Development of a forecast model from historical data

Challenge

• The aim is to develop a dashboard that displays material consumption at different granularities

• In addition, an algorithm is to be developed that predicts material requirements in order to have a more precise purchasing lever of quantity commitments and price scales.

Solution

• Linking of purchase orders, framework agreements, scaled quantities and prices, quantity commitments, call-off information and material master data

• Categorisation of master agreements and master agreement items based on term, target value and quantity commitments

• Investigation of ordering behaviour and price variance at material number level

• Creation of a forecast model using ML methods on the basis of historical order quantities at material number level per business area

Result

• Mapping actual data on material consumption at different granularities using KPIs

Challenge

An automotive company would like to visualise various market-specific data in order to create a Competitive analysis for the US market.

Solution

There will be a interactive and Flexible application, including of different maps with two different views implemented.

Result

Relevant markets are identifies, analyses and visualises. The dealer or the respective sales department have the possibility to compare the direct competition with their own product and to visualise the relevant data.