Though traditional forecasting methods such as time-series forecasting are good indicators of future sales, in practice, only half the consumer packaged goods items sold in North America have the required two years of historical data necessary for proper statistical analysis that accurately accounts for seasonality. This leads to forecast errors and they particularly become ineffective during volatile markets. For example: in events such as a hurricane, the sales of essential commodities like water can spike up unreasonably. To understand this unexpected rise in demand and to deal with it, historical data is not a good indicator to be considered.