By Ellie Gabel, Contributor
Since the profit margins in the restaurant sector are so slim, you should seek to save wherever possible. While the cost of food waste isn’t a secret, you probably overlook it, considering it a part of doing business in this industry. In reality, it’s easily solvable with the right tools.
Artificial intelligence (AI) technology has enhanced predictive analytics, enabling you to anticipate changes and predict which strategies will work best. It can help you fix discrepancies in ordering and inventory management, minimizing food shrink. What else can it do for you?
The Problem with Restaurants’ Supply Chain Food Waste
You’ve probably felt forced to raise menu prices to offset losses incurred by wholesale prices rising and fewer people eating out. The consumer price index for restaurant food costs increased by 7.7% from 2021 to 2022, the most significant increase in nearly one decade.
Sometimes, making your menu more expensive is counterproductive. While people pay more per meal, it can drive away business. Instead of raising prices, consider cutting expenses, like eliminating food shrink.
The integrity of your cold chain is at risk. Distribution has been busy lately, so supply chains have had more perishable freight than usual. If those trucks experience delays or malfunctions on the road, the chance of premature spoilage increases substantially.
The good news is that food waste is usually preventable. Whether things spoil or customers leave a lot on their plates, predictive analytics can help.
The Role of Predictive Analytics in Waste Reduction
Predictive analytics is the use of data to predict future trends or events. It uses a machine learning algorithm to compare current and historical data. It can factor in seasonality, promotions, inventory levels, logistics bottlenecks, and best-before dates into its analysis to forecast food waste.
This way, you can predict how much customers will eat, when ingredients will spoil, when your deliveries will arrive. It eliminates guesswork, allowing you to cut the messy spreadsheets and frantic phone calls to suppliers out of your routine.
Whether you want to predict delivery timelines, perishable spoilage rates, or customer consumption, you only need a single tool. As a result, you can adjust portion sizes, tweak ingredients, or change your ordering habits to minimize food waste.
Benefits of Using Predictive Analytics Technology for Waste Reduction
Speed and automation are arguably the most significant benefits predictive analytics offers. Since these algorithms can process massive amounts of data in seconds, you can extract critical insights faster than ever and around the clock.
This tool is also cost-effective. Research shows AI-enabled supply chain management optimizes inventory levels by 35%, improves service standards by 65% and reduces logistics costs by 15%. It can help you get your priorities straight, which saves you time and money.
Reducing waste is actually one of the best ways to make inventory management more affordable. Cutting food shrinkage by just 20% could save you thousands of dollars. It’s a great alternative to raising menu prices or renegotiating vendor contracts.
3 Ways Predictive Analytics Solutions Can Help
Predictive analytics enables you to reduce food waste throughout your entire supply chain.
In the Fields
Everything from the weather to crop disease can affect yields. A machine learning model can factor these variables — and hundreds of others — into its analysis to predict what harvests will look like each season. This way, you know whether you’re facing a surplus or scarcity.
Post-harvest food waste is common. Farms account for 21% of food waste in the United States.
Luckily, since it happens yearly, you can plug that data into your algorithm to learn how to prevent it. Being able to anticipate those losses helps you improve handling and storage. This can help you figure out if any menu items will be in limited supply or no, so you can adjust your menu before it becomes an issue.
During Distribution
Under- and over-ordering happens to the best of us. If you have a history of ordering too much or too little, feed that data to your model. It’ll use your restaurant’s foot traffic and inventory levels to forecast demand, so you always have the right amount of ingredients.
Predictive analytics technology can help you coordinate with your suppliers and vendors. It can estimate delivery time frames and predict delays, helping you avoid disruptions. Since the cold chain is time-sensitive, it’ll be a huge help.
In the Kitchen
When ingredients go bad or a recipe goes wrong, your restaurant’s kitchen wastes food. However, the specifics are often fuzzy. Which worker makes the most mistakes? What items spoil most often? Predictive analytics can help you identify and close these gaps.
Customers are also a big source of losses. According to the Natural Resources Defense Council, plate waste accounts for 30% of food waste in restaurants. Using machine learning to predict menu items’ popularity lets you adjust prices and quantity, reducing this percentage.
The Truth About Using Predictive Analytics in Restaurants
In reality, predictive analytics technology can’t do it all — it needs your help. It gives you insights so you can take action. Making sure you can strategically implement those data-driven changes is a fundamental driver for success.
