🎤 Logistics and data: towards a decision support tool
- 👤 Charlotte Ledoux
- Twitter: @LedouxCharlotte
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Slides:
https://www.slideshare.net/CharlotteLedoux/logistics-and-data-towards-a-decision-support-tool
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Video:
https://youtu.be/JrlLxljwupM
In logistics services, the only way to grow is to reduce costs, as this is a cost centre for many managers. On average, in France and in all business sectors, logistics costs represent between 8 and 10% of sales. Data science and associated tools can help reduce these costs while improving customer satisfaction. This means faster delivery, lower costs and fewer errors. Take, for example, a situation of over-stocking of maintenance parts in all warehouses: this implies high capital costs (space, obsolescence, etc.) and it is normal for companies to seek to optimise their inventory levels while guaranteeing a sufficiently high service rate. Once the best model is found for predicting the consumption of maintenance parts, the importance of business rules is critical for parts that cannot be modeled. Charlotte also discusses the choice of an optimal model by the inventory manager, which parameters are analyzed? Finally, successful integration of the model into the value chain is based on business ownership. Keep in mind that a model intelligence requires human intelligence to be adapted to a specific context.
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