Analyst Insight: AI is emerging as a powerful tool for businesses to reduce waste in their supply chains. It can help optimize processes, predict demand more accurately, and make data-driven decisions that minimize waste and improve efficiency.

A global focus on sustainability is growing more urgent as climate change intensifies and the UN weather agency issues a “red alert.” While many businesses think about their environmental footprint in terms of scope 1 emissions — the ones they emit most directly — the much bigger effect comes from their supply chains. CDP’s Global Supply Chain Report shows supply chain emissions are 11.4 times higher, on average, than operational emissions. 

Reducing waste can minimize environmental impact and improve critical performance indicators like efficiency and profitability. For instance, manufacturing food that will ultimately go to waste causes nearly 10% of the world’s emissions.

Business leaders increasingly turn to artificial intelligence (AI) as they look for answers. A recent report shows roughly 70% of manufacturing CEOs see “significant” ROI from AI implementations, including in key areas such as supply chain management, quality control and procurement.

The potential for AI to reduce waste in supply chains is immense, as it can help companies optimize their processes, predict demand more accurately, and make data-driven decisions. Those factors can greatly impact companies that have set ambitious decarbonization goals and roadmaps, like the 1,430 businesses in the food and consumer goods sectors that have committed to the Science Based Target initiative (SBTi). 

The following are four specific ways AI can play a leading role in reducing supply chain waste to drive improvements in accuracy, speed, and agility.

Demand forecasting.  AI-powered inventory management systems excel in reducing waste by offering key insights into both macro and micro demand trends. By analyzing historical sales data, seasonal patterns and consumer behavior, these systems can accurately forecast demand and ensure that the right amount of product is ordered for each store. This reduces the risk of overstocking and unnecessary waste, and improves product availability for customers.

In the food industry, managers typically handle ordering based on their own observations and limited data. They often don’t consider the macro trends that AI could highlight at the company’s headquarters, ensuring all stores make smarter ordering decisions. Failing to leverage the full scope of demand data creates an environment ripe for food waste — stores order too many wrong, or too few right, products to address their customers’ preferences.

The same benefits of AI-powered demand forecasting apply to consumer goods. These tools provide a high level of visibility into demand trends so that planners can make the best decisions, and ensure there’s enough inventory if a particular product is seasonal.

Replenishing Inventory

Automating replenishment and allocation tasks is another way AI can help deliver high levels of product availability for customers while minimizing waste. By ensuring that the flow of goods is synchronized with real-time demand, businesses can reduce the chances of overstocking and making deep markdowns that often fail to clear excess inventory.

AI-powered systems can optimize and automate routine replenishment and tasks for even the most challenging categories — from fresh and seasonal fruit to new and promoted consumer products. Technology can help accurately forecast the impact of demand drivers like the day of the week, price, promotions, holidays, local events and weather.

By taking the guesswork out of replenishment, AI can help base inventory requirements on accurate store order projections, and proactively leverage supply chain visibility to manage capacity and resource planning. 

Markdown and Clearance Optimization

Retailers face a delicate balance with inventory — it’s economically and environmentally costly to hold onto products too long, but it’s essential to quickly deliver for customers who can’t wait to get their hands on your products. AI can help by dynamically adjusting prices throughout the season, ensuring that products reach consumers before they lose relevance, and avoiding the post-holiday slump that turns potential sales into waste.

Take Halloween, for example. According to The U.S. Department of Energy, roughly 1.5 billion pounds of pumpkins are grown each year, with the majority in high demand between October and December. Only about 20% of them are used for food, while most of the rest end up in landfills. Around Halloween, retailers must minimize how many end up in the trash.

Collaborative Supply Chain Management

Coordination between retailers and producers is vital, especially for products with long lead times, like pumpkins, which require 90-120 days from seed to shelf.

By sharing forecasts and planned orders well in advance, the supply chain can adjust and reduce the risk of over-production and subsequent waste. Suppliers can provide continuous and up-to-date availability, constraints and lead-time information, while retailers can monitor supplier performance for a more reliable, punctual supply, and make more informed business decisions about promotions and price-range changes.

By leveraging advanced algorithms to provide accurate demand forecasts and to optimize inventory levels, retailers and CPGs can work together to reduce waste and improve product availability. This collaborative approach, powered by AI, ensures that the right products are produced and delivered to the right places at the right time, minimizing the risk of overstocking and waste while meeting customer demands.

As more businesses adopt these technologies and share their successes, the potential for AI to transform supply chains and create a more sustainable future becomes increasingly evident. The journey toward reducing waste is not an easy one, but with the help of AI, businesses can overcome the challenges and emerge as sustainability leaders.