130 Popular Decision-Making Methods

Our personal and professional lifes are determined by the decisions we make. A decision-making framework is often made up of a number of methods. This blog categorises 130 decision-making methods, which together form a toolkit to assist you in making important choices.

decision-making methods

2 January 2024 19-minute read

What is a Decision-Making Method?

A decision-making method specifies techniques and steps for making decisions at various stages of the decision-making process.

A decision-making framework is a broader concept and concerns principles and standards that can be used to guide decision-making across a range of situations.

Popular Decision-Making Methods

The methods are grouped below by decision-making stages.

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  • During this phase, several techniques are utilised to establish when decisions must be made. These provide an overall picture and mark areas where strategic decisions are crucial to the success and improvement of an organisation.
    • Market and industry analysis: Examines market trends and industry shifts, revealing strategic decision needs. Use it for long-term planning.
    • Trend analysis: Analyses patterns over time, signalling changes requiring decisions. Ideal for strategic forecasting.
    • Compliance and regulatory changes: Monitors legal changes, promotes compliance-related decisions. Essential for legal adherence.
    • Client feedback and surveys: Gathers client opinions, highlighting areas needing action. Use it for client-centric decisions.
    • Employee feedback and suggestion schemes: Collects internal insights, indicating internal improvement areas. Ideal for operational improvements.
    • Risk assessments: Identify potential risks, necessitating preventative decisions. Use in risk management.
    • Gap analysis: Compares actual vs. desired performance, showing areas for decision. Ideal for performance improvement.
    • 5x why technique: Asks Why? repeatedly to uncover root causes, indicating problem areas. Use for problem-solving.
    • Fishbone diagram: Breaks down causes of problems, highlighting decision points. Ideal for complex issue analysis.
    • Root cause analysis: Delves deep into problem origins, signalling specific decision needs. Use for in-depth problem-solving.
    • FMEA: Anticipates failure modes in processes, encouraging preventive actions. Ideal for quality assurance.
    • Kepner-Tregoe decision analysis: Works by breaking down complex problems into manageable parts, analysing causes, prioritising issues, and defining clear objectives. It uses structured techniques to guide problem recognition, ensuring a systematic and thorough approach to decision readiness.
  • Gathering relevant information is critical in decision-making because it allows you to comprehend the whole context, recognise risks and opportunities, and make informed choices that match your goals. It guarantees that decisions are based on information rather than intuition.
    • Environmental scanning: Assess external trends and forces. Use for broad strategic planning.
    • Competitor analysis: Study rivals to inform strategy. Ideal for market positioning.
    • Benchmarking: Compare with best practices. Use for performance improvement.
    • SWOT analysis: Assess internal and external factors. Use for strategic planning.
    • Scenario planning: Explore potential future scenarios. Ideal for long-term strategy.
    • Regular reviews and audits: Evaluate processes and compliance. Use for operational integrity.
    • KPIs monitoring: Track key metrics for performance insights. Use for ongoing performance assessment.
    • Financial analysis: Analyse financial data for health and trends. Use for financial planning.
    • Customer data analysis: Study customer behaviour. Ideal for market strategy.
    • Data mining and analytics: Extract insights from big data. Use for informed decision-making.
    • Feedback mechanisms: Gather stakeholder opinions. Use for continuous improvement.
    • Focus groups: Collect targeted feedback. Ideal for product or service development.
    • Expert consultation: Seek specialised knowledge. Use for complex decisions.
    • Issue tracking systems: Monitor and manage issues. Ideal for operational risk management.
  • After defining the problem, the next phase is to create potential solutions or ideas. This stage promotes creativity and open-mindedness in order to investigate a wide range of prospective options. These methods aid in the consideration of a wide range of prospective solutions, resulting in more complete and effective decision-making.
    • Brainstorming sessions: Group idea generation; ideal for initial, unrestricted idea flow.
    • Lateral thinking: Encourages unconventional approaches and is useful for breaking norms.
    • Random stimulus: Introduces unexpected elements to spark innovation; great for creative blocks.
    • Role storming: Adopt different perspectives for new ideas; suitable for diverse viewpoints.
    • Mind mapping: Visual idea organisation; helps in connecting and expanding thoughts.
    • Starbursting: Focuses on questioning all aspects; good for thorough exploration.
    • Reverse brainstorming: Thinks about causing the problem; useful for innovative solutions.
    • Brainwriting: Individual idea generation reduces the influence of dominant voices.
    • Attribute listing: Breaks problems into parts and reveals new angles for solutions.
    • SCAMPER Technique: Systematic exploration of ideas; suitable for detailed analysis.
    • TRIZ: Uses patterns of invention; good for innovative, technical solutions.
    • Six value medals: Evaluates decisions based on key values; ensures balanced decisions.
    • Osborn's checklist: Set of exploratory questions; ideal for thorough examination.
    • Blue ocean strategy: Creates new market space suitable for strategic innovation.
    • Idea lotus: Expands central ideas in a structured way; fosters comprehensive exploration.
    • Affinity diagrams: Groups related ideas; useful for organising brainstormed ideas.
    • Conjoint analysis: A market research technique to understand customer preferences by analysing how they trade off different product attributes. It's used in decision-making for product design, pricing, and marketing strategy when generating alternative product configurations to meet customer preferences and market demands.
    • Nominal Group Technique (NGT): Combines individual and group brainstorming; reduces groupthink.
