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Les facteurs de réussite d’un réseau social d’entreprise | #CI #analytics #RSE

Les facteurs de réussite d’un réseau social d’entreprise | #CI #analytics #RSE | e-Xploration | Scoop.it
Les performances des réseaux internes d'une vingtaine d'entreprise ont été comparées par le cabinet de conseil Lecko pour déterminer ce qui les mène au succès... ou pas.

Via Eric Laurent
luiy's insight:

Beaucoup de sociétés ont des réseaux sociaux d’entreprise (RSE), mais toutes ne rencontrent pas le même succès avec ces projets. Pour tenter de déterminer les facteurs de réussite de ces espaces collaboratifs, le cabinet de conseil Lecko a réalisé un benchmark pour la deuxième année consécutive. Une vingtaine de grandes entreprises ont été comparées via l’outil Lecko RSE Analytics qui renvoie des métriques sur l’activité sociale enregistrée sur les plateformes (création d’un profil, ajout d’un commentaire ou « like »). Pour compléter le tout, plus de 90 community manager ont été interrogés pour comparer leurs pratiques. L’importance des community manager ne se dément pas. 71 % des espaces performants sont nés de l’initiative d’un community manager (voir le tome 7 de l'étude sur l'Etat de l'art des réseaux sociaux d'entreprise de Lecko)

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Priorité à l’intelligence collective pour accélérer l’ #innovation | #CI #coConstruction

Priorité à l’intelligence collective pour accélérer l’ #innovation | #CI #coConstruction | e-Xploration | Scoop.it
Les entreprises sont condamnées à innover : l’innovation est le meilleur moyen pour opérer une croissance durable et profitable au XXIe...
luiy's insight:

Intrapreneuriat et intelligence collective

 

Le "Think out of the box" doit se faire aussi bien à l’extérieur qu’à l’intérieur de l’entreprise. L’intrapreunariat, en s’appuyant sur une culture commune, reconnue et partagée, est tout aussi essentiel et prioritaire pour quiconque souhaite développer de nouveaux business.

 

L’alliance entre une organisation, des processus et des valeurs, et enfin des comportements, autour d’une vision partagée engendre cette culture de l’innovation. Et cette alliance, centrée autour de l’humain, va bouleverser les schémas classiques de leadership, mais aussi de considération de ce capital humain, devant être reconnu comme générateur de valeur ajoutée pour l’entreprise.

 

On voit de plus en plus apparaître dans les politiques managériales notamment du côté des États-Unis des Managers Inspiring, qui sont "des managers porteurs de sens", qui partagent leur passion. Aussi, pour faire émerger l’innovation, faut-il développer de nouveaux modèles d’organisation. 


 

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Une #cartographie des différences dans les #cultures de #management | #dataviz

Une #cartographie des différences dans les #cultures de #management | #dataviz | e-Xploration | Scoop.it

Les différences culturelles sont la source de nombreux malentendus dans un cadre professionnel international et multiculturel. Erin Meyer, professeure de management interculturel à l’INSEAD (Fontainebleau), a développé un outil pour visualiser ces malentedus qui peuvent survenir entre des équipes de deux pays différents. La Harvard Business Review publie une version interactive de ces comparaisons internationales.


Via Annie Longeot, François Le Pivain
luiy's insight:

BY ERIN MEYER. To help managers negotiate this complexity I have developed a tool called the Culture Map. It plots culture on eight scales that apply to the most common challenges managers face. By comparing the relative position of one culture to another on each scale, a manager can decode how culture influences day-to-day collaboration. Try the pairs illustrated in this exhibit to see how the map can help. Many other culture pairs are available in my new book The Culture Map. 

