to bolster financial results is critical in this process. Guesstimating profits is no longer acceptable--profit management has to be precise, and organizations need a way of identifying their profit drivers.

Managing real growth entails reducing costs while boosting sales volume, rather than managing sales growth and cost reduction independently. The focus has to be on understanding how profit drivers affect profits--in other words, understanding how businesses make profits.

But defining profit drivers can be a challenge. Below, we explain what they are and how they interact to generate profits for a business.

The four profit drivers

Businesses of all types are subject to production and distribution capacity limits for each of their product families. These limitations affect the flow of products the company is capable of producing and selling. The primary profit factor is therefore the organization's capacity to produce and sell each product family. That's what generates the sales dollars.

However, a product family is a production and not a sales-related concept. A company's capacity is therefore measured according to the similarity in production processes or paths for the different product families. The potential of each of these production paths is what determines a company's capacity.

For instance, figure 1 shows the manufacturing speeds of five product families in one plant. From this, it would appear that D is the weakest product line.

Manufacturing speed is only one consideration, however. The second is average selling price per product family. This gives a snapshot of the market from the company's perspective. Identifying the average selling price per product family helps determine the company's actual revenues per production stream.

The third consideration is average material costs (per product family), which are incurred directly through the production of the products. They would include all materials used to create a product.

Figure 2 illustrates these last two considerations per product family, as well as the resulting unit contributions. According to these criteria, to maximize profits, the company should promote the sale of D-A-E-B-C, in that order. The combination of these two profit drivers measures the organization's capacity to interact with its markets through the sale of its products and the purchase of raw materials, but doesn't take into consideration its capacity to manufacture the products.

Figure 3 shows the effect of manufacturing speed on unit contributions. Combining unit contributions with manufacturing speed leads to another criterion--dollars per hour, as described by the theory of constraints. The order in which the organization should prioritize product sales therefore becomes E-A-B-C-D. Surprisingly, the D product family, which initially appeared to be the most profitable, falls into last place on the list.

The fourth profit driver is operating expenses, which involves assessing all the costs a company incurs independent of its production activities--specifically, the sum of direct labour costs, indirect labour costs and overhead expenses (production, sales, etc.).

Some might maintain that direct labour costs are proportional to the company's level of activity. However, although direct labour costs may vary, they tend to stay fairly stable. Today's increasingly automated companies don't want to lose their knowledge base, which continues to require significant investments in training. Moreover, the proportion of direct labour in the operating expenses equation has been on the decline, since it has been optimized in recent years. An evaluation of daily operating expenses clearly indicates that operating expenses are relatively stable and are independent of the company's production activities.

The operating costs in our example amount to about $28,000 per day, or $7 million per annum over the past three years.

A clearer picture

The four profit drivers above interact and represent a partial explanation of what profit is. As described by the theory of constraints, the dollar per hour component is used to classify product families according to the company's capacity to absorb its operating expenses. It's therefore possible to determine which product family contributes the most to the absorption of operating expenses. The company can then use this information combined with market demand to identify sales strategies consistent with its strengths and market demand.

There are, however, three other profit drivers that have an equally significant impact on a company's profits. They are work in progress (WIP) change, other revenues and amortization.

WIP change represents the variation in the work in progress and finished goods inventory from one period to the next, a variation that can serve to either over-estimate or under-estimate a company's profits. When the value of WIP change increases, profits are over-estimated by the same amount, and vice-versa. This is a significant issue because it can conceal the profitability of an operation if, for example, the value of the inventories decreases.

Other revenues aren't directly related to product sales, but represent a source of revenues in addition to sales. These revenues contribute to the absorption of operating expenses without being classified in terms of dollars per hour. They include the sale of spare parts, service fees and similar items.

Amortization is the final driver--one that can conceal a company's true cash flow performance. It's therefore essential to identify its impact on profits.

