Choosing the optimal distribution of purchases among the suppliers.

I. The Challenge

The challenge we faced was to develop advanced algorithms to optimise decisions about the distribution of raw material purchases among several available suppliers in the packaging industry. Our Client’s organisation had many variables and limitations which had to be considered each time a decision was made. At the same time, some data was difficult to measure, while most of it was subject to dynamic (e.g. daily) changes. Our Client was a manufacturer of paper and paper packaging, one of the European leaders in this industry. Their goal was to implement the GORDION analytical engine that would generate savings and clear up and facilitate the process through optimisation of raw material ordering.

II. Action

First, we gathered information about the key limitations and data related to the procurement process. In the next step, we sorted out the sources of this data and reduced it to a “language” understood by our GORDION analysis engine. We then taught the program to interpret the data and calculate the optimal operating scenario. Finally, we created the right reports to reduce human work as much as possible.

Work on the implementation was based on the goal of the least possible involvement of the Client’s team and maximum automation of data collection reporting results.

GORDION is based on advanced algorithms that select an optimal scenario from thousands of available options and on elements of artificial intelligence to learn from consecutive cases.

III. Solution

Initially, the implementation was to include factories in Poland. However, after obtaining the first effects, the Client decided to implement it in all his factories in Europe! GORDION allows them to generate savings of between 1.5% and 5% of the purchase value per year. It eliminates errors and minimises the time of human involvement in the process. GORDION indicates the costs of taking decisions in a simple way, enabling the optimisation of subsequent areas.