We define network leadership as…

The capability to work across social boundaries, connecting ideas with action and people with resources, in pursuit of shared goals. Leaders who, while open to possibility and opportunity, remain true to the core beliefs of alignment, synergy and restless persuasion.

And in our experience network leadership is about facilitating network action through four key practices:

1. Understanding the social systems in which you operate
2. Having the convening power to bring people together to achieve goals
3. Leading beyond formal and positional authority
4. The power of restless persuasion: the energy and resilience to get things done

Network leaders recognise the interconnected world we live in, they understand the social system of organisations, they bring people together, they can lead informally but know when to use their formal or positional power, and are relentless in what they want to achieve for their organisation or community.

A Network Leader is someone who can see across organisations and communities, and make the sum of the parts greater than the whole. Leaders who know that opportunities and threats do not come neatly parcelled to fit within the hierarchical structure of teams, departments and neighbourhood boundaries into which we have organised ourselves. Leaders who take responsibility for problems other than their own and recognise that the best way to get things done is not to mind who gets the credit for doing them.

Network Leaders can identify and make the most of the informal networks that inevitably exist within all teams, organisations and communities, in order to get things done. Effective Network Leadership facilitates the exchange of accurate information about who does what, who knows what, and who needs what, in order to:

• Better target scarce resources.
• Challenge the silo mentality.
• Restructure the formal organisation to complement the informal.
  ‘Rewire’ faulty networks to achieve goals.
• Deepen the quality of relationships.
  Reduce transactional costs (e.g. micro-managing and second guessing).
• Be more innovative.

Networks are a universal structure. The brain is a network of cells, which are themselves a network of molecules. Societies are networks of people. Food webs and ecosystems are networks of species. Networks pervade human technology, from the internet, to power grids and transportation systems, and now networks are challenging the way we organise ourselves, with top down hierarchies being replaced by flatter and other more informal network structures of social collaboration.

Some might argue that this is a paradigm shift in the way we see and order ourselves, but in reality this is how human beings have always understood and ordered themselves. Niall Ferguson argues that the secret of our success as a species has always resided in the collective brain of our communities. Humans learn socially through teaching and sharing, and perhaps our species should be known as Homo dictyous (network man), because our brains seem to have been built for networks.

Anne-Marie Slaughter makes a similar point, describing humans as Homo sociologicus (humans as social beings) as opposed to Homo economicus (humans as rational agents). Our early ancestors were collaborative foragers, who became interdependent on each other for food, shelter and warmth. All that has happened since, beginning with the invention of written language, is that new technologies have facilitated our innate, ancient urge to network.

And today’s technologies have us more connected and immersed in data than ever. In today’s world of networking and collaboration software, big data, analytics, and AI, managers simply cannot continue to assume a static, hierarchical model of the firm for the convenience of seeing how to manage it. Now that firms’ activities are so intertwined and their successes so interdependent, the old tools and techniques will simply no longer work.

Facebook is an example of a social network, but it is only one of many. We are all part of social networks, whether knowingly or not. They can be seen as superorganisms, which link individuals and groups, where the whole is greater than the parts. A network, like a group, is a collection of people, but it includes something more: a specific set of connections between people in the group. These ties and their particular pattern of connection are often more important than the individual people themselves. In effect, we are as much a part of our social networks as our social networks are part of us.

Real everyday social networks (natural networks) are not typically composed from the top down. They evolve organically from the natural tendency for social interaction. Consequently, social networks can be positive and negative. They allow us to do things together that a disconnected collection of individuals could not. So we all stand to benefit from them, but we must all work together to ensure that they remain healthy and productive. Left to their own devices social networks can reinforce inequality, privileging those who are already better off or those who are better off in terms of their location in the network.

Social networks provides a distinct way of seeing the world because it is about individuals and groups, and about how the former become the latter. Understanding how they form and work requires that we grasp two fundamental aspects of human social networks and comprehend five rules.

The two fundamental aspects of human social networks are connection and contagion. Connection refers to the shape, structure, or anatomy of a network, which will be of variable quality and quantity, and its topology: the arrangement of nodes (people and organisations) and ties (connections between them). Contagion, on the other hand, refers to the networks function or physiology. What, if anything, flows through and across the connections, whether it be ideas, fashion or viruses and germs.

Rule 1 describes how we shape our network. We make and remake our social networks all the time depending in large part upon homophily and propinquity.

Homophily, colloquially known as birds of a feather flock together, is our conscious and unconscious tendency to associate with people who resemble us – physically, emotionally or cognitively. We also choose the structure of our networks: we decide how many people we are connected to; we influence how densely interconnected our friends and family are; and we control how central we are to these social networks. Research suggests that typically we have a ‘core discussion network’ of between 2 and 6 close social contacts, with whom we discuss important matters.

