Most data repositories used for forecasting don’t factor in all demand causal factors like historical event data
Without it, companies struggle to know what drives their demand anomalies. Real-world event data is always changing, difficult to standardize, and often messy with duplicate events and spam. So many teams don’t factor this dataset into their models - creating a huge gap in teams’ analytical efforts.