Rick Phelps

Synchronous Solutions

I was listening to a conversation between a stone fabricating shop owner and a software developer, discussing integrating a bunch of data from the production process to better understand the profitability of individual jobs. They talked about data points like whether or not the job was run on overtime. It reminded me of something my dad used to say: “Some people are just too smart for their own good.” I didn’t really get what he meant back then, but I am beginning to!

There is just one metric you need to know to understand the relative profitability of a job in your fab shop: the Throughput Dollars ($T) per Constraint Minute. Okay, that one metric is actually two things – the amount of $T the job carried, and the amount of shop capacity the job consumed.

Actually, in special circumstances, it IS only one thing: the $T carried, but I digress…


Do we understand how $T flow?When I was a new industrial engineer, I was asked by the leadership of the aluminum smelting and fabricating complex where I worked to help solve a paradox. The complex was not profitable and was slated for shutdown by the Board. This complex made a very wide range of aluminum products, from high purity capacitor foil to guard rails for the side of the highway. Some of these products were “highly profitable,” others, not so much. Apparently in the aggregate, they weren’t profitable enough to keep the 3000+ jobs.

The leadership team believed that if they focused the entire complex on making just one product, beverage can sheet (think the body of your typical beer can), they could make the complex profitable and keep it open. The problem they faced was interesting. We ‘lost money’ on every pound of can sheet we produced at the time, and they wanted to throw out all the products that we “made money” on to produce this loser. Essentially what they were telling the Board was, “Yes, we know we lose money of every pound, but we will make it up in volume.”

Not surprisingly, all the financial wizards and seasoned engineers couldn’t come up with the financial justification for spending the better part of a billion dollars to modernize the facility to concentrate on a money loser… so they gave the problem to the kid who didn’t know any better. It was a classic example of my dad’s “They’re too smart for their own good.”

It took a week (this was before personal computers and Lotus 123), but working on the assumption they were wrong, I started with the most profitable product and cranked the numbers, processing step by processing step, for how many millions of pounds a month we could make if we just produced that product. Turned out, not many. After cranking out the top three most profitable products, a pattern emerged. The hot rolling mill limited the production of every one of them. Being lazy, I jumped to the biggest loser, can sheet production, and what do you know, we could produce A LOT of that loser! We really COULD make it up in volume!

Throughput Dollars is Revenue minus Truly Variable Expenses (TVE). Since every pound of aluminum had the exact same TVE, Revenue and $T were basically synonymous. The hot rolling mill was the constraint. The actual relative profitability of the product mix we produced was the rate $T per hot rolling (constraint) minute. When you compared the list of most profitable to least profitable products based on the financial accounting system, you got almost the exact opposite of the list of most profitable to least profitable products, when considering the impact of the hot rolling mill – the system’s constraint.

Here’s the thing. To calculate the Margin of each product, cost accounting tracked reams and reams of data. Times at every processing step, the burden rate of each process, and on and on. And the more detailed the analysis they did, the more they knew and the less they understood…

Now, if you are thinking, Hmmm, I wonder if my understanding of relative profitability of jobs in MY shop is as screwed up as the aluminum company’s? I can assure you – it is.

The more you invest in knowing  “the important details,” the less you will  understand your business…  And here’s the kick in the pants. The more you invest in knowing the “important details,” like was the job produced using overtime hours, the less you will understand your business, the worse decisions you will make in your business, and the cherry on the top – the more you will be sure you are right.

One process in your shop limits your production capacity, just like the hot rolling mill limited theirs. Understand how this process limits the rate of $T in your shop, and you will finally understand how you actually make money.

Curious about the special circumstance where it is actually ONLY $T?

Supposed your shop is profitable and you have the opportunity to bid a large commercial job that, with the right incentives, you could produce with your existing crew on overtime. You really want to do work with this company. How low can you go with your bid to win the job?

Since your shop is already profitable, ALL additional $T will fall straight to the bottom line.

The only additional costs your business will incur for taking on this project is the overtime pay. Consider this as part of TVE when calculating $T for the job.

You can bid this job at a rate that the competitors will look at and say, “There is NO WAY they are making money at that price.” And they would be absolutely right AND positively wrong. Right from their cost account perspective, and wrong because they don’t understand $T. If they don’t understand $T, they don’t understand how they make money.

They are too smart for their own good.

Don’t be that guy.

Oh, and don’t think just because you make a windfall profit on that job, that you can bid ALL your jobs that way. You cannot. Look at the assumptions…

Rick Phelps has been applying the concepts of Synchronous Flow to difficult industrial problems at dozens of businesses and organizations around the world, since the early 1980s.

In 2009, as Cleveland Cliffs’ Director of Continuous Improvement, Rick took on a failing Lean Six Sigma organization, refocused their improvement work using Synchronous Flow, and created a shop floor, engagement driven, continuous improvement process that Cliffs credits with creating a sustained $100M per year reduction in production costs.