Amazon's warehouse productivity targets were so aggressive that workers peed in bottles

Amazon's fulfillment centers use a productivity tracking system that monitors workers' 'time off task' (TOT) — every second not spent scanning, packing or stowing items is logged. Workers are expected to handle approximately 300 items per hour, and those who fall below the threshold receive automated warnings that can lead to termination.

In 2021, reports emerged that Amazon warehouse workers were urinating in bottles and bags because bathroom breaks would trigger TOT warnings and jeopardize their jobs. Amazon initially denied the claims, then acknowledged the problem after internal investigations confirmed it. The revelations sparked public outrage and intensified unionization efforts.

The case illustrated how a productivity metric, optimized without regard for human biology, creates inhumane working conditions. Amazon's system treated workers as components in a machine, measuring output to the second. The metric was not wrong — it was the only thing the system measured, and what gets measured gets optimized, even when the optimization dehumanizes.

Amazon's time-off-task tracking and 300-item-per-hour targets made workers urinate in bottles; the metric ignored human needs, sparking outrage and unionization.

Amazon's TOT tracking system logged every second of non-productive time, creating pressure to skip breaks.

Workers reported urinating in bottles to avoid TOT warnings and termination.

The 300-item-per-hour target was optimized for throughput without regard for human needs.

Amazon initially denied the reports, then acknowledged the problem after internal investigation.

What gets measured gets optimized. Amazon's TOT system measured productivity to the second but not whether workers could use the bathroom. An optimization that ignores biology is cruelty.

Amazon adjusted its TOT policies and invested in workplace improvements. The Bessemer, Alabama warehouse held a union vote (which Amazon won, but the effort continued). The case became a focal point in the debate about warehouse working conditions and algorithmic management.