Great problem-solving has never been more important for business and society.
The problems facing humankind are larger, more complex and moving faster than ever before. Learning how to define a problem, creatively break it into manageable parts and systematically work towards a solution has become the core skill for the 21st-century workforce.
We all know the consequences of poor problem-solving can be costly to business and communities, human health and the environment. Here, we set out a long-tested and systematic approach that can be taught to anyone who wants to become a better problem-solver.
Good problem-solving is just as much about what you don’t do as what you do, and good prioritisation makes solutions come faster and with less effort
The new era of focus on creative problem-solving has been ushered in by massive disruption of the older order in business and society.
New business models are rapidly emerging from revolutionary internet, machine learning and bioscience technologies that threaten the status quo in every field.
New rules are being written for conducting business and dealing with social and environmental challenges. Succeeding requires complex problem-solving skills.
When we listen to people describe their approach to problem-solving, they invariably identify one step they feel they do well.
Some will confidently describe their approach as SMART (specific, measurable, achievable, relevant and time-specific); others will cite their knowledge of inductive and deductive logic; some will point to their ability to carry out fact gathering and analysis; and a few will mention using pyramid principles to write a persuasive document with a governing thought.
But we see very few who say they do all of the above along with a way to cleave problems and address bias. To be good at problem-solving, you need to carry out all the steps in concert.
STEP 1: Define the problem Getting a crystal-clear definition of the problem you are solving is the critical starting point to bulletproof problem-solving and it should be relatively straightforward.
However, a surprising amount of failures in problem-solving originate in poor problem definition.
When a problem’s context and boundaries aren’t fully described, there is a lot of room for error. The first step is to arrive at a problem definition that is agreed upon by those involved in making a decision.
We test the problem definition against several criteria: that it is specific, that we can clearly measure success, that it is appropriate in terms of time frame and the values of the decision-maker, and that it involves definitive action being taken.
STEP 2: Disaggregate the issues 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.
We use logic trees of various types to disassemble problems into parts for analysis. There is both an art and a science to ‘cleaving’ problems – revealing their fault lines – that drives better solutions.
Theoretical frameworks from economics and science provide useful guides to better understand the drivers of a problem’s solution.
STEP 3: Prioritise the issues Good problem-solving is just as much about what you don’t do as what you do, and good prioritisation makes solutions come faster and with less effort. Step 3 is to identify which branches have the biggest impact on the problem, by applying a simple matrix.
STEP 4: Build a work plan and timetable Once the component parts of a problem are defined and prioritised, you then have to link each part to a plan for fact gathering and analysis.
This work plan and timetable assigns team members to analytical tasks with specific outputs and completion dates.
STEP 5: Conduct critical analyses Data gathering and analysis is often the longest step in the process. For speed and simplicity we start with simple heuristics – shortcuts or rules of thumb – to gain an order of magnitude understanding of each problem component and to assess priorities quickly.
This helps us understand where we need to do more work and especially when and where to use more complex analytical techniques, including game theory, Monte Carlo simulation and machine learning.
That said, complex techniques are rarely needed and when they are, new online analytical tools make them much more accessible.
STEP 6: Synthesise findings from analysis Problem-solving doesn’t stop at the point of reaching conclusions from individual analyses. Findings have to be assembled into a logical structure to test validity and then synthesised in a way that convinces others that you have a good solution.
STEP 7: Prepare a powerful communication The final step is to develop a storyline from the conclusions that links back to the problem statement and the issues that were defined.
A powerful communication will use a governing thought or argument drawing on refined analyses from earlier stages. It will either lead with action steps, or pose a series of questions that motivate action, depending on audience receptivity.
Good problem-solving is a process not a quick mental calculation or a logical deduction.
The seven-step approach requires good questions that become sharp hypotheses, a logical approach to framing and disaggregating issues, strict prioritisation to save time, solid team processes to foster creativity and fight bias, smart analytics and commitment to turning findings into a story that galvanises action.
With practice and experience you will dissect problems in new and clever ways, and stay on the path of efficient problem-solving.
The above is taken from Bulletproof Problem Solving: The One Skill that Changes Everything, John Wiley 2018
Charles Conn is CEO of the Rhodes Scholarship at Oxford Sciences Innovation; and Robert McLean is director emeritus at McKinsey & Co. Both began their careers at McKinsey
This article was taken from The Treasurer magazine. For more great insights, log in to view the full issue or sign up for eAffiliate membership