When we think of retail waste, we likely think of the discussion around food waste. Any time something is expired, returned, or out of refrigeration for too long, it’s thrown away. Not to mention employee errors like incorrect orders, dropped food, etc. But in an industry as all-encompassing as retail, waste extends beyond food — like a shirt that’s pulled off the sales floor because an employee spots a hole in it. This is also true of sustainability in retail, like freezer aisles where lights turn off inside the coolers after a certain amount of time, or an even larger example – the environmental cost of returning items and throwing them away.
According to The Verge, five billion pounds of returned goods end up in U.S. landfills each year – this doesn’t even include e-commerce, whose issues with waste and sustainability were evident long before the pandemic sent even more business online. The resources that went into creating a product, raising livestock, growing produce, etc. are likewise wasted when these items are thrown away, and the emissions from trucks tasked with making the returns all further contribute to pollution, degraded air quality, and ultimately climate change.
As a result of these problems, businesses are being forced to consider change. Some retailers are beginning to partner with businesses that offer AI and machine learning capabilities in order to make better use of company data to address these issues and accelerate innovation. While “green” efforts and increased sustainability have been high priorities for businesses for the last decade, retailers need to make better, smarter decisions with the data they have in order to impact the bottom line with COVID-19 still making an impact.
Here are a few areas we are seeing leading retailers focus on when it comes to leveraging their data to address issues of waste and sustainability:
By providing operational insights to managers and employees on the frontline, retailers can make smarter decisions in the moment that increase sustainability. As an example, with the right data, a retailer can determine that they threw X amount of a product away and why. Over time, this helps people make better decisions regarding how much of a given product they continue to stock based on consumption or number of purchases.
This data often exists at the business level, but making it available and digestible to those who interact with consumers on a daily basis is difficult to do. Retail organizations can empower employees to make in-the-moment decisions (regarding inventory, specific products, etc.) by ensuring that insights are easy to digest and seamlessly fit into teams’ day-to-day tasks. To address this, companies need to work to provide better insights and tools to employees, to empower them to make decisions in the moment, drive impact, and improve sustainability.
A retailer’s assortment planning process can make or break their selling season or even their entire fiscal year if executed haphazardly. While assortment teams typically have considerable expertise with tailoring product assortments, they tend to struggle to get a clear picture of the impact of their decisions.
Enter augmented assortment planning. With assortment planning powered by AI, team members can make smarter choices about quantities and stocking shelves. They’ll have better insights as to what’s on the shelf and how much of it there is – so teams stock the appropriate amount of product before things expire or run into other quality issues. By leveraging AI, retailers can balance the art and science of assortment planning — complementing teams’ historical knowledge with critical data to improve decisions over time.
In this space, RevUnit worked with a leading retailer’s gas stations that were tossing a considerable amount of hot dogs from their roller grills every day at every store. RevUnit helped predict how many hot dogs to cook with simulated institutional knowledge of workers paired with external factors like public events and sports games, with the goal of decreasing waste across thousands of stores.
Retail shrink continues to be one of the largest threats to brick-and-mortar stores, but the necessary inventory intelligence to alleviate the issue is often siloed within retail organizations. The hitch here though is, without inventory intelligence, retailers must have excess inventory on hand to meet customer demand. This isn’t ideal for a company seeking to reduce waste and improve sustainability, but the amount of redundant inventory has only increased in the last year.
When retailers are equipped with smart data that’s tied to product status and can better determine what (if anything) is wrong, inventory counts can be more accurate, ensuring appropriate stocking in the future according to current demand and current waste.
Revunit helped a multinational food processing company in this space when they found they were losing $60M a year due to mislabeled products. Anything mislabeled that went across the scale and into the blast freezer was deemed unmerchantable. With AI tools and machine learning, we were able to help them address inventory loss more accurately by capturing critical data.
With shortages impacting supply chains and many sought-after products being seemingly impossible to find, retailers are reassessing ideas of what retail waste is and whether it can be repurposed or otherwise still provide value before it’s tossed. For its part, New England supermarket chain Price Rite implemented a free app that gives shoppers access to exclusive deals on all manner of products — dairy, produce, meat, seafood, deli and bakery, etc. — that are nearing their best-by date. By making these products available at greatly reduced prices, Price Rite is able to earn revenue on items that otherwise would be counted as a loss.
Another well-known example is Panera Bread’s Day-End Dough-Nation®. As soon as the doors close at any given location, all unsold inventory (baked fresh and meant to sit on the shelf for no more than a day) is packaged up and given to a waiting volunteer from a local non-profit organization so it isn’t wasted and goes to neighbors in need.
As consumers, we can all likely recall a situation where we’ve put an item in the cart that we don’t want by the time we’re at the register. What many shoppers don’t realize is that if the specific item is cold, many retailers need to dispose of it for safety and quality control instead of returning it to the shelves. But what if you were able to give frontline employees the insights to address issues like this one before the product needs to be thrown out?
With tailored task management solutions that integrate into existing systems, retailers are beginning to be able to surface better, real-time insights for their frontline teams in the moment and improve in-store collaboration. How might this look in the wild? If you’re operating a grocery store and a refrigerator door is open too long in the dairy section or the temperature goes up in a service case in your deli, alerts could be created (e.g. “close door 4 in the dairy department”) to help limit what is wasted – the products themselves and the energy required to keep them at their optimum quality.
It’s past time for company leaders to provide environmentally conscious choices, and not just ones focused on speed at any environmental cost – and many are already making strides in this space. But a retailer's challenge often isn't that they lack the right data to do this, it's leveraging that data across the entire retail value chain from supplier to shelf, pin-pointing areas that can be improved upon for waste reduction and sustainability. Data transformation in these areas will certainly take investment from retailers, but without it, both the economic and environmental impacts of waste will continue to be felt globally.
Need help getting started? Our teams have partnered with some of the world’s largest retailers like Walmart, H-E-B, Zappos, and Tyson to help them reduce inventory loss and enhance their sustainability efforts, faster. Learn More.