Tailoring Knowledge Management Systems: Embracing Soft Systems Thinking
Authors
Hosbond, Jens Henrik ; Ørtoft, Rasmus
Term
4. term
Education
Publication year
2003
Abstract
Dette speciale undersøger, hvordan vidensledelsessystemer—værktøjer og praksisser, der hjælper organisationer med at indsamle, dele og bruge viden—kan tilpasses konkrete behov. Vi ser på, om to tilgange, Soft Systems Methodology (SSM) og prototyping, kan forbedre denne tilpasningsproces. SSM er en struktureret måde at forstå komplekse, virkelige situationer ved at inddrage interessenter og afklare mål og begrænsninger. Prototyping betyder at bygge enkle, fungerende versioner af et system for tidligt at teste ideer med brugere. Sammen med WM-data gennemførte vi først en dybdegående SSM-analyse og derefter en række prototypeeksperimenter for at afprøve, om de underliggende systemideer var relevante i praksis. Vores hovedbidrag er en kombineret model med to arbejdsmåder: en analytisk arbejdsmåde med SSM og en eksperimentel arbejdsmåde med prototyping. Vi fandt, at metoderne supplerer hinanden, udligner hinandens svagheder og tilsammen understøtter effektiv tilpasning af vidensledelsessystemer.
This thesis examines how knowledge management systems—tools and practices that help organizations capture, share, and use knowledge—can be tailored to specific needs. We explore whether two approaches, Soft Systems Methodology (SSM) and prototyping, can improve this tailoring process. SSM is a structured way to understand complex, real-world situations by engaging stakeholders and clarifying goals and constraints. Prototyping means building simple, working versions of a system to test ideas early with users. Working with WM-data, we first carried out an in-depth SSM analysis and then ran a series of prototype experiments to see whether the underlying system ideas were relevant in practice. Our main contribution is a combined model with two modes of work: an analytical mode using SSM and an experimental mode using prototyping. We found that these methods complement each other, balancing each other’s weaknesses and, together, supporting the effective tailoring of knowledge management systems.
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