Supply chain analysis – from controlling to optimization

Traditional reporting is out. If you want to be technically and analytically up to date in logistics and supply chain management, you have to understand “data mining”; business intelligence tools are in! But what do we do with all this information? It is certainly extremely important to be able to carry out ad hoc analyses. However, those who are thrown information at them are almost as stupid as those who receive no information. In “information overflow”, important information is often so well hidden that it is almost impossible to find.

The graphic above (source:, which was created by two IBM authors, is interesting. They attempt to distinguish between different types of supply chain analyses. Traditional reporting and data mining are seen as purely descriptive analysis tools. States are described, the user must draw the conclusions himself.

A more intelligent level is achieved by analysis tools that use the existing data pool to make predictions. Alerts, simulation, forecasting and prediction models are the keywords in this area. We are pleased to hear this, as these are key areas in which we have been operating successfully for many years. We work with what-if simulations in many projects. These analysis methods are worth hard cash. Not only do they enable supply chain and logistics analyses to be carried out much more efficiently and cost-effectively, the results are also of a higher quality and more accurate.

However, we have been talking about supply chain optimization in our projects for a long time, with the aim of balancing inventories and delivery readiness or inventory costs and flexibility costs, for example. We are still quite alone in the field. We map the results of such optimization calculations, for example, in decision tables and sets of rules that have little to do with the “old” dispensing parameter optimization, which is still uncharted territory for many of our customers.

These activities place us at level three of the supply chain analysis scale. We are pleased to see that we are obviously heading in the right direction!

Prof. Dr. Andreas Kemmner

Prof. Dr. Andreas Kemmner

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