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HP Enterprise Services Uses Optimization for Resource Planning

Author

Listed:
  • 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)

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.

Suggested Citation

  • Cipriano Santos & Tere Gonzalez & Haitao Li & Kay-Yut Chen & Dirk Beyer & Sundaresh Biligi & Qi Feng & Ravindra Kumar & Shelen Jain & Ranga Ramanujam & Alex Zhang, 2013. "HP Enterprise Services Uses Optimization for Resource Planning," Interfaces, INFORMS, vol. 43(2), pages 152-169, April.
    • Handle: RePEc:inm:orinte:v:43:y:2013:i:2:p:152-169
    DOI: 10.1287/inte.1110.0621
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    References listed on IDEAS

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    Cited by:

    1. Berk, Lauren & Bertsimas, Dimitris & Weinstein, Alexander M. & Yan, Julia, 2019. "Prescriptive analytics for human resource planning in the professional services industry," European Journal of Operational Research, Elsevier, vol. 272(2), pages 636-641.
    2. Chidambaram Subbiah & Andrea C. Hupman & Haitao Li & Joseph Simonis, 2023. "Improving Software Development Effort Estimation with a Novel Design Pattern Model," Interfaces, INFORMS, vol. 53(3), pages 192-206, May.
    3. Zhang, Yucheng & Xu, Shan & Zhang, Long & Yang, Mengxi, 2021. "Big data and human resource management research: An integrative review and new directions for future research," Journal of Business Research, Elsevier, vol. 133(C), pages 34-50.

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