A comparative study of task domain analysis to enhance organizational knowledge management: Systems thinking and Goldratt's thinking processes



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Texas Tech University


The focus in this research is the evaluation of the effectiveness of two problem solving or task analysis methodologies in order to enhance of knowledge management in organizations. The two methodologies are systems thinking and Goldratt's thinking processes.

One of the goals of the research is to investigate the effectiveness of the two theories in managing task domains when controlling for individual differences. The effectiveness of each methodology relative to task domain is investigated. The synergies between the two theories are also investigated. In this research, knowledge management centers more on humans rather than on computers.

As a leadoff, a background overview of knowledge and knowledge management is first presented. Within the context of knowledge management, the subject of task analysis or problem solving is then presented. The literature on problem solving is surveyed and a research model using the two methodologies of interest is developed and validated. Fundamentally, knowledge management has to do with the creation of explicit processes that enhance knowledge and learning throughout the organization. Knowledge could be defined more generally as "any text, fact, example, event, rule, hypothesis, or model that increases understanding or performance in a domain or discipline" (Liebowitz and Beckman, 1998, p.49). Maintaining this perspective, knowledge management is defined as "the systematic, explicit, and deliberate building, renewal, and application of knowledge to maximize the enterprise's knowledge-related effectiveness and returns from its knowledge asset" (Liebowitz and Beckman, 1998, p.51).

According to Liebowitz and Beckman, knowledge asset refers to the organizational knowledge imbedded in the human resources that make up given organization. Knowledge management requires systematic attention to learning processes, culture, technology infrastructure and measurement (Brown and Massey, 1999). Since organizations are often made of workgroups or teams, and the workgroups are, in turn, made up of individuals, when we speak of organizational learning or knowledge management, aggregation should be preceded by analysis at the individual level.

Ten major hypotheses are generated and tested using laboratory experiments. The results of the study would help managers gain a better understanding of how to evaluate programs in general, and the dynamics of the two investigated task analysis methods in particular. Other theoretical contributions and future research plans are discussed.



Organizational behavior, Knowledge management, Problem solving, Organizational effectiveness, Information resources management