Designing Collaborative Governance Decision-Making in Search of a ‘Collaborative Advantage’

Abstract

Collaborative governance institutions consisting of government and civil society actors often emerge to solve complex policy problems. Yet decades of research on collaborative governance has found that realizing the ‘collaborative advantage’ is often very difficult given the multitude of actors, organizations and interests to be managed. This article deploys a participant observation approach that also harnesses data from a natural experiment in collaborative governance for homelessness policy in Vancouver, Canada, to reveal the distinct collaborative advantage produced in terms of policy, using empirical decision data and counterfactual analysis. The data reveal that nearly 50 per cent of the policy decisions made in the collaborative institution would not be made in the alternative scenario of unilateral bureaucratic control. The collaborative advantage realized in this governance institution that is premised on horizontality, deliberation and diversity is the result of a series of small interventions and the strategic deployment of rules devised by the bureaucratic metagovernor in charge of steering the governance collaboration.

Key words:

• Collaborative advantage
• collaborative governance
• metagovernance

Notes

1 The concepts developed in the literature to describe such governance patterns are varied – network governance (Sørensen and Torfing 2007), partnerships (Pierre 1998; Kernaghan 1993), new public governance (Osborne 2010), empowered participatory governance (Fung 2004) and collaborative public management (Huxham and Vangen 1996) – but they all share a focus on examining the relationships between interdependent government and civil society actors as they collaborate on public policy development and implementation.

2 This should not be interpreted as claiming that bureaucrats are cautious and conformist individuals, but ‘that government bureaucracies are caught up in a web of constraints so complex that any big changes are likely to rouse the ire of some important constituency’, and thus tend to favour the most defensible and objective criteria when making decisions (Wilson 1989, 69).

3 The ‘network management’ literature similarly aims to understand how governance networks are structured and managed, emphasizing strategies of ‘process management’ and institutional design as key levers for network managers that shape policy outcomes. Yet specific strategies for how network managers or ‘metagovernors’ steer productive collaborative governance decision-making remain under-specified.

4 This is rarely achieved even in the political experiment world, as it is very uncommon to get experimental and control groups to complete precisely the same tasks (Gerber and Green 2012). As such, we can directly compare their scoring and decision-making without engaging in typical (speculative) counterfactual analysis – in this case, we have data for the counterfactual.

5 Recall that RSCH members formally make the decisions, but parallel to all of this activity is a group of bureaucratic staff who individually review and score proposed programmes considered by each RSCH team as a system of support for the decision-making.

6 These values are measured in absolute value terms because at this point we are most interested in identifying difference, not the direction of difference.