Propinquity means nearness or physical proximity, and in network terms describes our propensity to associate with people who are physically near us or who we come into frequent contact with. That is, we are more likely to form relationships with those closest to us, rather than those who are more distant. Thus groups are more likely to form among colleagues who sit together than those who work in different offices. It is summed up by the rhyming phrase: those close by form a tie.

Rule 2 describes how our network shapes us. Transitivity describes how connected your social contacts are, thus how tightly interwoven your network is. If you know Alan, Alan knows Michelle and Michelle knows you, the relationship is transitive. High transitivity normally indicates those deeply embedded within a single group, while those with low transitivity tend to make contact with people from several groups who do not know each other. Being more central (high transitivity) makes you more susceptible to whatever is flowing in the network, whether it be gossip or germs.

For example, mutual best friends (those who both name each other as best friends) have a triple obesity risk. A medical study by Nicholas Christakis showed that body weight can be strongly influenced by social networks of friends. A densely connected network of over 12,000 people was examined over a period from 1970 to 2003 and found that ‘a person’s chances of being obese increased by 57% if a friend became obese, 40% if a sibling became obese and 37% if a spouse became obese.’

Rule 3 describes how our friends affect us. A fundamental determinant of flow (e.g. of ideas) is the tendency of human beings to influence and be influenced by (copy) one another, i.e. conform to what others do. Structurally, the more paths that connect you to other people in your network the more susceptible you are to flows within it. However, the difference in the nature, not just the number, of social contacts is also important. Primarily, as we saw in Rule 2, we tend to measure ourselves against our friends. Friends affect us more than parents and spouses, even if they live further away.

Smoking, happiness, obesity, loneliness and even terrorism are all like viruses that spread best among friends. As Scott Atran observed, “The key difference between terrorists and most other people in the world lies not in individual pathologies, personality, education, income, or in any other demographic factor, but in small group dynamics where the relevant trait just happens to be jihad rather than obesity. This is the ordinariness of terror.”

This phenomena can create niches, where weight gain or loss become a kind of standard. A niche is a community within a network that shares certain ideas and behaviours. What is less clear, however, is whether these ideas/behaviours exist because people of similar ideas spend time together (homophily); or because people share common exposure (conformity); or is there a causal effect, one person causing the adoption of an idea or behaviour in another (social contagion).

Rule 4 is that our friend’s friends’ friends also influence us. The extent of network connections is perhaps best exemplified by research pertaining to ‘Small Worlds’, where the focus is on the social phenomena many people experience when encountering a stranger for the first time, only to discover that both share a friend or acquaintance in common. You may have heard it referred to as ‘six degrees of separation’ which posits that any two people on Earth are six or fewer acquaintance links apart.

The concept was originally dreamed up by the Hungarian author Frigyes Karinthy in 1929. In a short story called Chains, in which his characters postulated that any two individuals could be connected through a maximum of five acquaintances. The idea being based on globalisation and the ever-increasing connectedness between the world’s people in the wake of the First World War.

Subsequently, this caught the imagination of the public and academics. Stanley Milgram, the social psychologist, carried out a series of experiments in the mid-20th century, which showed that people in the US were connected by three friendship links. Columbia University’s ‘Small World Project’ in 2008 also backed up the theory, suggesting that the average number of links was six.
Further research has revealed that Twitter users are 5.5 steps or less from any other tweeter. Facebook ‘friends’ are 4.74 connections away from every other user of the social network.

The key point of Rule 4 is contagion across these connections, the tendency of effects to spread from person to person beyond an individual’s direct social ties, also known as Hyperdyadic Spread. There are two varieties of hyperdyadic spread. The first are germs, gossip and information, where once infected additional contact is redundant. The second are norms or behaviours, which often require reinforcement through multiple social contacts.

However, in terms of influence the connections are more limited than six degrees, with the reliability of information decaying rapidly beyond three degrees of separation. This appears to apply both temporally and spatially. Most of us can remember are grandparents and can relate stories about them and perhaps name their siblings, but beyond that our personal genealogies tend to become rather vague. This is likely to be because our lifetimes tend to span three generations.

Spatially, it may be explained by intrinsic decay (the sort of information decay found in the game Chinese Whispers); network instability, the evolution of the network makes links beyond three intrinsically unstable; or our hominid past, where there was simply no one beyond three degrees of separation. Whatever the reason it may always constrain our ability to connect, even with advances in technology.

Rule 5 is that the network has a life of its own. Social networks can have properties or functions that are neither controlled nor even perceived by the people within them. This can be likened to trying to understand the causes of a traffic jam by asking a single driver. Other examples include ‘La Ola’ the Mexican Wave during stadium sports games and flocking birds, the murmuration of starlings for example. In short, social networks obey rules of their own, rules that are distinct from the people who form them. Social networks have emergent properties: new attributes of the whole that arise from interaction and interconnection of the parts, and which are beyond the control or even understanding of the individual actors. A real world example, familiar to many, is the wicked problem.

