Higher-order organizational learning occurs when a company adopts new principles, assumptions, and paradigms, which often turn into competitive advantage. Systems development and implementation offer an opportunity for higher-order organizational learning that is rarely exploited. Advanced information systems, in particular expert systems (ES) and executive information systems (EIS), provide ample opportunities for higher-order organizational learning if the development process is structured in certain ways. This work includes an analysis of three organizations in terms of project outcomes, organizational learning outcomes, and organizational performance. On the basis of these assessments, five critical success factors are identified that may contribute to organizational learning during advanced system development. The relationships between these factors and organizational outcomes are summarized in a preliminary model that can form the basis for future research. The work closes with some recommendations for ways information systems managers can encourage higher-order organizational learning during advanced system development.
Preservation of organizational memory becomes increasingly important to organizations as it is recognized that experiential knowledge is a key to competitiveness. With the development and widespread availability of advanced information technologies (IT), information systems become a vital part of this memory. We analyze existing conceptualizations and task-specific instances of IT-supported organizational memory. We then develop a model for an organizational memory information system (OMIS) that is rooted in the construct of organizational effectiveness. The framework offers four subsystems that support activities leading to organizational effectiveness. These subsystems rest on the foundation of five mnemonic functions that provide for acquisition, retention, maintenance, search, and retrieval of information. We then identify the factors that will limit the success of OMIS implementation, although full treatment of this issue is outside the scope of the paper. To initiate a research agenda on OMIS, we propose an initial contingency framework for OMIS development depending on the organization's environment and its life-cycle stage, and discuss the relationships between an OMIS and organizational learning and decision making.
The purpose of this work is to introduce a systematic method for identifying expertise (knowledge identification). The technique, borrowed from the social sciences and known as network analysis, may be used to identify human experts as well as documented sources of knowledge within organizational settings. Network analysis is simple to administer, cost-effective, and complements interview methods. Following a discussion of the theory underlying the technique, its application in a field setting is demonstrated. The results are checked against what would be expected due to chance, and cross-validated through interviews. To ensure the efficacy of the method, knowledge identification at a second site is briefly described. The work closes with some ideas for future management information systems research using network analysis.