Delegation Technologies: Environmental Scanning with Intelligent Agents

Abstract:

Identification and evaluation of relevant trends and patterns are critical steps in an organization’s business environment monitoring. Not surprisingly, the “experts” that perform this evaluation are seldom skilled in all the disciplines necessary to accomplish a thorough evaluation of the environmental indicators. While one expert may be skilled at recognizing the potential for political turmoil in a foreign nation, another at Motorola is skilled at recognizing how Japanese government deregulation is meant to complement the development of new products. Moreover, these experts often benefit from each other’s skills and know ledge in assessing activity in the organization’s environment. Often the interchange among variously skilled analysts becomes a distributed problem-solving activity that creates the high-quality, interdisciplinary analysis essential for an effective environmental monitoring activity. Problems in the environmental monitoring process often occur when a particular expertise, an agent in the problem-solving network, is unavailable, and knowledge from that domain does not playa role in the analysis. The focus of this paper is on the distribution of expertise and the sharing of knowledge in the critical process of environmental monitoring. A technical approach is adapted in this effort—an architecture and a prototype of “delegation technologies” are described that provide the capability of capturing, organizing, and distributing knowledge that may be used by experts in classifying patterns of qualitative indicators in the business environment. The redistribution of responsibilities through the delegation to, and coordination of, intelligent agents is examined.

Key Words and Phrases:

• blackboard model
• delegation technology
• environmental scanning

Additional information

Notes on contributors

Gregg Elofson

Gregg Elofson is Assistant Professor of Computer Information Systems in the College of Business Administration at the University of Miami. He holds a Ph.D. in MIS from the University of Arizona. His research interests include the relationships between organizational learning, attention, design, and information technology; distributed decision making; and knowledge-based systems. He has published conference proceedings and book chapters, and has served as a staff scientist in the artifical intelligence architectures group for Science Applications International Corp., and as a consultant for Andersen Consulting.

Benn Konsynski

Benn Konsynski is a Visiting Professor at the Harvard Business School. Prior to that he was a professor at the University of Arizona, where he was cofounder of the university’s group decision support laboratory. He received his Ph.D. in computer science from Purdue University. His current research interests are organizational and information systems design issues. He has published in such diverse journals as Communications of the ACM, Harvard Business Review, IEEE Transactions on Communications; MIS Quarterly, Journal of Management Information Systems, among many others.