The aim of the potential analysis for the furniture manufacturer Vitra AG was the improvement of production planning through a better turnover prediction of its product. The challenge for the company’s forecast was the wide pallette of colours and materials.
In cooperation with Vitra, the SDSC-BW experts developed a predictive model based on the sales figures of the previous year to find hidden information and patterns in the data. In building the predictive models, the team used on the one hand the direct data of the complete time series, and on the other hand, the additionally extracted statistical information, such as average value and autocorrelation from the time series.
The comparative analysis showed that the complex model performed better than a time series model. It could improve forecast accuracy especially for products, of which Vitra AG had difficulty predicting its turnover. The results of the analysis revealed Vitra the great potential of the data for more accurate predictions and that further data analysis can additionally enhance the business processes.
Further information can be found at: www.sdsc-bw.de/vitra
Data Innovation Community
Vitra AG, Smart Data Solution Center Baden-Württemberg
Thomas Schwehr, Vitra AG, Head of Production Central Europe Mishal Benz, SDSC-BW, email@example.com