Insights > Product Profitability: Making the Right Decision

Product Profitability: Making the Right Decision

Revenues are growing and new business is being won, yet profit margins continue to shrink. Inevitably, companies wonder whether they have priced their products wrong or if their costs are simply too high. Unfortunately, the answer is not always clear, as most companies lack a true understanding of their costs at the part level. This means that many companies make critical decisions armed with incomplete or even bad cost data. With extreme pricing competition and pressure, it is critical that companies have an accurate picture of part-level costs in order to maximize profitability. Key decisions around product rationalization, make vs. buy, new product pricing, and capacity optimization all rely on accurate part costing.

Experience alone will only go so far when making critical decisions to maximize profit and pinpoint which products are the real winners.

Problems with standard cost

A company’s leadership generally has an idea of which product lines are profitable. However, experience alone will only go so far when making critical decisions to maximize profit and pinpoint which products are the real winners. Most leaders in this situation will turn to their standard cost models to gain further insight, but these models are often overly simplified and do not reflect the real cost of products. Often, standard costs are optimized to price and win business, which means actual product and process changes that naturally arise in manufacturing are likely not considered.

There can also be issues with the standard cost model itself. Most models will allocate overhead based on direct labor hours, which in the past was the primary cost in manufacturing. As a result, 20% of cost (direct labor) is sufficiently accurate, but 80% of cost (overhead) is generalized. Today, higher levels of technology, machine complexity and automation are significant drivers of cost. The logic behind splitting fixed and variable cost tends to be less than deliberate. Usually this analysis is done once and not revisited, meaning that fundamental changes in operations, like a change in shift pattern, can be overlooked when refreshing standards. These simplifications are usually done to ease maintenance of the model and accounting functions but come at the detriment of truly understanding part profitability.

Finally, a standard cost model on its own does not analyze inefficiencies.  For example, analysis of actual scrap rates, actual machine throughput, and overtime requires a separate model. Typically, all of these off-standards fall into a variance account and only through additional analysis are applied to a specific product. Unfortunately, most companies don’t get to this level of detail and the companies that do go this far commonly spread these variances evenly, causing the result to be less than helpful.

Benefits of operative costing

Many business leaders are familiar with the term activity based costing (ABC), but models using this approach require a significant amount of time, sophistication, and dedication. As a result, they can be expensive and time consuming to implement and maintain. The good news is that there is an approach achieving significant improvements in accuracy with better bang for the buck. Said differently, an analysis of part level profitability that provides essential accuracy to support key business decisions can be done in a fraction of the time and cost of a full ABC approach. This approach is called operative costing.

Assessing an accurate fixed vs. variable or semi-variable cost is critical so that contribution margin is meaningful when making important decisions. The first step to operative costing is to take an existing standard cost model and improve the logic splitting fixed and variable cost. The next step is to improve the logic behind the drivers allocating overhead.

Utilities, for example, can be split between fixed and variable by using the high-low method and allocated based on drivers such as machine type, complexity, size or floor space occupied. This approach, for example, yields enough detail and precision to capture the differences in machining vs. assembly, but enough simplicity to require only a small amount of legwork. In another example, production control manpower can be allocated based on product complexity. If these costs were allocated based on volume, two products could absorb the same amount of cost even though production control may spend far more time delivering or sequencing parts for the more complicated product.  Overall, the key in this process is to determine the best and most logical driver for each line item in the profit and loss statement without burdening staff with excess and unnecessary analysis.

The last step is to use the improved standard cost model and deep dive into the variance account to understand actual performance. Combining the standard cost model with actual cost by allocating the variance account using meaningful drivers results in actual profitability by product. Repeating this analysis over multiple periods yields enough data to show how products perform over time and compare to one-another. Again, the key to this process is determining the best and most logical driver for each cost variance, whether that driver is cycle time, batch size, scrap rate, or breakdowns.  Once in place, these cost drivers become key performance indicators that can better explain financial variances or, better yet, drive profitability improvement.

Experience, even when augmented by standard costing, is not enough to make the right decision. Even if the logic behind standard costs is sound, it does not reflect actual costs, and in turn does not reflect profitability at the part level. Due to modernization in manufacturing, a typical standard cost model applies the “reverse” Pareto principle, where the majority of effort is focused on getting 20% of costs accurate while over generalizing 80%. The goal should be the opposite: get 80% or greater of cost analyzed accurately so that the right decision may be made.

While activity based costing can achieve this goal, the application of this approach is costly and time consuming. An operative costing model provides the required accuracy to support critical business decisions without putting undue burden on staff. In other words, with operative costing, a part level profitability analysis can be completed in fraction of the time, with a fraction of the resources and achieve the requisite accuracy to make the right call.

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