 

 

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Didier Lebouc's curator insight, June 15, 2014 4:05 AM

Il faut surtout aller voir la carte interactive en ligne sur HBR

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Asset Management Tools for #Change: Social Network Analysis | #SNA #KM

Asset Management Tools for #Change: Social Network Analysis | #SNA #KM | e-Xploration | Scoop.it
Asset Management Tools for Change: Social Network Analysis
luiy's insight:

SOCIAL NETWORK ANALYSIS (SNA)


SNA is a methodology for determining and analyzing relationships between people in order to show how information flows and decisions are made, ultimately investigating how work gets done. This enables managers and teams to understand:

 

Who the prominent players are and whom others depend on to solve problems and provide technical information. Who do people turn to for advice? The actual nature of the communication network in reality, demonstrating how communications actually occur regarding work related issues and who is central to these communications. This illustrates both informal collaborative relationships and holes within the structures. Whether subgroups emerged that are disconnected or partially connected to the core. Which individuals are isolated and limited in their roles or, conversely, who faces a situation of overload.  

SNA is a means to analyze the informal organization beyond the organizational chart. The analysis allows managers and teams to visualize and understand the myriad of relationships that can either facilitate or impede information flow, decision processes and knowledge creation. Thus, mapping opportunities and constraints in invoking change within the organization.

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#Individualisme en entreprise et intelligence collective | #CI #management

#Individualisme en entreprise et intelligence collective | #CI #management | e-Xploration | Scoop.it
© DOC RABE Media - Fotolia.com J’étais invitée il y a deux semaines par l’équipe du Master RTNO de l’IAE de Metz à m’exprimer sur ce sujet dans le cadre d’une conférence sur l’intelligence collective au service de la performance et de l’innovation, organisée avec quatre intervenants ; sujet passionnant pour lequel je souhaite retranscrire par écrit les propos que je souhaitais proposer lors de mon intervention.
luiy's insight:

Le sens au service de l’intelligence collective ?

 

Le sujet de l’intelligence collective en entreprise suppose donc la sollicitation de facultés qui ne sont pas uniquement soumises au statut de salarié, mais bien davantage aux personnes (globales) qui dans leur volonté de s’émanciper et de construire leur propre chemin exigent de comprendre le sens (signification et direction) des projets pour s’y intégrer pleinement et participer activement et avec d’autant plus de ferveur qu’on leur reconnait un rôle particulier et que les responsabilités sont partagées. La confiance aide les individus à se dépasser, et donc à créer des solutions nouvelles. Le management apporte ensuite la cohésion d’équipe et la solidarité qui vont aussi la plupart du temps émaner de moments de partage créés spécifiquement pour créer des relations privilégiées, des moments moins focalisés sur le projet que sur l’intérêt d’être ensemble.

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The Surprising Science Behind How Super Connectors Scale Their Networks | #SNA #CommunityBuilding

The Surprising Science Behind How Super Connectors Scale Their Networks | #SNA #CommunityBuilding | e-Xploration | Scoop.it

How one of the world’s top super connectors uses scientific principles of social network analysis to dramatically scale the size and depth of his network without increasing the time spent. 

 


Via Kenneth Mikkelsen
luiy's insight:

The basic idea behind Metcalfe’s Law is that the ‘potential value’ of a network increases exponentially as you add new interconnected nodes. In the context of relationship building, this means that as you build relationships that are connected to each other, the value of the network increases exponentially.

 

In the parlance of social network analysis, density is the percentage of people in your network connected to each other that could be. By increasing density, new things spread more quickly through it.

What sorts of new things?

 

New research by professors Nicholas Christakis and James Fowler, authors of Connected: The Surprising Power of Social Networks And How They Shape Our Lives, shows that a surprisingly large number of things are spread through networks such as violence, money, happiness, germs, obesity, gossip, ideas, norms, and behaviors.

In other words, as we increase the density of our networks based on mutual support, we dramatically increase the rate at which its participants learn from each other and deepen their relationships.

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Our Self-Inflicted #Complexity | #economy

Our Self-Inflicted #Complexity | #economy | e-Xploration | Scoop.it

Our ability to make progress against large-scale problems requires that we figure out how to tackle inter-domain complexity writes Roger Martin. The HBR blog post is part of a series of perspectives on complexity leading up to Global Drucker Forum in Vienna 14 + 15 November 2013. 


