Translate lofty financial goals

A profit-per minute metric can really optimize operations. The chemical industry is discovering that it needs better tools to help capitalize on the products and maximize profits — to generate cash faster. It needs a new metric: profit per minute.

By Richard Batty, Maxager Technology

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The chemical industry is finally seeing better volume growth and tightening capacity. Eventually, there will be opportunities to raise prices. Yet, rapidly increasing raw material costs, increased competition and continued commoditization of specialty products across the industry are forcing chemical producers to look beyond standard practices; cost cutting and pricing programs will not significantly improve profits. They are discovering that they need to better tools to help them capitalize on the products and maximize profits — to generate cash faster. They need a new metric: the Return on Assets (ROA).

ROA is perhaps the most important measure of profitability for shareholders (Figure 1).

Figure 1. Like a vector, ROA is a multiplication of a magnitude and a direction.

Figure 1. Like a vector, ROA is a multiplication of a magnitude and a direction.

It represents how much cash has been generated during the course of a year (or quarter) with the huge investment in manufacturing facilities. Typically reported as a percentage, ROA is in reality a measure of profit over time that is calculated by adding up the margin-based profits attained by all the company products during the year and dividing this number by the value of the asset base.

There is a problem with the margin-only approach to profitability. First of all, maximizing margin is typically the focus of the sales and marketing teams whereas production concentrates on making products faster — improving production speeds, efficiency, yields, etc. As a result, production tends to have little say about which products are made in the first place, although they know very well which ones run best through manufacturing facilities. As a result, marketing and production are looking at two different metrics when evaluating products as “good” or “bad.” No common ground exists for making key product decisions.

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A very real danger exists in focusing on margin alone and not considering production speeds. Consider product A, which has a margin of $10 per kg and product B, which has a margin of $7 per kg. Looking solely at margin, product A appears to be the more profitable of the two. However, if 1 million kg of A are produced in a year as opposed to 1.5 million kg of B, product A will generate $10 million in profit and product B $10.5 million. Incorporating the production velocity of each product gives a completely different ranking for profitability when compared to the margin-only approach. Another example of the danger of over-simplification is shown in Figure 2.

Figure 2. Although product C and A have similar margins, their ROAs widely differ.

Figure 2. Although product C and A have similar margins, their ROAs widely differ.

It is evident that efforts to maximize profitability based on margin alone will not optimize the ROA.

Finding a common language

Combining margin and production velocity data produces a metric — profit per minute — that is analogous to the ROA, since, unlike margin alone, it is time-based. Looking at profit-per-minute at a product level is, therefore, really looking at the ROA at a granular level. Using profit-per-minute as a guide for operational decisions would ensure that the ROA for the company at the end of the year is truly optimized. It would constitute an operational link that would allow the overall company ROA to be managed proactively, rather than being a “rear-view mirror” metric of profits the company achieved.

So why haven’t companies adopted this approach? The simple two-product example above would be easy for a company to calculate. But what happens when a company makes thousands of products in numerous plants and sells them to hundreds of customers? The calculations are no longer easy. With the focus on margin due to the evolution of accounting systems, companies have settled for margin as the best proxy for profitability.

The margin-only focus creates other problems besides sub-optimal profitability. Sales and marketing departments focus on margin as the best measure of profitability available to them, while production focuses on the amount of product made per unit of time. This creates an environment where each department has a different measure for which is the “best” product. Sales and marketing will direct initiatives toward higher-margin products that may seem like “poor” products to production due to their slow production rates. The profit-per-minute approach enables, for the first time, production and sales teams to speak a common language that aligns them toward producing and selling products that generate higher profits.

From theory to practice

While the profit-per-minute theory seems logical, the true litmus test is how the approach works in practice. In other words, how does profit per minute affect day-to-day operational decisions? With insight into the never-before-used profit-per-minute metric, manufacturers can now make decisions about plant profitability, alternative routings, capacity planning, capacity loading, lot size profitability, and can quantify and tie downtime and yield losses directly  to what shareholders want the most: ROA, and ultimately profitability. This method can be applied to measuring plant profitability, identifying where best to invest, estimating line efficiencies, and optimal lot sizes and, thereby, plant and line capacities.

Many chemical companies produce similar products at multiple plants. When profitability is viewed from a detailed profit-per-minute viewpoint, one plant may seem to generate more profits than another plant, even though the products produced are similar or even identical. Obviously a plant’s age, energy costs, raw material costs, personnel rates and personnel abilities may contribute to such a scenario. Knowing the differences in plant profitability enables production management to focus attention on possible improvements for less profitable facilities. Are capital improvements needed? Is maintenance sufficient? Does the production team need more training? Is the plant not well-suited for making certain current products?

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