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Food and Beverages | Monday, November 30, 2020
The baking companies are using real-time analytics so that it can help them to reduce waste.
FREMONT, CA: The retailers tend to order less than they expect to sell if the leftover products cannot be sold the day after. In most situations, the retailers fail to notice that product unavailability can create dissatisfaction among the customers. Companies can use information technology and artificial intelligence to improve their turnover and service level.
In the bakery industry, the retailers order their bread products just in time. Even during the process of production, companies can get changes in order. During the limited time for production, the baker production companies have to produce an accurate number and maintain the quality standard. Such companies have to deal with changes in demand, fluctuations in the production procedure created by several factors.
Meeting the Challenge
The bakery companies collaborate with software manufacturers to develop a predictive sales planning model to predict consumer demand per-day and per-retailer. The machine learning model can improve the availability of fresh bread products and decreases leftovers.
Many software companies are also building an artificial intelligence model that will regulate the exact amount of fresh bread products that are necessary by the supermarkets per day over a more extended period. It can be done by analyzing the transaction details combined with the external data. The model will provide the baker companies with accurate data to automatically produce the exact amount of bread for every supermarket based on demand and specific assortment choices of the retailers. The new technologies will also offer information on predicted demand over a more prolonged period. When the bakeries get to know about the exact production requirement, they can easily suggest promotion slots to the retailers, which will increase demand during overcapacity.
The teams can also implement a data cleaning procedure to filter the cash register's mistakes, like the transaction of large bread that is flushed immediately after being sold. It will help the bakery companies to enhance the quality of data. Feedback from the retailers is also essential during the model's training period as it identifies a pattern. It can be done by collaborating input from the retailers and the increasing amount of data. It will help increase the accuracy of the predictions and increase the retailers' confidence in the model.