You’re bad at working.

Worse, some of the best “workers” are the ones who are the worst at working. This seems paradoxical, if not outright impossible, but the math doesn’t lie.

Let’s consider what we mean when we say that someone is “good” or “bad” at working. For the purposes of this discussion, we do not mean the $$/hr of productivity, but rather, the percentage of a person’s maximum productivity achieved, given their role. Here are some concrete examples:

Brick Q. Laiher works at a construction site. He is capable of laying 50 bricks each hour¹ if he’s efficient and focused. This would be ~400 (50 x 8) bricks laid per day.

Nola G. Worker is a VP at a tech company. She sits in meetings throughout the day, answers her email when she has a break, drinks coffee from a Yeti thermos until 3pm, and makes strategic decisions with eight-figure potential.

Brick is probably somewhat inefficient. He makes a couple jokes with his buddies on the job, gets distracted by an unusual bird overhead, makes a questionable decision to add extra jalapenos to his burrito at lunch and loses a few minutes in the afternoon in the Port-O-John as a result, etc. So he doesn’t lay 400 bricks…he lays 341. And thus, Brick delivers roughly 85% of his hypothetical maximum output, and his foreman might sling a few somewhat salty sentences in his direction, but the 59 bricks he might have laid probably aren’t impacting the global economy in any significant sense.

And then there’s Nola. She makes more money. She produces more economic value.² But then, is she running a department that produces eight-figure annual value over the long-term or another busy-work-generating engine of bureaucracy? Nola is a human, and humans are not naturally strategic. Human beings like Nola spend too much time considering what task to complete next and too little time considering their broader goals and assessing whether their current strategies are the best way to reach them.

So when Nola earns her six-figure salary, delivers seven-figure value, and misses out on the opportunity to produce eight-figures of long-term ROI, she’s an order of magnitude below her potential impact. Brick delivers 85% of the best version of himself. Nola, despite her being “better at working,” her industriousness and aptitude still delivers 10% of what she ultimately could.

Goals

We are hardly optimal selectors of goals - and unlike Brick³, Nola is responsible for not only her goals, but the goals of so many around her.

When Nola chooses the wrong goals, the loss at day’s end isn’t 59 bricks, but, rather, the totality of problems that might otherwise have been solved and the difference between what was done and what could have been. With great responsibility comes great potential for loss.

Sometimes, the goals we select optimize our capacity for the demonstration of productivity rather than actual productivity - the work that actually generates long-term ROI. We learn how to work hard in school with contrived, well-defined tasks, each of which is expected to be completed within a certain time frame with a high rate of success.

This both helps Nola become a VP and “bad at working” when she does.

Now, as we select the tasks at work on any given day, as we choose projects in which to invest time and labor, we are often more concerned with the demonstration of progress and tangible outcomes than the expected returns. It is often the projects with the lowest probability of success and the least demonstrable progress after a few months that yield the highest upside opportunities. Of course, those are also the types of projects that get their managers fired, which is why your company won’t start high upside projects.

Flow

Professionals often discuss finding a state of “flow,” getting “into the zone,” and feeling focused, energized, and productive. David Melnikoff demonstrates in Nature that flow is “the mutual information between desired end states and means of attaining them.” Stated in less academic language, he posits that we enter the state of flow when we can connect our actions (means of attaining) to goals (desired end states).

This leads us, naturally, to choosing actions where we observe progress towards a goal, because this allows us to enter and remain in the oh-so-desirable state of flow. And thus, we lose agency to the need to see/feel immediate progress, when less certain avenues are available.

Most of us can think of a time when we chose the next action from our to-do lists based not on impact, but by procrastinating on a challenging, amorphous task. Instead, we picked something tangible we knew we could execute easily. That probably wasn’t the highest value task.

We’ve all wondered why that ambitious, world-shaking project remains unstarted, even when we’ve answered every email, chat, and inquiry and every spreadsheet value is triple-checked?

Chances are, you were attempting to maximize your sense of flow rather than your return on time. This is how we worship at the altar of working hard rather than smart.

Creativity

Would you rather work 100 hours without agency, slavishly completing a seemingly infinite list of easily-completable tasks or a smaller number of hours with the agency to ensure that those hours are offered in pursuit of what serves larger goals?

The answer is obvious, and yet, doing this requires creative assembly of the external structures⁴ that allow us to set priorities and avoid becoming discouraged when low-probability, high-upside tasks do not yield that dopamine hit as each interim task is completed.

Often, creativity emerges from the type of constraints that demand ingenuity. Personally, I enjoy writing parodies. Creativity, in this case, is forced upon us by the need to adhere to a rhyme scheme, a rhythm, a topical paradigm, and so on. And yet, despite these limitations, something entirely new can appear. Code imposes similar constraints in the form of syntax, compute time, and any number of forms and structures. And yet, incredible, original products appear daily.

Great ideas emerge from the constraints imposed by time, professional life, and the recognition that, for Nola (if not Brick), there are always more tasks to complete than hours in which to complete them.

If ultimately, Nola wants to be as efficient as Brick, she cannot simply work hard. She must trust herself to follow uncertain paths and remain undeterred without frequent reinforcement in the form of obvious, tangible progress.

The way she avoids becoming worse at working than she could be is by stepping back, assessing her goals early and often, and most importantly, assessing the paths she chooses in their pursuit. We all can be better at working, but especially those of us who already think we’re good at it.

_{1 He’ll be replaced with a robot that can lay 1,000/hr soon enough, but that’s another essay.}

_{2 Or so we hope/imagine, though David Graeber might disagree.}

_{3 Brick probably isn’t responsible for building the right wall in the right place.}

_{4 These are the people, software, and tools on which we rely to manage our work and more generally, our lives. If they are reliable, we thrive. If they are unreliable, we focus on concerns about the structures rather than the task at hand.}