Finding Right Problem to Solve
Finding and working the right problem is often a problem.
Solving problems is like painting. Prepping is ninety percent. That means ensuring we’re solving the right problem. It’s a common problem.
As example, a call center supported software for sales people. The sales people were giving them poor reviews. Supervisors listened to calls. Support representatives answered questions well. Supervisors were puzzled. However, representatives were answering the right questions to the wrong problems. They weren’t qualifying sales people’s questions to ensure they were asking the right questions.
Writing down the problem helps to find the right one. In “Are You Solving the Right Problem?” (Harvard Business Review, September 2012 edition) Dwayne Spradlin outlines steps suitable for large teams and complex problems. Step 4 is “Write the Problem Statement.” He also gives three examples of “The Power of Defining the Problem.”
Trimming Spradlin’s approach to fit small teams and individuals, it’s similar to planning’s benefits. It’s the process not the outcome that helps us. In finding the right problem, it’s important to:
Surrounding these are our biases. They encourage us to view problems in ways comfortable to us. We make them fit our experience, expertise, budgets, schedules, understanding and many others.
There are eight generalized biases influencing our perspectives too. They encourage us to view problems in ways we can easily understand, accept and resolve. As a result, we’ll end up tackling the easy but wrong problem.
Problems are also like crime scenes. They need enough scope to contain the information and give the perspective we need. Our need for security often as certainty, clarity and simplicity will emotionally trigger us to overemphasize statistics. Expanding our scope means searching and analyzing different types of information, not just the quantifiable.
Details help here. A glass filled with sand looks full. Diving deeper, gaps appear among the sand particles, more spaces to fill. Analogously, they are the gaps hard data leaves to intangible factors. It also means challenging definitions, demanding more specificity and applicability.
Yes, this is work and difficulty, naturally deterring us. This can’t deter us from the right problem though. If it does, paint will peel, and we’ll soon be painting again.
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Brilliant post, Mike. I think it was Aristotle who said: “Well begun is half done.” This certainly applies to your wise post.
Thank you Stephen for the compliment. I appreciate it. Thank you too for stopping by and visiting. ~Mike
I firmly believe everyone should develop their personal problem procedure, seeking always to make it better, and using it routinely such that it become habitual – especially in times of stress. Without question, that process must start with the correct problem statement – including what the problem is, what constraints exist, and what criteria will be used to optimize the outcomes. It should surprise no one involved that occasionally the problem statement is that there is no problem to be solved. Two other suggestions, both important during the problem solving process, including developing the problem statement: (1) routinely self-assess; and (2) embrace ambiguity. I’d suggest these help dealing with biases. The last step in problem solving has to be reflection; does it address the problem statement and what, with additional resources, might be done to improve the solution.
Thank you, John, for your insights. Yes, I’m chuckling. Perhaps there is no problem. I do believe as you do that problem solving is highly personal. That’s what makes diversity such an important ingredient to innovation. We ensure different perspectives and methods.
I don’t know if you looked into the article. I thought of you and your fondness for Einstein quotes. Spradin began his article with this Einstein quote: “If I were given one hour to save the planet, I would spend 59 minutes defining the problem and one minute resolving it.”
Yes, I did read the link – as I always do if I comment and usually do regardless. One of the great positives of the online blogs. Liked the Einstein quote and don’t remember seeing it before! I of course believe. One needs to know what problem is to be solved, as does planning. But I also advocate prototyping as quickly as realistic – for testing as refining.
Analytically I think most of us are used to solving problems linearly. We also favor things the we like to do and often avoid things that we are unconfortable with but might be more appropriate. Collaboration helps you work through much of this.
Not that you were suggesting it, but I can’t imagine a meaningful problem or situation being addressed in a linear fashion. Just think about it: Again, for a MEANINGFUL problem, how can one expect to know precisely what the order and content of the steps taken will be before starting or even as the previous step is completed. THERE WILL BE LOOPING BACK as I would remind my students! I guess maybe one could “go linear” if a mediocre outcome were accepted but certainly not the optimum solution possible from the group of solvers! Take a look at the problem solving procedure provided in most STEM textbooks at least; probably don’t use the linear word but take a look at the sample problems included – I’ve never noticed any looping. Another justification in students’ minds for all too many students asking without saying it: “Tell me all I need to know and be able to do to be successful.”
The requirement to be able to think critically, learn effectively, problem solve effectively, and have mastered the appropriate core knowledge does not align with linear approaches AND, I believe, is too infrequently really facilitated in education.
Yes, John, we seriously underestimate the power of looking at undesirable or outlandish solutions. Many times it’s those characteristics that help us expand our thinking beyond convention. They might not be the solutions we want, but they might be the paths to the ones we want.
You’re right about the linearity of problem solving, Ralph. We usually avoid wandering, tangential or free-response approaches even though they are very successful. Your point about comfort level is very important. Collaboration is a good approach. I qualify it by saying it should have a good level of diversity and conflict. Otherwise, collaboration is nothing more than group think in which everyone is basically looking at the problem in the same way. Nonetheless, the spirit of what you say is important.
I appreciate your insights and stopping by.
Yes, I think the linearity restriction has more to do with time restrictions,dependencies, and tools restrictions. At least in the data analysis part of the problem solving business. And of course linearity is part of the scientific method. I’ve worked with a few people who have been very creative in the way they approach data problems, yet be unable to express a linear approach to implementing them.
Yes, Ralph, I agree. I’ve witnessed the same with people’s use of data. It seems some are more adept at seeing patterns and connections in data that aren’t easily disclosed in more formulaic analyses.