Sunday 5 July 2020

Bulletproof Problem solving – Conn and McLean, 2018


 “Learning how to define a problem, creatively break it into manageable parts, and systematically work toward a solution has become the core skill for the twenty-first century workforce.” (Conn and McLean, 2018, p.´xiii).“Problem solving is decision making when there is complexity and uncertainty that rules out obvious answers, and where there are consequences that make the work to get good answers worth it.” (Conn and McLean, 2018, p.´xiii).

“problem solving means the process of making better decisions on the complicated challenges of personal life, our workplaces, and the policy sphere.” (Conn and McLean, 2018, p.3).

Define the problem
“A scattergun approach to data gathering and initial analysis always leads to far more effort than is necessary.” (Conn and McLean, 2018, p.32.

“The insight here is that the most granular and local solutions are often not optimal for the larger organization.” (Conn and McLean, 2018, p.40. “You find what makes sense for a single unit is not what makes sense for the company overall. Wherever you can, target your problem solving efforts at the highest level at which you can work, rather than solving the interest of smaller units.” (Conn and McLean, 2018, p.41).




Problem disaggregation and prioritization
“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.” (Conn and McLean, 2018, p.50). “when we can see all the parts clearly, we can determine what not to work on, the bits that are either too difficult to change or that don’t impact the problem much.” (Conn and McLean, 2018, p.50).

“Logic trees are really just structures for seeing the elements of a problem in a clear way, and keeping track of different levels of the problem.” (Conn and McLean, 2018, p.51).“Better trees have a clearer and more complete logic of relationships linking the parts to each other, are more comprehensive and have no overlaps.” (Conn and McLean, 2018, p.51). “The only rule here is to move when you can from trees with general problem elements to trees that state clear hypotheses to test.” (Conn and McLean, 2018, p.53).

A tree should be MECE: “MECE stands for “mutually exclusive, collectively exhaustive.” Because this tree confuses or overlaps some of its branches, it isn’t MECE. It’s a mouthful, but it is a really useful concept.” (Conn and McLean, 2018, p.55).

 “Good problem solving is just as much about what you don’t do as what you do. (…) But we don’t want to retain elements of the disaggregation that have only a small influence on the problem, or that are difficult or impossible to affect.” (Conn and McLean, 2018, p.71). “Expert practitioners of problem solving often employ existing frameworks or theories to more quickly and elegantly cleave problems into insightful parts.” (Conn and McLean, 2018, p.74).

Team process:“we don’t do any analysis for which we don’t have a hypothesis. We never go off and build a model without a very good idea about what question it answers. We sharpen our thinking even more by requiring that we can visualize what form the output might take (we call it dummying the chart), so we know if we would want it if we had it.” (Conn and McLean, 2018, p.89).“Focus your work on the 20% of the problem that yields 80% of the benefit.” (Conn and McLean, 2018, p.93).

 “But the best teams typically have relatively little hierarchy in the structure of brainstorming and ideation. (…) When we work within large organization, we nearly always set up temporary teams that act outside the normal reporting structures and deliberately have limited lives. This allows for non-hierarchical and creative team processes that are more likely to generate good solutions.” (Conn and McLean, 2018, p.98).

“This kind of mistake is sometimes called an availability heuristic (you use the framework you happen to have handy, not the right one) or the substitution bias (you substitute a simple model you know rather than understanding the more complicated actual model).” (Conn and McLean, 2018, p.100).

“To disagree without being disagreeable is the heart of great problem-solving team process.” (Conn and McLean, 2018, p.104).

 “Occam’s Razor – favor the simplest solutions that fits the facts – wich originated in the fourteenth century. It tells you to select the hypothesis that the fewest assumptions. (…) If you have four assumptions that are independent of each other, with an 80% separate chance of being correct, the probability that all four are correcr is just over 40%.” (Conn and McLean, 2018, p.114).

“Often data we would love to have shed light on our problem just doesn’t exist. Experiments give us a way to make our own data.” (Conn and McLean, 2018, p.149).

From one-day-answers to pyramid structures:
“We hypothesize a one-day answer using a situation-observation-resolution structure and we constantly pressure test this with our analyses.” (Conn and McLean, 2018, p.184). “The visual structure we use to represent our story structure is traditionally a pyramid – which is really just one of our logic trees turned on its side.” (Conn and McLean, 2018, p.186). “At the very top level is our lead or governing statement of the problem. Not surprisingly, your latest situation-observation-resolution statement is usually the best governing statement.” (Conn and McLean, 2018, p.187). “But our bias in most circumstances is to lead by answering the question “What should I do?” and then summarize the situation and key observations that support action.” (Conn and McLean, 2018, p.187).“While this conclusion (…) was rock solid, it was not one that the local management team wanted to hear. In circumstances like this, it can make sense to use a revealed approach to your arguments, employing decision tree structure rather than the traditional pyramid.” (Conn and McLean, 2018, p.190).

Long time frame and high uncertainty:“Uncertainty can be a good thing for strategic problem solvers! Hedge fund and other clever investors hope for uncertain and volatile markets – provided they have an analytic edge. If your problem solving is right you can earn good returns and guard your downside while others are floundering.” (Conn and McLean, 2018, p.198).