In our latest conversation with Progressive Grocer, we discussed how food waste has impacted grocery retailers and how one single centralized solution helps to drive waste reduction.
Food retailers generate 10.5 million tons of food waste annually, sending almost one-third of wasted food to landfills. With retailers at the center of the supply chain, they have the power to influence, drive efficiency within their stores, and communicate with their customers to reduce their waste.
In today’s world, grocery retailers are facing production planning challenges due to changing demand, inflation, supply chain issues, and labor shortages. Coupled with these macro challenges, grocery retailers are also facing increasing pressure from consumers and government agencies, like the EPA, USDA, and FDA, to take measurable action when it comes to food waste reduction.
Changing consumer behaviors are pushing Fresh to the forefront and it’s important to remember that Fresh isn’t just a concern for produce departments, it affects the entire perimeter business. With the enemy of Fresh being time, a key challenge for grocery retailers is to avoid over ordering and over producing. Both of those issues are easily done when you are operating without having the right forecasting data to understand shifts in demand throughout the day and week. Over production is a key contributor to increased waste, reduced margins, and non-sustainable operations.
When it comes to waste reduction, grocery retailers need to have greater visibility and control over their operations – whether in-store or commissary – from production planning to recipe management to fresh ordering. The question for grocery retailers is how can this be achieved?
Centralized Production Planning to Drive Waste Reduction
Having the right information at the right time and knowing how to operationalize the data makes the difference in profits, performance, and sustainability. To win in Fresh, grocery retailers must implement the right fresh-native technology to balance demand with supply and availability.
Invafresh allows grocery retailers to always have visibility and control across all their Fresh operations, whether in-store or commissary. Grocery retailers know that with Invafresh they deliver the most efficient and effective production planning solution on the market, allowing them to deliver a fresher experience for their customers, maximizing store revenue and minimizing food waste.
By taking a centralized approach to production planning, Invafresh provides grocery retailers with demand driven replenishment capabilities from both their in-store and commissary operations, based on perpetual inventory, merchandising requirements, and forecasts, to always maintain the freshest stock possible. This approach leads to a 50% reduction in replenishment time, 25% reduction in backroom inventory, and 30% reduction in shrink.
Built on an innovative and intuitive mobile-centric user interface, Invafresh’s Fresh Retail Platform (FRP) automates production planning for grocery retailers by providing real-time updates to production plans based on critical in-store data, such as inventory and demand, and enables retailers to accurately forecast required production requirements.
Price Chopper Slices Weekly Waste
By using Invafresh, Price Chopper now prevents 20 tons of fresh food from being wasted each week and is projected to prevent more than 3,000 tons of food waste over the next three years across its 131 stores. This reduces its methane emissions from landfills, lessening its carbon footprint, and helping to fuel a more sustainable, circular economy. They achieved this by integrating vast amounts of data into machine learning forecasting algorithms that allowed them to align supply and demand, with accurate merchandising, replenishment, production planning, and inventory control.
The FRP from Invafresh contributes to $150 million of food waste eliminated annually and 30% less shrink across 25,000 stores by optimizing forecasting and inventory management systems throughout production and operations with demand planning informed by artificial intelligence and machine learning.