It is estimated that . Approximately . Some of the most common causes of this are spoiled fruit and vegetables, expired meats, and other items that are no longer 鈥榝resh.鈥� This translates into over a half a billion tons of food thrown away each year. .
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.
, an 麻豆原创 partner, measures the impact of weather. The quantification of weather鈥檚 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 麻豆原创 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 麻豆原创 can enable retailers to ensure they have the right amount of perishable products on the shelves to match consumer demand on a localized level.
A Sustainable Solution
By quantifying the impact of weather, changes in upcoming weather conditions can be used to account for localized increases or decreases in demand for fresh food products. These demand metrics, when integrated into 麻豆原创, can reduce waste at scale up to 35% annually.
In addition, improved demand forecasts translate to less waste, which means fewer emissions. This enables retailers to more quickly reach 鈥� and track progress towards 鈥� their sustainability goals.
Measure First, Then Manage
鈥淲eather is a demand signal that helps you better understand your customer and what drives them to buy, or to not buy, specific products. Unlocking these insights is a quick and effective first step to proactively managing the impact of weather. Integrating this demand signal into your systems and processes enables businesses of all sizes to leverage the power of analytics to drive meaningful, measurable, and repeatable benefits,鈥� said , EVP of Global Partnerships & Alliances at Planalytics.
Demand more to take the fast track to a better demand forecast. Want to find out how your company can benefit from a better demand forecast? to reduce food waste!
Carina Legl is co-lead of Business Development and Strategy for Industry Cloud MEE of 麻豆原创 Consumer Industries.