Figure 4 shows the results of a simulation that reconciles net profit before income taxes and cash flow with the profit drivers. This exercise details financial performance and explains the source of company profits. And various scenarios may be simulated to determine how a company interacts with its markets to generate profits. The simulation provides answers to the following questions:

* What is the net profit based on a real or estimated sales mix?

* How can available production capacity be used to maximize net profits?

* What is the best strategy (low selling price--high volume versus high selling price--low sales volume) for each product to maximize its contribution to profits?

* What should the company's strategic plan be to ensure the best fit between the company and its markets?

* How should the efforts made by the company's various sectors (sales, marketing, production) be oriented?

Profit management is clearly not a random process, but the result of specific actions on the company's profit drivers. When they are tightly managed within clearly specified boundaries, a company's decision makers are more likely to meet the profitability targets set by investors.
Figure 1 - Manufacturing speed

Families Manufacturing speeds (flow)

 A 2000 units / hour

 B 2700 units / hour

 C 2700 units / hour

 D 420 units / hour

 E 3 000 units / hour

Figure 2 - Price and cost considerations

Families Selling price Material cost Unitary contribution

 D $2.75 $0.95 $1.80

 A $1.99 $0.45 $1.54

 E $2.35 $0.75 $1.60

 B $1.50 $0.59 $0.91

 C $1.65 $0.85 $0.80

Figure 3 - Speed and unit contributions

Families Selling Material Unitary Manufacturing Hourly
 price cost Contribution speed contribution
 $ $ $ Units / hr $ / hour

 E $2.35 $0.75 $1.60 3 000 4 800

 A $1.99 $0.45 $1.54 2 000 3 080

 B $1.50 $0.59 $0.91 2 700 2 457

 C $1.65 $0.85 $0.80 2 700 2 160

 D $2.75 $0.95 $1.80 420 756

Figure 4 - Considering three additional profit drivers

SIMULATION Family E Family A Family B

Sales (units) 1 500 000 1 250 000 500 000

% Utilization A-B-C-D 5 400 000 5 400 000

% Utilization A 4 000 000

% Utilization D

% Utilization E 6 000 000

Sales ($) 3 525 000 2 487 500 750 000

MTL costs (1 125 000) (562 500) (295 000)

Contribution (spread) 2 400 000 1 925 000 455 000

$ / hour 4 800 $/hr 4 158 $/hr 2 457 $/hr

Sub-contract costs 0 (75 000) 0

Other revenues 100 000 0 175 000

TOTAL CONTRIBUTIONS 2 500 000 1 850 000 630 000

Op. expenses (28 000 * 250 jours)

Profit << Cash flow >>

<< WIP Change >>

Profit after << WIP >>


Accounting Profit


Sales (units) 1 750 000 200 000

% Utilization A-B-C-D 5 400 000 5 400 000 68.5%

% Utilization A 31.2%

% Utilization D 840 000 23.8%

% Utilization E 25.0%

Sales ($) 2 887 500 550 000 10 200 000

MTL costs (1 487 500) (190 000) (3 660 000)

Contribution (spread) 1 400 000 360 000 6 540 000

$ / hour 2 160 $/hr 756 $/hr

Sub-contract costs (55 000) 0 (130 000)

Other revenues 35 000 0 310 000

TOTAL CONTRIBUTIONS 1 380 000 360 000 6 720 000

Op. expenses (28 000 * 250 jours) 7 000 000

Profit << Cash flow >> (280 000)

<< WIP Change >> 675 000

Profit after << WIP >> 395 000

Amortization 150 000

Accounting Profit 245 000

Available production capacity to promote high $ / hour families
Non profitable operation while the accounting profit shows a different

Jean-Francois Fontaine, P.Eng., M.A.Sc., ( is with Creative Cognitive Consulting Promoting Optimization (C3PO) Inc.
COPYRIGHT 2004 Society of Management Accountants of Canada
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2004 Gale, Cengage Learning. All rights reserved.

Article Details
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Title Annotation:Business Strategies
Author:Fontaine, Jean-Francois
Publication:CMA Management
Geographic Code:1CANA
Date:May 1, 2004
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