Camm, Jeffrey D.
(Department of Quantitative Analysis and Operations Management, University of Cincinnati, Cincinnati, Ohio 45221-0130)
,
Chorman, Thomas E.
(The Procter & Gamble Company, Cincinnati, Ohio 45224)
,
Dill, Franz A.
(The Procter & Gamble Company, Cincinnati, Ohio 45224)
,
Evans, James R.
(Department of Quantitative Analysis and Operations Management, University of Cincinnati, Cincinnati, Ohio 45221-0130)
,
Sweeney, Dennis J.
(Department of Quantitative Analysis and Operations Management, University of Cincinnati, Cincinnati, Ohio 45221-0130)
,
Wegryn, Glenn W.
(The Procter & Gamble Company, 2 Procter & Gamble Plaza, PNC-12, Cincinnati, Ohio 45201-5559)
In 1993, Procter & Gamble (P&G) began an effort entitled strengthening global effectiveness (SGE) to streamline work processes, drive out nonvalue-added costs, and eliminate duplication. A principal component of SGE was the North American product supply study, designed to reexamine and reengineer P...
In 1993, Procter & Gamble (P&G) began an effort entitled strengthening global effectiveness (SGE) to streamline work processes, drive out nonvalue-added costs, and eliminate duplication. A principal component of SGE was the North American product supply study, designed to reexamine and reengineer P&G's product-sourcing and distribution system for its North American operations. The methodology developed to solve this problem drew on OR/MS and information technology, merging integer programming, network optimization models, and a geographical information system (GIS). As a result of this study, P&G is reducing the number of North American plants by almost 20 percent, saving over $200 million in pretax costs per year and renewing its focus on OR/MS approaches.
In 1993, Procter & Gamble (P&G) began an effort entitled strengthening global effectiveness (SGE) to streamline work processes, drive out nonvalue-added costs, and eliminate duplication. A principal component of SGE was the North American product supply study, designed to reexamine and reengineer P&G's product-sourcing and distribution system for its North American operations. The methodology developed to solve this problem drew on OR/MS and information technology, merging integer programming, network optimization models, and a geographical information system (GIS). As a result of this study, P&G is reducing the number of North American plants by almost 20 percent, saving over $200 million in pretax costs per year and renewing its focus on OR/MS approaches.
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