In this phase, the outcomes of the decision analysis are presented to stakeholders in a clear, transparent, and understandable way.
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Objectives of the phase
- Present the results in an understandable format (e.g. rankings, trade-offs and sensitivities).
- Explain the reasoning, assumptions, and applied methods behind the results.
- Support informed decision-making and stakeholder acceptance.
- Ensure transparency and credibility of the decision process.
- Achieve a shared understanding of the results among stakeholders.
Modes of communication
The communication may take different forms depending on the audience and context:
- Technical reports (detailed and method-focused).
- Summaries for decision-makers (concise and action-oriented).
- Visual presentations (charts, dashboards, interactive tools).
- Participatory workshops or discussions (most interactive).
Effective communication requires tailoring the level of detail and technicality to the audience.
Outcome of the phase: A clear and transparent presentation of the decision analysis results to support final decision-making and implementation.
Follow up Questions for the AI
Ask the following questions to get more information from the AI:
- What are the key principles of effective communication of the decision analysis results?
- How can complex decision analysis results be explained to non-experts?
- What types of visualisations are best suited for presenting results? See also visualisations in Comparing Alternatives and Sensitivity Analysis.
- How can conflicting stakeholder perspectives be presented? This is especially important in terms of ensuring stakeholder acceptance, transparency and credibility of the decision process
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Benefits and Risks of Using AI
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Benefits (++)
- Translating technical results into accessible language for different audiences.
- Automatically generating summaries and reports.
- Creating visualisations (charts, dashboards, comparison figures).
- Tailoring communication to different stakeholder groups.
- Highlighting key insights, trade-offs and uncertainties.
- Supporting interactive exploration of results (e.g. Q&A formats).
Benefit Scoring: ++ Medium
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Risks (!!)
- Oversimplification or misrepresentation of complex results leading to generation of misleading or biased narratives.
- Loss of methodological transparency.
- Inconsistent interpretation of results across different outputs.
- All the above can lead to reduced trust of stakeholders if communication is not aligned with actual analysis
Risk Scoring: !! Medium
Questions to Better Understand the Benefits and Risks of AI
Questions to make use of the benefits
Prerequisite for each of these questions is that the results of the analysis as well as sensitivity analysis are available.
- Can you make a synthesis of the key results of the analysis in a clear and concise way?
- Can you explain the main trade-offs between the alternatives for a non-technical audience?
- Can you highlight the most important insights for decision-making?
Note on all the above questions: The stakeholders and/or facilitator should always validate the results, and AI can make misinterpretations of the provided information.
Questions to avoid the risks
- What are the risks of using AI to communicate decision analysis results? Understanding of the risks is essential in terms of successfully carrying out the DA process.
- Why is transparency critical when using AI to communicate decision analysis results? Even if the results are valid, trust is needed to put them into practice, in which respect communication has a central role.
Questions NOT to ask
Can you make analysis more convincing?
These kinds of questions can easily lead AI to add arguments that may not be valid.