Inventory Requirements Planning at Lucent Technologies

Alex Bangash (), Ramesh Bollapragada (), Rachelle Klein (), Narayan Raman (), Herbert B. Shulman () and Donald R. Smith ()
Additional contact information
Alex Bangash: Rumson Capital Advisors, Princeton Corporate Center, 5 Independence Way, Suite 300, Princeton, New Jersey 08540
Ramesh Bollapragada: Decision Sciences Department, College of Business, San Francisco State University, San Francisco, California 94132
Rachelle Klein: 147-34 70th Road, Flushing, New York 11367
Narayan Raman: Lucent Technologies Bell Labs, 101 Crawfords Corner Road, Room 4L-463, Holmdel, New Jersey 07733
Herbert B. Shulman: AT&T Corporation, 200 Laurel Avenue, Middletown, New Jersey 07748
Donald R. Smith: Department of Management, Monmouth University, 400 Cedar Avenue, West Long Branch, New Jersey 07764-1898

Interfaces, 2004, vol. 34, issue 5, 342-352

Abstract: The inventory requirements planning (IRP) system is a decision-support tool that Lucent has used to determine its buffering requirements for parts in a time-phased provisioning system. It measured the deviation of actual supply and demand from their planned values and, using the historical profile of these deviations, determined the safety-stock levels Lucent needed to meet the desired service levels. In doing so, it quantified the relationships among the inventory drivers: supply intervals, demand and supply variability, desired service levels, and part proliferation. It used these drivers to identify and drive initiatives to improve processes to reduce uncertainty in the provisioning process. Several Lucent locations have used the IRP system to realign inventories and to improve service in various manufacturing and distribution facilities. The IRP system's value has been recognized through several awards. It also contributed to Lucent's receiving the Malcolm Baldrige Award in 1992 (as a part of AT&T Corporation) and subsequently the INFORMS Prize in 1998.

Keywords: inventory; production; applications; information systems; decision-support systems (search for similar items in EconPapers)
Date: 2004
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