Key Capabilities for Long-Term Development Strategies in the Face of Unprecedented and Uncertain Large-Scale Global Change
Inevitable and uncertain systemic change demands transformational responses
It seems increasingly likely that by sometime in the second half of this century our world will be warmer by at least 2°C. This will inevitably drive substantial biophysical, policy, technological, and socioeconomic changes over coming years and decades. The human responses to mitigate greenhouse gas emissions—in the form of technological, regulatory, and financial disruptions—will continue ramping up in scope and scale as the world rapidly shifts to lower-carbon economies. These shifts will alter the ways cities and regions function and how individuals and communities live and interact. Such changes will compound the dynamics and complexities of the biophysical changes induced by climate change. In many instances societal adaptations will need to be transformational (i.e., calling into question current values and objectives about issues such as species triage or assisted relocation and the sanctity of individual liberties such as where and how to live one’s life), which will likely reinforce inequities and entail unavoidable power struggles, economic costs, and cultural and environmental losses and suffering (Fazey et al. 2018).
Challenges to long-term development planning due to uncertainty
Proactively planning for these eventualities and implementing strategic and transformational development strategies will substantially reduce the potential disruptions and costs. Yet there is little evidence of official, systematic, and coordinated efforts in this regard, especially not at the rate and scale required. Much of this inertia in strategic societal responses can be explained by the uncertainty of the changes, particularly due to their complexity and unprecedented scale. In other words, although large-scale biophysical and socioeconomic changes are inevitable under climate change, the interconnectedness and dynamics of systems will make us uncertain about the timing, likelihood, and consequences of these changes and how to respond.
Epistemic and existential uncertainty such as this often leads to confusion, contestation, or conflicts about problem definitions and proposed solutions and manifests in decision inertia or maladaptive short-term, reactive, and incremental decisions. This is because of humans’ inherently limited cognitive ability to understand complexity; the consequent adoption of default but inappropriate behaviors to cope with the resulting uncertainty and ambiguity (e.g., denial, arrogance, overconfidence, optimism bias, sticking to the tried-and-tested, adoption of reductionist and controlling decision-making approaches); prevailing rules and values that prevent new knowledge or new transformational options from being considered (e.g., prevailing risk and cost-benefit analyses ineffective at accounting for intangible values and unprecedented catastrophic events); and the powerful political influence of incumbent players with vested interests in the status quo.
Key capabilities required to create and implement climate-compatible long-term development strategies
Given the above context, long-term development strategies need to explicitly acknowledge and accommodate three things (Dunlop et al. 2013, 102). First, they need to account for the possibility of large, unprecedented, and irreversible change. Second, they need to acknowledge uncertainty and ambiguity about both the nature of this change and how to respond. And third, they need to accommodate the multiple values potentially affected by the change. But determining and agreeing on the what, why, and how of these elements is not easy. All of them have implications for the capabilities required to develop long-term development strategies. These capability requirements fall into four broad categories: (1) creating and sustaining an authorizing environment, (2) credible framing of problems and opportunities, (3) generating and prioritizing options to address the problem or harness the opportunity, and (4) adaptive implementation.
1. Creating and sustaining an authorizing environment
An essential first step to developing a credible and implementable long-term strategy is having an authorizing environment to do so. This helps ensure that the activities and products of the strategy are supported by actors with authority and agency. This authorizing environment may not exist initially and may be challenged or weakened over time. This is particularly the case when problems or opportunities are uncertain or ambiguous and span long time horizons, large geographies, and diverse economic sectors or jurisdictions. Inclusive processes are therefore required to build and maintain the collaboration required for collective action through aligned agendas, shared ways of measuring and reporting on successes and failures, mutually reinforcing activities, and continual communication (Kania and Kramer 2011).
2. Credibly framing the problem or opportunity situation
Little progress can be made if there is no or limited shared understanding among stakeholders of the problem or opportunity. This is because the options that comprise the long-term development strategy are determined by the problem to be solved. Yet developing a shared understanding of a problem or opportunity is not straightforward where the causes are dynamic and complex, uncertainties are pervasive and fundamental, and there are many stakeholders with diverse perspectives and experiences of the situation. Key capabilities required to frame complex problems or opportunities involve systems thinking, participatory knowledge mapping, and visioning or forecasting of possible unprecedented, uncertain futures.
