The Usefulness of Current AI Systems for Food Waste Management

Written by: Varun Khanna, research scholar

With the remarkable growth of the food and beverage industry, the issue of food waste management seems to be increasing. It has been identified that in the United States alone more than 86 billion pounds of food is wasted per year (Charlebois, Creedy and von Massow, 2015). Globally, 1.3 billion tons of food is wasted every year (Eriksson et al., 2017).


In its 2018 Wasted Food Report, the U.S. Environmental Protection Agency (EPA) revealed the following food waste data for commercial hospitality:

Hotel Sector: 1,137.83 pounds/employee/year
Full-service Restaurants, Food Service: 39.13 tons/facility/year
Limited service Restaurants, Food Service: 40.91 tons/facility/year


Food wastage not only consumes money and resources but also has many adverse effects on the environment. Experts suggest that this problem of food waste will continue to increase as more businesses come into the market, and the food and beverage sector keeps growing.

Technology has been used to support the cause of food waste management. A report from the Ellen MacArthur Foundation suggests that AI-implemented systems used to help reduce food waste could generate 127 billion dollars annually by the year 2030. These systems could include software that has the capability of visually recognizing food, producing trends and algorithms that would help forecast demand, and aiding in the prevention of over-ordering. (Rejcek, 2019).

Now, we need to find out if these systems are useful enough to be implemented in all food and beverage outlets. If the answer is yes, what are the positive and negative impacts of implementing these systems? And if the answer is no, what changes are needed for these AI- implemented food waste management systems to maximize their usefulness?

Let us begin with the impacts of implementing these systems.

Positive Impacts/ Motivating Factors

The first positive impact to be found was awareness, in terms of the amount of food that is being currently wasted and the economic losses because of it. This links to the second positive impact that is culture. Implementing these systems helps companies create a positive culture, focusing on social responsibility and doing something good for the planet. Another positive impact that was noted was reduction of labor costs. In an interview with a restaurant operator, what emerged was that when he implemented AI implemented food waste management systems, he was able to reduce his labor costs. Now, he only needs one person to monitor food waste instead of a whole audit team. Another motivating factor in implementing these systems involved the daily reports on Trend Forecast, which helps management analyze the demand and supply ratio, preventing over-ordering and reducing overall food costs.

Negative Impacts/ Demotivating Factors

The first and the most repeated demotivating factor is the startup cost or initial cost to implement these systems. Most participants think that implementing these systems will not be useful because they would end up spending more than the profit they make. However, this factor should not be a problem for larger establishments who bulk-produce. For smaller establishments serving a la carte options, it is one of the main demotivating factors. Other negative impacts noted include extra work and training employees to use these systems. Training employees is an added company cost and when these systems are implemented, employees might feel that this is extra work for them and subsequently may become demotivated. Additional issues include data privacy and input of false data. Since the systems are usually cloud-based, there are possibilities for data leakage, which can be very dangerous for a company.

Are these systems useful for all organizations?

The answer is no. Research suggests that AI systems are useful in some manner if you have very large operations but are not very useful for smaller-scale operations and restaurants featuring a la carte menus. This is one of the main reasons why small establishments and stand-alone restaurants or even fine dining restaurants are hesitant to implement these systems. Most feel that the initial implementation cost is too high, and they also feel that only a minimal difference can be made using these systems because there is a much smaller amount of waste to be measured.

Recommendations

These systems need to be more advanced and appealing, as currently there are more negative impacts than positive impacts regarding their implementation. Consumers need to be educated and made aware of the food waste issue, and governments need to provide a driving force to make more people aware of these systems and food waste management overall.

[Note: This blog is based on the author’s research in this field.]

Varun Khanna is a research scholar with the HFTP Middle East Research Center. He is also a student at the Emirates Academy of Hospitality Management in Dubai, UAE.

References

Charlebois, S., Creedy, A. and von Massow, M., 2015. “Back of house” – focused study on food waste in fine dining: the case of Delish restaurants. International Journal of Culture, Tourism and Hospitality Research, 9(3), pp.278-291. [Accessed 3 Nov 2020].

Eriksson, M., Persson Osowski, C., Malefors, C., Björkman, J. and Eriksson, E., 2017. Quantification Of Food Waste In Public Catering Services – A Case Study From A Swedish Municipality [Accessed 3 Nov 2020].

Rejcek, P., 2019. Food Waste Is A Serious Problem. AI Is Trying To Solve It. Singularity Hub. 47 Available at: https://singularityhub.com/2019/11/03/food-waste-is-a-serious-problem-ai-is-trying-tosolve-it [Accessed 3 Nov 2020].

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