Unit 3. Solution Identification

determining the most appropriate response through a holistic approach to brainstorming and decisionmaking

Module 3.2. Applicable Tools

Solution identification involves brainstorming and reviewing possible interventions that address the issue(s) identified during problem analysis.

This module presents a variety of tools for identifying and weighing the pros and cons of possible solutions.

Bear in mind that there are any number of ways to approach solution identification; you will need to consider which will be most useful in your given context. Combining several different techniques will help you think about various entry points and possible actions.

This module will help users:

  • explain the importance of broad brainstorming combined with feasibility and prioritisation considerations
  • consider how Linkage Charts can be used to help brainstorm connection ‘interruptions’
  • highlight the need for climate sensitivity and contextual awareness through scenario forecasting

Solution Trees

What is A Solution TREE?

A solution tree turns a problem tree into an intervention brainstorm. As a visual tool for breaking down complex problems, solution trees enable a systemic exploration of various potential solutions. A solution tree helps identify how to solve a central issue by mapping out possible responses and the steps required to implement them.

Why CREATE A solution TREE?

A solution tree provides a visual, structured, and quickly understood way to identify long- and short-term solutions to the issues identified in a problem tree. The solution tree helps visualise complex decisions, uncover alternative solutions, and clarify the most viable actions for solving a problem. It’s particularly useful for teams working collaboratively to brainstorm and assess multiple pathways toward a solution.

By using problem and solution trees together, it is easy to understand how a solution can effectively disrupt a problem. It can also highlight when a possible intervention would be incomplete and needs to be changed or complemented: if not all ‘branches’ of the problem will be addressed by an action, alternative or additional solutions need to be considered.

What are some limitations of A Solution TREE?

Solution trees depend heavily on the initial identification of solutions and actions. If relevant solutions or details are overlooked in the beginning, the tree may not fully represent all possible pathways.

For large, multifaceted problems, solution trees can become overly complex and difficult to navigate. A highly branched tree can be challenging to interpret and may lead to decision fatigue.

Solution trees tend to assume a straightforward progression from problem to solution, which may not be realistic for issues that require adaptive or iterative approaches. Within a given context, there can be a number of challenges, and they may interact with each other. Real-world problems often involve feedback loops, dependencies, and changing conditions that don’t fit well into a more linear tree structure.

Cooperation Timelines

What is A CONFLICT TIMELINE?

Cooperation timelines are chronological summaries of the key peace efforts and cooperative actions that have taken place in a conflict context. Cooperation timelines help remind us that collaborative action can coexist with ongoing conflicts and environmental stress, and encourage us to think more broadly about who and what we might engage in future efforts. By highlighting previously attempted solutions, they can also help us understand where interventions went wrong and/or reconsider solutions that were not properly implemented.

As with a conflict timeline, the horizontal axis represents time, and might indicate specific dates for a real-world scenario, or more generically denote the passage of time for a hypothetical case study.

A basic cooperation timeline can have just one vertical line, with all events plotted simply against time. More complex cooperation timelines can use the y-axis to plot a chosen factor against the progression of time, with events used to annotate the chart. Particularly useful for a cooperation timeline may be scale or actors: While certain actors (e.g., armed groups) were clashing, what were other actors (e.g., a local NGO) doing? Two-dimensional cooperation timelines take more time to create and read, but provide more information.

Cooperation events can also be plotted onto an existing conflict timeline, helping analyse the interplay between negative and positive interactions.

Why CREATE A cooperation TIMELINE?

Cooperation timelines serve to illustrate how a situation has evolved over time. For prolonged conflicts, a cooperation timeline can be useful in analysing conditions for peace and conflict, and identifying possible partners for solutions.

One of the greatest advantages of a cooperation timeline is its flexibility, as any number of factors can be considered via the y-axis. As with a conflict timeline, a cooperation timeline can visually summarise events taking place on various scales: A peacemaking effort may have been ‘spoiled’ more by an external shock than internal missteps; knowing this can inform more robust attempts in future. Cooperation timelines can also be made for successful interventions, providing inspiration for projects in other contexts.

What are some limitations of A cooperation TIMELINE?

