Inventory management
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Machine learning-bases approach with a deep neural network(DNN) at its core, solves an inventory optimization task more effectively than other approacches do. We skip the demand forecasting stage and calculate inventory directly. This means that we won’t have to make wild guesses about demand probability distribution. Instead, a DNN will scrutinize most detailed historical sales data and will consider multiple diverse factors that range from product promotions to store locations, weather conditions, etc. Then it will apply a loss function that will weight holding costs against shortage costs for the projected inventory figure to return the optimal one.
Benefits for the company
Proper management of inventory is essential for e-commerce businesses. The maintenance of the supply chain has become complex today and using inventory data analytics enables businesses to manage inventory effectively. Using machine learning algorithms and predictive analytics enables patterns to be detected that can define inventory strategies.
Feasability
Medium
Type of expertise/ AI domain
Machine Learning and Deep Neural Network
When customers are unable to get what they want when they want it, it’s a major deterrent to retaining them. They will simply move on to the next company that can offer this. They want to receive the right goods at the right time and in perfect condition