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In my decades of working with clients in the lumber industry, there is always one question I like to pose. The various answers I’ve received reflect the gap that often exists between a company’s purpose and its optimization strategy.

The question is, “What are you trying to make in this mill?” Some of the answers I’ve heard include:

• “Random length, dimension lumber.”
• “8’ and 9’ studs.”
• “We specialize in decking.”
• “High-grade 2×6’s.”
• “Wide dimension lumber.”
• “Prime.”
• “The highest lumber recovery we can.”

Despite these precise responses, they are all bad answers. The correct answer should reflect the company’s purpose: “We try to make the most profit possible.”

Unless a mill is run as some sort of social experiment, we all understand that maximizing profit is what allows companies to achieve their other goals long-term. Goals like providing good-paying jobs, having a positive impact on a community, being a good steward of the environment, maximizing return to shareholders, etc..

Garbage In, Garbage Out
At this point, some of you might be thinking that the wrong answers above reflect a misunderstanding of the question. Of course everyone is trying to make the most profit possible. But when you begin to dig into the optimization strategy that makes breakdown decisions on every log, cant, and board in a mill, too often it is set up in a way that does not drive profitability. You’ll find erroneous inputs such as:

• A “multiple” placed on the pricing of decking, wides, wane-free lumber
• Flat-pricing used to make all products “equal” so that lumber recovery is maximized
• Market pricing used to get a lumber mix with the highest average price

Optimizers are complex computer programs that allow sawmills to remove human error and influence from breakdown decisions. They leverage all available data to make the best decision in the blink of an eye. But just like every other computer system out there, an Optimizer defines “best” based on the input parameters that it is given. Proper inputs equal maximum profitability. Improper inputs lead to sub-optimum profitability. The difference to your bottom line can be significant, running into the millions of dollars per mill per year.

Before we continue, I highly recommend that you read our previous two articles about deconstructive manufacturing and predictability. Understanding these topics are crucial to fully grasping this topic of optimization strategy.

Margin, Margin, Margin
For simplicity’s sake, let’s assume things like wane allowances, product definitions, green lumber sizes, etc., are all setup properly. This will allow us to focus on the element that drives the optimized solution: pricing.

Achieving maximum profitability as a lumber mill means producing a product mix that generates the highest possible contribution margin per log. This is achieved by using mill-specific and product-specific contribution margin as the pricing in your optimizer.

Properly determining contribution margin isn’t straightforward. In fact, I’ve never walked into an organization and seen it done properly. Not only must applicable manufacturing costs be applied for the sawmill, kilns, and planer, but they must be applied based on the nature of the bottleneck of each lumber mill.

Imagine that LUMBERCO is a large, multinational corporation with many lumber mills scattered across North America. Among their holdings are mills that are bottlenecked in the kilns and others in the sawmill. Of those mills that are bottlenecked in the sawmill, some are bottlenecked at the primary breakdown, some at the trimmer, and some at the stacker. Each of these mills requires a different application of manufacturing costs to determine contribution margin of a given product in their facility.

Below are some examples of poorly defined contribution margin pricing driving an Optimization Strategy that is not aligned with maximizing profitability:

• If LUMBERCO has consistent optimization pricing across all its mills, or even across all its mills in a given region, they’re not reflecting the realities of each mill’s bottleneck-specific manufacturing cost.
• If a mill has applied a standard manufacturing cost per MBF to their entire product mix based on their P&L, they’ve developed an understanding of contribution margin that is a recipe for value destruction.

As was highlighted in our article “What Is Deconstructive Manufacturing? From T-Bones to 2x4s, Every Cut Determines Profit”, every optimization decision can have only one of two outcomes. It can either retain the maximum value inherent in the log/cant/board, or lose value. Put another way, every time steel meets wood, value is either retained or destroyed. It is your Optimization Strategy that defines every cut.

In light of this reality, you should review your Optimization Strategy to ensure that millions of dollars per year, per mill are not slipping through your fingers.

If you need help, let us know. We have more than 20 years of successful experience helping dozens of companies in 15 countries across 3 continents. We’ll work with your team to identify and capture the millions of dollars a year that may be slipping through the cracks due to suboptimal optimization strategy.