Via Kenneth Mikkelsen
luiy's insight:

My own clan — the economists — is particularly inclined in this direction. There are a thousand economists working on partial equilibrium problems for every one working on a general equilibrium problem. This is despite the fact that no one would contest that general equilibrium clarity is the most valuable knowledge by far. Why? Because it is really difficult to specify any general equilibrium cause-and-effect relationships.

 

Instead, most of the guns deployed in modern knowledge advancement are aimed at narrow problems for which the cause-and-effect relationship is specified with the famous “all other things being equal” proviso. Each narrow knowledge domain develops analytical tool-sets that deepen the narrow knowledge domain. Each narrow domain develops ever more algorithmic knowledge, and those developing the knowledge are extremely confident that they are right because they are so specialized within their own domain. The liver expert is completely confident that he or she is correct even if it is the interaction with another condition that threatens your health most.

This approach has created another kind of complexity: inter-domain complexity. Every field is segmented into multiple domains, each with deep algorithmic knowledge, specialized tools, and experts in the domain who think they are absolutely right. And they are indeed right, as long as we ignore the reality of detail complexity.

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Defining and Modeling Complex Adaptive Systems

Defining and Modeling Complex Adaptive Systems | e-Xploration | Scoop.it
Almost all the critical problems of our time are problems of control and almost all of them concern complex adaptive systems. If we want to know more about our bodies, it is not just to increase knowledge but so that we can control our health.

 

CAS are  “systems that don’t yield compact forms of representation”1. In other words a complex system cannot be described by a simple set of equations. Why would this be the case? It is the “adaptive” nature of these systems that leads to this intractability. Agents within the system respond to each set of environmental conditions within a complex adaptive system with a different set of responses and the number of such environments and their corresponding agent responses that need to be accounted for to construct an accurate model of the system is simply too large. But is this simply a problem of impracticality? Could we, at least in theory, construct a model that takes into account all possible environmental conditions and all possible agent behaviours? Although some scientists may argue that such an approach is theoretically possible, there is ample evidence that the critical “adaptive” component of some complex adaptive systems may in fact be unmodelable


Via Anne Caspari, A. J. Alvarez-Socorro
luiy's insight:
What Is A Complex Adaptive System?

The first question that then needs to be answered is: What is a complex adaptive system? David Krakauer defines complex systems as “systems that don’t yield compact forms of representation”1. In other words a complex system cannot be described by a simple set of equations. Why would this be the case? As Krakauer notes, it is the “adaptive” nature of these systems that leads to this intractability. Agents within the system respond to each set of environmental conditions within a complex adaptive system with a different set of responses and the number of such environments and their corresponding agent responses that need to be accounted for to construct an accurate model of the system is simply too large. But is this simply a problem of impracticality? Could we, at least in theory, construct a model that takes into account all possible environmental conditions and all possible agent behaviours? Although some scientists may argue that such an approach is theoretically possible, there is ample evidence that the critical “adaptive” component of some complex adaptive systems may in fact be unmodelable. There is no better example of this than the problems faced by the economist Hyman Minsky in formalising many of his most important ideas.

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Anne Caspari's comment, March 14, 2013 2:56 PM
complex adaptive systems can often be identified by observing the critical role that disorderly processes play in maintaining system resilience. For example, the disorderly and often unpredictable nature of flooding is a vital factor in maintaining the productivity and resilience of many complex river-floodplain systems. But the same rarely holds for simpler systems such as small temperate streams... Interesting the examples on trying to manage CAS with the opposite effect of reducing resilience and robbing them of antifragility. Forests, rivers, ecnomic systems..
Luciano Lampi's curator insight, March 19, 2013 9:02 AM

Interesting to read!

Léonne Willems's curator insight, March 25, 2013 4:27 PM

Another way to think about environmental influences at the source of tensions at work (as opposed to individual lack of employee performance or motivational problems). Are these 'tensions' actually symptoms of a system out of balance? Are these tensions the real gems for organisational steering? Check out how Holacracy capitalises just on that!