The retail world has been under high pressure in recent years, particularly following the emergence of e-commerce players such as Amazon. The habits and demands of the consumer have been drastically transformed as a result.
Today, they want a personalized product, available quickly, eco-responsible, and moreover inexpensive.
This level of demand requires mass retailers to manage more references and introducing new ones more and more frequently.
Added to this is the need to manage multi-channel distribution with new demand and sales channels such as the Internet and home delivery.
In order to maintain margins, retailers need to adopt new technologies such as big data, AI, and blockchain to implement more agile and reliable supply chains.
The major challenges for retail supply chains to reduce operating costs and gain market share are to track customer demand at the point of sale and pass it on as quickly as possible to regional distribution centers and suppliers, and to minimize stocks for an increasingly regionalized product mix.
Flowlity fits every specificities
Specialised distribution (DIY)
Optimization of packaging material stocks
One of the major players in distribution and e-commerce called on Flowlity to optimize its packaging material stock. We are talking about minimizing the stock levels of the material used to package the products before shipment, such as boxes, bags, labels, etc.
The increase in activity has led to the need to increase the storage space. An additional warehouse needed to be used and transportation between this warehouse and the shipping facility was set up at a frequency that varied between daily and weekly, depending on the volume of activity.
This way of operating therefore involves higher operational costs.
Average stock level reduction
Flowlity showed that it is possible to reduce the average stock level of these products by 40%.
This has led to a significant reduction in operating costs related to the management of these components.
Correctly predicting the needed amount of packaging material requires not only to accurately forecast the sales volume but also to precisely determine what the size of each order will be. Indeed, depending on the number of items to be shipped, the size of bags and boxes to be used varies.
Flowlity’s artificial intelligence algorithms have made it possible to overcome this problem and therefore make a better forecast of the consumption of these components.
Flowlity has won over our client’s users and managers, not only by the results on operational costs but also by its pleasant interface and its ease of use.
Following this success, we plan to roll out the use of the tool to the packaging suppliers.
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