Best-practice approaches to work planning: We don’t do any analyses that aren’t guided by very clear and testable hypotheses. Her advice is hard-won, garnered from stints in the New York Police Department and working in the security details of former presidents George H.W. Use a hypothesis to bring forth the arguments to either disprove it or support it. This cycle can be completed over any timeframe with the information at hand. These include placing too much emphasis on the mean outcome, typically called the base case, and insufficient weight on outcomes that are one or even two standard deviations from the mean in a normal distribution. What are the key criteria for success that our decision maker (which may be yourself) set out in advance? "Former Secret Service agent and star of Bravo's Spy Games Evy Poumpouras shares lessons learned from protecting presidents, as well insights and skills from the oldest and most elite security force in the world to help you prepare for stressful situations, instantly read people, influence how you are perceived, and live a more fearless life"-- Provided by publisher. The Sherlock Holmes approach of painting a picture of the problem by asking who, what, where, when, how, and why is a powerful root-cause tool to quickly focus problem-solving. We are very specific about who is doing what by when. There are no comments for this title yet. We sharpen our thinking even more by requiring that we can visualize what form the output might take (we call this dummying the chart), so we know if we would want it if we had it. Get started with nothing more than a problem statement. Problem-solving means the process of making better decisions on the complicated challenges of personal life, our workplaces, and the policy sphere. One answer is the natural experiment, also called a quasi-experiment: If you can’t run an experiment yourself, look to see if the world has already run it — or something like it — for you. Sometimes it is best to carefully lead the audience from situation to observation to resolution, which are your recommended actions. When we worked for McKinsey, we often saw problems that benefited from redefinition to a higher level. There is no vague “I’ll look into X or Y.”. Smart analysis starts with heuristics and summary statistics to assess the magnitude and direction of the key problem levers. Any problem of real consequence is too complicated to solve without breaking it down into logical parts that help us understand the drivers or causes of the situation. Inductive trees show probabilistic relationships, not causal ones. Structured to allow sufficient scope for creativity and unexpected results — too narrowly scoped problems can artificially constrain solutions. First-cut data analysis often points to direction of causality and size of impact, which are critical to evaluating the results of complex models later. We use logic or issue trees to visualize and disaggregate problems. Good problem statements have a number of characteristics. Start your analysis with summary statistics, heuristics, and rules of thumb to get a feel for the data and the solution space.