Like all solution identification tools, a cooperation timeline is dependent on the situational awareness of its creator(s). Multi-scalar cooperation and/or ‘failed’ peace attempts may not be widely known. Excluding or overlooking an action may affect the success of a proposed intervention: For example, if a suggested solution was tried by a different group years prior but did not succeed, there may be bitterness around the proposal. If the previous cooperative work of various groups is not included in a timeline that is seen by others, there may be an erosion of trust and/or disgruntlement around a lack of credit.

Linkage Interruptors

What are linkage interruptors?

As introduced in Unit 2, linkage charts visually showcase the interactions and relationships between various actors, aspects, and events in a given setting. Interruption brainstorming uses an existing linkage chart as a springboard for identifying possible solutions. Systematically working through each linkage (i.e., arrow) on a linkage chart, considering various technical and social interventions that would break that particular cause-and-effect relationship, helps create a wide-ranging list of actions that could positively influence a conflict context and/or reduce socioenvironmental stressors.

Why brainstorm linkage interruptors?

One of the advantages of linkage charts is that they visually summarise the complex relationships between social, environmental, political, and other factors in a conflict context. Interruption brainstorming is about identifying interventions that could ‘cut’, disrupt, or alter the relational links within that socioenvironmental system that exacerbate conflict, inequality, and insecurity.

By working to disrupt the multiple cause-and-effect relationships, including feedback loops, in a system, we can identify potential solutions that may not be readily apparent – especially when a problem and proposed solution are not obviously related, but have a connection uncovered by the linkage chart. For example, a multi-step pathway between gender roles and environmental degradation may suggest that a productive intervention to manage drought may be women’s literacy workshops, even though that may not be the most immediately evident solution.

What are some limitations of linkage interruptors?

Interruption brainstorming will only be as inclusive and creative as the linkage chart it works with: this approach relies on the robustness of an existing problem analysis tool. If a linkage chart is not carefully developed, using it to inform further stages of community environmental action planning will likely exacerbate biases and gaps.

Interruption brainstorming is also just that – brainstorming. It does not analyse the feasibility or efficacy of a proposed solution, and should be used in combination with other solution identification strategies.

Feasibility Matrix

What is a Feasibility Matrix?

A feasibility matrix is a decision-making tool used to evaluate and compare multiple options by determining their practicality and likelihood of success. Feasibility matrices assess the viability of various possible strategies in a structured and visual manner.

Why use a feasibility matrix?

Using a feasibility matrix helps compare and contrast different solutions in cases where there are a number of options. Creating a feasibility matrix will help you select which solutions or strategies make most sense to move forward with, depending on how realistic and practical they are. They will also help you identify any activities or strategies that are not practical enough to carry out, with attention to your internal capacity, external support, and contextual constraints. Feasibility matrices can also help refine ideas, making it easier to carry out proposed solutions.

What are some limitations of a feasibility matrix?

Reducing complex thinking about feasibility into single numerical scores can overlook nuances, trade-offs, or interdependencies. A feasibility matrix does not delve into the reasons behind feasibility issues, such as specific risks, uncertainties, or interdependencies.

It is important to remember that feasibility matrix is a snapshot of practicality at one point in time: the moment the matrix was created. It does not account for changes over time, such as shifts in locally available resources or technological advancements. Initial feasibility assessment might become outdated over time if the context or information availability changes. Further, some high-impact solutions that score poorly in an initial feasibility analysis could become feasible with additional support (for example, a community might not have the engineering expertise to create irrigation canals, and thus indicate such a solution as impractical; however, the support of a specialised partner could make canals a perfectly possible intervention).

Additionally, bear in mind that a high score on a feasibility matrix does not guarantee that a solution will succeed or tell you what will be necessary for success; instead, it helps indicate which solutions are particularly unviable. As with any tool, a feasibility matrix will work best when combined with other strategies that can help address its limitations. For example, scenario planning can help foresee and plan for future risks, uncertainties, or interdependencies not captured by the matrix.

Prioritisation Matrix

What is A prioritisation matrix?

