Throwing food away feels wrong. Yet in many service businesses, waste is rarely just a personal failure – it is part of a bigger puzzle. Food becomes waste when kitchens can’t anticipate quiet periods, when operations can’t keep pace with demand, or when diners take more than they eat.
Optimising the whole service flow means understanding its parts: kitchens, diners, staff, and the building itself. Smart data can help reveal patterns that would otherwise remain invisible. One surprisingly revealing source of data? Elevators.
“Elevator data provides a unique view of how people move through the building, helping businesses understand patterns that would otherwise go unnoticed,” says Fabien Fédy, KONE’s head of new business innovation.
In the Dining Flow project, KONE collaborated with the University of Turku, food service company Sodexo, and several other companies to study and manage dining flow at campus lunch restaurant Flavoria. Researchers collected data from elevators and building sensors, combined with external information like weather, to develop algorithms that anticipate customer movements and optimise restaurant operations.
Up to 20% less food waste
Carolina Islas Sedano, principal investigator from the University of Turku, describes food waste as a multilayered problem: “Not only is food waste a major cause of emissions, but it can also cause significant financial losses for businesses. Due to this complexity, we needed a large team with diverse expertise, from service designers to engineers.”
Besides the sensors, data was also gathered using smart scales that measured how much food was eaten or discarded. By using an application designed for the project, the customers were able to see the amount of their own food waste and better track the impact of their choices.
KONE’s elevator data was used to estimate daily visitor numbers, so the kitchen could adapt food volumes and minimise waste. Combining the data from different sources, the restaurant was able to reduce approximately 15-20 per cent of food waste.
“Real-time data on visitor volumes helped us to predict customer flows better and adjust our operations over time,” says Vuokko Hietaniemi, unit manager at Sodexo and head chef at Flavoria.
Understanding customer volumes is crucial because the number of diners fluctuates daily.
“We may go from 1,200 one day to 800 the following,” Hietaniemi describes. “The daily predictions based on elevator and sensor data were very accurate. Once we learned to trust them in the kitchen, we could prepare less food during slow periods and more when demand was high.”
What elevators can teach us
There are also other interesting examples of harnessing connected elevator data for more sustainable and efficient building operations. For example, KONE’s elevator data has been used to optimise heating, ventilation, and air conditioning (HVAC) systems. In Tallinn, Estonia, a business campus saw energy use and emissions reduced even by 36%.
“We are eager to explore more on how real-time elevator data can address societal issues and optimise building operations,” Fabien Fédy says. “Connected elevators that are linked to the cloud and provide real-time data are a significant asset for building owners and service providers especially in high-traffic environments, like campuses, shopping centers, or hospitals.”
Other potential applications include cleaning services in office buildings, which could be scheduled based on actual building use, he explains. This kind of real-time insight could even reshape contracts with service providers.
“Having access to real-time data provides opportunities for truly revolutionising services, even creating entirely new ways of doing business while tackling larger societal challenges,” Fédy states.