ETHOS Issue 09, June 2011
The "top-down versus bottom-up government" debate has become largely irrelevant, the consensus being that traditional top-down government is increasingly ineffectual in today's context. The discourse has instead turned to how governments can make that transition, and thrive in a new environment in which collaboration and networking are the norm. Consequently, policymakers around the world are now experimenting with novel ways of collaboration that bring together diverse stakeholder groups and provide more integrated and holistic responses.
Taking a network approach to public governance implies an increased reliance on (typically more informal) networks as a way to mobilise and engage citizens and organisations in the development, implementation, and monitoring of public policy. The rise of network governance and the new collaborative ethos of public institutions points to a more fundamental transformation and proliferation of the network paradigm, which Castells termed "the rise of network society".1
The key driver in the emergence of the network society is technology – primarily new information and communication technologies – although it is important to bear in mind that all new forms of societal organisation are only conditioned, not determined, by technology. Society shapes technology according to the needs, values, interests and identities of people who make use of it, and because political systems are largely dependent on the inputs from the public spaces of socialised communication for their conversion of demands into collective decisions, the political decision-making process is also transformed by the rise of the network society.
NETWORK GOVERNANCE – A NEW PARADIGM FOR GOVERNMENT
The rise of the network society changes not only the nature of public discourse and opinion formation, but also the form and content of concrete decision-making, policy development and implementation. Bang & Esmark argue that nation-states are being replaced by network states, which are “states embedded in local, regional, and global networks of governance hailed as necessary to meet the challenges of increased complexity, connectedness, and globalisation”.2 Such governance networks vary considerably in terms of the level of formalisation, stability and inclusiveness, but a common characteristic is the involvement of non-state actors from the private and third sector as stakeholders and partners in policy management and implementation. The reconfiguration of the political system according to the ethos of good governance based on the network paradigm thus calls for a re-evaluation of the relationship between government and its stakeholders. As Bang & Esmark (2009) note:
"The only reasonable approach to the rise of network ethos and network organisation in public governance is a clear refusal of the idea of the network state as a helpless victim of network society. The reorientation of steering and coordination from programmes of conventional democratic polity to the stakeholder and partnership programmes of governance intrinsic to network governance is not simply a necessary or functional response to economic globalisation, technological innovation, complexity, and wicked policy problems… Rather it is to be regarded as the core of a more fundamental transformation from a disciplinary society to a control society in which states, or at least governments, are key innovators and benefactors."3
MAKING NETWORKED GOVERNANCE WORK
A common misconception with policymakers is that collaboration with external stakeholders implies a process of democratic public consultation involving resource-draining feedback solicitation, and sorting through half-formed ideas and perennial complaints. The fact is that collaborative participation can be structured, selective and designed to be productive; dialogue can often be highly specialised, technical and closed (see sidebar).
New forms of societal
organisation are only
conditioned, not determined,
Unfortunately, while policymakers may seek to use more collaborative arrangements, they often still expect outcomes and processes that are consistent with the traditional, comfortable forms of working. Klijn4 concludes that – given existing efforts, including attempts to involve stakeholders in the designing of policy – interactive governance does not always foster more cooperation among stakeholders, nor does it necessarily facilitate better solutions or more democratic processes.
One critical reason for these failures arises from the tension between the horizontal accountability of these interactive governance mechanisms and the vertical accountability involved in the procedures of classical representative democracy. As such, an important factor to consider is the management efforts that go into collaborative processes, since they are complex and not easy to manage with traditional governance instruments. Unless policymakers understand what it means to work through network structures, they will continue to develop traditional policies and adopt management techniques that run counter to the positive results expected of networked arrangements.
Power and Trust
For a start, policymakers need to appreciate the nature of power in a network structure. As each member of a network is an independent entity, typical forms of authority do not work well, even if some actors have more formal power than others (in terms of resources or political clout). In fact, rather than relying on contractual arrangements, network structures depend on informal exchanges based on interpersonal relations. This calls for new modes of leadership which centre primarily on a facilitator or broker role. In addition, for the network to be effective, members must be able to trust each other to work to their mutual benefit.