Complex systems thinking requires that individuals recognize (1) that systems are comprised of diverse agents (people and organizations) that interact with each other in nonlinear ways and self-organize, (2) that these diverse adaptive agents are highly interconnected and coevolve with the material or biophysical world, (3) that these nonlinear interactions result in emergent properties (i.e., system behaviors) that are often deeply uncertain or unpredictable, and (4) the need for and importance of investing in mechanisms (language, concepts, tools, and processes) to promote communication and learning (McDaniel 2007). Systems thinking is a prerequisite to framing or defining a problem, as it promotes humility about one’s own understanding and empathy regarding how other people understand the system.
Knowledge mapping involves stakeholders collaboratively “mapping” or categorizing the levels of incompleteness in knowledge about the likelihood and consequences of changes in events or the state and dynamics of a system (Figure 1A) (Stirling and Scoones 2009). Categorizing knowledge in this way is useful as it enables diverse decision-makers to share, deliberate, and negotiate their diverse perspectives and understandings of the dynamics of the system or problem situation. In doing so, this process can reveal causes and consequences of gaps in knowledge and raise awareness of the reasons for confusion or contestation about a problem definition and the objectives of interventions. Mechanisms such as “boundary objects” (conceptual or tangible items that live “in multiple social worlds and . . . have different identities in each” [Star and Griesemer 1989]) and bridging organizations are essential in these processes to help overcome disciplinary, experiential, and ideological differences and power imbalances. Participatory knowledge mapping is important as it reveals where the incompleteness in knowledge is reducible through more research and where it is likely to be difficult if not impossible to reduce due to the complexity and continually changing dynamics of the system. The challenge, then, is more about managing uncertainty, ambiguity, and ignorance through mapping different framings of complex problems, reducing compounding exposure to surprise; and “opening up” greater accountability for the normative judgments in long-term development strategies.
Figure 1. States of Incomplete Knowledge Including Examples and Methodological Responses to Diagnosing and Addressing These
Source: Adapted from Stirling and Scoones 2009.
Future visioning and forecasting. If the future is expected to be the same or only marginally different from the present (or if the past is assumed to provide a reasonable approximation of the future) then long-term strategies will promote incremental nudges to business as usual (BAU). This will reinforce the status quo and in the presence of large, rapid, uncertain global changes will lead to maladaptive development strategies. Therefore a range of scenarios of possible futures is needed to inform the creation of long-term development strategies. In this regard, it is insufficient to only consider expected or optimistic scenarios, as this makes possible highly regrettable outcomes in a worst-case situation. Low-regret or robust strategies therefore need to be informed by a range of scenarios including a plausible worst-case scenario of the future. Developing and using credible catastrophic scenarios to create recognition that BAU is unlikely to be feasible is difficult, however, due to underdeveloped skills of imagination, storytelling, and translation of the implications of possible futures for today’s decisions and governance arrangements. There are, however, growing numbers of examples where these capabilities have been developed and combined with artificial intelligence, computer simulation, and the arts and humanities to allow stakeholders to create or “live through” plausible extreme scenarios of the future, thus informing the collaborative creation of long-term development strategies (Scharmer 2009; Tyszczuk and Smith 2018; Dulic et al. 2016).
3. Generating options for long term development strategies under uncertainty
Long-lived investments (such as in physical infrastructure) will need to withstand a range of changing climate conditions, which will make design more difficult and construction and maintenance more expensive. Additionally, the uncertainty of future climate makes it impossible to directly use the output of a single climate model as an input for infrastructure design. And we cannot rely on the needed climate information becoming available soon. Therefore, instead of optimizing based on the climate conditions projected by models, or ignoring these uncertainties entirely, new infrastructure investments should consider options that perform satisfactorily across a range of possible future conditions (i.e., robust options). Numerous principles or heuristics for doing this include selecting “low-regret” strategies that yield benefits even in the absence of climate change, favoring reversible and flexible options (e.g., nature-based solutions or retreat instead of hard infrastructure to protect coastal communities), buying “safety margins” in new investments, investing in improving information about the rate and magnitude of change, and reducing decision time horizons (e.g., increase the rate of depreciation to allow for earlier replacement) (Hallegatte 2009; Fankhauser et al. 1999; Wilby and Dessai 2010).
Yet many robust or low-regret options are currently not legal, legitimate, or credible, such as (1) widespread retreat of coastal infrastructure and communities in the face of rising sea levels, coastal erosion, and disappearing coastal ecosystems; (2) allowing species or ecosystems to migrate or become extinct as their environments inevitably shift and transform in order to avoid growing conservation costs in the face of inevitable failure; and (3) allowing for lower levels of critical service supply reliability to avoid the costs of attempting to resist disruptions. Making these legitimate, legal, and credible will require strategic actions to overcome regulatory, cultural, political, and behavioral barriers.
