Analytical Thinking Training Course

Participants can decompose a broad question into logically organised, answerable lines of enquiry.

• MECE issue trees breaking broad questions into testable branches
• Mutually exclusive categories preventing double counting and confused ownership
• Logic trees distinguishing drivers, processes, stakeholders and potential interventions
• Problem decomposition sequenced from governing question to answerable subquestions
• 80/20 prioritisation identifying few branches likely to explain most variation
• Scope boundaries documented through in-scope, out-of-scope and deferred questions

Participants can assess whether available evidence is sufficient, credible and relevant to a decision.

• Evidence hierarchy comparing direct observations, records, expert judgement and assumptions
• Source evaluation using CRAAP criteria: currency, relevance, authority, accuracy, purpose
• Sampling bias, missing data and survivorship bias identified before conclusions
• Triangulation across quantitative data, interviews, documents and operational observations
• Fact-assumption-opinion logs separating verified claims from inference and judgement
• Confidence ratings recorded beside claims, evidence gaps and unresolved questions

Participants can develop competing explanations and test them against discriminating evidence.

• Hypothesis statements specifying expected relationship, population, condition and measurable outcome
• Falsification tests designed before collecting confirmatory evidence
• Competing hypotheses compared using discriminating evidence and predicted observations
• Assumption maps ranking uncertainty against potential decision impact
• Bayesian updating explained through prior beliefs, new evidence and revised confidence
• Disconfirming evidence sought deliberately to reduce confirmation bias

Participants can use basic quantitative techniques to identify patterns and test operational claims.

• Ratio analysis translating operational data into comparable performance indicators
• Pareto charts separating vital few contributors from trivial many
• Trend analysis distinguishing seasonal patterns, shifts and random variation
• Base rates and denominators preventing misleading percentage comparisons
• Scenario tables testing sensitivity to assumptions, ranges and decision thresholds
• Simple break-even calculations comparing fixed costs, variable costs and volumes

Participants can distinguish root causes from symptoms and validate causal explanations with evidence.

• Fishbone diagrams organising possible causes across people, process, technology and policy
• Fault tree analysis tracing combinations of failures to an event
• Process mapping locating handoffs, rework loops, queues and control failures
• Correlation and causation distinguished through mechanisms, timing and confounders
• Root causes validated against evidence rather than plausible explanations
• Cause-and-effect chains identifying leading indicators and downstream consequences

Participants can evaluate alternatives transparently using agreed criteria, risks and trade-offs.

• Weighted decision matrices scoring alternatives against agreed criteria
• Cost-benefit analysis separating cash impacts, nonfinancial effects and opportunity costs
• Risk matrices assessing likelihood, consequence, controls and residual exposure
• Expected value calculations comparing uncertain outcomes and response choices
• Trade-off analysis making value conflicts explicit before recommendation
• Decision records documenting rationale, evidence, dissent and review triggers

Participants can present analytical findings in a concise format suited to decision-makers.

• Pyramid Principle messages leading with answer, supporting arguments and evidence
• Claim-evidence-reasoning structure converting analysis into defensible recommendations
• One-page decision briefs tailored to executive questions and constraints
• Data visualisation choices matching chart form to comparison purpose
• Uncertainty communicated through ranges, confidence language and stated assumptions
• Challenge questions anticipated before presenting conclusions to decision-makers

Participants can recognise cognitive bias and apply structured challenge to improve judgement.

• Common cognitive biases recognised: anchoring, availability, framing and overconfidence
• Pre-mortems exposing failure modes before commitments become difficult
• Red-team reviews testing recommendations from opposing stakeholder perspectives
• Devil's advocate protocols separating constructive challenge from personal disagreement
• Calibration reviews comparing confidence estimates with later outcomes
• Decision journals recording assumptions, forecasts, rationale and subsequent results

Participants can plan a structured analysis for a current workplace decision or problem.

• Workplace problem selection based on urgency, impact, access and authority
• Analysis charter defining question, stakeholders, scope, evidence and milestones
• Stakeholder maps planning interviews, challenge sessions and decision checkpoints
• Evidence collection plans assigning sources, owners, dates and quality checks
• Recommendation roadmaps sequencing analysis, review, decision and implementation actions
• Personal application plans setting first-use commitments and feedback measures