Going beyond the purely descriptive approach, a distinction can be made between methods that assume that outcomes of institutional arrangements can be predicted and those that assume that this is in principle not possible.

If it is assumed that, due to for example complexity in the social system, outcomes of institutional arrangements cannot be predicted, the appropriate task is explaining governance emergence.

Governance emergence approaches take as a fundamental theoretical assumption that it is inherently difficult to predict outcomes of institutional arrangements because of the complexity in action-outcome linkages and the importance of contextual factors (Ostrom 2005, 2007, 2009; Huitema et al. 2009). These methods are based on in-depth description of the many factors, material, ideational and historical, which lead to the emergence of institutions. It logically follows from this assumption that designing institutions or policies in order to achieve a policy goal (such as, e.g., reduced climate vulnerability) cannot be meaningfully addressed before governance emergence has been explained. Governance emergence approaches, therefore, strive to understand the existing institutions, particularly addressing which contextual factors give rise to a particular institutional arrangement in a given case. While these approaches can be further differentiated based the subsequent decision node in the decision tree, it should be pointed out that understanding and explaining the emergence of institutions is a broad field and these decision nodes provide only some high level entry points (see the Toolbox section on institutional analysis for discussion and examples).

On the other hand, if the assumption is made that governance and policy outcomes can be predicted then the task of governance (or policy) design may be addressed. Governance design approaches assume that it is possible to predict outcomes of institutional arrangements with some confidence and on this basis addresses the question of how to design effective policies and institutions. Because adaptation concerns many different policy domains, the task of adaptation policy design may be to mainstream the consideration of climate change risks into existing sectoral policies (see Toolbox section on institutional analysis). Mainstreaming approaches can be further differentiated on the basis of whether climate is already considered in a given policy. If climate has not been considered, then policy screening (or portfolio screening) aimed at analysis of whether potential climate impacts threaten existing policies is appropriate (see Klein et al., 2007). On the other hand, climate proofing is appropriate to design policies in which climate impacts has been identified as a risk. ‘Proofing’ policies involves addressing relevant risks early in the policy formulation process, to identify any obvious effects on other sectors or objectives. The practice of proofing policies is well-established in other sectors, such as health, and rural development (Urwin and Jordan 2008: 188).