Complex systems: Why do they need to evolve and how can evolution be supported (original) (raw)
SOCIAL COMPLEX EVOLVING SYSTEMS: IMPLICATIONS FOR ORGANIZATIONAL LEARNING
2000
This paper argues that some of the principles of Complexity Science may be very useful in our efforts to explore and more fully account for the evolving social complexity that constitutes learning practices in organizations. We review the main principles of complex adaptive systems, steeped in the new science of complexity, and we apply these principles to our analysis of the main dimensions that have been employed so far in studying Organizational Learning (OL). Our analysis provides a new way of conceptualising OL as a complex evolving social system emphasising self-organization, emergence and co-evolution as central dimensions. We compare this new perspective, the complex view of OL, to the two main dominant perspectives of Organizational Learning: the individual and the social view.
Systems Research and Behavioral Science
Policy makers, managers and leaders in organizations, governments and business institutions are under increasing pressure to make the right management decisions in the face of a continually changing political and socio-economic landscape. To make matters more challenging the complex environmental, socio-economic, business-financial issues that decision makers need to deal with tend to transcend the jurisdictions and capacities of any single organization.
Problem solving as a complex, evolutionary activity
Proceedings of the 2005 conference on Computer support for collaborative learning learning 2005: the next 10 years! - CSCL '05, 2005
Viewed through the lens of complex systems science, one may conceptualize problemsolving interactions among multiple actors, artifacts, tools, and environmental structures as goal-seeking adaptations, and problem-solving itself, as a complex adaptive activity. Theories of biological evolution point to an analogical equivalence between problem solving and evolutionary processes and, thus, introduce innovative methodological tools to the analysis of computer-supported, collaborative, problem-solving processes. In this paper, we present a methodological framework for characterizing and analyzing these processes. We describe four measures that characterize genetic evolution -number, function, fitness, and persistence -to characterize the process of collaborative problem solving, and instantiate them in a study of problem-solving interactions of collaborative groups in an online, synchronous environment. Issues relating to reliability, validity, usefulness, and limitations of the proposed methodology are discussed.
System Evolution Barriers and How to Overcome Them!
Creating complex systems from scratch is time consuming and costly, therefore a strategy often chosen by companies is to evolve existing systems. Yet evolving a system is also complicated. Complex systems are usually the result of multidisciplinary teams, therefore it is essential to understand barriers those teams face when evolving a system. From the research carried at Philips Healthcare MRI, we have identified that main evolution barriers employees face are; managing system complexity,communication across disciplines and departments, finding the necessary system information, lack of system overview, and ineffective knowledge sharing. Those barriers were identified as the root cause of many development problems and bad decisions. To overcome those barriers, and therefore enhance the evolution process, effective reuse of knowledge is essential. This knowledge must be presented in a fashion that can be understood by a broad set of stakeholders. In this paper system evolution barrie...
Contradictions and critical issues during system evolution
2002
Abstract In this paper the issue of system evolution is addressed. Activity Theory and the concept of exapansive cycles are reviewed as theories to explain systemic evolution. Contradictions often manifest themselves in deviating human behaviour or in modifications to external artefacts, ie, they result in a form of systemic behaviour which has often been treated as undesirable. It is shown that contradictions within activity systems are both catalysts and opportunities for system change.