  Formal coordination mechanisms are of growing importance as human-based
service delivery becomes more globalized and informal mechanisms are no longer
effective. Further it is becoming apparent that business environments,
communication among distributed teams, and work performance are all subject to
endogenous and exogenous uncertainty.
  This paper describes a stochastic model of service requests in global service
delivery and then puts forth a cognitive approach for coordination in the face
of uncertainty, based on a perception-action loop and receding horizon control.
Optimization algorithms used are a mix of myopic dynamic programming and
constraint-based programming. The coordination approach described has been
deployed by a globally integrated enterprise in a very large-scale global
delivery system and has been demonstrated to improve work efficiency by 10-15%
as compared to manual planning.
