TITLE: Integrated
Stochastic Resource Planning of Human Capital Supply Chains

SPEAKER:   Mark Squillante

ABSTRACT:

In this talk we present an
integrated
suite of operations research models and methods that supports
the effective
and efficient management and planning of human capital supply
chains by
addressing distinct features and characteristics of human talent
and skills.
This consists of solutions for: (1) the statistical forecasting
of future
demand and resource requirements; (2) a new form of risk-based
stochastic
resource capacity planning; (3) the stochastic modeling and
optimization/control
of supply evolutionary dynamics over time; (4) a new form of
optimal multi-skill
supply-demand matching; and (5) the stochastic optimization of
business
decisions to manage resource shortages and overages. These
solutions include
contributions in the areas of stochastic models and stochastic
optimization/control.
 The suite of models and methods constitutes an end-to-end
solution
that is deployed as an important part of the human capital
management and
planning process within IBM.



Mark S. Squillante is a Research
Staff
Member in the Mathematical Sciences Department at the IBM Thomas
J. Watson
Research Center, where he leads the Applied Probability and
Stochastic
Optimization team.  His research interests concern mathematical
foundations
of the analysis, modeling and optimization of the design and
control of
stochastic systems, including stochastic processes, applied
probability,
stochastic optimization and control, and their applications.  He
is
the author of many research articles across these areas, and has
received
several internal (IBM) and external research awards.  He is a
Fellow
of ACM and IEEE, and currently serves on the editorial boards of
Operations
Research, Stochastic Models and Performance Evaluation.