Problems are ubiquitous and arise daily.  Despite that fact, parents, schools, and organizations rarely teach structured problem solving skills.  Our culture then expresses surprise at divorce rates for first marriages over forty percent and at rampant corporate inefficiency that manifests itself in disappointing profits, high employee turnover, and stunning customer service breakdowns.

Management consulting firms are the one exception to the problem solving training vacuum.  New associates are indoctrinated in a veritable alphabet soup of frameworks such as 7S, 5 Why’s, 4P’s, Five Forces, SWOT, and so on.  While management consultants should master as many useful frameworks as possible, managers should pick the one they find most valuable and stick to it.  Though no single approach can solve every type of problem, you should strive to consistently use a single system that is both simple to apply and that works in most situations.

This chapter delivers a framework that meets both criteria.  Those practiced in problem solving techniques will recognize this as a variant on the situation-complication-resolution framework with a few twists thrown in.

Define the problem and make sure it is worth solving

Most problem-solving frameworks leave off the single most important first step – understanding the problem and making sure it is worth solving.  Even modest sized organizations have hundreds if not thousands of problems.  There are inefficiencies in production, service delivery, personnel, and on and on.

Economics courses routinely teach the importance of accounting for opportunity costs of capital.  There are of course tremendous opportunity costs of time and energy that lurk beneath every decision to resolve a particular problem.  You must spend enough time thinking about the range of problems that need solving and target the low hanging fruit possessing the greatest return on investment.  As you do this, never lose sight of business and societal ethics; more directly, immediately prioritize problems that represent threats to environmental health and safety.

To rank problems – high, medium, low will do – you must visualize, at least at a conceptual level, what the outcomes look like.  The litmus test of whether or not a problem is worth solving is whether or not the solution meets primary strategic objectives.  January 28^th, 1986 confronted President Ronald Reagan with a particularly stark example of this, when space shuttle Challenger and its seven-member crew perished in a nationally televised fireball seventy-three seconds after launch.  In the aftermath, beyond the obvious moral imperative to figure out what happened, the United States needed to get the space shuttle program back on track in the interest of national defense.  At the time, the country was deeply embroiled in the Cold War and space supremacy signaled to the Soviet Union that United States warheads posed an unambiguous nuclear deterrent.  Moreover, in order to maintain faith in their government, American citizens needed to know that they would not be annihilated by their own arsenal.  For President Reagan, the outcome of getting the space shuttle program back on track clearly met the primary strategic objectives of maintaining national defense and faith in government.

Though less dramatic, businesses must prioritize problem solving as well.  Suppose you work for a firm with high fixed costs and low variable costs and whose customers make repeat purchases at some reasonable frequency.  Three primary strategic objectives for you are likely customer acquisition, customer retention, and sales effectiveness.  All three of these drive revenue growth.  By contrast, operational efficiencies that drive cost control are secondary objectives rarely worth prioritizing unless you compete in a totally commoditized space.

Very often, people will present you with a collection of symptoms or with a request for you to embark on a labor intensive solution such as a complex analytical task.  Slow them down and ask two questions.  First, ask ‘What is the problem you are trying to solve?’ Second, ask them and yourself ‘Is this problem worth solving?’. The former question allows you to understand the outcome, to diagnose their approach, and to think of creative out-of-the-box alternatives.  If you are problem solving with others, you need to agree on the outcome.   The latter question tells you whether or not you should bother in the first place.

Form an initial hypothesis

From your earliest days, you were probably told to wait until you had sufficient facts before forming an opinion or making a judgment.  We take as undeniable truth expressions such as “Don’t judge a book by its cover” or “Avoid making decisions based on first impressions.”  Though great advice when browsing for a book or a potential mate, this advice is flat out wrong during the initial phases of problem solving.

When confronted with a problem to solve, immediately form a hypothesis.  Remember that a hypothesis is merely a proposed explanation that must be rigorously tested.  A good problem solver will search for facts, all the while updating their hypothesis.  Great problem solvers not only seek information that confirms their hypothesis but also mercilessly hunt for disconfirming information.

In statistics, a hypothesis can never be accepted.  Rather, your only options are to either reject or fail-to-reject the hypothesis.  Statistics loves uncertainty and this treatment of testing your hypotheses leaves an air of mystery.  When you think about it, decisions in your personal or professional life are pretty much that way too.  You can never know with absolute certainty that you are making the right or best decision; you do the best you can with the information you have at the time.

Merely failing to reject something feels pretty unimpressive.  It is a lot more definitive to outright reject something.  Hence, statisticians always construct their hypotheses (known as the null hypotheses) to test the opposite of what they think is true.  By trying to prove the opposite of what you believe, you are forcing yourself to take the high road of seeking disconfirming information.

An example will clarify.  Let’s say you believe that taller people make more money (as psychologists Timothy Judge and Daniel Cable theorized in a 2004 study).  For starters, you might have some decent data that taller people make more money. The best approach is to play devil’s advocate and posit reasons why taller people might actually make equal or less money.  To do that, you should get as much data as you can on people, data that includes not only wage and height information, but also physical and socioeconomic descriptors.  Next, remove the influence of gender, weight, age, industry of employment, and so on.  Keep searching for material (or information) that would explain why taller people earn more money than their diminutive friends other than height itself.  In the end, if you cannot find anything, then you can sleep pretty well at night with your hypothesis that taller people are better remunerated.  (For the record, according to Judge and Cable’s study, every inch of height adds $789 per year.)

