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Agile Management - Complexity Thinking

Related:  Complexity Theory.caisson

How the size of networks can skyrocket The growth process of networks. Left: In the beginning, only a few elements join to form many small networks. Middle: In the intermediate phase, several mid-sized networks have been created. Researchers from the Max Planck Institute for Dynamics and Self-Organization (MPIDS), the Bernstein Center for Computational Neuroscience Gottingen, and the University of Gottingen have mathematically described for the first time the influence of single additional links in a network. Neurons in the brain constantly establish new connections, websites link to each other and a person traveling infected with influenza creates a network of infected places with each intermediate stop. To answer these questions, the scientists from Göttingen tracked the growth of networks link by link. The situation can be compared to the social contacts established in a summer camp for children, whose participants all don’t know each other at the beginning of their vacation.

The Future: An Instruction Manual Complex systems tutorial Jan Burian burianj (at) vse.cz You can find here: Basic introduction to Complex Systems Science and relevant modeling tools Many links to web resources and a list of relevant literature "Complex systems" (4IZ636), lecture on University of Economics, Prague Content Intuitive definitions of complexity Basics of (complex) systems science Self-organization and related concepts Formal definitions of complexity Very short introduction to modeling methodology Cellular automatons Complex networks Agent-based models References Intuitive Definitions of Complex Systems System is an entity in terms of parts and relations between them. Structural relations define which parts are connected together. Structurally complex system A system that can be analyzed into many components having relatively many relations among them, so that the behavior of each component can depend on the behavior of many others. Basics of (complex) systems science Remember: Interconnection of parts matters in complex systems! Feedback

Build organizations that are fit for the future For companies to survive and strive in today’s competitive environment, they will need to change quickly and successfully. Managing change is now a core competence that can no longer be considered a discretionary “nice to have”. The accelerating pace of change coupled with increasing uncertainty and complexity has pushed up this skills gap to what is now a major area of concern. Array of challenges No organization is exempt from a daunting array of challenges: In a world where exponential change is the new normal, how do you build a company that can change as fast as change itself? Tackle those mega-challenges As Gary Hamel argues in the video “Reinventing the Technology of Human Accomplishment”, you can’t tackle those mega-challenges if you’re not willing to do three things: Resilient, inventive, inspiring and accountable Hamel paints a vivid picture of what it means to build organizations that are fundamentally fit for the future – resilient, inventive, inspiring and accountable.

COPING WITH COMPLEXITY Coping with the complexity of today’s business environment is not about predicting the future or reducing risk. It’s about building the capacity, in yourself, your people, and the organization to adapt continuously and learn speedily, in order to maximize the chances of seizing fleeting opportunities. These authors’ excellent suggestions will help today’s leaders cope with complexity. As business leaders, policy makers, the academic community, the media and an outraged public search the rubble of the global economic crisis for clues as to what went wrong, all fingers point to a common perpetrator, poor risk management. But while risk management, or lack thereof, played its part in the disintegration of the world financial system, we contend that another culprit played an even bigger role: complexity, and an inability to cope with it. Complex environments, complex organizations Complexity is one of the salient hallmarks of the 21st century. 1. 2. 3. 4.

The Remarkable Properties of Mythological Social Networks Ten years ago, few people would have heard of a social network. Today, Facebook, Twitter and LinkedIn permeate our lives. They show us how we are linked to each other and how we are more broadly placed within society. What fascinates scientists is that the general properties of social networks seem to be invariant regardless of where they crop up. For example, one of the remarkable properties of social networks is their small world character. This means it is possible to go from one part of a network to any other part in a small number of steps (this is where the phrase “six degrees of separation” comes from). That was entirely unexpected and counterintuitive when it was discovered in the 1960s by the American social psychologist Stanley Milgram. Today, P J Miranda at the Federal Technological University of Paraná in Brazil and a couple of pals study the social network between characters in Homer’s ancient Greek poem the Odyssey.

caos La vita si evolve verso un regime di equilibrio tra l’ordine e il caos. Suggestiva l’immagine che la vita esiste ai confini del caos. Quasi come se la vita esistesse in una sorta di transizione, nello stato ordinato adiacente alla transizione di fase che porta al caos. I sistemi che si trovano nello stato ai confini del caos - un compromesso tra l’ordine e l’imprevisto- sono quelli che meglio sono in grado di coordinare attività complesse, e allo stesso tempo di evolversi. Il mondo vivente è abbellito da una sovrabbondanza di ordine. Vengono considerate reti, in particolare reti booleane, ed esaminati i cicli di stato che in esse si formerebbero. Si può regolare la connessione della rete e modificare le regole di controllo. Proprio in mezzo, tra l’ordine e il caos, vicino alla transizione di fase, possono verificarsi i comportamenti più complessi: abbastanza ordinati da assicurare una stabilità, ma pieni di flessibilità e di sorprese. Un programma per PC è un insieme di istruzioni.

Visualizing Your Facebook Network with Gephi | Social DynamicsSocial Dynamics This is a visualization of my own Facebook network that I made using the (free) software Gephi and the Facebook application netvizz. Each node in the network is one of my Facebook friends, and two friends are connected to one another if they are Facebook friends with each other. The size of the node corresponds to the "degree" of the node, which means how many connections it has. In this case, that means how many of my Facebook friends that person is Facebook friends with. (Note: I deleted the names from the nodes to protect my Facebook friends' privacy). The colors of the nodes indicate communities of friends found using a clustering algorithm based on the "modularity" of the network. We did this as an exercise in the Social Dynamics and Networks course that I teach at Kellogg.

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