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Demand and order‐fulfillment planning: The impact of point‐of‐sale data, retailer orders and distribution center orders on forecast accuracy
Author(s) -
Narayanan Arunachalam,
Sahin Funda,
Robinson E. Powell
Publication year - 2019
Publication title -
journal of operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.649
H-Index - 191
eISSN - 1873-1317
pISSN - 0272-6963
DOI - 10.1002/joom.1026
Subject(s) - demand forecasting , order (exchange) , supply chain , point (geometry) , operations research , computer science , distribution center , supply and demand , distribution (mathematics) , supply chain management , business , operations management , marketing , economics , microeconomics , finance , mathematics , mathematical analysis , geometry
Industry consultants claim that investing in systems that base forecasting on point‐of‐sale (POS) data throughout the supply chain will improve forecast accuracy. We explore what actually happens to forecast accuracy for demand and order‐fulfillment planning when the forecast demand signal is based on POS, retailer orders, or distribution center (DC) orders. We begin by comparing the forecast accuracy for different demand signals using daily demand and operating data from a large consumer‐products supply chain. We then extend the analysis by varying the demand and supply‐chain parameters to evaluate their impact on demand signal performance. We find that POS data improve forecast accuracy for demand planning but not for order‐fulfillment planning. These findings thus challenge consulting‐firm claims about the ability of POS‐based forecasting systems to improve forecast accuracy across all contexts.