In logistics, intelligent process data can help make processes more efficient. At a time when requirements are becoming ever more demanding, this is increasingly important. But simply gathering the data is not enough. This simply leads to a huge big data pool that no one can make sense of. A much better approach is to generate the relevant measurement data straight from the individual steps of the picking process and analyze it. One of the tools that enables this is the business intelligence solution Picavi Cockpit.
How do you make sense of big data? The order picking process contains a huge amount of data that can be used to improve warehouse performance. But this data must be managed intelligently. Anyone working in logistics will tell you that requirements are becoming ever more demanding. Not only is the volume of orders growing, they need to be processed ever more quickly to allow for same-day delivery. This means that pickers need to work as fast as possible, while also avoiding errors.
