Fresh category management - a way to reduce food waste
According to the information from UN, about a third of the food produced for human consumption in the world each year is lost or wasted. And this is about 1.3 billion tons. The highest loss rates are fruits and vegetables.
This creates a huge problem of food waste, which has negative humanitarian, environmental and financial consequences. Retail chains also play an important role in this process, annually writing off tons of products that have to be disposed of, spending resources, money and time on them.
There are various methods to avoid this: selling goods at a reduced price, working with charities, animal shelters or zoos, etc. However, there are other ways to effectively fresh category management that help minimize the write-off of perishable products. Let's understand in more detail.
Prevent a problem or deal with its consequences?
Forecast accuracy and quality have been and remain essential elements in loss prevention. Especially when it comes to fresh category management.
Today's forecasting of demand for perishable goods requires processing huge amounts of information and taking into account factors that affect the forecast, such as weather, promotions, daily fluctuations in food prices, etc. This is almost impossible to do by hand. Moreover, not every software (SW) is able to make an accurate forecast.
And if at the same time, it is still necessary to control the storage conditions of goods and manage the expiration dates of fresh products, the task becomes even more difficult
The write-off of fresh category goods and own-produced goods (culinary) makes up the bulk of food waste in retail. In addition to the traditional write-off caused by product spoilage, there is an additional write-off, which results from the lack of a close relationship with the forecasting solution and production control systems.
The close integration of processes and software solutions for fresh categories management and own production is not only about data integrity and user convenience, but also about forecast accuracy, reducing stocks, and reducing write-offs.
In addition, an important element of the package of measures aimed at reducing losses in perishable categories in partnership with suppliers and ensuring transparency along the entire supply chain.
Analyze your business processes with our demand forecasting and ordering checklist and see what can be improved and automated!
From problem to solution
To turn data streams into accurate forecasts, traditional approaches and stand-alone solutions are no longer enough. The required level of accuracy can only be achieved using artificial intelligence (AI).
Therefore, leading retailers are increasingly using state-of-the-art AI-powered software that can predict demand based on weekly, daily, intraday, and even hourly models, down to store-level granularity for some products.
Fresh category management solutions should:
- Be comprehensive and tightly integrated in terms of SKU information, characteristics and attributes. Also, tight integration in terms of sales data will reduce the time for their synchronization and reduce the number of errors caused by the need to exchange data between disparate systems such as auto-order or category management solutions.
- Process large flows of contextual data in connection with historical data in order to identify and understand previously undiscovered behavior patterns. At the same time, historical data means not only sales figures for the fresh category, but also data on the consumption of culinary products. This makes it possible to predict demand for each store, in each cluster, down to hourly demand, allowing retailers to quickly and efficiently respond to fluctuations.
- To consider not only fresh produce but also the accompanying demand for packaging and additional SKUs such as sauces and dressings to minimize out-of-stocks and reduce wastage.
- To forecast daily production, taking into account the time needed to fulfill the order, defrost and cook the product, as well as offer the optimal quantity of goods to ensure their availability to the customer.
- Track individual SKUs anywhere in the supply chain.
For all questions about demand forecasting solutions or auto-order systems, please contact the specialists: write to [email protected] or fill out the form to order a call back.
In addition, modern solutions are able to support:
- information on ingredients and fresh products: units of measurement, packaging, origin, allergen content;
- all elements of ingredients for recipes, taking into account possible substitutions, as well as the need to deliver some ingredients to the store;
- expiration dates and offer recommendations for correcting the situation so that users can quickly respond and eliminate possible shortcomings.
As practice shows, the use of services based on AI and machine learning can reduce the amount of waste by 40% due to the ability to process large amounts of information faster and, accordingly, make faster decisions in the management of fresh categories.
This will help retailers not only reduce costs and increase the profitability of their own business but also contribute to such an important and noble cause as protecting and restoring the environment.
Want to learn more about fresh category management and reduce wastage? Improve forecast quality, order accuracy, and improve SKU traceability throughout the supply chain? Fill out the form on the website or write to [email protected], and our specialists will provide you with comprehensive information on the selection and implementation of IT solutions for your business.
Based on materials from symphonyretailai.com
