How can we manage decision making within our CO in the face of uncertainty and complexity?

Why is it relevant?

In contexts of uncertainty, change, and complexity, decision making within your CO becomes more challenging as there are multiple unknowns, rapidly changing circumstances, and intricate interconnections between various factors. This often creates hesitation, fragmented responses, or reliance on narrow expertise in decision-making processes. By gaining insights into effective decision-making strategies, you can navigate these complexities and make informed choices that address emerging issues and maximise the impact of your CO. This understanding allows for adaptive and flexible decision making, enabling your CO to respond promptly to new information, adapt strategies, and engage stakeholders in a way that is responsive to evolving needs and dynamics. Additionally, managing decision making under uncertainty and complexity requires careful risk assessment, integration of diverse knowledge sources, and the ability to balance short-term actions with long-term goals, ultimately leading to more resilient and sustainable outcomes within your CO.

How can this be done?

Addressing this challenge requires practices that both structure and legitimise decision-making while leaving room for adaptation. One way is through adaptive management, operationalised by an iterative Plan–Do–Check–Act cycles, which allow participants to incorporate new information, monitor outcomes, and adjust strategies accordingly. A second approach is polycentric decision-making, supported by multi-level negotiation platforms that create parallel arenas for deliberation and coordination across scales, ensuring that no single perspective dominates and that interdependencies is explicitly addressed. Finally, deliberative resilience can be fostered through structured deliberation methods such as Multi-Criteria Decision Analysis (MCDA), which help participants systematically weigh diverse values and uncertainties, making disagreements transparent and productive rather than paralysing (Stirling, 2008). Together, these tools operationalise decision-making as an iterative, inclusive, and adaptive process that can hold complexity rather than collapse under it.

Existing (adapted) approaches	Featured tools
A. Adaptive management	Flexible and iterative approach to decision-making within the CO using Plan–Do–Check–Act (PDCA cycle) - also known as the Deming or Shewhart cycle
B. Polycentric negotiation	Create multiple parallel spaces where different actors can advance solutions, which can later be aligned using Scenario building workshops
C. Deliberative resilience	Accepting that disagreement itself can be productive, and focus on building the capacity to stay engaged despite unresolved differences using Multi-Criteria Decision Analysis (MCDA).

A. Adaptive management

Adopting an adaptive management approach can greatly support decision making within your CO, particularly when operating under conditions of high uncertainty and complexity. Adaptive management approaches emphasise flexible and iterative processes that allow for continuous monitoring, evaluation of outcomes, and adjustment of strategies based on new information and changing circumstances (Williams & Brown., 2018). This approach enables your CO to respond to uncertainties and complexities effectively, ensuring that decisions remain relevant and impactful.

Key to adaptive management is the development of a comprehensive monitoring strategy. Data on environmental conditions and CO activities (for example, sensor measurements, observations, or reported events) should be regularly collected, monitored, and reviewed, allowing for monitoring protocols and action plans to be adjusted if required. This iterative process enables your CO to adapt its strategies based on emerging patterns, challenges, and opportunities, ensuring that decision making remains evidence-based and responsive to the dynamic nature of the observed system (Levin et al., 2013).

A variety of tools have been identified for the implementation of adaptive management (Norton, 2018). However, commonly all approaches share four concrete, iterative steps: Plan, Do, Monitor, Learn (Webb et al., 2017). This cyclical approach to adaptive management incorporates a learning cycle, highlighting the importance of using lessons learned from previous stages to inform the next.

Plan, Do, Monitor, Learn Adaptive Management approach (Webb et al., 2017)

This tool taps into these iterative learning principles is a six-step activity, that aims to promote creativity when dealing with uncertainty, risk and change (Nyberg, 1999). This tool provides a structured process to simultaneously implement and evaluate actions, and to modify or refine future activities as needed.

Steps:

1. Problem Assessment – Problems (with decision making in your CO in contexts of uncertainty, change, and complexity) can be identified in a variety of ways. One approach is to use facilitated workshops, in which participants define the scope of the issue. Participants can integrate existing knowledge about the system or issue and explore potential outcomes of different actions. To evaluate which actions are most likely to achieve management objectives, explicit forecasts are generated. This process also helps identify crucial gaps in understanding that hinder outcome prediction.

2. Design – Creating a plan and monitoring program that offer reliable feedback on the effectiveness of chosen actions. Ideally, the plan should address the identified gaps in understanding from Step 1. Proposed plans or designs should be assessed based on factors such as costs, risks, informativeness, and their ability to meet management objectives.

3. Implementation – Implementing the plan

4. Monitoring – Focusing on tracking indicators to determine the efficacy of actions in meeting management objectives. It also involves testing the hypothesized relationships that formed the basis for the initial forecasts.

5. Evaluation – Comparing actual outcomes to the earlier forecasts, and the reasons behind any disparities are analysed and interpreted.

6. Adjustment – Modifying practices, objectives, and the forecast models based on new insights gained. The understanding acquired in each of these six steps may lead to a re-evaluation of the problem, generation of new questions, and exploration of alternative options, forming an ongoing cycle of improvement.

Such tools have considerable overlap with co-evaluation tools, such as the MICS Impact Journey Approach (Wehn, Gharesifard & Somerwill, 2021). This outlines a methodology for citizen science or CO projects to incorporate a wide range of stakeholders in iterative problem identification, and impact assessment. This tool is comprised of three steps.