Understand the current situation

Before delving into problems and brainstorming solutions, you first need to understand how you got here and what the current state of the world is.  Though vital even when you problem solve alone, this is downright critical when you are problem solving with others, since they need unbiased facts and context to be able to lend their full mental muscle.

With that in mind, let’s revisit the Challenger disaster.  Formed on February 3, 1986, the Rogers Commission started laying out the facts.  What was the timeline in the hours, minutes, and seconds leading up to the explosion?  What was the temperature on the launch pad?  What processes and procedures were followed in the mission control room?  Who manufactured the shuttle’s various components and to what specifications?  Like the Commissions’ fact list, yours needs to be neither too elementary nor too comprehensive.  Yet, while not being exhaustive, ideally the list of facts should give a nearly complete context to the problem you are solving and start to uncover the levers that might be used to fix it.

In laying out the specifics, you want to consider structural information as well as behavioral information.  Structural information includes physical and descriptive attributes such as time, temperature, geography, and industry.  Behavioral information captures the human element including attitudes, actual processes, and the like.  Between the two, behavioral information requires more heavy lifting to obtain. The effort will be well rewarded, however, because in most circumstances, it is the behavioral information that holds the key to solving the problem.

The fastest and most effective way to capture behavioral information is through interviewing.  Take any population, say flight safety engineers, and identify your best performing employees and your worst.  In doing so, you must select candidates by applying objective measures such as the number of missed safety violations, not subjective measures such as managers’ opinions.  Now, interview both groups and ascertain what the top performers do differently than the bottom.  In the case of the Challenger investigation, the Rogers Commission interviewed more than 160 individuals.  In most business settings, interviewing ten to twenty people is sufficient.

Uncover the complications

Once you have articulated the current situation, you must now find specific complications and occasionally hidden opportunities.  In your first pass, you should enumerate the distinct, comprehensive set of top level complications.  Resist the urge to deep dive on individual issues.  In subsequent passes, drill down one level deeper at a time.

The more information you have, the surer you will be that you have identified the true root of the problem.  First, you need to examine structural data.  As the Challenger disaster played out in an endless loop on television, hot exhaust gases could be seen escaping from the rubber o-rings that were supposed to seal the joints on the shuttle’s solid rocket boosters.  Looking back at past shuttle launches, Roger Boisjoly – an engineer working for solid rocket booster manufacturer Morton Thiokol –found that potentially catastrophic exhaust gas leaks occurred around o-rings every time the temperature fell below freezing.  With launch day temperatures hovering around eighteen degrees Fahrenheit, the space shuttle was doomed before takeoff.  The striking exclamation point was made on this structural complication on February 11, 1986 when Nobel Laureate Richard Feynman famously dunked an o-ring in a glass of ice water during a Rogers Commission hearing.  When he pulled the rubber ring from the water, the ring had lost its resiliency.

Feynman not only dramatized the o-ring structural complication but also relentlessly pursued behavioral complications to the apparent dismay of commission chairman William Rogers, who reportedly characterized Feynman as “becoming a real pain.” As it turned out, Roger Boisjoly warned both his employer and NASA about the poor low-temperature performance of the o-rings as early as six months before the tragedy.

Select a resolution that can be executed

In the final stage of problem solving, you should articulate the range of possible resolutions and identify the best one as the recommended option.  Each resolution should be clearly described and should include potential benefits and risks.  An excellent best practice is to characterize benefits as either primary or secondary in order to maintain focus on what truly matters.  In addition, acknowledging risks as known and acceptable prevents the unknown from paralyzing the decision making process.  If behavioral complications are at the root of the problem, as they often are, you are likely going to get the most mileage teaching the best practices of your best performers to the rest of your organization.

In business settings, a great resolution has two necessary preconditions.  First, the solution must leverage existing capabilities in the form of both resources and knowledge.  An elegant solution that cannot be executed is worthless. Second, the solution must carry strong executive commitment or the organization will never embrace the necessary change.

The Rogers Commission could have recommended doing nothing (an oft under-considered option though rightly ruled out in this case), discontinuing the existing space shuttle program, or making structural and behavioral modifications to the program; They chose the last, suggesting nine sweeping modifications that spanned redesigning the solid rocket booster joints and seals, overhauling the shuttle management structure, improving safety controls, and decreasing the shuttle launch rate.

To its credit, the Rogers Commission achieved the final component of a great resolution.  Specifically, its members embraced the concept of test, then measure, then iterate.  In their directive to redesign the solid rocket booster joints and seals, they required that certification include “Tests which duplicate the actual launch configuration as closely as possible.”  As for measurement, the final report called for NASA to “perform periodic structural inspections when scheduled and not permit them to be waived.” The test-measure-iterate sequence is as essential in business as it is in space travel.

Recap

Your objective as a great problem solver is to become a trusted thought partner.  Consider the difference between an impressive associate and a great partner.  Talented associates can encounter any situation and draw compelling insights.  They can expertly and concisely extract the so-what.  In contrast, exceptional partners do two things.  First, they maintain the hypothesis defining the full vision for the final solution.  As they receive new confirming and disconfirming information, they update the hypothesis.  Second, and equally important, they are expert in communicating the vision every step of the way.

Here are the concepts you can immediately apply to be a great problem solver:

• Define the problem and make sure it is worth solving
• Form an initial hypothesis
• Understand the current situation
• Uncover the complications
• Select a resolution that can be executed