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Profit-Per-Minute: The Missing KPI to Business Performance Management Success

Business performance management (BPM) initiatives all ultimately target the same goal - generate optimal corporate financial performance, or, simply put, increase profits. To increase profitability, organizations either cut costs or increase revenue by introducing new products or expanding sales and marketing efforts. But according to recent research, performance is quickly becoming the number-one concern for business leaders as they strive to improve results and increase the value of their businesses. In other words, companies are looking for ways to become more effective by making more strategic choices with existing assets.

From a shareholder perspective, this focus on effectiveness targets return on assets (ROA) - the critical profitability KPI for asset-intensive manufacturers. It represents the profit obtained over the course of a year for the company's asset base, which can represent investments of hundreds of millions or even billions of dollars. ROA is a major driver of stock price and reflects the performance of the executive management team. However, many manufacturers do not achieve optimal ROA results. Why is this? The answer lies in the mismatch between the corporate KPI of profitability (ROA) and the one that is used at an operational level (margin) to make everyday decisions related to products, customers, assets and pricing. For a manufacturer with $1 billion in revenue, using an operational KPI which is directly analogous to ROA can add $30 to $50 million to the bottom line.

Maximizing the Margin KPI Does Not Maximize ROA

Often expressed as a percentage (e.g., $100 million profit for an asset base of $1 billion is an ROA of 10 percent), ROA is essentially a measure of profit over time, typically a year or quarter. It is a measure of how fast that profit is made.

Given that overall end-of-year profit is a summation of the profit made by all individual products, it would seem logical, because ROA is time-based, to consider how fast these individual products are made. The profit generated in a year by a single product is not just a function of its margin per unit, but also of the number made over the course of the year. However, most companies have focused on maximizing only margins of individual products. They increase prices as much as the market will bear and attempt to reduce costs. Accounting systems have evolved to be able to manage margins in detail.

Many manufacturers have long known that production speeds are an important contributor to profitability. However, they have found the challenge of incorporating production run-rate data with margin information insurmountable. As such, they have had to settle for using margin alone as the KPI for day-to-day decisions aimed at maximizing profits and ROA.

Consider Product A, which has a margin per unit of $100, and Product B, which has one of $80. On a margin-only basis, A is obviously more profitable than B. What if we can make only 1,000 units of A in a year but 1,500 units of B? At the end of the year, Product A will have generated a profit of $100,000 ($100 profit x 1,000 units per year) while Product B will produce profit of $120,000 ($80 profit x 1,500 units per year). When the production speed, or product velocity, is taken into consideration, Product B is more profitable over the course of the year. For a given asset base, Product B will generate a higher ROA than Product A.

Figure 1: Profitability with Margin and Velocity Considered

This example makes a very profound point. If companies focus efforts on higher margin products, they will not necessarily maximize ROA, the metric we consider the critical KPI for effectiveness-focused profitability. For example, they may focus marketing efforts on high-margin products when in reality these should be directed toward lower margin products that generate more profit per year due to faster production speeds. There is a mismatch between the shareholder and operational KPIs for profitability.

A New KPI to Link Strategy and Execution

The two-product example above would obviously be very easy for a company to handle, but the situation for a manufacturer who produces hundreds or thousands of products for hundreds of customers in multiple plants with multiple production lines is a completely different story. As stated earlier, the problem has been too complex to deal with. However, successfully combining margin per unit and production velocity information creates a new KPI called profit-per-minute. Knowing profit per minute at a granular level - by product, customer, market, region, plant and production line - enables decision-making that will optimize profits and ROA. Profit-per-minute is time-based, just as ROA is, and so we now have an operational KPI that is directly analogous to ROA. Furthermore, profit-per-minute aligns sales, marketing, production and finance with a common metric, obviating the debates of "this one has a higher margin versus this one runs faster through the plant."

