How Does Consumption-Based Forecasting Improve Business Results?

It seems intuitively obvious that the companies who figure out how to best engage with their consumers will get more than their fair share of growth. As a result, integrating consumer demand into the demand forecasting and planning process to improve shipment (supply) forecasts has become a high priority for many companies. Most supply chain professionals are quickly realizing that their supply chain planning solutions have not driven down costs and have not reduced inventories or speed to market. Consumption-based modeling using a process called, “multi-tiered causal analysis” (MTCA) which links consumer demand to supply (downstream data to upstream data), using a process of nesting advanced analytical models. Although this process is not new in concept, it is new in practice. Consumption-based forecasting using the MTCA approach is a simple process that links a series of causal models through a common element (consumer demand) to model the push/pull (sell in/ sell out) effects of the supply chain. It is truly a decision support system that is designed to integrate statistical analysis with downstream (POS and/or syndicated scanner) and upstream (shipment) data to analyze the business from a holistic supply chain perspective.