In a demand-driven environment where the focus is on meeting customer expectations, accurate demand forecasting is only achieved when a collaborative process integrates various forecasting systems. By adding performance analytics to measure the iterative plan and understand trends, along with exception processing to generate alerts, companies can become even smarter about anticipating shifts in demand. The end result of improved forecast accuracy is reduced inventory cost; better customer service and improved cycle time and fill rates.
During this session, we will discuss the key elements of a collaborative forecasting process, methods for gaining forecast consensus among stakeholders, as well as the technology needed to support the process. A demo that puts all of the discussion points into practice based on a collaborative forecast scenario will also be provided for the benefit of session participants.