How to Improve Line Flow, Increase Speed of Service

By Juan Martinez, PhD, PE, FCSI and Principal at Profitality® 

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To Queue or Not to Queue…that is the question. If you think about it, you already have an answer when you consider that your life is but a series of queues throughout your day, made up of activities and waits. Perhaps you might want to process-map yourself through the day to help you understand this concept. This exercise may even give you a base knowledge to help you run your life better, or maybe just more efficiently.

Just like in life, running a restaurant is a set of queues. If you want to run it right, make sure you accept this, understand it, and manage it. How do you improve line flow and optimize the way you manage queues in your restaurant concept? It could be a queue that a customer experiences, a production queue in the back of house, or a queue in equipment usage, among many others.

In a service system, the total time is made up of smaller time segments and queues. If you think about the total change or impact that you want to achieve — in customer wait time, for example — you might think it’s not doable. But when you attack it in terms of components, the story and complication may be quite different.

The following are examples of what I’m talking about, and how looking at the queuing components and the theory of constraints can help with this quandary. Both of these are Industrial Engineering techniques that we use constantly to help drive impact in line flow and queuing management for foodservice concepts.


Consider that during peak volumes, drive-thru has an average of six cars in different points in the queue (e.g. menu board line, menu board, pick-up window queue and pick-up window). If you think about how to reduce the total customer wait time by two minutes — say, from six minutes to four minutes total time — you may get stumped because the impact is so significant. But if you realize that the total time is made up of six different one-minute stops, the last one being the pick-up window, the task to improve the service time and throughput becomes one of reducing these shorter stops in the queue.

The pick-up window is typically the step that takes up the most time, unless you have a double order board system. If you reduce this time by 20 seconds each (from 60 seconds to 40 seconds per stop), the actual total impact to the guest ends up being the reduced two minutes you were looking for. A simplified depiction of this explanation is shown in Figure 1, in which the queue segment times are the same. In reality, they are not, but the process of analysis and re-engineering would be the same.

Production Constraints

So, how do you reduce time at each window? You go to the next level of queues, on the production side, and apply the same queuing analysis to uncover the constraints that are driving the throughput roadblock and re-engineer the necessary steps to achieve the desired result.

A typical production time is made up of several components, including reaction time, cooking/heating time, assembly time, and expediting time. Reaction time is typically where the biggest opportunity lies for a quick-serve restaurant. You can have a fast assembly and expediting time, with no cooking time, but if you take long to get started with the assembly (reacting to the order), then the production time will be long and, subsequently, so will the window time.  

As you are embarking on solving for a minimum production time, I suggest that you use the following question as the goal: “How do I get the food to beat the car to the window?” If the food beats the car to the window, fast window times are not far behind. How can changes in deployment, layout, workstation, processes and procedures, and equipment and technology platforms be used to enable this goal?

As you go down the line fixing the constraints, you need to consider the cost of fixing each and use this additional information to define how far you will go. Somewhere along the way, due to the cost of equipment, quality, labor, space, or other areas, the payback of fixing the next constraint is not worth it. Think of the 80-20 (Pareto’s) rule: How do I get 80 percent of the impact for 20 percent of the cost?

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Computer Simulation

To improve line flow and minimize queuing time, we can also use computer simulation, another Industrial Engineering technique, to model and quickly test any production or queuing system. An example cafeteria system is shown in the picture to the right. Our role in this project was to define the peak hourly capacity of different designs. Here is a link to this dynamic 3-D simulation.  

The way you set up the actual queue and line flow can also have a significant impact on the guest experience. I would contend to you that in queuing management, not all time is created equal. Is it the same to wait three minutes in one spot within a line, or one minute in each of three spots? The time is the same (three minutes), but I would offer that the experience is not. When it comes to customer experience, the latter is much better than the prior. Perception is reality. If the wait time feels shorter, then it must be. Perhaps this is why Disney has many phases and stops in their line management processes, and they entertain you as you go along. They clearly want perception to be the guest’s reality.  

For more information on the application of Industrial Engineering Techniques and queuing management, do a search of the phrase “Disney Industrial Engineering.” Here, you can find where Disney applies these techniques to drive significant impact to the business.

You can say that all flows and queues are “coldly calculated” in Disney to make sure the guests have a great experience. No detail is left to chance. So, if using queuing theory is important to Disney — arguably the number one company in providing a great customer experience to its guests — why would it not be important to you also?

Whether you like it or not, you are dealing with queues and line management everywhere. To better deal and manage this reality for your customers, knowledge of queuing is very important in the design process. It allows you to drive more throughput and better customer service, which can result in higher sales and profits that drive brand growth.