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OnTheMark: Integrated Stochastic Resource Planning of Human Capital Supply Chains

Author

Listed:
  • Heng Cao

    (Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598)

  • Jianying Hu

    (Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598)

  • Chen Jiang

    (Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598)

  • Tarun Kumar

    (Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598)

  • Ta-Hsin Li

    (Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598)

  • Yang Liu

    (Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598)

  • Yingdong Lu

    (Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598)

  • Shilpa Mahatma

    (Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598)

  • Aleksandra Mojsilović

    (Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598)

  • Mayank Sharma

    (Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598)

  • Mark S. Squillante

    (Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598)

  • Yichong Yu

    (Business Analytics and Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598)

Abstract

In this paper, we present a suite of innovative operations research models and methods called OnTheMark (OTM). This suite supports the effective management of human capital supply chains by addressing distinct features of human talent that cannot be handled via traditional supply chain management. OTM consists of novel solutions for (1) statistical forecasting of demand and human capital requirements, (2) risk-based stochastic human-talent capacity planning, (3) stochastic modeling and optimization (control) of human capital supply evolutionary dynamics over time, (4) optimal multiskill supply-demand matching, and (5) stochastic optimization of business decisions and investments to manage human capital shortages and overages. The OTM suite was developed and deployed as an important part of the human capital management and planning process within IBM, providing support for decision making to drive better business performance. This is achieved through important contributions in the areas of stochastic models and optimization (control), and the innovative application and integration of these models and methods in human capital management applications.

Suggested Citation

  • Heng Cao & Jianying Hu & Chen Jiang & Tarun Kumar & Ta-Hsin Li & Yang Liu & Yingdong Lu & Shilpa Mahatma & Aleksandra Mojsilović & Mayank Sharma & Mark S. Squillante & Yichong Yu, 2011. "OnTheMark: Integrated Stochastic Resource Planning of Human Capital Supply Chains," Interfaces, INFORMS, vol. 41(5), pages 414-435, October.
    • Handle: RePEc:inm:orinte:v:41:y:2011:i:5:p:414-435
    DOI: 10.1287/inte.1110.0596
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    Citations

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    Cited by:

    1. Michael J. Davis & Yingdong Lu & Mayank Sharma & Mark S. Squillante & Bo Zhang, 2018. "Stochastic Optimization Models for Workforce Planning, Operations, and Risk Management," Service Science, INFORMS, vol. 10(1), pages 40-57, March.
    2. Kyomin Jung & Yingdong Lu & Devavrat Shah & Mayank Sharma & Mark S. Squillante, 2019. "Revisiting Stochastic Loss Networks: Structures and Approximations," Mathematics of Operations Research, INFORMS, vol. 44(3), pages 890-918, August.

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