Do cashiers or service agents work faster or slower depending on how a queue is structured and the apparent length of the queue?
A 2016 Purdue University study, Humans Are Not Machines: The Behavioral Impact of Queueing Design on Service Time, sought to answer this question. Researchers studied the impact of queue design on worker productivity. The aim was to determine the impact of queue structure and queue-length visibility on worker productivity.
Here’s what the study found:
1. The single-line queue slows down service rates.
The Humans Are Not Machines study points to research that suggests, “a single line queue has a higher level of task interdependence, which leads to dispensability of individual effort and, therefore, to reduced effort.”
In other words, when agents are pulling customers one after the other from the same single queue, they are less likely to feel pressured to work quickly because they don’t see a direct connection between their work pace and the length of the queue. Others can pick up the slack.
How to mitigate the slowdown:
Knowing that this finding somewhat contradicts other well-known research which suggests single-line queues result in shorter wait times for customers overall, the researchers acknowledge that the slowdown in worker productivity can be mitigated in two ways:
- Provide real-time information about the queue to servers, and/or
- Explicitly monitor individual performances
Queue analytics systems, such as our own Qtrac iQ, can correct these findings by achieving both the recommended mitigation strategies. Agent dashboards can offer a real-time look at how many people are waiting in line, how long they’ve been waiting, and send alerts when wait times get out of acceptable range. These systems can also offer management detailed insights into agent productivity to determine when an individual performance level is less than expected.
2. Poor visibility of queue lengths slows servers down.
Researchers explored the notion that servers work more slowly in a queuing environment in which the queue is blocked from the view of the servers as opposed to when servers have full visibility into the queue. In other words, when servers can see how many people are standing in line they work faster than if they cannot see the full queue.
The study proved this hypothesis correct in finding that within each structure, queue visibility played an important role in productivity.
How to mitigate the slowdown:
Managers can address the potential slowdown by adjusting the physical layout of the queue to reduce visibility barriers (e.g., lowering the height of display cases) or adding visibility enhancements (e.g., mirrors or video displays of the line or electronic displays of customer movement within the store).
However, surprisingly, the research uncovered that when servers are compensated for performance (per cart incentive setting) in the single-queue structure, blocking visibility may actually lead to improved performance.
Before you decide to question your queue structure, the researchers point out another important consideration: fairness. Social justice would favor single-queue systems due to the first-come-first-serve order of serving customers.
How can you use this research to improve worker productivity in your queues?
Source: Shunko, Masha and Niederhoff, Julie and Rosokha, Yaroslav, Humans Are Not Machines: The Behavioral Impact of Queueing Design on Service Time (June 1, 2016). Available at SSRN: https://ssrn.com/abstract=2479342
