SUBJECTUnderstanding Problems
Problem Solving & Decision Making
Life presents problems that rarely have obvious answers. Effective problem solving requires more than intelligence — it requires a repeatable process.
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Prefer the whole picture first? See the Problem Solving & Decision Making study guide — full lesson outline, key terms, and practice on one page.
Understanding Problems — Lessons
- 1
What Is a Problem?
A problem is a gap between where you are and where you want to be. Learn to separate objectives from constraints and spot a solution disguised as a problem statement.
16 min · beginner - 2
Breaking Problems into Smaller Parts
Decomposition with issue trees and the MECE test — how to split a problem into parts that do not overlap or leave gaps, and how to choose which part to attack first.
17 min · beginner - 3
Root Cause Analysis
Five Whys, fishbone diagrams, and the discipline of not stopping at the first plausible cause — including why 'human error' is almost never a root cause.
17 min · beginner - 4
Systems Thinking
Feedback loops, delays, and unintended consequences — why fixing a part can break the whole, and how to find leverage points instead of obvious levers.
18 min · beginner - 5
Creative Problem Solving
Why the first idea is rarely the best, how reframing and constraint manipulation escape fixed thinking, and why generating alone beats group brainstorming.
17 min · beginner - 6
Evaluating Possible Solutions
Set criteria before you score, weigh feasibility against impact, ask how reversible a choice is, and know when a cheap test beats more analysis.
17 min · beginner
Modules in this subject
Understanding Problems
6 lessons · ~6-8h
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Making Better Decisions
7 lessons · ~6-8h
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Tackling Complex Problems
7 lessons · ~6-8h
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Sharper Judgment
7 lessons · ~6-8h
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The Problem-Solving Mind
7 lessons · ~6-8h
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Great Problem Solvers
7 lessons · ~6-8h
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Solving Problems Together
7 lessons · ~6-8h
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Concept map
How the core concepts in Problem Solving & Decision Making relate to one another.
- Problemdefined byGoal
- Problemlimited byConstraint
- Symptomarises fromRoot Cause
- SystemcontainsFeedback Loop
- BrainstorminggeneratesSolution
- Decision MatrixcomparesSolution
- Trade-offinfluencesDecision
- Feedback LoopsupportsContinuous Improvement
- Problemis part ofProblem Solving & Decision Making
- Objectiveis part ofProblem Statement
- Problem StatementdefinesProblem
- Decompositionapplies toProblem
- Issue Treeis aDecomposition
- MECEtestsIssue Tree
- Bottleneckrevealed byDecomposition
- Five WhysfindsRoot Cause
- Cause-and-Effect DiagramfindsContributing Cause
- CountermeasureaddressesRoot Cause
- Reinforcing Loopis aFeedback Loop
- Balancing Loopis aFeedback Loop
- DelaydistortsFeedback Loop
- Unintended Consequencearises fromSystem
- Leverage Pointacts onSystem
- Divergent ThinkinggeneratesSolution
- Convergent ThinkingsupportsDecision
- BrainwritingimprovesBrainstorming
- ReframingsupportsDivergent Thinking
- Functional FixednessunderminesDivergent Thinking
- Evaluation Criteriais part ofDecision Matrix
- Feasibilityis aEvaluation Criteria
- Impactis aEvaluation Criteria
- Reversibilityis aEvaluation Criteria
- Pilot TesttestsSolution
- Decision TreestructuresDecision
- Expected ValueinformsDecision
- ResultingmisjudgesDecision
- Decision JournalcountersResulting
- Opportunity Costis part ofTrade-off
- RiskinvolvesDecision
- Ruinis aRisk
- PremortemreducesRisk
- Sunk Costis aCognitive Bias
- Cognitive BiasdistortsDecision
- Outside ViewcountersPlanning Fallacy
- Planning Fallacyis aCognitive Bias
- GroupthinkdistortsDecision
- Psychological SafetyreducesGroupthink
- Decision RightsassignsDecision
- Stakeholderaffected byProblem
- Post-mortemexaminesFailure
- Hindsight BiasdistortsPost-mortem
- Near MissprecedesFailure
- PDCA Cycleis aIteration
- Iterationis part ofContinuous Improvement
- Standard WorkenablesContinuous Improvement
- Problem Solving & Decision Makingrelates toCritical Thinking
- Pilot Testrelates toScientific Thinking
Problem Solving & Decision Making: frequently asked questions
- Is the first solution that works good enough?
- Rarely. The first workable idea is usually just the most familiar one, and settling on it skips better options you never generated. Better practice is to produce several genuinely different solutions, write your criteria before scoring them, and treat 'do nothing' and the smallest useful version as real contenders.
- Is human error a root cause of a problem?
- Almost never. 'Human error' is where analysis stops, not where it should. If someone made a mistake, keep asking: why was the mistake possible, why wasn't it caught, why did the system let it cause harm? A process that only works when nobody slips has a design defect.
- Does every problem have a single root cause?
- No. Most real failures have several contributing causes that combined to make the failure likely, none sufficient alone. The Five Whys digs deep but follows one chain and can miss parallel causes, so widen the search — a fishbone diagram forces you to consider people, process, tools, and environment together.
- If a decision turned out well, was it a good decision?
- Not necessarily. Judging a decision purely by its result is called resulting, and it misleads. A good decision is one made well with the information available; under uncertainty, sound reasoning sometimes gets unlucky and reckless bets sometimes pay off. Someone who runs a red light and arrives safely didn't decide well.
- Should you factor in what you've already spent when deciding whether to continue?
- No. Money and effort already spent are gone whatever you choose, so they shouldn't sway the decision — that's the sunk cost trap. The useful question is: knowing nothing about what we've already put in, would we start this today? Decide on future costs and benefits, not past investment.
- Is being aware of a bias enough to avoid it?
- No. Biases operate before a conclusion reaches your awareness, so you can't simply concentrate them away — and learning about them can even boost false confidence. What works is changing the process: estimate independently before hearing others' numbers, assign someone to argue the opposite, and check base rates instead of vivid examples.
- What makes a good problem statement?
- A good problem statement names a gap between where you are and where you want to be — both stated observably — without smuggling in a solution. 'We need a better ticketing system' names a fix and forecloses others; 'resolution takes too long' is the real problem that many things could solve.