{"62518":{"#nid":"62518","#data":{"type":"event","title":"Integrated Stochastic Resource Planning of Human Capital Supply Chains","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETITLE: \u003C\/strong\u003E\u003Cstrong\u003EIntegrated\n          Stochastic Resource Planning of Human Capital Supply Chains\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003E\u003Cstrong\u003ESPEAKER:\u003C\/strong\u003E\u0026nbsp;\u0026nbsp; Mark Squillante\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003E\u003Cstrong\u003EABSTRACT:\u003C\/strong\u003E\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EIn this talk we present an\n        integrated\n        suite of operations research models and methods that supports\n        the effective\n        and efficient management and planning of human capital supply\n        chains by\n        addressing distinct features and characteristics of human talent\n        and skills.\n        This consists of solutions for: (1) the statistical forecasting\n        of future\n        demand and resource requirements; (2) a new form of risk-based\n        stochastic\n        resource capacity planning; (3) the stochastic modeling and\n        optimization\/control\n        of supply evolutionary dynamics over time; (4) a new form of\n        optimal multi-skill\n        supply-demand matching; and (5) the stochastic optimization of\n        business\n        decisions to manage resource shortages and overages. These\n        solutions include\n        contributions in the areas of stochastic models and stochastic\n        optimization\/control.\n        \u0026nbsp;The suite of models and methods constitutes an end-to-end\n        solution\n        that is deployed as an important part of the human capital\n        management and\n        planning process within IBM.\n      \u003Cbr \/\u003E\n      \u003Cbr \/\u003E\n      Mark S. Squillante is a Research\n        Staff\n        Member in the Mathematical Sciences Department at the IBM Thomas\n        J. Watson\n        Research Center, where he leads the Applied Probability and\n        Stochastic\n        Optimization team. \u0026nbsp;His research interests concern mathematical\n        foundations\n        of the analysis, modeling and optimization of the design and\n        control of\n        stochastic systems, including stochastic processes, applied\n        probability,\n        stochastic optimization and control, and their applications. \u0026nbsp;He\n        is\n        the author of many research articles across these areas, and has\n        received\n        several internal (IBM) and external research awards. \u0026nbsp;He is a\n        Fellow\n        of ACM and IEEE, and currently serves on the editorial boards of\n        Operations\n        Research, Stochastic Models and Performance Evaluation.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Integrated Stochastic Resource Planning of Human Capital Supply Chains"}],"uid":"27187","created_gmt":"2010-11-03 12:05:07","changed_gmt":"2016-10-08 01:53:24","author":"Anita Race","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2010-11-16T10:00:00-05:00","event_time_end":"2010-11-16T11:00:00-05:00","event_time_end_last":"2010-11-16T11:00:00-05:00","gmt_time_start":"2010-11-16 15:00:00","gmt_time_end":"2010-11-16 16:00:00","gmt_time_end_last":"2010-11-16 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}