Our story starts with a journalist who kept getting delivery-attempted stickers. After she left a note asking that packages be left at the nearby laundromat, still she got the notice. Even when she was in her apartment, the UPS man left an attempted delivery note.
Where are we going? To see how big data is monitoring work place productivity.
An $11 billion industry, “workplace management systems” are keeping an eye on many of us at work by monitoring what we do and how long it takes us. Here are some examples:
Delivery Truck Sensors
We could say that UPS is data driven.
In addition to the handheld devices in which our UPS drivers enter delivery information, more than 200 sensors monitor what happens in their trucks. They tell UPS when and where a package is scanned for delivery and when the customer gets it. The firm knows when the driver buckles a seatbelt and when he (she) starts the motor. Drivers have a special key that cuts the time it takes them to get into and start a locked truck.
Knowing how long each segment of the delivery process takes lets UPS minimize inefficiencies. As a result, while domestic deliveries were up from 2009-2013, the number of drivers was down. Also though some drivers report that performance monitoring has created additional stress and perverse incentives to guarantee speed—like using the delivery attempted sticker.
Starbucks Flashing Lights
My Starbucks has a drive-thru. If you look at a high shelf near the window through which the baristas hand the coffee and food to drivers, you see a screen with little cars and numbers. Changing from green to yellow to red, the color of each car indicates the wait time for that driver. Explained by my very knowledgeable barista Josh, I learned that green is excellent, yellow means you are close to the deadline and a red light indicates the car has waited too long. The goal is to serve each customer in no longer than 3 minutes. Drinks they can process quickly but heating food slows them down.
A Chocolate Factory
For many smiles, I suggest these two minutes of productivity from a 1950s I Love Lucy show.
Our Bottom Line: Productivity
Almost 50 years ago, economists William J. Baumol and William G. Bowen hypothesized that industries like health care and education and also the performing arts would experience “stable productivity.” Using their now-famous quartet example, they said “The output per man-hour of the violinist playing a Schubert quartet in a standard concert hall is relatively fixed, and it is fairly difficult to reduce the number of actors necessary for a performance of Henry IV, Part II.”
Now called Baumol’s Disease, the inability to boost human productivity in certain industries might be cured by performance monitoring data. But, I do worry that the cure would “kill the patient” because of perverse incentives.