How the Next Wave of the Food and Beverage Industry Will Be Shaped by AI
Michael Mueller
Exclusive to TRN
Artificial intelligence has already sparked change in the food and beverage industry. But so far, this technology has been focused on the product. For example, AI has made portions more consistent and made the process of sorting produce more efficient.
But there’s another possibility for AI. The next wave of AI in the food and beverage industry will be to improve the people, not the product. In today’s difficult hiring landscape, people-focused AI can help businesses discover what they truly need–and get creative about how to find it.
What if you could discover the key behavioral traits of a chain manager or a franchise owner? What if you could decode the most helpful habits of a server or use a rewards program to better understand your customer’s buying habits? Artificial intelligence, when united with behavioral science, can do just that. We can merge findings from psychology, sociology, and neuroscience with the computing power of AI to make better hiring decisions, lead more effectively, and stay on top of new food and beverage trends.
How?
First, let’s clarify some terms. Artificial intelligence is a bit of a misnomer—as AI is neither artificial nor intelligent. “Artificial” refers to the fact that it’s a computer doing calculations (or running equations) rather than a human. “Intelligence” is used because the computer running these equations or algorithms is trying to find patterns and discover connections—the way a human brain would. So when it comes to using AI to improve decisions about people, it is crucial that the technology is used in partnership with human reasoning. This is sometimes called “hybrid work.” For any AI to be successful, there must be a human component. Moreover, we need to hold these algorithms to the high standard of transparency—leaders should demand to know exactly how the AI reached its conclusion.
The bottom line?
Humans can use AI to collect and assess data, but they need to be in the driver’s seat. People—and the human brain—are still best when it comes to interpreting information and thinking strategically. But with these human strengths come human bias. “If you have a brain, you’re biased,” as the saying goes. Enter AI. With the right technology, a hiring manager may consider candidates they might otherwise rule out. Perhaps the candidate didn’t have the “right” experience, but an assessment shows they have the growth mindset and acumen needed to succeed in the role.
Let’s say you are overseeing the opening of 15 new locations across a geographic region. You have several positions to hire, from managers to cashiers to line cooks. Each position requires a different set of skills, behaviors, and experience. Typically, an employer would hire candidates based on previous experience and an interview. But behavioral science research shows that humans tend to hire people like themselves. You’re smart enough to know that you don’t need a bunch more yous—what’s needed is a mix of skills. Furthermore, research shows that interviews are deeply biased: for instance, they favor people who are tall when all other factors are the same.
Here’s where AI blended with behavioral science can help. Using behavioral science assessments called psychometrics, a profile can be created for each position. Our firm creates these profiles by benchmarking positions. For example, a profile would indicate which behaviors, motivators, and habits are best for someone in charge of stocking ingredients.
Another might detail what psychological traits are needed for someone to manage the branch well. Then, assessments can be used in hiring to find the right fit for the right position. Think of it as a recipe for hiring. People-centered AI can look for someone with a big dose of problem-solving and a dash of sales ability. It can look for someone who is inherently
social for front-facing roles and someone who is meticulous and process-oriented to place orders. The key—and this is essential—is for the algorithm to be explainable by design. This means the decision-maker knows how the algorithm came to its decision: they can see that one candidate ranked higher than another because of, for instance, their perseverance score.
This transparency is essential to navigating sensitive decisions and mitigating potential legal risk. AI cannot give a “take-it-or-leave-it” answer. Instead, it must assess fit and the likelihood of success. Explainability by design gives owners the confidence they need to hire and manage employees. Because at the end of the day, the human makes the decision.
Recent tectonic shifts in the food and beverage industry have only accelerated the need to adapt—especially when it comes to hiring. Tomorrow’s leaders will understand that it is the people, alongside the product, AI can supercharge. The most productive, most beneficial AI tools will give leaders the ability to make clear, data-driven decisions in real time. That’s the power of a technology that’s here to stay.
Michael Mueller is Vice President of Aperio Consulting Group. He leads the development of Decoding Performance, a tool that blends behavioral science and AI to tackle to hiring and leadership challenges. Michael is passionate about data-driven, human-centered decision-making and loves working with leaders who understand the value of their people. He holds a degree in biochemistry and an MBA. You can find him on LinkedIn.
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