OM in the News: Amazon’s Way of Measuring Work

Amazon warehouse workers who can’t ‘make rate’ don’t last.

Austin Morreale worked at the Amazon fulfillment center in Edison, N.J.. “It was 10 hours of pretty much mind-numbingly boring work, pretty much standing in the same position for the whole shift,” he said. “But at the end of the shift, I was drenched in sweat and aching like I hadn’t ached since I was playing competitive soccer.”  Morreale was slow, he says, and kept messing up the patterns for efficiently putting items on robotic shelves—known as “stowing.” He couldn’t “make rate”: Amazonese for keeping up with the pace of work. In Amazon’s fulfillment centers, writes The Wall Street Journal (Sept. 11-12, 2021), human productivity is measured by an overall pick or stow rate calculated for each worker at a robot-fed pick-and-stow station.

On the job, no one ever stood behind Morreale and barked at him to work faster. But twice a day at a stand-up meeting, his shift managers told the group how everyone was doing. They knew because Amazon’s software, and an assortment of sensors in the warehouse, tracked workers’ every move. Knowing that if you don’t make rate you’ll get a warning, triggered by an algorithm, and if it happens often enough your job is in danger, can be a powerful psychological spur to work harder, and possibly to exceed your physical limits. (In 2019, Amazon reported 5.6 injuries per 100 workers. The average rate for warehouses in the U.S. that same year was 4.8 per 100).

More than a century ago, Henry Ford pioneered systems for speeding up work that we take for granted today (see Chapters 1 and 10). What Morreale experienced was Amazon’s 21st-century, algorithm-driven successor to Fordism. It’s a mix of surveillance, measurement, psychological tricks, targets, incentives, sloganeering, and an ever-growing array of technologies. This system of technologically supercharged management can be benevolent, or sinister, or both.

Imagine the delight of  Ford, if he could know, to the millisecond, how long it took every worker to complete a task, every day, in every facility he owned. Imagine what early time-and-motion experts Frank and Lillian Gilbreth could have accomplished had they been able to discard their film cameras and replace them with millions of hours of video captured from the digital cameras that watch every station at Amazon’s fulfillment centers.

 

Classroom discussion questions:
1. How would the use of time studies, detailed in Ch. 10, be impacted by the Amazon approach for setting standards?

2. What are the responsibilities of operations managers in dealing with productivity and safety at their warehouses?

 

 

OM in the News: Looking Back–and Forward–on Productivity

productivityFrederick Taylor revolutionized manufacturing at the turn of the 20th century with a simple insight. Most manufacturing work was a sequence of physical motions. You would load coal onto a shovel, carry it to a furnace, throw it into the furnace, walk back to the coal pile and repeat. In a time and motion study, he quantified each step and how long it took. Then he analyzed how to improve the whole process. He noted, for example, that a typical worker could lift 21 pounds for maximum efficiency. Workers varied in size and strength, but on average this weight balanced the number of shovel lifts per minute against the volume per lift. In those early days, workers used the same shovel for all materials, regardless of the density of the stuff being lifted, so less weight was being lifted for the less dense materials. Taylor’s elegant and simple solution — bigger scoops for shovels used to haul the less dense materials — illustrates how careful analysis of a specific work process can increase productivity.

Today, his time and motion studies seem antiquated. Phone calls and memos have replaced shovels and picks for many workers. “Yet despite its association with early factories, a modern version of the spirit of Taylorism is sorely needed,” writes Harvard’s Prof. Sendhil Mullainathan in the New York Times (Sept. 28, 2014). “It’s time to identify and optimize the specific psychologies that constitute the mental alchemy of productivity,” he says.

In one Stanford experiment, some workers were randomly assigned to work at home, others worked in group call centers. The work habits of both groups were carefully monitored electronically, and the workers knew it. Those working at home were 13% more productive than those in call centers. With modern technology, we now have so many ways to quantify, track and motivate productivity, and are just beginning to scratch the surface of doing so.

Classroom discussion questions:

1. Why is productivity such an important issue in OM?

2. Describe how time and motion studies are conducted (see Chapter 10).