By Shirin Malekpour and Jens Newig
This research was a collaboration between Monash Sustainable Development Institute, Monash University (Melbourne, Australia), and the Research Group Governance and Sustainability, Leuphana University (Germany). Dr Shirin Malekpour (Monash) is the recipient of the Green Talents award, which enabled her to undertake a research sabbatical at Leuphana in 2019, conducting this study in collaboration with Prof. Jens Newig.
Adaptive planning is an approach to long-term strategic planning when confronted with significant uncertainties that dwarf any seemingly robust forecast (think Covid-19 pandemic). It is a shift from the conventional ‘predict-and-act’ approach, which assumes that we can anticipate the most likely future scenarios, and optimise our strategies accordingly. When uncertainties are profound and we have no good grasp of what can happen in the future, adaptive planning posits that decision makers should not even dream of an optimal strategy that can work in the long term. Instead, they need to adopt strategies that are flexible, and a planning approach that remains open to adaptation over time, in order to proactively respond to changing circumstances.
In today’s world overwhelmed by unprecedented events and profound shocks, adopting an adaptive approach to long-term strategic planning might sound like a no-brainer. There are, in fact, a range of tools for adaptive planning available to decision makers, such as those developed by the Decision Making Under Deep Uncertainty (DMDU) community. However, reactive planning and over-reliance on narrow projections still appear to prevail.
Some scholars have argued that the poor usage of adaptive planning is not due to a lack of appreciation of adaptive planning, but because of unfavourable governance processes, institutional frameworks and organisational arrangements within which adaptive planning should take place. Some of these issues impacting adaptive planning have been discussed in individual case studies, but there has been no larger scale comparison across various cases to provide a comprehensive picture of what it takes to put adaptive planning into practice.
In our recent publication, we present a meta-analysis of 40 cases of adaptive planning applications. The cases were from diverse geographies (i.e. all continents), sectors (e.g. water, transport, etc.) and implementation scales (i.e. local to national). We assessed: 1) to what extent those applications adhered to the principles of adaptive planning – in other words, how adaptive were those adaptive planning applications, and 2) what enablers and barriers they faced in the broader governance and institutional arrangements.
So, what did we find?
Figure 1: Adaptive planning in different geographies. The data has been sorted (left to right) based on the number of reported cases of adaptive planning. Check the publication for further details on how we calculated average adaptiveness.
Figure 2: Adaptive planning in different sectors. The data has been sorted (left to right) based on the reported number of cases of adaptive planning. Check the publication for further details on how we calculated average adaptiveness.
We found that in the studied cases, adaptive planning applications are far from ideal. The main challenge is in setting up a monitoring regime that can identify early signals, and a systematic process that can assist with activating contingency plans when needed. The principal barrier to this is the lack of long-term investment strategies that go beyond short-term budgetary cycles for individual projects. There is a need for a redefinition of planning priorities and success indicators, from efficient delivery and implementation (i.e. a quick fix), to long-term outcomes achieved through experimentation, learning and adaptation.
Another challenge has been in using a wide range of future scenarios as the basis for decision making, which is another principle of adaptive planning, in addition to monitoring and keeping options open. The implicit assumption that future conditions could be estimated from existing trends was identified as a significant barrier to using a wide range of scenarios. This confirms earlier observations in the literature that, despite encountering major uncertainties, decision makers still rely on forecasts and a limited number of future scenarios to plan for the future. Another barrier is decision makers’ risk aversion and reluctance to acknowledging that ‘they do not know’. They prefer to squeeze future scenarios into a manageable set that is easier to grasp and communicate with stakeholders and the broader public.
On the other hand, there are a range of enablers that can facilitate adaptive planning. When strategic planning takes place in a transdisciplinary environment through effective and uninterrupted science-policy exchange, it is easier to avoid a reductionist approach to decision making.
Furthermore, adaptive planning is better enabled when there is a dedicated governance body that takes on the coordination role for adaptive planning activities. This would avoid situations where adaptive planning is taken on as an add-on to ongoing activities of a strategy team, with little to no dedicated resources for effective implementation. A coordinating body is not meant to drive all activities in a top-down approach, but rather to broker and negotiate activities across different stakeholders, and to absorb some of the transaction costs for adaptive planning.
The findings of our study shed light on some of the ingredients of a governance framework for enacting adaptive planning. They indicate what enablers should be harnessed, and what barriers should be overcome in an adaptive planning endeavour. Future research could extend the findings of this study to fully articulate how adaptive planning could be operationalised: who should be involved, what structures should be set up, what resources would be needed, and what practices would need to be put in place to successfully exercise adaptive planning.