How many times have you been in this situation? Your company’s crews have fallen behind on site. Nanoseconds later, you find yourself confronted by a stressed and exasperated client. You parry back and forth a bit, but at a point sooner rather than later, the owner utters that legendary and time-tested phrase (say it with me!): “Can’t you just add more men?” Now that you’re older and more seasoned, you skillfully resist your initial, more primitive urge to plunge your mechanical pencil into his forehead.
You pause for a moment to prepare your response. You’ve already used the “Listen, qualified workers don’t just grow on trees, you know! I can’t just pull them out of my—er—thin air” tact in a previous confrontation, and it was only partially effective. The client (who’d been around the block with this sort of thing) came right back with the highly effective, “Well you’re the professional! This is your business! I am paying you good money to … etc.” argumentative volley. This adeptly undermined your strategy. Stalemate.
Today however, you’re in luck, because you have another card to play. As it happens, the reason(s) behind the slowdown on site are (as is so often the case on a construction job site) nebulous and hard to pin down. Progress has slowed, but nobody’s really sure why. Nothing and no one is specifically to blame. Seizing on this opportunity, you decide to go with the tried-and-true, “The slowdown isn’t our fault! We’ve had to wait on the [enter any other work trade besides your own here] at every turn! We’re going as fast as the job will let us!” You feel just a hint of momentum, so you quickly follow up with “Why should we be blamed for somebody else’s shortcomings?”
This final entreaty was delivered in what may be the finest, most exasperated victim-voice you’ve ever assembled. A master performance. Indeed, it appears to have hit its mark. You sense your opponent growing weary and you begin to relax as the conversation devolves into that post-conflagration portion of the argumentative process where both men still speak but both have also given up on listening. It concludes and the client sulks from your office. You relax your grip on the mechanical pencil. After brooding over it for a full afternoon, you add two more workers to your crew. You heroically resist the urge to make the new workers dress in bright orange and wave their arms every time the client walks by on site. This would be immature. (Sorry. Couldn’t help it. Still bitter.)
Storing Ammo
But here’s the thing: Did you know you could have avoided this outcome all together? Do you know there’s a response to the add-more-men demand that is sound, demonstrable and backed by mathematics? It’s known as The Law of Diminishing Returns (TLDR). In more ivory-tower terms, TLDR is defined as “the decrease in marginal (incremental) output of production in relation to a single factor of that production being incrementally increased.” Don’t panic. Though it rings of high academia, the law itself is actually quite fundamental and practical in practice.
TLDR demonstrates that by adding more of one factor of production (in our case, this would be another worker on site) to a productive process (the task our crew is performing) will at some point (guaranteed) begin to yield lower returns. In short, a magical point in time exists in virtually every process ever created when adding more resources causes you to lose productivity (and profit!). This assumes all other outside factors remain the same.
Now, I’m reasonably certain most contractors, as businesspeople, already intuitively understand this concept although many may not be entirely clear on the forces that back it. They know from experience that dumping more workers into a limited area of work—a work “system”—will only end up with those workers stumbling over one another, waiting longer for access to work elements, and growing more disgruntled and less motivated over the lapses in work rhythm and continuity. And it’s this empiric observation that is essentially at the heart of TLDR.
But knowing TLDR is there still doesn’t make it any easier, in a moment of argumentative need, to explain and clearly articulate its effects. The goal, of course, is to convey to the owner the reasons why adding more workers to the crew may indeed end up causing more harm than good.
So, let’s see if we can fix that. Let’s examine and break down TLDR and see if we can transform this seemingly ethereal concept into something the contractor can wield as an argumentative tool the next time an anxious owner comes calling.
The Law of Diminishing Returns
Let’s look at an example based on our dilemma above. Suppose our current crew is made up six carpenters. As is common, this crew includes craftsman of varying ages, experience levels, work ethics and capabilities. Indeed, some members contribute more and are more productive than others. Let’s also assume that like many contracting firms, there is only so much equipment to go around. Of course, each worker comes with all the standard hand tools, but on this particular site, there is one stationary table saw, one power mitre box and only so many drills, circular saws and jig saws to go around. In the TLDR universe, this limited larger equipment is known as your fixed assets. Think of this as assets that remain relatively static and unchanged.
