Several of the papers featured in this issue concern the questions of how to think, to plan and to act in a complex world in which uncertainty abounds. This is something that the modern world still has difficulty in accepting. For many, the advance of science implies that we can expect to know the future […]
The aim of this paper is to present a bench marking and diagnostic tool within the hierarchical Linnaean and cladistic representation of the discrete manufacturing systems presented. This is achieved through attempts of moving away from the ignorance of the past through a knowledge creating process exploring the opportunities of the future. The paper develops a theoretical perspective facilitating a knowledge creation process for moving away from the ignorance of the past and present, an engaging in a collective inquiry for developing instruments for manufacturing change. There are two main stages for the research methods in this paper. Firstly, there is a speed-read technique of quick species identification. The Linnaean hierarchy of discrete manufacturing organization is the map into which the manufacturing organization can search out its closest present identity. Secondly, there is a practical application on fitness/performance improvement. This is characterized by a comparison of a current company species to the ideal or typical textbook species. This exercise is done within the high-resolution profiles or representations of both the current and ideal states of the species. Using the speed-read and the kiviat comparison approach, a manufacturing organization can identify where they are in evolutionary history of discrete manufacturing systems. Then it can be assisted in searching out the general improvement potential of their organization. The classifications forms the basis for a further practical stage of the research—a web-based expert system and diagnostic tool that will complement a larger software system architecture. The aim of this is to simplify, and make accessible, essential tools for the rapid design, simulation and virtual prototyping of factories. The classifications also have a novel use in an educational context as it simplifies and organizes extant knowledge and adds another layer of information in terms of the evolutionary relationships between manufacturing systems. The work presented here is the first attempt at unifying extant classifications producing complementary, comprehensive, classifications of generic production systems that spans industrial sectors of discrete manufacturing. Based on this classification it presents application for manufacturing change.
Teams are framed as individuals embedded in hierarchical and knowledge networks, who interact among each other with the aim of accomplishing a common task. Social interactions are the means through which team members exert their mutual social influence, change opinions, and converge to a common understanding. In this paper, we investigate how the density and connectivity of the team knowledge network and the team organizational structure relate to team performance. The latter is measured in terms of level of agreement among the team members (consensus outcome). We first develop a theoretical model grounded on social influence theory and then a computational model based on the Ising approach. Successively, we carry out a broad simulation analysis in environments characterized by different levels of uncertainty. Results show that high-density values of the team knowledge network are beneficial in the majority of cases, but may become detrimental, when the uncertainty of the environment is low, the team knowledge network exhibits a random connectivity, and the team organizational structure is characterized by high centralization of the authority and a strong leadership behavior. We also find that scale-free connectivity of the team knowledge network hinders the achievement of consensus, compared to the random connectivity case. Based on the simulation results, we finally identify the best organizational structure that should be adopted to improve the consensus outcome.
Governments of the Republic of Korea have an exemplary record in providing leadership through published visions and strategies. This review is inspired by seven such endeavors conducted since 1999. All of these efforts use the future to motivate changes in the present. However, over time there has been a gradual shift in the content of the visions, revealing an unresolved tension between predictive targets based on benchmarking that is effective for emulation and a recognition that on the frontier of socio-economic change there are no knowable targets. As a result the capacity of strategic foresight processes to bring complexity and emergence to bear on the identification of opportunities in the present becomes more important. The perspective presented in this review can be summarized in three hypotheses: one is that South Korea is now at the frontier of existing socio-economic models and therefore catch-up and benchmarking are no longer sufficient foundations for South Korea’s vision, although still highly important for incremental improvement and competitive positioning on already existing markets/organizational aspects of society; two is that recent developments in strategic foresight theory and practice are enhancing the capacity to focus on complex, emergent systems that are rich with unforeseeable novelty and, critically, make a practical connection to the processes of sense making and making sense that are the basis for action; and three that South Korea is in a good position to invest in developing its strategic foresight capabilities on the basis of the outstanding track record of previous efforts to use the future for the benefit of all South Koreans.
Leadership and management are increasingly expected to base themselves on evidence, i.e. knowledge. This article does not disagree that knowledge may be beneficial. Yet, based on sociological insights on the complex relation between knowledge and ignorance, the article argues that more knowledge does not lead to less ignorance or non-knowledge. Building on Luhmann’s systems-theoretical concept of knowledge as selecting structures which reduce complexity, the article outlines a different approach to ignorance in management and leadership. It raises the question what an intelligent approach to ignorance looks like. Inspired by Foucault’s historical analysis of the emergence of liberal ideas of government, the article argues that managerial self-limitation is crucial in the development of a ‘management of non-knowledge’ to complement evidence based management.
Introduction This issue of E:CO is reprinting a classic paper by Heinz von Foerster, one of the key players in the formation and development of cybernetics. Von Foerster was an Austrian/American engineer, scientist, science expositor, philosopher, and cultural commentator (rather than listing each reference which would render this document unwieldy, history of cybernetics were taken […]
When Karen Tse invited my wife, Laura, and me to work with her world-class social entrepreneurial organization, International Bridges to Justice (IBJ), as part of our Creating Good Work Initiative, we were truly honored. It was not just that the work IBJ was doing to end the use of torture as an investigative tool had […]