Supply Chain Design & Controlling
Forecasting of future scenarios plays an important role in the optimization of logistic networks as well as in intra-logistics. Forecasting as such already is a rather complex task. Furthermore, by only considering quantitative aspects other important changes are such as the range of articles or order structures. In order to cope with the diverse changes in the supply chain we developed sophisticated statistical methods and implemented them in W2MO to provide the extrapolation of amounts, articles and structures.
By changing some parameters one can calculate, e.g., the changes of amounts, number of articles and order structures. These generated scenarios can be taken as a basis for the further supply chain and intra-logistics optimization. The entire dynamic of the distribution process is extrapolated as well, affecting, e.g., inventory.
The extrapolation approach enables new articles, orders and orderlines based on existing data. Using the current data the logistics services can be tested. To extrapolate the current order structure the extrapolation algorithm creates new orderlines and reassigns them to new orders. Changing of input parameters determines whether there will be increases or decreases in the respective dimensions.
For instance a scenario with a descreasing number of orderlines per order can be easily obtained by setting the value -20% (decrease of 20%). In the same way with an increase. The algorithm changes the defined structures in such a way that the default values are achieved by changing as little as possible of the current structures. That's why W2MO includes various statistical approaches.
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