Making The Net Work: Three Models
NOVECK: "COLLABORATIVE DEMOCRACY"5
Technology can help solicit and gather relevant expertise from large numbers of self-selected peers working together in groups.
How it works
Noveck offers 10 ways to support collaborative decision-making across a range of activities
- Ask the right questions: The more specific the question, the better targeted and more relevant the responses will be.
- Ask the right people: Self-selection, along with baseline participant requirements, lets relevant expertise flow to the problem.
- Design the process for the desired end: Methodologies used should be chosen to achieve clearly defined goals.
- Design for groups, not individuals: "Chunk" the work into smaller problems that can be easily distributed to members of a team, who can then work in short productive bursts.
- Show the group back to itself: If people perceive themselves to be part of a mini-movement, they will work more effectively together across a distance.
- Divide the work: Map out available tasks and roles, and let participants choose their own.
- Bubbling-up: Solicit solutions broadly, and allow people to rate submissions for relevance and usefulness.
- Make policies, not websites: Don't count on technology alone: redesign internal processes in response to opportunities for collaboration.
- Pilot new ideas: Use pilot programmes, competitions and prizes to generate innovation.
- Focus on outcomes, not inputs: Design practices to measure success towards desired goals.
MALONE, LAUBACHER & DELLAROCAS: "THE COLLECTIVE INTELLIGENCE GENOME"6
Basic building blocks in appropriate combinations enable the wisdom of crowds to be harnessed successfully in enterprises such as Wikipedia and Threadless.
How it works
A framework of "principal genes" which addresses four basic characteristics of a decision-making system:
What is being done?
- "create" – generate something new
- "decide" – assess/choose alternatives
Who is doing it?
- "hierarchy" – assigned by authority
- "crowd" – voluntary performance
Why are they doing it?
- "money" – direct or expected gain
- "love" – intrinsic satisfaction of task
- "glory" – peer recognition
How is it being done?
How-Decide (Group Decision)
- "collection" – independent contributions
- "contest" – a small set of solutions needed
- "collaboration" – interdependent parts
How-Decide (Individual Decision)
- "Voting" – group commitment matters
- "Averaging" – decision based on statistics
- "Consensus" – agreement is feasible
- "Prediction market" – based on evolving data
- "market" – choices motivated by money
- "social network" – non-profit, peer-based choice
Together, these form a "collective intelligence gene-table" that can help in designing appropriate systems for each task, with many possible combinations of suitable traits.
For example, collective intelligence systems that rely on the "crowd", "love" and "glory" genes often explicitly feature opportunities for recognition, e.g. "top contributor" lists or performance-based classes such as "Power Seller" on eBay or "Top Reviewer" on Amazon. Getting the motivational factors wrong is often the single greatest factor behind failed efforts to launch new collective intelligence systems.
KREBS & HOLLEY: "NETWORK WEAVING"7
Collective intelligence is only
as good as the people contributing to it. “Network weaving” nurtures
the network community, allocating scarce resources and maintaining the
network’s overall health.
How it works
Unmanaged networks tend to
form many small and dense clusters with little or no diversity (the
classic "old boys' network"). Everyone in the cluster knows what
everyone else knows, but not what is going on outside. While this
density and commonality can make for strong working groups, parochialism
and resistance to change can build, greatly limiting the possibility
for new ideas and innovations.
A vibrant community network is generally built in four progressively adaptive and resilient phases:
Most communities start as small, isolated, emergent clusters
organised around common aims. If these fragments do not organise
further, the community remains weak. An active leader called a “network
weaver” is needed to create interactions between them.
Network weavers begin to serve as a hub, connecting individuals and
clusters which can collaborate or help expand the network. Power and
vulnerability are concentrated in the hub/weaver.
Multi-hub small-world network
s network information grows, complementary clusters join up and
support one another. The central weaver begins to groom new weavers to
take over network building and maintenance. When the various weavers
connect with each other, a more robust multi-hub community forms.