A wicked problem is a problem that is difficult or impossible to solve because of incomplete, contradictory, and changing requirements that are, in themselves, often difficult to recognize. Wicked problems are often confronted in the arena of public planning and policy, in areas such as climate change, natural hazards, healthcare, epidemics, international drug trafficking, energy and social inequality. But the concept has been extended to include a wide variety of other environments including business strategy, terrorism and warfare.

They are problems that manifest the following characteristics: they are difficult to clearly define; have multiple causes and many interdependencies; are socially complex and involve multiple stakeholders; are hardly ever the responsibility of one organization to solve; and attempts to address them often lead to unforeseen consequences. In terms of solutions they are often unstable and continually evolving, have no clear solution, and indeed may never be solved having no right or wrong, and instead can only be judged as better, worse or good enough.

Social network analysis (SNA) is a technique for understanding a social network, which, is made up of a set of actors (individuals or organisations) and the ties (connections) between these actors. It is based on two key elements: quantitative mathematical analyses to identify important links between people and groups, and qualitative investigation to interpret and add social context to the structures identified by the quantitative analysis.

Both these elements can then be visualised as a 2D picture using network visualization software, such as UCINet or SocNetV, and then analysed to determine what is causing the levels of revealed interactivity and how to ameliorate poor connectivity. In the example below, the coloured shapes (nodes) represent people and the blacklines with arrowheads represent the connections (ties) between them, who speaks to whom for instance. The nodes are further divided into different teams (different colours) and locations (different shapes).

Organisational Network Analysis is the application of Social Network Analysis to organisations. For example, An organisational chart (org chart, organogram, call it what you will) is a schematic social network, a diagram showing the structure of an organisation in terms of the reporting relationships between individuals, departments and teams. But the truth is that organisations only look like this on paper. In reality, they look more like social networks (sociograms), see below.

The organogram is valuable in that it enables us to visualize a complete organisation. The problem is that it only shows the formal hierarchical relationships and tells us nothing about the pattern of informal human (social) relationships illustrated above. This has two principal drawbacks:

1. 1. It can constrain thought and action, forcing us down artificial tramlines in terms of how we act and what we expect. Communication and instruction go down and responses or reports of action come back up, and it is poor form to jump the chain of command (up or down), or communicate laterally without seeking permission from above first.
   2. It is also manifestly incomplete, hiding gaps and blockages as well as alternative lines of connectivity. It can leave uncharted a vast terrain of connection and disconnection, which can make or break change, strangle innovation, and cripple day to day operations.

The advantage of the sociogram is that it illustrates the actual relationships that exist beyond the formal reporting chain. For example: who talks to whom, who seeks advice from whom, and who trusts whom. The sort of relationships that show how information and knowledge is passed and how things get done in an organisation.

The aim of analysing community networks, much like network analysis in organisations, is to uncover, connect and create value through greater connectivity and co-creation, rather than simply relying on traditional models of resource management. Principally, it offers a solution to the challenge facing many charities and most public sector services: that of being asked to do more and more with less and less.

Traditionally, some local government and charitable organisations have adopted a deficit approach to community development and regeneration, meaning that they started by looking at the problems: crime, unemployment and poor health for example, instead of asking what is right and what is valued in the area. An approach which can be very damaging to the self-esteem of these communities.

In contrast, community network analysis builds upon the concept of community asset mapping to uncover value: identifying and then connecting individuals, groups and institutions in order to facilitate the exchange of resources, skills and knowledge, between those who have and those who need. Community Asset Mapping is a networked approach, which seeks to redress the balance by cataloguing everything of value and creating a picture or map of what it is actually like to live there.

Map in hand, you are then able to ask insightful questions to help connect those who have with those who need and target your own organisational resources more effectively and efficiently. Such questions might include:

• • Are the right connections in place?
  • Are any key connections missing?
  • Who are playing leadership roles?
  • Who is not, but should be?
  • Who are the experts in process, planning and practice?
  • Who are the mentors that others seek out for advice?
  • Who are the innovators?
  • Are ideas shared and acted upon?
  • Are collaborative alliances forming between individuals, groups, departments, organisations and communities

Fundamentally, community network analysis is about mapping, weaving and building. Mapping to uncover inherent value in communities. Weaving to connect providers and clients; managers and employees; public servants, community activists and voluntary groups, in order to facilitate the exchange of resources, skills and knowledge, between those who have and those who need. And finally building, allowing organisations, whether public bodies or charities, to target their finite resources to where the impact in the network will be greatest.