Data science in the field of logistics
From the vehicles used to the distribution centers: due to the ongoing digitalization, you have an extensive database in almost all processes in logistics.
The possible applications of data science range from higher availability of the vehicle fleet to optimized warehousing to avoid out-of-stock situations.
Take advantage of our know-how as one of the leading data science providers and our many years of experience in implementing analysis projects in logistics. We support you in turning your data potential into competitive advantages.
A selection of questions we have answered in our projects in the logistics industry:
How can the maintenance of a fleet of trucks be optimized?
Implementation of a predictive maintenance approach to predict the occurrence of faults in the vehicles.
How can warehousing in the wholesale trade be improved?
Analysis of customer buying behavior and the effect of past offer promotions to determine when a customer will trigger the next purchase.
What is the right location for a new distribution center?
Determination of the optimal combination of factors for successful locations. Replacing the "gut feeling" factor and reducing the investment risk.
How can picking distances be shortened?
Development of an optimization algorithm to reduce the time required for manual picking by outputting a route-optimized picking list.
How can out-of-stock situations in spare parts warehouses be avoided?
Forecasting future sales by means of time series analyses based on historical sales volumes.
How can logistics on the "last mile" be improved?
Recognition of patterns in the historical delivery processes to derive measures for a more efficient use of the existing transport logistics.