Accurately forecast production requirements for 6 international markets using 2,000 internal and external parameters
No company operates in isolation and is therefore subject to market variations at some level, be it because of raw material price variations or more local constraints on customers. As a consequence, demand forecasting accuracy is most often enhanced by the use of data external to a company: in addition to sales data and information on customer behavior, commodity prices (e.g. oil or copper prices), exchange rates, consumer price indices, or even local temperature variations affect demand levels.
However, which parameters are influencial and at what level is often unknown and difficult to uncover, especially in fast moving markets. This is compounded by large amount of data that are usually available within an industry, from historical variations in raw materials, experts projections, consumer price indices, to temperature and humidity variations, and more. As a consequence, it is likely that a large number of models can provide seamingly good predictions but only a few models are robust, simple, do not overfit the data, and produce reliable forecasts.