    • Crowdsourcing ideas: Leverages diverse external insights, making it great for wide-ranging perspectives.
    • Stepladder technique: Sequential idea addition; promotes equal participation.
    • Cross-pollination: Applies ideas from different fields; suitable for unique solutions.
  • Before moving on to prioritisation and evaluation, it is important to identify any biases that may impact the decision-making process and critically evaluate the options to ensure they are founded on objective and rational factors.
    • Cognitive bias awareness training: Educate decision-makers about common cognitive biases such as confirmation bias, anchoring, overconfidence, and availability heuristics. Understanding these biases helps in recognising and mitigating them.
    • Critical thinking training: Enhances analytical skills. Employ early to improve judgement quality.
    • Diverse perspectives inclusion: Encourage participation from individuals with diverse backgrounds and perspectives. Different viewpoints can challenge prevailing assumptions and help uncover hidden biases.
    • Peer review: External review to offer objective insights and uncover biases. Implement after the initial decision draft.
    • Checklists and structured frameworks: Ensures all factors are considered, reducing intuitive biases. Use during decision formulation.
    • Six Thinking Hats: Explores different perspectives (emotional or factual) to reveal biases. Apply in brainstorming sessions and group talks.
    • Socratic questioning: Disciplined questioning to probe ideas and uncover biases. Use in analytical discussions.
    • Heuristic evaluation: Identifies reliance on mental shortcuts that bias decisions. Apply post-analysis.
    • Pre-mortem analysis: Imagines failure to identify potential biases. Use it before finalising decisions.
    • Scenario analysis: Examines outcomes under various scenarios. Apply it when assessing risks.
    • Devil's advocacy: Challenges assumptions. Use in meetings for critical examination.
    • Contrastive thinking: Considers opposite views. Employ when evaluating options.
    • Mindfulness and reflection: Uncovers hidden insights and biases through contemplation. Integrate regularly.
    • Journaling and reflection: Tracks decision processes. Apply periodically for self-evaluation.
    • Feedback mechanisms: Gathers anonymous opinions. Implement during and after decision-making.
    • Decision audit: Reviews past decisions to identify biases. Conduct periodic post-decision interviews.
    • Root cause analysis: When a decision leads to a negative outcome, conduct a root cause analysis to determine if biases influenced the decision-making process.
    • Historical analysis: Studies past decisions for patterns. Apply when facing similar situations.
    • Blindspot analysis: Reveals unnoticed biases. Utilise as a final check.
  • During this phase, the numerous ideas or solutions generated are evaluated and prioritised. This assists in narrowing down a large number of alternatives to the most vital ones.
    • Pareto analysis (the 80/20 rule): Determines the most important factors in a set of problems. When prioritising chores or problems, this is the best way to go.
    • Cost-benefit analysis: Compares costs and benefits to assess value. Suitable for financial decisions.
    • Cost-effectiveness analysis: Evaluates cost per unit of benefit. It is useful for healthcare and resource allocation.
    • Cost of inaction analysis: Measures consequences of not taking action. Apply in to risk assessment.
    • Cost of delay: Calculates costs of delaying decisions. Use when time-sensitive.
    • Expected-value optimisation: Calculates expected values for decision outcomes. Suitable for risk analysis.
    • Marginal analysis: Assesses benefits of incremental changes. Apply for resource optimisation.
    • Monte Carlo simulation: Models complex scenarios with probabilistic outcomes. Useful for risk assessment.
    • Decisional balance sheet: Quantifies pros and cons. Apply for personal decisions.
    • ROI analysis: Measures returns on investments. Suitable for financial assessments.
    • Value analysis: Focuses on value addition. Use for process improvement.
    • Weighted scoring model: Assigns weighted scores to criteria. Apply in multi-criteria decisions.
    • Multi-Criteria Decision Analysis (MCDA): Considers multiple criteria or factors to evaluate and rank alternatives. It helps with complex choices by quantifying preferences and trade-offs among diverse criteria, aiding in informed decision selection.
    • SWOT analysis: Evaluates strengths, weaknesses, opportunities, and threats. Use for strategic planning.
    • Syntegrate: Analyses systems. Apply for complex problem-solving.
    • Interrelationship Diagraph: Illustrates relationships among factors. Useful for process analysis.
    • Pros and cons list: Lists advantages and disadvantages. Suitable for simple decisions.
    • Scenario analysis: Explores outcomes under different scenarios. Apply for long-term planning.
    • SWOT+ analysis: Extended SWOT. Use for comprehensive analysis.
    • Quality Function Deployment (QFD): a systematic method for translating customer needs and requirements into specific product or service features, characteristics, and actions.
    • Pairwise comparison: alternatives are evaluated in pairs to determine their relative importance or preference. Because you always have to choose from two options, this prevents choice stress.
    • Decision matrix (or Eisenhower matrix): Prioritise tasks by urgency and importance. Suitable for task management.
    • Decision trees: Graphical representation of decisions and outcomes. Use for complex decisions.
    • Pugh matrix: Compares alternatives against criteria. Apply for design or concept selection.
    • Value stream mapping: Analyses process flow. Useful for process improvement.
    • Analytic Hierarchy Process (AHP): Especially useful when decisions involve trade-offs between conflicting criteria and when there is a need to consider both qualitative and quantitative factors.
    • Analytic Network Process (ANP): assesses complex relationships among criteria and alternatives, aiding in prioritisation and evaluation in situations with interdependencies. It's valuable for decisions involving multiple factors and interactions.
    • Flipism: Playful, random approach. Not recommended for serious decisions.
    • Gut-check test: Trusting intuition. Use it for quick, personal choices.
