WHEN PROCESSES LEARN - STEPS TOWARD CRAFTING AN INTELLIGENT ORGANIZATION

Two trends in information systems research provide an opportunity to a dd an additional link between information technology and organizationa l learning. First, there is an increasing penetration of information t echnology into the firm's processes and structures. Second, research i n artificial intelligence has given rise to the first generation of fu lly computational architectures of general intelligence. In this resea rch note we explore a melding of these two trends. In particular, we p resent the crafting of an organizational process which can learn, and develop and apply a new set of organizational learning metrics to that process. The process is a simplification of a complex, parallel-machi ne production scheduling task performed in a local manufacturing firm. The system Dispatcher-Soar, generally supports a symbolic, constraint propagation approach based, in part, on the reasoning methods of the human scheduler at the firm. The implementation of this process is bas ed on a dispatching rule used by the expert. The behavior of Dispatche r-Soar centered around a small case study examining the effects of sch eduling volume and learning on performance. Results indicated that the knowledge gained can reduce within-trial scheduling effort. An analys is of the generated knowledge structures (chunks) provided insight int o how that learning was accomplished and contributed to process improv ements. As the knowledge generated was in a form standardized to a com mon architecture, metrics were used to evaluate the production efficie ncy (eta(prod)), utility (eta(util)), and effectiveness (eta(eff)) Of the accumulated organizational knowledge across trials.