Doing this, however, also will require capabilities almost entirely absent in most organizations, such as how to diagnose systemic and knowledge barriers that constrain these options, and how to identify and implement societal change processes to overcome these barriers to create decision contexts more enabling of transformation. Existing approaches to effectively diagnose systemic barriers include the values-rules-knowledge model of decision contexts (Gorddard et al. 2016), the Institutional Analysis and Development framework (Huntjens et al. 2012; Ostrom 2011), and the “regimes of truth, rule and accumulation” approach to understanding political dynamics (Scoones 2016). Diagnosis of the problem reveals potential leverage points to shift the system away from undesirable trajectories, while “theory of change,” “systemic action research,” “system change,” and “transformational adaptation pathways” have been shown to be effective ways of identifying and sequencing options to adaptively act upon these leverage points (Aragón and Macedo 2010; Burns 2014; Wise et al. 2014).
4. Adaptively implementing the strategy
Due to the relentless uncertainty and ambiguity associated with rapid global change, long-term development strategies need to be implemented within an ongoing adaptive monitoring, evaluation, and learning (MEL) framework. The approaches to MEL need to be flexible and informed by the nature of change and associated knowledge deficits, the presence and causes of contestation or conflict among stakeholders, the intent of any interventions being considered, the capacity of the people involved, and the resources (time and money) available to invest in learning activities (Butler et al. 2016).
In complex systems such as interconnected energy, water, or food systems, learning is fundamental even to simply build understanding and shared framing of the problems. To be effective, learning processes need to respect and manage the diversity of not only frames, values, and worldviews but also positional and personal power and the politics of broader material and social relations (Leach et al. 2010). Pivotal to these are (1) the design and structuring of group-work informed by understanding of adult learning, knowledge cultures, complex systems, and human psychology and behavior, and (2) the use of “boundary objects” such as conceptual models, theoretical frameworks, drawings produced by the group, and material objects. Material objects have been shown to be especially effective as boundary objects in contested, antagonistic situations as they “objectify” knowledge, promote thought, and “slow down” thinking, leading participants to question and disassociate from previous networks or their relationships with the material world (Eisenhauer 2016).
Another approach to learning involves targeted experiments such as pilot projects of alternative management approaches or governance arrangements as part of the long-term development strategy (Heilmann 2008). These experiments promote experiential learning about the performance or effectiveness of the management option (single-loop learning) or governance intervention (double-loop and triple-loop learning) at meeting the strategy’s objectives or against the preexperiment assumptions as described in the theory of change (Butler et al. 2016; EAP 2018).
The effectiveness of experiential learning approaches such as these, however, can be limited in situations of rapid, unprecedented, and ongoing global change where understanding of options’ past and present performance cannot confidently be used as a basis for projecting their future performance. In such situations, experience-based learning ought to be complemented with forward-looking mechanisms, such as foresighting and scenarios, that promote learning and leading from the future as it emerges (Scharmer 2009). Elements of future-oriented learning involve personal reflection and transformation (“presencing”) to be able to sense emerging novel trends; developing and drawing on abilities such as intuition, judgment, and ethics to preemptively formulate assessments about what these might mean for management and governance; understanding and being comfortable with irreducible uncertainties and ambiguities; preemptively creating flexible options to exploit possible opportunities and avoid problems as they emerge; and having the trust and confidence of stakeholders to legitimately act on this intuition (Scharmer 2009). This forward-looking learning is essentially focused on testing and modifying one’s sense-making, intuition, and judgment about the potential future performance of current management.
Summary and key recommendations
The unprecedented scale, complexity, and uncertainty of climate change demands long-term development strategies that are transformational and adaptive in their approach and intent. Yet such strategies face many barriers in the form of highly constraining societal values, rules, or knowledge. Pragmatic steps to make progress in such contexts ought to involve combinations of top-down institutional and narrative changes and bottom-up, community-based, or private-sector-led initiatives that purposefully (1) build the key capacities outlined above in people of all ages through diverse forms of education and training, theoretical and applied; and (2) create communities and networks of research and practice around transformational projects to capture and share lessons that enable wider, faster, more adaptive, and sustained implementation of strategies.
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The author would like to acknowledge and thank Rachel Williams and Seona Meharg from the CSIRO for their valuable insights and advice, which definitely helped make this article more comprehensive, credible and salient.