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Predicting DemandFundaments and latest developments
Chancellor's Professor, The University of Tennessee, USA
Predicting demand is critical to all organizations. Without accurate demand predictions, organizations cannot make efficient and effective plans. World class organizations go through a process of first developing predictions of future demand for their products and/or services and then making organizational plans to meet that demand. Worst-in-class organizations make these... read moreplans without any assessment of how accurate the underlying predictions are (we call this ‘inadvertent forecasting’). The result is overproduction of under-demanded products and services and underproduction of over-demanded products and services. Both are detrimental to organizational performance.
Predicting demand has been consistently recognized as an important capability for organization planning and management. Regardless of industry or whether the organization is a manufacturer, wholesaler, retailer, service provider or government agency, effective demand forecasting helps organizations to identify market opportunities, enhance supply chain relationships, increase customer satisfaction, reduce inventory investment, eliminate product obsolescence, improve logistics operations, schedule more efficient production, and anticipate future financial and capital requirements.
To improve forecasting, organizations increasingly take advantage of computer and information system technologies. Point of Sale (POS) data collection is gathering near-real-time sales movement at a stock keeping unit by location (SKUL) level of detail. Electronic Data Interchange (EDI) is used to transmit detailed sales information throughout various supply chains to product distributors and manufacturers. Forecasting systems that were once housed on large central mainframes are now capable of running on desktop computers and in client server environments. Legacy systems, which have historically been limited to a single forecasting technique for all products and services, are being replaced by systems that select from a series of alternative forecasting techniques or employ a combination of techniques to analyze demand and related information in an effort to improve forecasting accuracy.
While forecasting research continues to pursue improvements in systems and techniques, studies have identified gaps in our understanding of the relationships between systems and techniques used for predicting demand and the behavioral factors associated with the management of forecasting in and across organizations.
The new reality of predicting demand dictates that the developers and users of demand predictions work together with customers and suppliers to bring the power of techniques, salespeople, supply chain partners and intra-organizational functions to bear on improving the process of predicting demand.
This series of talks addresses all these aspects of how organizations can become world class at predicting demand.