A prioritisation matrix provides an analytical way to evaluate any number of potential projects based on specified criteria. By quantifying and systemically ranking various actions, a prioritisation matrix helps make an informed decision about where resources and efforts should be allocated. During the solution identification phase, a prioritisation matrix can help determine which of the proposed possible interventions is most relevant or important to pursue. Prioritisation matrices may also be helpful in program design and project implementation, if applied to specific tasks or possible variations of an intervention.

Why CREATE A prioritisation matrix?

Given the complexities of ecosystems and conflict contexts, there will be a wide range of problems – and potential solutions – to tackle through community environmental action planning. Each of these potential interventions will have different potential costs and outcomes. A prioritisation matrix is a valuable tool for decision-making, as it provides a clear, structured way to evaluate and rank tasks based on their importance and impact.

Prioritisation matrices can help focus efforts on activities that will yield the greatest benefits within the existing context. A prioritisation matrix also reduces subjective biases, ensuring that actions align with strategic goals and constraints such as time, budget, or resources. When used at more micro levels of project management (see Units 4 and 5), prioritisation matrices can simplify decision-making, promote team alignment, and ensure critical tasks are addressed first.

What are some limitations of A prioritisation matrix?

Depending on the criteria used for scoring, a prioritisation matrix may favour projects with immediate impact while overlooking long-term goals or strategic initiatives that require sustained effort. This is especially relevant for community environmental action planning, which often have long-term time horizons for resource investment and outcomes.

Most prioritisation matrices use only two or three criteria, which might not capture the full complexity of certain decisions, such as those requiring trade-offs between cost, risk, and long-term impact. Prioritisation matrices thus run the risk of oversimplifying complex issues and tasks if not used carefully; however, this must be balanced with the reality that more complex prioritisation matrices (i.e., those with a greater number of evaluated criteria) become more and more unwieldy.

While prioritisation matrices reduce bias in the decision-making process by making decision factors explicit and introducing quantified ranking, they are still based on people’s assessment of subjective criteria like importance, impact, or effort. This can lead to skewed or inconsistent outcomes if not carefully managed. Similarly, people may interpret criteria differently or have conflicting priorities, leading to disagreements and misalignment during the evaluation process. Participatory approaches can help mitigate these concerns and yield more robust calculations.

Scenario Forecasting

What is scenario forecasting?

Conflict contexts and environmental systems both involve a great many unknowns; these uncertainties feed into each other, while being exacerbated by climate change.

Scenario forecasting is about identifying a range of possible futures and determining how well a proposed intervention will hold up within each potential reality. Though we cannot predict the future, we can use patterns to imagine likely situations, and then ‘test’ a possible action by considering how it interacts with various forces in each setting.

Note: Robust scenario forecasting involves specialised expertise and complex mathematical models capable of predicting climate change effects and other conditions; however, even a vastly simplified version of scenario forecasting can be helpful as a thought exercise when evaluating possible solutions.

Why Conduct scenario forecasting?

Scenario forecasting is a particularly important tool for climate-sensitive and conflict-sensitive solution identification. Its purpose is to ensure an intended solution makes a positive impact on the socioenvironmental system in a wide range of possible futures, and identify programmatic aspects that may need flexibility in light of existing uncertainties.

Through scenario forecasting, a bit of forward-thinking imaginative analysis helps avoid wasting resources on solutions that seem useful right now but could quickly become meaningless, counterproductive, or downright harmful if certain external realities shift in a non-optimal way. Scenario forecasting can be especially helpful if there is a shortlist of proposed solutions that need to be decided between.

What are some limitations of scenario forecasting?

As with many conflict analysis and solution identification tools, scenario forecasting builds on baseline information: the more is known about a system, the more accurate and useful its results will be; if there are inaccuracies or biased in the starting assumptions (in this case, the scenarios chosen for analysis), so too will the outcome be skewed.

There is also a trade-off between the number of scenarios tested and the amount of time and complication involved: considering fewer scenarios requires fewer resources and can be more accessible to a group, but also limits the findings. Devising and testing three or four scenarios (with varying scales of positive and negative climate and conflict realities) is generally a good rule of thumb.