  • If a group is involved in the decision-making process, this stage focuses on obtaining a consensus or agreement on the best course of action. It entails talks, bargaining, and, on occasion, voting to reach a final decision.
    • Plurality voting: The simplest method where each voter selects one option, and the option with the most votes wins.
    • Majority rule: A straightforward method where an option must receive more than 50% of the votes to win.
    • Borda count: A more complex method where voters rank options and points are assigned based on their ranking.
    • Score voting (or range voting): Allows voters to assign scores to options within a specified range, and the option with the highest total score wins.
    • Dotmocracy: A visual and participatory method where participants place stickers or dots next to their preferred options.
    • Quadratic voting: A more complex method that allows voters to allocate votes with a quadratic cost based on preference intensity.
    • Confirmation with higher authorities (if applicable): A straightforward method involving seeking confirmation or approval from higher authorities, if applicable. It doesn't involve a complex group settings.
    • Participative decision-making: Involves active participation of group members in the decision-making process, but it can vary in complexity depending on the group dynamics.
    • Stepladder technique: A structured approach that introduces information and input from group members in a step-by-step manner to reach a final choice collaboratively.
    • Delphi method: A more complex and iterative approach that collects and aggregates expert opinions through multiple rounds to reach a consensus.
  • This is the phase entails overseeing the implementation process, allocating resources, and ensuring that actions are completed as intended.
    • Critical path analysis: A project management method to identify the shortest path and timeline for decision implementation. Use for complex projects with interdependent tasks.
    • Force field analysis: A technique to assess factors driving and restraining a decision. Use when analysing forces impacting the success of a decision.
    • Action planning: Develop a detailed action plan that outlines the steps needed to implement the decision. This plan should include specific actions, timelines, resources required, and responsible parties.
    • Resource allocation: Ensure that the necessary resources (such as time, budget, personnel) are allocated to support the implementation of the final decision.
    • Communication strategy: Communicate the decision and the implementation plan to all stakeholders. Clear and transparent communication helps in managing expectations and gaining support.
    • Change management: If the decision involves significant changes, apply change management principles to manage resistance and facilitate smooth adoption. This might include training, workshops, and regular updates.
    • Setting milestones and deadlines: Break down the implementation process into manageable parts with specific milestones and deadlines. This helps in tracking progress and maintaining momentum.
    • Delegation of tasks: Assign tasks and responsibilities to team members or departments based on their skills and capacities. Effective delegation is key to efficient implementation.
    • Risk management: Identify potential risks and challenges that could arise during implementation and develop contingency plans to address them.
    • Stakeholder engagement: Keep stakeholders involved and informed throughout the implementation process. Their ongoing support can be crucial for success.
    • Training and support: If the decision involves new processes, technologies, or behaviours, provide adequate training and support to those affected by the change.
    • Pilot testing: If possible, conduct a pilot test of the implementation on a small scale before full-scale deployment. This can help identify and address potential issues early.
    • Celebrating milestones: Recognise and celebrate milestones and successes along the way. This can boost morale and encourage continued effort towards full implementation.
  • This stage evaluates the decision's effectiveness, learns from the results, and makes improvements as needed. It's also where you gather information to help you make better decisions in the future.
    • Regular review meetings: Periodic meetings to assess decision progress and address issues. Use for ongoing evaluation.
    • Monitoring and feedback loops: Continuous monitoring and feedback to track decision performance.
    • Performance metrics evaluation: Evaluate decision success based on predefined metrics.
    • Financial analysis: Assess the impact of decisions on finances, e.g., ROI analysis.
    • Outcome audits: Conduct audits of the outcomes to ensure that the decision achieved its intended objectives and adhered to any relevant standards or regulations.
    • Benchmarking against best practices: Compare outcomes with industry standards. This helps in understanding how the decision fares in a broader context.
    • SWOT analysis (post-decision): Conduct a SWOT analysis after the decision has been implemented to understand the strengths, weaknesses, opportunities, and threats that became evident as a result of the decision.
    • Document review and analysis: Examine decision-related documents for insights. This can help identify any deviations from the plan and their consequences.
    • Long-term impact analysis: Assess the long-term impacts of the decision, which may not be immediately apparent in the short-term review.
    • Client and market response analysis: Analyse client and market reactions.
    • Comparative analysis: If similar decisions have been made in the past, compare the outcomes to understand differences in approach and results.
    • Post-implementation review: After implementation, conduct a review to evaluate what worked well and what didn't. This helps in learning from the experience and improving future decision-making.
    • Feedback collection: Gather stakeholder feedback on decision impact.
    • Lessons learnt session: Reflect on decision-making experiences for improvements. This should focus on what worked well and what could be improved in the future.
    • Process improvement plan: Based on the review, develop a plan to improve future decision-making processes. This should address any identified weaknesses or gaps.
    • 360-degree assessment: Gather feedback from all organisational levels.

