|Project title||Forecasting model for the prognosis of short and medium-term sales by search engine data (ProSuma)|
|Project duration||01.06.2016 – 31.05.2018|
The planning of delivery dates and sales volumes presents a challenge in the enterprise logistics planning. This planning is complicated by hardly forecastable sales fluctuations for example caused by promotion. Deficiently forecasted sales lead to supply shortages and with it to poor logistics performance, whereas overestimated sales cause increased logistics costs due to inventory and capital commitment. Conventional forecasting methods show deficits in countering this uncertainty because of low data timeliness, low level of detail and extensive effort.
The aim of the research project is to develop a forecast model for sales volumes on specified product level based on search engine data. It is expected that, in comparison to conventional forecast models, the forecast error can be reduced as well as the forecast horizon can be increased. Overall, the central issue is to ascertain whether and to what extent the logistics performance can be improved by search engine data-based forecast.
Master thesis, Bachelor thesis, Project thesis