The Dirty Secret About Productivity

This expert opinion by Joe Procopio, founder of joeprocopio.com, was originally published on Inc.com.

One of the best affirmations of real business advice I ever got was from my friend Ricky Spero, a CEO I’ve watched succeed for a long time. We were talking about productivity, goals and results, and company culture and he dropped this line on me:

“I don’t worry about whether our people are working enough. I worry obsessively about whether we’re working on the wrong things. If you worked on the wrong things, your productivity was 0 percent”

I mean, there’s something everyone can agree with. In theory. Putting it into practice is why CEOs and leaders get paid. Not putting it into practice is why they get fired.

Productivity is indeed a giant business issue, which has only grown more critical and thorny over the past five years. It has both played a role in and been impacted by decisions around RTO, labor and layoffs, technology and AI, and even the very nature of what a job is these days.

In fact, I could have dropped a way more controversial headline on this column, like “Productivity is the enemy of innovation” or “How the tech industry has weaponized productivity.”

Those columns are coming.

But every rabbit hole starts with a half-cocked first take. And since, right now, the top priority of every CEO and investor and board is optimum productivity, I want to start with this controversial shot:

Productivity can’t be optimized, because it can’t be measured.

I know the counterargument. Bring it.

What We’re Actually Measuring

When we think about productivity, we all need to open our minds and think a little bigger.

Another way to say that is, “Hey, MBA guy. Get your BS formulas out of my real world.”

Fine, let’s take it literally then. Productivity, in its simplest form, is output over input. Result divided by effort.

I’m not arguing that. Like most business issues that trip people up and make me write about them, the problem isn’t in the premise—it’s in the execution. 

This is a great equation when talking about assembly lines, commodities, and repeatable tasks with known outcomes. Those are all the kinds of business models that have failed or are failing because it’s 2025 and most businesses stopped operating that way in the 1980s—despite how much the AI crowd wants you to believe it still works that way, and customers will just accept the same offering delivered the same way in perpetuity. 

Ah, dammit, I said I was going to lay off AI for one post this month.

Next counterargument. Productivity aims to put a stake in the ground for improvement to happen.

Why the Productivity Metric Is Always a Guess

Well, define input.

Let’s go back to my friend Ricky’s brilliant line, which I later synthesized into:

“I’d rather have my team focused on the right goals for an hour a day than focused on the wrong goals for 12 hours a day.”

When the output in the productivity equation is a goal, or anything non-quantifiable, the input, time, becomes meaningless. When the output is quantifiable, like dollars, the equation then assumes that the input mechanism, the labor, is completely interchangeable. 

And don’t get me started on how we’re using the wrong metrics to make hiring decisions. Well, do get me started, but not for another week. It’s in the queue.

But wait! Did I just disprove my own argument? That’s what leadership is trying to fix! By measuring and improving the outcomes of each labor component! 

But that’s not leadership. If dollars are your only goal, you have an assembly line. You don’t need leadership. You need stopwatches to measure and machines to execute. Those same AI people will tell you those machines are already here, and they brought their own stopwatches.

True productivity is the result of real leadership, and like all leadership-driven results, it is not quantifiable. Just like satisfaction, or loyalty, or happiness, all of which impact productivity. 

OK, next counterargument. If you’re not measuring the making of money, you’re doing business wrong.

The Myth of Numbers-Based Businesses

The true numbers-based business is the holy grail of the marriage of MBA schools and technology.

Let me tell you another holy grail story. No, not the Indiana Jones face-melting one. But that’s what you were thinking, right? Because of my overall tone? 

Back when I was at Automated Insights and we were building one of the first NLG/generative AI platforms, starting in sports and with Yahoo Fantasy Football as our first major success, one of the projects I was always chasing (and it became a company thing) was using data to create a better betting spread for sports.

We had all this highly advanced data about teams, players, games, weather, past performance, future projections, you name it. Couldn’t we develop a better betting spread than the current human-driven model, which is often some Vegas guy shooting a dart and then immediately following the money as it comes in?

Algorithms will tell you yes. The real world laughed at me. There are too many factors, too many variables, too many unknowns. There’s a reason that old crusty guy in Vegas puts half a point here or there: It’s because he’s seen everything.

But I couldn’t let it go until I put reverse thinking on it: If sports really worked that way, where outcomes could be forecast by models, no one would care about it enough to make the bets to fund the quest for the better spread.

In other words, the revenue would dry up.

Well, business doesn’t work that way either.

Next counterargument. We can get close enough to make the right decisions.

If Money Is All That You Love

No, we can’t. We’re not getting close to a decision. We’re getting exactly right on two or more static, numeric axes. 

To go back to my sports example, it’s like taking two teams, taking the score of all their games throughout their history, and thn predicting the next score based on the averages.

That’s not close.

Taken in that context, think about this.

Even if one were to think that revenue is the only metric worth chasing, and that’s something I get very close to saying sometimes, so I’m with you, we can’t escape the fact that cost is never the sole driver for the customer. If that were the case, then the cheapest product would win every time.

There are other factors, and a lot of them are non-quantifiable.

So if we want to optimize productivity, we need to stop trying to measure it, and optimize leadership instead.

And I know the counterquestion: What’s the formula for that? Well, I’ve been dropping hints on what comes next and I’ll indeed be bending productivity and hiring and technology into some interesting ideas for 2025. If you liked the jokes and hidden references, please join my email list and follow along.