Using Organizational Semiotics and Conceptual Graphs in a Two-Step Method for Knowledge Management Process Improvement Measurement

Abstract

The semantic normal forms of organizational semiotics extract structures from natural language texts that may be stored electronically. In themselves, the SNFs are only canonic descriptions of the patterns of behavior observed in a culture. Conceptual graphs and dataflow graphs, their dynamic variety, provide means to reason over propositions in first order logics. Conceptual graphs, however, do not of themselves capture the ontological entities needed for such reasoning. The culture of an organization contains natural language entities that can be extracted for use in knowledge representation and reasoning. Together in a rigorous, two-step process, ontology charting from organizational semiotics and dataflow graphs from knowledge engineering provide a means to extract entities of interest from a subject domain such as the culture of organizations and then to represent these entities in formal logic reasoning. This paper presents this process, and concludes with an example of how process improvement in an IT organization may be measured in this two-step process.

On Improving the Visibility of Hard-Measurable Process Performance

“…Subjective measures can either support and replicate objective measures or be fully subjective without relation to any given or known measure in a PMS (Richard et al, 2009). The meaning of measures is rather based on intentional semantics and individual sensual experiences (Strecker et al, 2011), and this knowledge itself is again adjusted according to individual mental outlooks (Schiffel, 2009).…”