As technology, algorithms, and artificial intelligence are increasingly projected to upend the work world, humans and their decision-making prove to be a rich source of business analytics. Co-authored research by ITOM Assistant Professor Tom Tan examines how people make decisions in a labor-intensive service setting. Routing problems, a focus of the study, are particularly difficult to solve, but solutions provide an operational and competitive advantage.
“The assumption is that if there is a rule, people follow it like a machine,” Tan says. “We find that front-line workers in a labor-intensive setting actually use their discretion in routine routing decisions, like assigning incoming parties to their waiters,” says Tan. Overstepping the rules, it turns out, benefits operational performance and profitability. The study examines a large data set from 66 casual restaurants in a metropolitan area.
This study points to the important role of people and their judgment alongside rules or policy — they can complement each other.
This study points to the important role of people and their judgment alongside rules or policy — they can complement each other. Tan and his co-author analyze 2 million check-level observations from sales data and nine months of work time data and conclude that to develop a better service system, frontline worker training is key. The research estimates 24 percent rise in sales by deviating optimally from the round-robin seating rule, which rotates seating based on the next available waiter’s section for fairness.
“A lot of information or knowledge is not reflected in the rules,” explains Tan. “Nuanced information may be held by the routers on the frontlines. Analytics could identify these nuances, feed them into a system and improve it. We have scratched the surface.”
Operations research is about matching supply and demand, says Tan. “Considerable research has been done on a macro level, for example, global sourcing decisions that match supply with demand,” he explains. “Our research fits into this micro-level research matching jobs and employees.”
“Our research fits into this micro-level research matching jobs and employees.”
Artificial intelligence, disruptive technologies, and digitization across industries are all improving performance in settings such as health care and manufacturing. However Tan points to labor-intensive industries that rely on human interaction and operate in less digitized spaces, such as restaurants, car maintenance shops and dry cleaners.
“These businesses are investing in technology, but they are very labor-intensive businesses requiring human interaction.” Restaurants are nonetheless investing in technology related to analytics, payments, and mobile capabilities.
“We should learn about how humans actually do things and continuously improve their programs and systems. By incorporating new knowledge from human decision-makers, we can create a positive feedback loop moving forward,” he says. Labor plays an important role, especially in how people interact with the technology, Tan concludes. His working paper, “Behavioral Drivers of Routing Decisions: Evidence from Restaurant Table Assignment,” is under review.