Power of networked teams

Photo courtesy of ‘PixelPlacebo’
How can you divide the labor in your organization to optimize for innovation rather than efficiency? ~Dave Gray 

Networked workers are a critical asset for today’s organizations. But in the end of the day, it does little good to be a networked worker if the organizational context will simply drive you back to ineffective patterns. In order for an organization to benefit of the power of its networked workers, it needs to instill a culture that scales the social and intellectual capital of its employees to a level that meets organization’s purposes. And that’s where networked teams come into play. 

What is a networked team?
A networked team is a social entity that carries out tasks in order to serve the needs of a customer (internal or external) and is embedded in one or several larger social systems . It stands out from regular teams by its network awareness, which mainly manifests itself in the following characteristics:


Cohesive construct: A networked team is a cohesive social network. It is not too tight that homophily takes stage nor too loose that it becomes difficult to diffuse knowledge and  new innovations. A networked team can have a core subgroup that instills the team’s culture and insures a good environment for nourishing peripheral members with the needed knowledge. If many subgroups emerge within the team, they need to be interconnected to keep the knowledge flow going.


Connected unit: A networked team is anything but siloed. It doesn’t evolve in an independent realm but rather bridges the gaps among itself and other teams effectively. It recognizes its weavers and leverages their access in order to reach out to novel ideas and processes.


Just the right amount of power : While a certain degree of leadership is necessary for stimulating innovation, the power within networked teams is decentralized to some extent. Team members are actually empowered enough to function as a business within the business.



Why networked teams are winner teams?
Networked teams grant the organization a fluid structuring based on relentlessly changing templates, quick improvisation and ad hoc responses. This can easily be translated into competitive advantage as it allows for innovation through continuous creation of new (combination of) resources.

Networked teams are network-aware, which means they manage their social and intellectual capital better, they know how to retain and access talent across the organization (thanks to their bridges) and their inherent structuring allows them optimal knowledge diffusion (Fully connected with more or less decentralized power).
Networked teams have been proven to perform better as they empower their members, interface with different other groups and collaborate internally and externally in more effective ways.
And finally, a networked team is not as strong as its weakest tie because it is resilient (small world characteristic). It is as strong as its core structure which is much stronger than a single player. 

Engineering a networked team

As we’ve said before, if the organizational context does not offer the right ecosystem for networked teams to thrive, any attempt to build one will fail systematically. Indeed, “Culture eats strategy for lunch”. So before engaging in the engineering of a networked team, make sure the general context won’t hinder its progress.


1. The map: X-Raying your teams’ external and internal ties is the first step. A Social Network Analysis of every team member’s relationships with colleagues in and out-side the team’s boundaries can help profile the actors and give a general overview of the network’s structure.


2. The measures: Cohesion, centralization and clique analysis are three measures to start with.
The measures addressing network cohesion are the density of the network (number of linkages), its average path length and diameter (longest possible path in the network to which extent linkages effectively connect nodes). 
Centralisation of a network entails the emergence of  ‘hubs’ which are highly-connected nodes. While peripheral structures of nodes with a lower degree of centrality emerge, highly differentiated structures are known to be generally more robust. 
Clique analysis looks into subgroups using the clustering coefficient. It has been proven that the most efficient network architecture is the small world topology, where cohesive subgroups are connected to each other.  
3. The gap: Once the measures are laid on the table, all is left is bridging the gap between the “As-Is” and the “To-Be” networks. It is not an easy task as it grazes organizational and cultural aspects. And there is no silver bullet. Many initiatives can be taken according to the problem at hand and the context of the organization. If we note, for example, many peripheral members that barely link to the subgroups, a  mentoring program can be implemented to shrink their distance from the hubs, giving them access to the majority of team members. If the team looks highly cliquish with no interconnection among subgroups, maybe it’s time for some conflict management workshops… 

While knowledge workers are the working force of an organization, teams are its backbone. If teams can really be businesses within the business, and of they can leverage the power of networks, then there is no saying to the potential they can unleash.


2 thoughts on “Power of networked teams

  1. it sounds like there’s some cumbersome work to do for engineering a networked team and maintaining it in a good shape.as you said the organisational context should be realy willing to priorize the internal Social aspect.but i wonder how the SNA preceding the conception of the networked team will deal with intimate data about relationships between nodes? some people might have some secret conflicts that might hinder the reliability of the collected data .so my question is should SNA be a periodic study , or continuous and real time monitoring to the network? does it just rely on tracable data or even little whispers of secrecy in the halls?

  2. Thanks for reading!The questions you asked are at the heart of the concern of SNA practitioners today. There are many ways in tackling a social network. The static approach takes snapshots of the network in different time slots, before and after a change for example. A dynamic approach would monitor the network in real time (predict its evolution even). The challenge here is the data collection. While this could be possible if we are to monitor a 100% online community (virtual groups for example), it is very difficult for real life social networks. (many other variables come into play). Surveys are used to gather the information needed, but its accuracy is still raising many concerns and still subject to enhancement.

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