How AI Is Helping Grocers Reduce Food Waste and Landfill Growth

Posted in Company, Retail
By Erika Szoboszlai on May 1, 2019

Everyone knows the feeling of guilt that comes from throwing away food from the home refrigerator that just never got eaten for one reason or another.

After all, consumer food waste is a major problem in the United States. Piling up to nearly a quarter of all total municipal solid waste, more food reaches our nation’s landfills and incinerators than any other material in our everyday trash, according to the Environmental Protection Agency.

But while consumers take most of the blame in our shared environmental conscious, grocers are also adding to this predicament with inventory overstock and shrink. In fact, 43 billion pounds or 10 percent of the total available food supply is tossed each year at the retail level before consumers ever enter the check-out aisle.

The problem is not limited to our landfills, either. Disposable plastics used for packaging often find their way into our oceans. Recently, the World Wildlife Foundation reported that a 26’ whale was found dead with nearly 49 lbs. of plastic in its belly. According to the organization, plastic is one of the greatest threats to marine life and has killed at least five other whales over the last two years. Taking the example of lunch meat alone, grocers tossed away nearly 17,500 lbs. of product last year, containing enough plastic to fill up almost 10 whales.

To get serious about food waste, landfills and climate change, it’s not enough to look merely at what we as consumers can do at the individual level. Faced with these enormous challenges, the retail and grocery industries need to evaluate what practical steps they can take to address the preventable causes of food waste, including through better management, training and use of AI software.

Doing so will not only help slow landfill growth and ocean pollution but also result in more profitable and efficiently-run businesses.

The Challenge of Grocery Overstock and Shrinkage

Shrinkage, or the measure of goods lost annually to lost to theft, error or spoilage, is not unique to grocers. It affects all retailers. In fact, the National Retail Federation estimates that shrinkage cost retailers more than $46.8 billion in 2017.

However, what sets grocers apart is their notoriously high shrinkage rates. Whereas the retail industry averages a combined shrinkage rate of around 1.3 percent, according to the National Retail Federation, grocers are often 2 or 3 times worse than the rest of the industry. The result? Grocers have among the lowest gross profit margins in all of retail.

That means even small reductions in shrinkage could significantly improve grocers’ annual profitability by allowing them to sell more of their inventory. From both an environmental perspective and a business lens, it is clearly in everyone’s best interest to reduce shrinkage. But how?

The challenge – and opportunity – of grocery shrinkage is that preventable factors are often its biggest causes.

Shoplifting, employee theft and inadequate training leading to goods being tossed by mistake or human error can be addressed by management in a number of ways, including through better training and security. Similarly, regional and store management can implement procedures to improve inventory receiving and handling to reduce the amount of food damaged in transport.

The more difficult causes of food spoilage, poor inventory management and demand forecasting, are harder problems to solve. These require a more sophisticated data-driven approach. Thankfully, these are also the areas where grocers can make the most significant gains in reducing shrinkage through the help of recent advances in artificial intelligence or machine learning technology.

How AI Can Help Grocers be Better Environmental Stewards

While better store-level management can address the human-caused sources of shrinkage, AI can eliminate degrees of uncertainty in the supply chain.

Referencing historical trends and hundreds of thousands of data points all at once, AI can make complex predictions down to the SKU level to help grocers order exactly what they need. In this way, grocers can make sure they have just the right amount of product at just the right place and at just the right time. No more, no less.

Not only can this help reduce overstocking and food waste, but it can prevent empty shelves due to poor demand forecasting – making customers happier and grocers more profitable. Management can also use their expertise to program different variables to measure the effects of pricing and promotional campaigns before testing in the field, so new products are more likely to succeed and not be thrown out and wasted.

Yes, consumers bear responsibility for the environmental problem of food waste. We can clearly see its collective impact on our landfills and oceans, and more should be done to limit our contributions after leaving the grocery store. However, grocers also bear responsibility – especially now that AI-enabled tools exist to help them eliminate the biggest causes of shrinkage.

Shrink is a triple negative. It hurts the environment, it hurts the retailer’s bottom line, and it hurts the consumer shopping experience when shelves are empty.

This article originally appeared here.