Evaluate the Impact of Problem Solving
Evaluate the expected business impact of solving a problem and compare it to the effort required. Determine if the problem is worth solving before committing resources.
ONE OF SEVEN WAYS OF SEEING
Bring structure to complex choices and trade-offs.
Evaluate the expected business impact of solving a problem and compare it to the effort required. Determine if the problem is worth solving before committing resources.
The final step in a structured problem-solving process, where you assess whether the implemented solution worked and consider what could be done differently if it didn't.
When evaluating potential solutions, use criteria that are clear, decisive, and goal-promoting. Avoid ambiguous, non-decisive, or misaligned criteria that lead to poor decisions driven by emotion or inertia.
A framework for critically evaluating written reasoning by examining eight elements: purpose, question, information, concepts, assumptions, inferences, point of view, and implications.
A framework for conducting evaluations, focusing on four critical areas: defining scope and objectives, ensuring timeliness and intentionality, employing rigorous methodology, and effectively communicating findings. It emphasizes clarity, stakeholder agreement, and actionable outcomes.
Before evaluating norms and standards, define the purpose, scope, method, timetable and intended use of the findings. Plan how to consult stakeholders, protect impartiality and select evaluators with the skills needed for the work.
The evaluation session occurs after brainstorming, where ideas are sifted to extract useful ones by picking directly applicable solutions, extracting functional kernels from flawed ideas, and identifying new approaches or information gaps.
After a lateral thinking session, ideas are sorted into three lists: ideas of immediate usefulness, areas for further exploration, and new approaches to the problem. This evaluation requires creative effort to extract value from ideas that might otherwise be discarded.
Evidence pooling combines information from several sources while examining its quality, overlap, and consistency. This approach first reviews evidence within each type, then considers how the different types bear on the decision together.
Evidence-based management uses best available evidence to reduce biases and improve decision-making under uncertainty. However, applying the medical model of evidence-based practice to management is limited due to the academic-practice gap and lack of standardized education and credentialing.
Evidence-based management (EBM) is a decision-making framework that involves systematically acquiring, appraising, aggregating, and applying the best available evidence from multiple sources, including scientific literature, organizational data, practitioner experience, and stakeholder values.
The Evidence-Based Movement advocates for using objective evidence in decision-making, particularly in professional fields like medicine and management, to overcome barriers such as information overload and ingrained beliefs that cause variability in outcomes.
Evidence-based practice combines relevant research with professional expertise and the circumstances of a decision. Systematic reviews and meta-analyses help assess and summarize research, but managers must also consider whether findings apply to their organization and arrive in time to be useful.
Banasiewicz’s evidence-driven approach combines operational data, research, and other evidence to inform management decisions. It emphasizes computation and simulation as ways to examine current conditions and test possible actions.
After evaluating options, select the most practical solution or combination of solutions and put it into action.
Expected value is the sum of each possible outcome’s utility multiplied by its probability. In utility-tree analysis, it provides a probability-weighted score for comparing options; the ranking depends on the utilities and probabilities assigned.
Expected-value analysis compares actions by weighting each possible outcome’s value by its probability and adding the results. Nisbett relates this to Franklin’s method of weighing pros and cons and illustrates it with Pascal’s wager about religious belief.
Expert judgment draws on people with relevant knowledge and experience. Their assessments can be combined mathematically, such as by averaging probabilities, or developed through discussion and repeated feedback, as in the Delphi method.
A framework for identifying and selecting experts based on technical credentials, relevant experience, independent contributions, forecasting ability, and willingness to engage, drawing on explicit and tacit knowledge dimensions.
Source expert advice in three stages: define the information you need, evaluate people’s relevant knowledge and conflicts, and structure how you use their input. The process helps assess the quality and limits of advice before it informs a decision.
Explicit consent is an opt-in rule requiring active registration for organ donation, but many supporters fail to register due to inertia, procrastination, or limited attention, so opt-in may not reflect true preferences.
When faced with a business problem like improving government sales, the available options may be unclear. This challenges decision-makers to identify and evaluate potential actions despite ambiguity.
Erikson recommends adapting feedback to the recipient’s communication preferences. The aim is to make a specific concern understandable and discuss change; a color label does not ensure that feedback will be accepted.
A fishbone diagram organizes possible causes of a problem into categories. It helps a team generate and compare hypotheses, which must then be checked against evidence.
The fishbone diagram is a root cause analysis tool that visually maps cause-and-effect relationships for an incident, using predefined categories like 5M+E or 8Ps to guide investigation and identify multiple root causes by asking 'why' along different bones.
A structured problem-solving framework emphasizing objectivity, firsthand observation, delayed solution identification, fact-based cause-effect analysis, and persistent root cause inquiry.
Five methods for formulating questions that support disciplined thinking; the methods themselves are not included in the excerpt.
Paterson describes using Failure Mode and Effects Analysis (FMEA) ratings to decide which risks need board attention. The organisation reduced routine reporting while setting warning signs and escalation thresholds for the remaining risks.
A proposal to adapt an existing problem-solving model or create a personal one. The excerpt does not give the four steps.
Before designing a choice environment, ask what makes the decision difficult and what people need to judge their options. Stakes, uncertainty, timing, and conflicting interests can affect which defaults, comparisons, or reminders are appropriate.
The debate between active choice and default options in choice architecture. While active choosing respects freedom, it can be impractical in complex domains; well-designed defaults often improve outcomes while preserving freedom to opt out.
