Abstract :
For many organizations today building goods and services over a period of time, the continuous production of documented product development information is necessary for immediate as well as future internalization and reuse. Especially, in an environment where multiple, often geographically dispersed, teams of workers are involved, it becomes imperative that the information be generated in optimally balanced distributions of project resources, so that it can be disseminated and reused efficiently. We introduce in this study a model to address this problem. The model is validated by formulating its structure on the essential characteristics of the underlying problem domain. To simulate development situations where creative human endeavor is more emphasized than automated applications of routine procedures, we use a set of human-centered input decision variables and examine the optimal output production relative to their dynamics and control. Our model is not tied to the characteristics of any individual project per se but can be easily modified and generalized to address other allied types of production situations. Simulations are performed for a variety of practical decision-making scenarios. Our results suggest that workers´ contextual work experience, interactions, and background learning all govern production optimality, although nonuniformly in distinct temporal domains of development.
Keywords :
decision making; management information systems; product development; production engineering computing; production management; team working; workflow management software; decision-making scenario; distinct temporal domain; documented product development information; human-centered input decision variable; optimal balanced distribution; optimal information production; optimal output production; product development environment; project resources; routine procedure; worker contextual work experience; Context; Humans; Input variables; Optimization; Product development; Production; Software; Managerial decision making; numerical simulations; optimal production; performance and learning rates; resource distribution;