It should measure the impact of events on demand behavior, identify patterns in which sales may increase suddenly and investigate the causes of these behaviors to be able to weigh them and forecasting their impact towards future. It is necessary to measure the performance of forecast comparing actual value vs the pronosticado, identify causes and take action. It is very important to have a tool that allows modeling this kind of situations.Review and ConsensoCabe recorded as qualitative adjustments are will continue performing for those references in which the history of past events (promotions, advertising etc.), or those who were not studied during the meetings of predemanda has not been incorporated. Once generated, the Statistical forecasts are reviewed with the demand planning team in order to include those new products that should be predicted, which should be excluded from the forecast Statistician and finally those that require additional information. As result of this review will reach a consensus on the statistical prognosis. After reaching consensus on the statistical prognosis are formalized scheduled reviews which involves the departments of sales, Marketing, operations and management.
The reasons for the additional changes include new planned promotions, winning or losing major clients, contraction of production, and actions directives orientadasa to align sales with strategic objectives of the company as the decision to promote a particular product to achieve the projected market share. Conclusion many companies taken as base forecasts generated from software to start its cycle of demand Planner, then make manual adjustments to knowledge of sales, marketing and operations group. To incorporate and formalize knowledge within the construction of forecasts basis can increase the accuracy of the forecast between 10% and 15% and reduces the manual settings in approximately 40%.