Game theory models decisions whose outcomes depend on what other participants choose. By specifying players, available actions, information, and payoffs, it helps analyze conflict, cooperation, and strategic responses.
When asking an expert for help, show the work you have already done, make a specific request, respect their time, ask how they reason, and follow up with what happened.
A communication technique that involves using specific, factual examples (e.g., timing someone's talk time) to deliver clear feedback, making the message harder to dismiss and easier to acknowledge.
Break large tasks into smaller subtasks with deadlines to avoid procrastination and mental clutter. This approach helps maintain focus and reduce overwhelm.
Good arguments combine logic and emotion, aiming to understand differing perspectives rather than to win. They involve finding the root of disagreement, building bridges, and engaging emotions to foster connection and mutual understanding.
Taleb favors funding many adaptable researchers and small experiments, allowing them to pursue discoveries beyond a fixed initial plan. He argues that this spreads exposure to rare, large successes; the passage presents a funding philosophy rather than a proof that equal small grants are always optimal.
Graphic facilitation is a visual communication tool that uses real-time drawing and mapping to capture group discussions, improving clarity, focus, and collaborative decision-making.
Formulate operating procedures (like checklists and automatic rules) to create a pause and align decisions with your goals, overriding automatic default responses.
A structured seven-step framework for problem solving that uses reflective questions to clarify goals, analyze problems, gather information, evaluate options, and monitor outcomes.
Gather better information by testing an assumption on a small scale, examining a source’s incentives, and asking how someone reached a recommendation. These practices can reveal evidence and assumptions that a confident opinion alone leaves hidden.
High-Reliability Organisations (HROs) are entities in high-stakes industries that maintain safety and quality over the long term by going beyond quick fixes through double-loop learning—continuously monitoring, avoiding oversimplification, and building resilience to prevent minor issues from becoming catastrophes.
Difficult choices can reflect competing priorities. Clarify the values and goals that should guide the decision, then make room for them by reducing lower-priority work.
The Swedish pension system reveals that nudges have persistent effects: most people stick with their initial default or active choice for years, and even significant events like fund changes or fraud allegations fail to induce substantial switching.
IRADE—Introduce, Relate, Apply, Demonstrate, Examine—organizes an explanation around context, examples, practice, demonstrations, and checks of understanding. Hollins presents it alongside Feynman’s emphasis on clear explanations and learning through teaching.
Test competing explanations by asking what evidence would count against each one, especially the explanation you favor. This helps reveal weaknesses that a search for confirming evidence can miss. Jones uses Disney’s abandoned Virginia theme park to illustrate the cost of overlooking opposition.
A historical case exercise uses competing hypotheses to examine an unusual concentration of cardiac arrests around a nurse’s shifts. The nurse was acquitted. The task is to assess the supplied evidence and alternative explanations without confusing a statistical association with proof of murder.
A hypothesis matrix compares competing explanations with the available evidence. It highlights contradictions, identifies gaps, and helps investigators decide what information would distinguish the remaining possibilities.
Before learning or problem-solving, write down everything you know about the subject to map the boundaries of your current knowledge and identify gaps.
Step 7 covers implementing a solution: it requires coordinating the work, obtaining approvals, and planning its rollout. Timelines vary with the organization, the solution, and the people affected.
Identifying which phases of problem-solving you handle well can help you practise weaker skills or work with someone whose strengths complement yours.
Drawing lessons from aviation, this framework emphasizes the need to provide decision-makers with the right amount of timely data while avoiding overload. It calls for filtering information, tracking KPIs and KRIs, setting milestones, avoiding 'hockey stick' forecasts, and corroborating data through multiple sources.
Informational Domain Specification (IDS) means choosing and organizing data to fit an analytical question. It calls for relevant variables, compatible levels of aggregation, and a model that avoids unnecessary complexity. The framework describes domains as just-specified, under-specified, or over-specified according to whether the chosen information supports the task.
Assess data quality by checking what existing measures mean, whether their values are dependable, and how they vary. New indicators, combinations, and aggregates may answer questions the raw fields cannot answer directly. Visualizations can help reveal gaps, unusual values, and limited variation.
Conceptual frameworks must be put into practice. The 3E framework’s Insight Extraction step identifies the best way to measure each evidence category (operational data, theoretical research, norms & standards, expert judgment) and capture its essential information.
Instant-runoff voting (IRV) lets voters rank candidates. The candidate with the fewest first-choice votes is eliminated, and ballots transfer to the next remaining preference. Rounds continue until a candidate has a majority of the continuing votes. The system can reduce vote splitting, but does not eliminate every spoiler scenario.
Educated and reasonable thinkers use intellectual standards—clarity, precision, accuracy, relevance, depth, breadth, logicalness, and fairness—to assess reasoning. Skilled thinkers routinely ask targeted questions to ensure their thinking meets these standards.
Break a complex problem into questions from relevant disciplines. Economic, political, social, biological, and other perspectives can reveal different causes, constraints, and evidence to investigate.
A weekly practice of focusing on a specific intellectual standard (e.g., clarity, precision) to increase awareness and improve thinking, using a four-step method: state, elaborate, illustrate, and exemplify.
Intuition is pattern recognition: experts draw on a repertoire of patterns from experience to generate a single plausible option, then mentally simulate it to check if it works, as described by Klein's recognition-primed decision (RPD) model and supported by Herbert Simon.