Sensing, Shaping, and Linking Demand to Supply: A Case Study Using MTCA
Integrating consumer demand into the demand forecasting process to improve shipment (supply) forecasts has become a high priority in the consumer packaged goods (CPG) industry as well as in many other industries over the past several years. Until recently, many factors, such as data collection and storage constraints, poor data synchronization capabilities, technology limitations, and limited internal analytical expertise, have made it impossible to integrate consumer demand data (i.e., point-of-sale [POS]/syndicated scanner data from ACNielsen/Information Resources Inc. [IRI]/Intercontinental Marketing Services [IMS]) to shipment forecasts. This chapter outlines a framework using multi-tiered causal analysis (MTCA) that links demand to supply using a process of nesting causal models together using data and analytics. Although this process is not new in concept, it is new in practice. With improvements in technology, data collection and storage, and analytical knowledge, companies are now looking to integrate consumer demand with their shipment forecasts to capture the impact of marketing activities on supply. As a result, MTCA is receiving renewed interest. MTCA is a process that considers marketing and replenishment strategies jointly rather than creating two separate forecasts (i.e., one for consumer demand and another for factory shipments).
Since the early 1990s, the CPG industry has been moving ...