Using Weather Analytics to Reduce Food Waste

Using Weather Analytics to Reduce Food Waste

It is estimated that over one-third of all food produced globally is wasted. Approximately 40% of this waste comes from within the retail supply chain. Some of the most common causes of this are spoiled fruit and vegetables, expired meats, and other items that are no longer ‘fresh.’ This translates into over a half a billion tons of food thrown away each year. This food waste accounts for about 3% of global carbon emissions.

Whether motivated by the food waste epidemic, climate change, the growing desire of consumers to support sustainability-minded retailers, or impending carbon taxes, many food producers and retailers have defined goals to reduce their food waste and carbon footprints. This includes investing in systems and processes to bring about meaningful and measurable improvements to their business.

Understanding Demand Signals

Retailers and businesses in the food supply chain are increasingly turning to analytics and technology to help address this problem. Often, the solution begins with understanding how existing systems and processes can be improved. Common areas to focus on include demand planning and replenishment.

Retailers can reduce the amount of waste they produce simply by improving their forecasts. There are a lot of approaches to do this, which all come back to better understanding and anticipating customer shopping patterns. One factor to consider is the weather. No other external variable shifts consumer buying as frequently, immediately, or directly as the weather.

Most retailers lean heavily on recent performance to determine how much to replenish in different regions or individual stores. While recent sales trends are important, they are distorted by weather conditions and do not factor in how upcoming weather conditions are going to change sales volumes.

Planalytics, an SAP partner, measures the impact of weather. The quantification of weather’s impact is called Weather-Driven Demand (WDD). WDD precisely calculates when, where, and how much demand for specific products increases or decreases due to changes in the weather. Planalytics WDD values integrate into SAP at scale to enable retailers to proactively manage the impact of weather and improve both preseason planning and in-season inventory management. Using weather as a demand signal in SAP can enable retailers to ensure they have the right amount of perishable products on the shelves to match consumer demand on a localized level.