Let us now consider some examples of how the profit-per-minute approach can lead to different operational decisions than would be taken with a margin-only approach. The graph below shows margin on the vertical axis and units per minute on the horizontal axis. The contour lines represent constant levels of cash or profit per minute. Since, as we discussed, ROA is also a profit-over-time measure, profit-per-minute is analogous to ROA. It is really ROA at the product level. For a given amount of assets, profit per minute will represent a specific ROA.

Figure 2: The two-dimensional view produced by combining margin and production speed gives a vastly different picture than the margin-only view.

Looking at the products shown, the margin-only view would favor targeting sales and marketing efforts on Product A rather than on Product B due to its higher margin. However, using the profit-per-minute approach, Product B is more profitable in this example, matching the 11 percent target overall ROA for the company. Despite its higher margin, Product A generates profits at a slower rate, at only a 5 percent ROA level.

Rather than throwing sales and marketing dollars at Product A, what if those dollars were invested in Product B, which is far more profitable for the company?

Consider another possible scenario for these two products. What if production efforts were being considered to increase the productivity of Product B? One can see from the graph that it would take a rather large increase in productivity for B to increase its profit-per-minute or ROA significantly. It might make much more sense to direct these productivity improvement resources toward Product A where only a small productivity increase is required to dramatically improve ROA.

Similarly, a price (and margin) increase in Product A would have to be large in order to substantially increase profit-per-minute and ROA. However, a slight increase in price for Product B would generate significant profit-per-minute and ROA improvements.

While some of these potential changes are obviously dependent on various factors, including state of the market, the competitive situation, product similarities and company internal factors, they might not have even been considered when margin alone was used to gauge profitability. Using the profit-per-minute KPI opens up previously unseen options that can provide attractive profitability improvements.

Consider a rather dramatic example. Based on margin alone, Product B could even be a candidate for being killed off or outsourced. From the profit-per-minute point of view, this would be a very damaging decision.

Going Beyond Historical Analysis: Using What-if Modeling to Make Strategic Changes

If Products A and B were similar, a possible scenario would be to increase the price for Product A, thereby reducing demand for it, and simultaneously dropping the price slightly for Product B and increasing its demand. Manufacturing capacity could be saved on Product A and used on B to generate greater profits for the company. The impact on profitability can be determined by modeling such a change.

Consider the data shown in Figure 3. This easily generated, but powerful topographical map constitutes a very powerful lens to suggest strategic operating changes. We can see that, while having a higher margin, the PL-Blue-230 product generates far less cash per minute than the PL-Blue-100 product, which is produced much faster ($103.80 per minute versus $162.70 per minute.)

Figure 3: Stratgetic Operating Map for Decision-Making

Let's assume that increasing the price of the 230 product will decrease its demand by 8,000 units, and decreasing the price of the 100 product by $10 increases its demand by 4,000 units. What will the impact on profitability be? The two tables in Figure 4 show before-and-after scenarios using what-if modeling. As shown in the second table, this change results in a profit increase of over $42,000. It also frees up over 2,000 minutes of production time.

Figure 4: Before-and-After Scenarios Using What-if Modeling

This powerful modeling capability makes effective use of the profit-per-minute KPI to expose possible strategic changes that were previously hidden and make decisions at the operational level that will directly improve profits and ROA. While the historical analysis is essential and very useful, what-if modeling takes the profit-per-minute KPI to another level of capability. It enables everyday operating decisions to produce optimal profits and ROA at the end of the fiscal year.

For manufacturers looking to increase profitability through more strategic decision-making, using profit-per-minute, directly analogous to ROA, is the key. Using this KPI at a granular level - by product, customer, market, region, plant and production line - enables the management of ROA at a transactional level. When daily and weekly sales, marketing, finance and production decisions are based on profit-per-minute, the decisions are made in a way that ensures overall company ROA is maximized at the end of the year, putting millions of dollars back into the bottom line.


Richard Batty is director of Product Marketing at Maxager. He is a 22-year veteran of the IT industry, with experience in marketing, product management and operations. He has a background at Hewlett-Packard and an IPO startup. He may be reached at rbatty@maxager.com.

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