Mental models for strategic management: Representation and inference in a management support system.

Abstract

The objective of this research is to present a theoretical framework and to describe a computational representation for the mental models that a manager uses when implementing a strategic plan or when attempting to improve an organization's productivity. A mental model consists of some dynamic internal representation that reflects the essential features and relationships in a corresponding real-world system. An integral part of a mental model includes procedures for examining and manipulating its contents and its structure in order to answer questions about the status of goals or the progress of plans. It is suggested that, for an effective manager, these models incorporate a highly integrated network of concepts and propositional relationships that this manager uses to understand strategies and organizations, to infer relationships among indirectly related concepts, and to initiate communication with other managers. The design for this research includes two case studies which were used to clarify and refine the theoretical concepts about the structure and processing of mental models in strategic management tasks. First, the implementation of a Total Quality Management strategy was studied from the perspective of the Director of Quality Assurance at one division of a large financial services organization. The second study was conducted at a computer manufacturing organization where coordination among functional managers was investigated as they introduced new products to manufacturing. The computational model developed as part of this research, called SPRINT (Strategic Plan and Resource INTegration), is implemented as a frame-based semantic network using a hypertext interface and is programmed in Smalltalk/V286. This model is used to represent some of the knowledge gathered in the case studies as a means to evaluate the adequacy of the representation scheme and to provide insights into the use of a management support system for similar tasks. The contribution of this research consists of: (1) clarifying the notion of mental models as used in managerial decision making; (2) specifying a computational representation which accommodates the theoretical framework and the empirical evidence from these case studies; (3) implementing a computational model which embodies the representation scheme; and (4) suggesting how this computational model would be applicable in a management support system for actual management tasks.