Psychology of Queueing & Disneyland
- queueing theory: part 1
- On Queueing, Oil Change, and Customer Experience
- Queueing Theory: Part 4
- On Time-Traps and Waste
- queueing theory: part 2+
- Queueing Theory: Part 3
- Little’s Law for Product Development
- Psychology of Queueing & Build-A-Bear Workshop
- Travel Time & Waste
- Call Centers as Queueing Systems
- What is Waste?
- YouTube’s Queueing Properties
- Queueing Theory and Terrorism
- Queueing, Disneyland, and FastPass
- Psychology of Queueing & Disneyland
- Multi-Tasking Leads to Lower Productivity
- Queueing Psychology at the Gas Pump
- On Queueing and Elevator Mirrors
- The Variability Tree
- Attitude and the Pyschology of Queueing
- Emergency Room (ER) Wait Times
- Staring at Acoustic Ceiling Tiles
I went on vacation last week to Disneyland. We had a lot of fun. It was also a time to learn how organizations like Disneyland deal with queueing challenges, especially with systems under high stress and load. In this post, I want to cover the Psychology of Queueing and how Disneyland satisfies several of the positive properties.
There are a few key behavioral responses or reactions to queues, or waiting. Below are the propositions:
- Unoccupied time feels longer than occupied time.
- Process-waits feel longer than in-process waits.
- Anxiety makes waits seem longer.
- Uncertain waits seem longer than known, finite waits.
- Unfair waits are longer than equitable waits.
- The more valuable the service, the longer the customer is willing to wait.
- Solo waits feel longer than group waits.
In almost every ride at Disneyland, they provide the following metric at the beginning of the ride:
The message above signals to the customer approximately how long she or he is expected to wait. This strategy satisfies property 4 of the Psychology of Queueing — it is no longer an uncertain wait, but a finite (albeit seemingly long) wait. This helps to manage the customer’s expectations or helps the customer decide whether he or she is willing to wait or willing to move on to a different ride. This visual display is a simple, yet powerful move that helps the customer.
Now, to arrive at the average wait time above, requires some understanding of the physics of queueing. The physics of queueing that helps us approximate the average wait time is below:
- λ = Arrival Rate, or more specific, the time between arrivals. For most queues, we can assume that the arrival distribution can be approximated by a Poisson distribution; which means that the time between arrivals are not deterministic, but random.
- μ = Service Rate, or more specific the time for a arrival to be serviced.
So, we get the following to conclude the average wait time:
Tw = (λ / μ(μ – λ))
The calculation is simple, yet powerful. Couple the physics of queueing with a positive approach in the psychology of queueing, then you’ll better manage the expectations of your customers, better forecast the load and requirements of a system, and better predict requirements on labor or resources.
This post is part of a series on Queueing Theory. Other articles can be found here:
- Queueing Theory: Part 1
- Queueing Theory: Part 2
- Queueing Theory: Part 3
- Queueing Theory: Part 4
- What is Waste?
- On Time-Traps and Waste
- Call Centers as Queueing Systems
- Travel Time & Waste
- Little’s Law for Product Development
- YouTube’s Queueing Properties
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Comments
Hey Peter,
I don’t think they used that formula for that approx wait time. I would imagine that it would be as simple as knowing how many people on average can fit into the physical line and knowing the service time.
I agree that it is really comforting knowing what the wait time will be and even more comforting when that wait time is actually shorter than shown!
@James,
No, that is definitely the equation used to calculate average wait time.
Comfort — good point, but it helps to be honest, though. Honesty has the added effect of building trust that the average wait time is approximately correct. If a lower number than the actualy calcualated number was shown, it would most likely build distrust in customers because after x time has passed, the line still has more to go before the customer is served. Plus, it’s just good business to be honest.
Hi, I enjoy your blog. I think James is correct that the equation you provide is not what Disney would use to calculate the waiting time. The equation you provide is ffor a M/M/1 queue, which has alot of assumptions including steady-state, Poisson interarrival times, and Poisson service times. Living in Florida and having been to Disney World several times I would say the variation in service times is low for many attractions due to the way they stage guests in front of the rides. While not deterministic, it is close. Also, I would guess the arrival rate for most attractions is usually greater than the service rate during peak times of the day for these attractions (so lambda > mu). In other words, the system is not in steady-state, and therefore the equation is not valid.
Hi everyone,
I really enjoyed this blog and I was wondering if anyone could help me. I am a fourth year business student and I have to provide simple calculations for average waiting time at one Disney World ride. The equation I am using is the exact same as the one first mentioned (it may not be
100% accurate but for the purpose of this class it is just right). Anyways, my problem is that I cannot find any statistics regarding number of arrivals or average number of customers who complete the ride in a given time period. If anyone could help it would be greatly appreciated!
Thanks in advance,
Laura
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Last week I was at a seminar featuring the very lean guy John Bicheno, and he told a similar story about the psychology of queueing. He told that elevator manufacturers knows that people hate standing in line at elevators, but that almost disappear if a mirror is introduced. Suddenly there is something to do while standing around waiting. It seems simple, yet very powerfull.