If the potential of data analysis in logistics is used correctly, it is possible to proactively respond to customers’ many different needs. This then creates a better shopping experience. Greater warehouse efficiency and procedures that are better planned and prepared have a positive effect on customers’ experience. Logistics companies can specifically adapt to fluctuations in demand and order peaks by analysing data. For example, how long does it take to pick or pack an order? Resources like employees, warehouse space and infrastructure can be sensibly assigned if this kind of analysis work has been completed.
Regardless of which processes are involved, it is important to ensure that the incoming data is reliable and matches the real situation. The challenge here is whether a direct link to the original source of the data is possible, regardless of the storage space. If there is no direct link, CSV files are used, but they need more storage space and also slow down the analysis processes. In this case, it is preferable to download the largest data models at night when the server load is lowest.