If you attended The NAFEM Show last month in Atlanta, I don’t need to remind you that the idea of applying automation remains alive and well. You could see it clearly in many booths displaying innovative solutions related to automation and other advanced technologies.

Implementing these solutions can often be complicated and costly, so before taking the next steps to implement these promising technologies, foodservice operators want to know about the return on investment, specifically the impact on restaurant profitability. Indeed, measuring the impact of technology on restaurants remains top of mind and among the most important calculations to make as operators look to evolve.

Technology can positively impact restaurants in a variety of ways, including:

• Labor deployment (savings and/or redistribution)
• Order accuracy
• Ticket average
• Sales increases
• Balancing labor and work content (impacts labor retention)
• Product quality
• Customer service
• Peak hourly throughput

Measuring technology’s impact on some of these factors can happen quickly since the metric would come out of the application. For example, it quickly becomes apparent whether order accuracy has improved or sales have increased.

Other factors, such as labor deployment, often require a systematic redesign of the guidelines restaurants use. When making updates, it is important to make sure the new guidelines account for all the employees’ work content that goes into delivering the brand’s promise. This includes measuring the time it takes to complete each action, both those that are customer-facing and those that are considered behind the scenes.

This pie chart provides an objective breakdown of the guest-specific labor that goes into a quick-service restaurant being able to deliver the desired customer experience. Different forms of technology could impact specific aspects of employee work content, which could lead to changes in the deployment of labor. When calculating the return on investment, it becomes important to factor in how these changes impact employees' time during their shifts.

The following list shows a hypothetical example breakdown of the possible work content time savings for different technologies:

• Self-serve kiosk: reduces time associated with order taking and collecting cash
• Voice recognition AI: reduces the time associated with taking orders
• Kitchen technology: may reduce time cooking food, order assembly and expediting food

Objectively quantifying the time it takes to complete these tasks is just the first step in calculating the impact these technologies could have on a foodservice operation. The second step is to make the appropriate changes to the labor modeling the concepts use. These changes should be based on the reduction in times and/or shifts in labor responsibility that will be brought about by implementing the new technology.

After updating the labor guidelines, the concept should begin testing the technology to get a better idea as to the true impact implementing such a solution will have on the business. When considering potential changes, it is important to vet the logistics of applying the technology at the unit level. Gathering input from the team can help provide additional and important insight as to whether the assumptions made and the integration required make sense and could be done.

For example, when implementing voice recognition AI, the technology requires some time to learn how customers order. The learning capability of this application is what categorizes it as intelligence. One of the challenges of implementing voice recognition technology lies in the fact that customers can order the same item in a variety of ways. Additionally, surrounding noise and a customer’s accent can impact the voice recognition platform’s ability to be successful. This is particularly the case in drive-thru applications. In other words, implementing voice recognition AI offers lots of potential, but reaping those rewards requires plenty of thought and preparation.

Regardless of the technology a foodservice operation seeks to implement, it’s always important to understand how the restaurant will receive the orders and route them to the appropriate stations. Optimal order routing represents another potential benefit of AI. Systems can take into consideration the dynamics of the business at the time the order comes in and make intelligent decisions on how and where to route the order to drive a higher level of efficiency when handling the order. The result would be an improvement in hospitality to the guest and a better balance of what the employees must do, resulting in less stress for them.

As you consider the application of innovative technology, I would offer the following checklist to consider:

• What is the technology trying to solve?
• What is the potential and objective impact of implementing this solution?
• How do these materialize in the labor deployment guidelines currently in use?
• What is the best way to vet the solution to ensure objective testing?
• How does the technology interface with the existing infrastructure at the unit level?
• What are the appropriate cognitive and physical employee ergonomics that need to be considered?
• What are the systems necessary at the unit level to ensure the intended consequence and impact are achieved? As noted in the third bullet, a key one is to have the appropriate labor deployment guideline that accounts for the impact on the labor workforce.

Without a doubt, there is interest in technological innovation. Success and widespread use of such solutions, though, will require a return on investment for both suppliers and for the foodservice operation. I am bullish on the growth of smart technological applications in the industry but somewhat uncertain about the speed of absorption, especially since many moving factors impact this, including the cost and availability of labor.

In a subsequent article, we will detail best practices on adjusting labor guidelines to drive the best impact on hospitality through the application of industrial engineering techniques in foodservice.