QSR 4.0: Improving Operations in the Fast-Food Industry Using Simulation Software

Quick-Service Restaurant (QSR) operations face a litany of challenges from razor-thin margins, staffing, and quality to the amount of time it takes to get products made and in the hands of customers. At the same time, every input has an increasing number of variables that compound to make optimizations difficult to navigate. Should there be two drive-through windows or two drive-through lanes? How about both, but at different times of day? What is the impact on staffing?

Often in such situations, there are tradeoffs that must be accounted for before they are encountered. For example, customers may cherish fresh, local ingredients, but if unseasonable frost affects the crop yield, what alternatives are in place?

The frequency and variety of scenarios where you might want to improve or optimize an aspect of operations can be overwhelming. For that reason, the leading companies are beginning to use software that can simulate every potential outcome to ensure they’re making the best decisions. Multi-store operations can use the same simulation software to test the efficacy of a successful initiative at different locations. The use of simulation software is no longer theoretical but practical and, in many cases, essential to be competitive, making it a defining cornerstone of modern QSR industry innovation.

In every business, the goal is to align throughput, regardless of whether that throughput is achieved via machines, humans, or a combination thereof. This could be determining how a manufacturing plant, a line of food production, a commercial kitchen application, or the drive-through is performing (how the cars are coming through and what is the wait time). This alignment is critical to minimize unnecessary time buffer and improve consistency, a key ingredient to quality. It is also essential to promote smooth operations in resource-constrained environments, whether that resource is space, time, equipment, or something else.

The small commercial footprint of most commercial kitchens is a good example. Simulation could be used to ensure a smooth walking path for employees; they have enough space to maneuver around each other, they aren’t walking more than they need to, nor are they over-reaching for supplies. A business with sit-down table service could use simulation to forecast the status of tables to help staff turn tables faster, minimizing guest wait times, and improving profitability due to seating more guests.

Simulation could also be used to challenge the “gold standard” for the time it takes for a customer to pull into the parking lot and drive away with their food by doing the comparison on cost and performance of a robot versus a human for an aspect of the task.

With so many potential applications for simulation software in the QSR industry, where to start can be daunting. To get up to speed faster, ABI Research identifies the following best practices:

• Perform What-if Analysis in the Case of Underperformance: What if there were a new trend for burritos with French fries? There could be a big order backup on a busy Saturday—not necessarily due to people assembling the burritos, but the equipment cooking the fries. “What-if” analyses can identify the optimal staffing and equipment requirements at different times in the week.
• Focus on Cost Allocation over Cost Cutting: It is better to balance funds in favor of areas with higher Return on Investment (ROI) potential. Focus on where a small change has a big impact, such as optimizing machine maintenance schedules based on past and projected points of failure.
• Go Digital-First: Use a virtual environment to model a potential outcome, such as equipment configurations, before buying the equipment to achieve the best layout, minimize changeover time, and eliminate repetitive injuries for people operating the equipment.

Simulation software differs from traditional business intelligence software by taking a more comprehensive view of problems with greater context. For example, a cash register system can record an event, but it may not be able to fully contextualize the scene and its meaning. The same data in a simulated environment can be used to discern customer traffic at different times of day, and that data can be used to improve worker shift capacity. For larger operations, front of house transactions can tie back into distribution centers for Just-in-Time (JIT) inventory management. These are just some of the reasons why companies using the software are seeing a 12:1 ROI in just 8 months.