In the final phase, a core of key community members act swiftly on
relevant new ideas, while a periphery (consisting new members, bridges
to diverse communities elsewhere, and unique resources outside the
community) provides access to ideas and information not currently
prevalent in the network.
Traditional policies and
run counter to the positive
results expected of
While trust is not easy to build, there are two characteristics of network structures that may mitigate these constraints. First, the formation of a network structure means that at least some of the members recognise they are not able to achieve their purposes on their own, and that all action is thus interdependent. Second, many of the participants may already know each other and may have formed pockets of trust before the network structure was formed. These pockets of trust can be capitalised on through effective management strategies.
Risk and Indicators
Inter-organisational arrangements often depend on cooperation and coordination as their primary mode of operation because they entail low risk and an acceptable level of comfort. These processes usually involve sharing of information, maintaining the autonomy of individual departments, and maintaining the ability to deliver services as usual. There is a desire to continue to tightly control what occurs in the network structure. Furthermore, government often expects it will be able to see traditional results, and see them quickly. The difficulty is that the types of results that occur through network structures have to do more with changing relationships and perceptions, which are more intangible than generating traditional programmes and numbers. Managing expectations and having the right indicators are thus critical to the survival of network structures.
There are, unfortunately, few definitive outcome measures that can conclusively demonstrate the effectiveness of a programme designed to work in a network structure among government agencies. If this deficiency persists, the true benefits of the network structure (that is, systemic change, relationship-building, innovative operating procedures and community inclusion) could be seen as less significant than it deserves. The reality is that the way governments work today is not conducive to changing traditional processes because of the risk involved. Network structures are unique responses to very complex, messy, wicked problems that do not lend themselves to business as usual. Policymakers must realise that their key role in a network environment is to lay the foundation for members to operate with the authority they need, and then get out of the way.
New modes of leadership
centre primarily on a
facilitator or broker role.
With greater experience and working knowledge of the benefits of network structures, as well as an understanding of what outcomes can be expected, decision makers may be more prepared to make changes – at the margins, initially, but in ways which could enable fuller network structures to emerge as a means to address more intractable issues. Allowing longer timeframes for evaluation, putting emphasis on integration rather than simply delivery of services, changing perceptions about each other's contribution to the whole, and recognising the value of relationship-building – these signal a promising start to new ways of working together.
- Castells, M., The Rise of the Network Society (Cambridge, UK: Blackwell, 2000)
- Bang, H. and Esmark, A., "Good Governance in Network Society: Reconfiguring the Political from Politics to Policy", Administrative Theory & Praxis, 31 (1) (March 2009), pp7-37
- See Endnote 2.
- Klijn, E., “Governance and Governance Networks in Europe”, Public Management Review, 10 (4) (2008)
- Noveck, B. S., “Wiki Government: How Technology Can Make Government Better, Democracy Stronger, and Citizens More Powerful”, Brookings Institution Press (Washington, D. C., 2009), http://dotank.nyls.edu/communitypatent/P2Panniversaryreport.pdf
- Malone T. W., Laubacher, R. and Dellarocas, C., “The Collective Intelligence Genome”, (MIT Sloan Management Review, Spring 2010)
- Krebs, V. and Holley, J., “Building Smart Communities through Network Weaving”, http://www.orgnet.com/BuildingNetworks.pdf
- Brown, K., and Keast, R., “Citizen-Government Engagement: Community Connection through Networked Arrangements”, Asian Journal of Public Administration, 25 (1) (June 2003), pp107-131, http://sunzi.lib.hku.hk/hkjo/view/50/5000083.pdf 02. Keast, R., Mandell, M. P., Brown, K., and Woolcock, G, “Network Structures: Working Differently and Changing Expectations”, Public Administration Review, 64 (3) (May/June 2004), pp363-371, http://www.csus.edu/indiv/s/shulockn/executive%20fellows%20pdf%20readings/keast%20network%20structures.pdf