On the other hand, your workers are considered variable assets. They come and go and can be increased or reduced with relative ease. In our quest to better understand TLDR, the first thing we’ll want to do is assign an average rate of production to our variable assets (the crew). This might end up looking like this:
Unit Output – Crew
Carpenter #1: 9.25
Carpenter #2: 8.15
Carpenter #3: 8.90
Carpenter #4: 7.20
Carpenter #5: 9.50
Carpenter #6: 7.90
Crew Average: 8.48
A “production unit (PU)” score is assigned to each worker. These scores are then added up and divided by the six members on the crew to reach an average of 8.48 PU/worker for that particular crew, or a total of 50.88 PUs for the crew itself. Once you have this score, the next important step is to ascertain the optimal level of production (OLP) that is possible for that particular task system. Think of it as a ceiling or a cap on how efficient that task could ever be performed under any circumstances by those six workers.
Now, you’re either going to be sorely disappointed or highly relieved to learn we’re not going attempt the math concerning the OLP calculation. Candidly, when taking into account the vast complexity and fluidity of the construction industry as a system, I’m not sure we could, even if we wanted to (I talk more about this later). For now, let it suffice that these calculations were performed and that the optimum level of production assigned to this task system using a six-person crew came in at 54.00 (or 9.00 production units/worker) for this particular system at this point in time.
Also know that the numbers used are for example only. In real use, these productivity numbers would be supplied by individual firms/businesses that have likely gone to extensive pains and energy (tracking, cataloging, weighing, assigning, adjusting) to arrive at their company’s own proprietary production factors.
So, given that 54.00 is the best the laws of nature will allow, the graph at right shows what happens when we add two more workers.
Due to the fact that this task system can’t go over 54 units, when we add our seventh worker, there is a severe drop (likely caused by congestion, redundancy of task, etc.) in the seventh worker’s marginal individual production, which in turn brings down the overall crew score. By the time we add the eighth worker, it grows all too clear that not only is our crew not maintaining its level of production but is now heading for a steep decline. The good news? You were right all along! Six was the optimal number of workers for this task at this time for this situation, and the only way productivity was ever going to increase was by increasing the task system. You’d done all you could with your variable assets.
There are abundant other ways to demonstrate the TLDR effect. Another common example is to imagine a factory floor with a fixed number of machines all lined up in a row, and a variable supply of labor for operating those machines. As the floor manager increases the number of workers, the total output on the floor grows until lines form for the machines and the general overcrowding and congestion builds until the extra workers are not only not being productive, but actually just standing around. Again, at this point, and as it was above, the only way to increase production is by increasing the system; in this case, by buying more floor space and machines.
A World of Inexact Science
Please keep in mind that we’ve been discussing economic theory only, and given our vast and mercurial industry, theory may indeed be the best we can hope to apply. Why? Because although the mathematical basis (backed by mountains of field observation and verification) behind TLDR are rock solid, the TLDR equation is only as good as data entered into it. Garbage in, garbage out. And this is where our industry falls sadly, sorely short.
The harsh reality is, with the exception of the simplest of the most controlled task, there is simply far too much complexity, incongruity and (most damaging) disruptive human factors (including morale, sloth and motivation) to ever arrive at a universal set of productivity factors that are accurate, responsible and transferable from place to place, time to time, or application to application.
But this lack of quality data isn’t the fault of TLDR. The science is sound. I still maintain that the TLDR argument is a position of formidable merit when discussing field operations with a client. Just explain it as I have to you. You may be surprised by the client’s reception. Remember, too, that many of our clients are businesspeople themselves who have likely seen and experienced the TLDR concept in action. So you’re already halfway home.
Good luck!
S.S. Saucerman is a retired commercial construction estimator and project manager who worked for a large upper-Midwest general contractor. He is also an established freelance writer and author whose work spans 20 years.
