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SylviaLudwig
Employee
Employee


How to reduce food waste in retail with better planning

Food waste is global topic that concerns all of us. Almost a third of all food produced is wasted every year according to research of the United Nations. This is estimated to be 930 million tons of food in 2019.

The fact that this huge amount of food is produced and not eaten by humans has substantial negative impacts. Not only to the loss of food as such but also for the climate of our planet. Estimates suggest that 8-10% of global greenhouse gas emissions are associated with food that isn't consumed. It needs to be grown which consumes resources but also it has to be disposed.

If food waste could be represented as its own country/region, it would be the third largest greenhouse gas emitter, behind China and the United States.

Can technology help to reduce food waste?

When we look along the supply chain, there are several stages where food gets wasted and there are many different reasons for it. It starts with the food production and ends with households. Whereas some circumstances are difficult to control from a planning perspective such as diseases or contamination, it gets more tangible when going further down to the Retail sector. Overstocks - too much food with short shelf life left in shelves – this is the main reason for retailers that food gets wasted.

How could better planning help to avoid and reduce food waste of fresh products such as convenience food, meat, fish, fruits, and vegetables, bread in retail?

With scientific demand forecasting and intelligent replenishment planning, retailers can get the right balance between revenue and spoilage/cost. They can achieve better product availability and reduce inventory at the same time and reduce wastage of fresh food.

How does this work in detail?

The fundamental thing in all retail supply chain planning processes is to know what customers want to purchase, how much and when. And for fresh food this is even more important because everything that is overstock will get waste. At the same time retailers want to make sure that customers who walk into a store find exactly what they want, also for these short-shelf-life items because they are important to attract and retain customers.

The first step consequently is a smart and precise forecast, based on granular daily sales data. It should consider all important influences on sales like promotions, events, public holidays, trends, and other relevant factors such as weather. If sales trends change, it must be self-learning and self-adjusting to cope with new situations automatically – in essence Machine Learning´.

The next step is optimal replenishment in the stores. Important points to call out are:

  • Consider shelf-life information and factor in potential spoilage

  • Balance waste against out-of-stock considerations

  • Base your replenishment on real-time inventory information and if needed use intraday schedules for multiple deliveries a day

  • Look at delivery schedules and pack sizes - are they set up in an optimal way? Or is it better to order more frequently or smaller pack sizes to reduce potential spoilage?

  • Share information along the supply chain, internally and externally, for better alignment and a sustainable supply chain planning


But how to make this happen?

Part of SAP’s sustainability portfolio is SAP Replenishment Planning. This solution is an add-on of the SAP Customer Activity Repository and part of its end-to-end planning suite. As such it uses the underlying Unified Demand Forecast (UDF), a sophisticated AI based retail forecast, well suited for fresh products. It's a true day forecast that can even provide intraday insights if necessary. SAP Replenishment Planning has besides to its general store replenishment capabilities a strong focus on fresh assortments:

  • Cost-optimal ordering by considering expected spoilage of a product but also lost sales probabilities

  • Intraday replenishment possibilities and planning on SAP CAR’s real-time stock data

  • Simulation of parameters based on KPIs, for example what if pack sizes or order schedules were different -would this result in less waste?


And it's easy to work with - in case something exceptional has to be reviewed planners are guided by alerts to take action.

Are you curious? See for yourself in this 2-minute video!

Further information can also be found on this one pager about the solution.