Knowledge Management and Triangulation Logic in the Foresight Research and Analyses in Business Process Management

Abstract

The idea of the article is to integrate knowledge management thinking to triangulation logic. Triangulation logic can be seen as a quality control mechanism in the field of knowledge management. Triangulation logic can also see as a critical knowledge management mechanism, which helps integrate inductive and deductive thinking in scientific projects. Triangulation is a vehicle for cross validation when two or more distinct methods are found to be congruent and yield comparable data. Today various scholars have noted that qualitative and quantitative methods should be viewed as complementary rather than as rival approaches. In fact, most textbooks underscore the desirability of mixing methods given the strengths and weaknesses found in single mono-method designs. In this kind of scientific discussion, the triangulation logic, which integrates quantitative and qualitative methods, is a highly relevant knowledge management issue. Today future-oriented foresight research is mostly based on quantitative and qualitative analyses. The three key elements of foresight activity are diagnosis (hindsight), prognosis (foresight) and description (decision support). In order to integrate triangulation logic to these foresight activities, experts and knowledge management scientists must think carefully alternative strategies, how to build up logical link between triangulation logic and foresight activities. This article provides some new ideas, how these novel knowledge management strategies could be constructed, when we look KM issues from broader triangulation perspective.