Challenges and Limitations

It is critical to consider the challenges and limits of these methods while making decisions. Think about:

  • Oversimplification: Methods may oversimplify complex problems, resulting in suboptimal choices.
  • Subjectivity: Human judgement and bias can have an impact on method outcomes.
  • Data requirements: Some approaches necessitate a large amount of data, which can be difficult when information is limited.
  • Interdependencies: Methods may struggle to deal with decisions involving multiple interconnected aspects.
  • Time- and resource-intensive: Complex procedures can be time- and resource-intensive.
  • Resistance to change: Methods implementation in organisations may encounter resistance.
  • Context sensitivity: Methods may not be appropriate for all decision settings, requiring flexibility.

Can These Methods Be Combined?

Yes, decision-making approaches can be blended to take advantage of the benefits of several methods while mitigating their specific shortcomings. As a result, decision-making processes will be more comprehensive but also more balanced.

Integrating the Analytic Hierarchy Process (AHP) with scenario analysis in investment decisions is one example. AHP helps in prioritising investment criteria, whereas scenario analysis evaluates prospective future situations. Combining these methodologies allows investors to analyse alternative investment possibilities based on risk, return, and market conditions, taking into account several scenarios to make judgements that are robust and flexible to changing economic situations. This method allows for a more thorough review of investment options and improves financial decision-making.

How Do I Choose the Best Method?

Choosing the optimal decision-making process entails examining the specific choice context, objectives, available resources, and decision complexity. Begin by defining the issue and determining the decision criteria. Then think about the following factors:

  • Decision complexity: Select a method that corresponds to the decision's complexity.
  • Data availability: Make sure that you have access to the necessary data and resources.
  • Time constraints: Consider the amount of time available for decision-making.
  • Stakeholder involvement: Determine who should be included in the process.
  • Expertise: Evaluate the team's familiarity with various methodologies.
  • Objectivity: Select methods that are free of bias.
  • Cost: Consider how cost-effective each option is. Finally, the approach chosen should be compatible with the decision's distinct qualities and objectives.
“Choosing the right decision-making method is analogous to selecting the correct key for a lock. The best decision is unlocked by the correct fit.”

Symbio6 & Decision-Making Methods

Our focus is on automated decision-making. Human judgement is used in traditional decision-making methods, whereas algorithms are used in automated decision-making. They can often reinforce each other by augmenting, integrating, or even replacing existing approaches. In both approaches, ethical considerations are critical.

Conclusion

This overview of decision-making methods shows that there are many tools available to improve our decisions in both personal and professional realms. The breadth and depth of these approaches highlight the complexities of decision-making and the need to select the best technique for each individual case.

Take action: Experiment with multiple methods, adjust them to your situation, and monitor their influence on your decision-making process. Consider this an opportunity for growth and learning, and keep in mind that good decision-making is a skill that can be cultivated and polished over time.

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