HP Enterprise Services Uses Optimization for Resource Planning

Cipriano Santos (), Tere Gonzalez (), Haitao Li (), Kay-Yut Chen (), Dirk Beyer (), Sundaresh Biligi (), Qi Feng (), Ravindra Kumar (), Shelen Jain (), Ranga Ramanujam () and Alex Zhang ()
Additional contact information
Cipriano Santos: HP Labs, Palo Alto, California 94304
Tere Gonzalez: HP Labs, Palo Alto, California 94304
Haitao Li: College of Business Administration, University of Missouri, St. Louis, St. Louis, Missouri 63121
Kay-Yut Chen: HP Labs, Palo Alto, California 94304
Dirk Beyer: MarketShare L.L.P., Los Angeles, California 90025
Sundaresh Biligi: HP Enterprise Business, Bangalore 560 100, India
Qi Feng: McCombs School of Business, University of Texas at Austin, Austin, Texas 78712
Ravindra Kumar: HP Enterprise Business, Bangalore 560 100, India
Shelen Jain: HP Labs, Palo Alto, California 94304
Ranga Ramanujam: HP Enterprise Business, Bangalore 560 100, India
Alex Zhang: HP Labs, Palo Alto, California 94304

Interfaces, 2013, vol. 43, issue 2, 152-169

Abstract: The main responsibility of resource and delivery managers at Hewlett-Packard (HP) Enterprise Services (HPES) involves matching resources (skilled professionals) with jobs that project opportunities require. The previous Solution Opportunity Approval and Review (SOAR) process at HPES addressed uncertainty by producing decentralized project staffing decisions. This often led to many last-minute subjective, sometimes costly, resource allocation decisions. Based on our research, we developed a decision support tool for resource planning (RP) to enhance the SOAR process. It optimizes matching professionals who have diverse delivery roles and skills to jobs and projects across geographical locations while explicitly accounting for both demand and supply uncertainties. It also embeds capabilities for managers to incorporate tacit human knowledge and judgment information into the decision-making process. With its 2009 deployment in Best Shore, Bangalore operations of HPES, the RP tool’s significant benefits include reduced service delivery costs, increased workforce utilization, and profitability.

Keywords: resource planning; workforce optimization; decision support; mathematical programming; supply and demand uncertainty; human knowledge (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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