Steps:

1. Context analysis – During this stage, stakeholders can reflect on the context in which the initiative is being established and identify pathways of change, desired outcomes and impacts. Relevant stakeholders are identified, and political, environmental, social, and economic contexts are evaluated.

2. Development and validation of an impact journey map – Relevant domains of change, expected impacts, and expected outcomes are drafted in this stage. Based on this, strategies for achieving desired changes are formulated, and cause and effect relationships are identified. Key impacts are then operational by the stakeholders.

3. Developing an impact monitoring strategy/continuing co-evaluation – Indicators and methods for measuring indicators are identified, and an overall plan for monitoring and evaluation of citizen science impact is created. If required, context analysis is conducted again at regular intervals to ascertain if the strategy is still appropriate.

The Plan–Do–Check–Act (PDCA) cycle, (also called the Deming Cycle) is a classic iterative management method for continuous learning and improvement. It’s often used in adaptive management, governance, and citizen science because it provides a simple, yet structured way to deal with uncertainty.

Steps:

1. Plan: identify a problem, set objectives, and design an intervention or action plan.

2. Do: implement the plan on a small scale or pilot basis.

3. Check: monitor and evaluate the outcomes against the objectives, looking for successes, failures, and unintended effects.

4. Act: adjust the plan, scale up what works, and revise or abandon what does not, before beginning the cycle again.

This cyclical process ensures that decision-making isn’t static but is continually updated in light of new evidence and experiences. In governance contexts, it helps stakeholders experiment safely, learn collectively, and adapt strategies over time rather than locking into rigid solutions.

B. Polycentric negotiation

Polycentric negotiation refers to the practice of creating multiple, overlapping spaces for discussion where authority and decision-making are shared. Instead of relying on a single authority, negotiations unfold across levels (community, municipal, regional) and between sectors (civil society, government, academia). This approach draws from polycentric governance theory, which highlights that complex problems are better addressed through interconnected centres of decision-making that can adapt, experiment, and learn from one another (Ostrom, 2010). In your CO, polycentric negotiation helps prevent dominance by a single person/group and provides space for all voices to enter discussions. It creates opportunities for alignment across scales while respecting contextual diversity, making agreements more robust and legitimate.

One practical tool to support this approach is scenario-building workshops. These workshops allow each group to map out possible future pathways and outcomes in a structured way. The results from different groups can then be compared, aligned, and synthesised to build a shared direction across the CO.

Steps:

1. Identify critical drivers and uncertainties shaping their system (e.g. water scarcity, budget constraints, institutional mandates).

2. Develop multiple plausible scenarios by combining these drivers into contrasting but realistic trajectories.

3. Map sector-specific responses to each scenario, enabling participants from different governance levels to stress-test their strategies against those of others.

4. Compare and align pathways across groups, highlighting interdependencies, synergies, and potential conflicts.

5. Agree on robust strategies that can hold across multiple futures, ensuring flexibility and resilience.

This tool is widely used in environmental governance. For example, the U.S. National Park Service facilitated scenario workshops in Acadia National Park, where communities, scientists, and managers co-developed climate futures and aligned them into adaptive management plans. These workshops bring representatives from each decision-making space together to co-develop and compare future scenarios. As explained by SessionLab, scenario planning involves guiding groups through the process of identifying key uncertainties, crafting alternative storylines, and stress-testing assumptions – creating future-ready, resilient strategies rather than predicting a single outcome.

C. Deliberative resilience

Deliberative resilience involves fostering the capacity of participatory processes to withstand disagreement, tension, and uncertainty without collapsing. Rather than aiming for quick consensus, deliberative resilience emphasises the value of open discussion as part of problem-solving. It encourages stakeholders to keep engaging even when discussions are difficult, thereby normalising conflict as part of democratic practice. In COs, this means designing spaces where participants can confront trade-offs, revisit assumptions, and adapt solutions over time. By cultivating resilience in deliberation, your CO can move beyond fragile agreements and instead develop adaptive pathways that can evolve as new information, values, and uncertainties emerge.

The ability to navigate disagreement constructively can be strengthened through Multi-Criteria Decision Analysis (MCDA). MCDA provides a structured process for identifying, comparing, and weighing different perspectives and options. By turning conflicting viewpoints into systematically assessed criteria, MCDA ensures that differences are not dismissed or suppressed but recognised as legitimate inputs for decision-making. Through conducting an MCDA participants learn to acknowledge and respect different viewpoints and accept that difference is inevitable and can be constructive. Through the analysis participants will give structure to the different opinions and options that exist and develop a system for considering these and moving forward with a dynamic framework to help manage decisions.

Steps:

1. Define the decision context - Clarify the problem, objectives, and scope of the decision.

2. Identify stakeholders and perspectives - Ensure relevant actors are involved; gather their values and concerns.

3. Generate alternatives/options - List the possible courses of action or solutions to be assessed.

4. Develop decision criteria - Identify the dimensions along which options will be evaluated (e.g., cost, equity, environmental impact).

5. Weight the criteria - Determine the relative importance of each criterion, often through stakeholder input.

6. Score the alternatives - Assess how well each option performs against each criterion.

7. Aggregate the results - Combine scores and weights to compare alternatives transparently.

8. Conduct sensitivity analysis - Test how robust the results are to changes in weights, scores, or assumptions.