Efficiency Has a Cost
How record profits and record layoffs are the same spreadsheet
A handheld inventory scanner weighs about twelve ounces. It fits in the palm. Each time a warehouse worker logs an item — picked from a shelf, placed in a bin, moved to a conveyor — the scanner emits a short, high-pitched beep. Across an eight- or ten-hour shift, the sound becomes ambient. Workers stop noticing it after the first hour. What they do not stop noticing is the absence of it — the silence that means they have fallen behind rate, that the algorithm monitoring their throughput has flagged a gap, that a supervisor may appear. In Amazon’s fulfillment centers, the target pick rate is calibrated to the capacity of the system, not the capacity of the person holding the scanner. The beep is not the problem. The silence is.
Amazon operates more than 1,000 of these facilities globally, employing roughly 1.5 million people. The architecture of each building is designed around a single proposition: minimize the time between a customer clicking “Buy Now” and a package leaving the dock. Every process is measured. Every measurement has a target. Every target is calibrated to the system’s capacity, and the humans inside the system are expected to match it.
In 2023, the company’s net income increased roughly 190 percent. In the same twelve months, it eliminated approximately 27,000 positions. Meta posted a 201 percent increase in quarterly profit and cut 10,000 jobs. Alphabet reported record revenue and laid off 12,000 employees. These companies were not cutting costs to survive. They were cutting costs to optimize. The distinction — between managing crisis and engineering margin — changes what the numbers mean.
The logic of removal
A company has revenue and expenses. Profit is the gap. Widening the gap is the job. One can increase revenue or decrease expense, but decreasing expense is faster, more predictable, and more legible to investors. A cost line eliminated is immediately visible on a balance sheet; a revenue opportunity foregone is invisible. The asymmetry is structural: cutting is concrete, building is speculative. Financial markets reward certainty, and cost reduction is the most certain move available. Meta’s Mark Zuckerberg declared 2023 the “Year of Efficiency.” Amazon’s annual letter to shareholders referenced “operational efficiency” fourteen times. The term operates as a directive: applied to any cost structure, it targets whatever the spreadsheet identifies as excess. Headcount, benefits, safety margins, maintenance budgets — all are legible as cost lines, and cost lines are what efficiency eliminates.
The Senate HELP Committee’s 2024 investigation into Amazon’s warehouse operations found that the company’s internal total injury rate — including injuries not required to be disclosed to OSHA — was just under 45 per 100 workers. Nearly half the workforce, in a given year, was injured. The publicly reported recordable rate ran 6.5 per 100 employees, 71 percent higher than the rate at comparable non-Amazon warehouses. Sixty-nine percent of workers surveyed had taken unpaid time off due to pain or exhaustion. Fifty-three percent attributed their injuries directly to productivity pressure. Musculoskeletal disorders — the specific cost of performing the same reaching, bending, and lifting motions at speed for hours — account for a disproportionate share. These injuries are not accidents. They are the predictable output of a system that measures throughput and does not measure what maintaining that throughput does to the body over time. The injury rate is not a failure of the efficiency model. It is the efficiency model’s externality — the cost that appears on no spreadsheet, in no quarterly report, in no earnings call where the word “efficiency” was used fourteen times.
The metrics work. Amazon ships billions of packages per year at speeds that would have been logistically impossible two decades ago. The metrics are not miscalibrated. The targets are not arbitrary. The system is, by every measure designed to assess it, performing.
The boundary
Efficiency, as a practice, requires a boundary. A line is drawn around the things being optimized, and everything inside that line improves. Everything outside it is, by definition, someone else’s problem. The smaller the boundary, the more efficient the interior becomes — and the more cost accumulates on the exterior.
These are the same event, described from two sides of a measurement boundary.
The people on Meta’s cost line had names, mortgages, health insurance that ended the day they were let go. None of these facts are legible to the efficiency metric. The metric sees full-time equivalents and total compensation burden. It sees what it was designed to see. In healthcare, hospitals that spent two decades optimizing nurse-to-patient ratios — the leanest, the most efficient by every measure their boards reviewed — were the ones that broke first when a respiratory virus arrived, because surge capacity was the cost that had been cut. In retail, companies that shifted to part-time workers scheduled by algorithm, cutting hours to just below the threshold that triggers benefit obligations, saved money that appeared on the balance sheet and created costs — turnover, lost institutional knowledge, workers holding three jobs and performing well at none — that appeared nowhere.
Systems do not have intentions. They have incentives.
An efficiency metric incentivizes the removal of cost. If cost includes human labor, the incentive is to remove labor or reduce its price — lower wages, fewer benefits, faster rates, automation. Each choice is rational within the boundary the metric draws. Each transfers cost from the entity being measured to entities outside the measurement: workers, families, public health systems. The transfer is not a malfunction. It is the mechanism. Optimization is always optimization of something, which means it is always optimization away from something else. The spreadsheet does not know what it is optimizing away. It knows only that whatever it is costs more than the alternative.
What gets optimized out
This produces brittleness. Systems stripped of redundancy perform well under normal conditions and fail under abnormal ones, because the buffer was the cost that got cut. Southwest Airlines spent years optimizing its crew scheduling for maximum aircraft utilization — planes in the air, not on the ground; crews rotating through tight connections with minimal downtime. The system was efficient. Then, in December 2022, Winter Storm Elliott disrupted enough flights that the scheduling software could not reassign crews. Not because the software crashed, but because it had been built with no tolerance for deviation. The airline canceled more than 16,700 flights in ten days. Two million passengers were stranded over the holidays. The eventual cost exceeded $1.2 billion. The airline had known the software was outdated. It had been warned. But modernizing the scheduling system was a cost, and the existing system was working — by every metric used to evaluate it, it was working well — right up to the point where it encountered a situation it had no capacity to absorb. The scheduling system that had saved the airline money every quarter for years could not handle a single week of weather. The margin was the cost that got cut.
Geoffrey West, in his work on organizational scaling, identified a version of this pattern in biology: living systems maintain inefficiency as a survival strategy. An organism that operated at peak efficiency — no fat reserves, no redundant neural pathways, no excess lung capacity — would be optimized for exactly one set of conditions and would die the moment those conditions changed. Living systems carry slack. They are, by the narrow measure of input-to-output ratio, inefficient. They are also durable. Corporate systems face the opposite selective pressure. Markets reward tightness. The quarterly earnings call is a report on how much slack was removed, how lean the operation has become. The incentive runs in one direction: toward the minimum viable configuration, toward the system that performs well today and has nothing left to absorb tomorrow.
Whether the measurement boundary is a design choice — something that could be drawn to include injury rates and surge capacity alongside throughput and margin — or whether it is an inevitability of measurement itself is not yet clear. Both possibilities lead somewhere difficult. If the boundary is a choice, the failure to redraw it is a decision. If it is inherent to measurement, then every act of optimization necessarily produces an exterior that absorbs what the interior discards.
What the data does show is where the boundary currently sits. The workers who absorb the injuries are the workers who move the packages. The laid-off engineers were the ones building next year’s product. The communities priced out of insurance are the communities that generate the premiums. The exterior is not separate from the system. It is where the system’s inputs come from. At some point the exterior stops being someone else’s problem — not because the system develops a conscience, but because the system runs out of exterior. The data, by design, only covers the interior. The exterior is where the costs collect, and the costs are not yet anyone’s metric.
Not yet.
-Aimé