Problem solving discussions on news broadcasts, in newspaper op-eds, on social media, and in political speeches have a consistent thread: “We can fix it by changing (one thing).”
Most problems are not particularly simple. Societal and economic problems are incredibly complex, even in a small community. Winning a game of chess against Bobby Fischer or IBM’s Watson might be easier.
As a result, problems usually require a multi-faceted approach. Unfortunately, that often tempts us to eliminate any “one thing” strategy under the presumption that it’s ineffective, naive, or “too simple”.
Problem solving cause & effect
Rotary has for decades funded and built simple hand pump water wells in villages where there’s no dependable, convenient source of clean water. Many other organizations do similar water projects.
Does convenient access to a dependable source of water (ie: eliminating a three hour round trip hike) solve 100% of a third-world village’s problems? No. However, gaining easy access to clean, disease-free water for a village’s people is comparable to the impact of U.S. rural electrification projects of the mid 1900s. Electrification didn’t solve every rural problem, but it had a huge positive impact on rural communities.
Vilfredo Pareto was an Italian engineer, sociologist and economist of the late 1800s and early 1900s. While he “invented” modern microeconomics, many recognize his last name thanks to his “Pareto principle” – what we call “the 80/20 rule”. The principle states that 80% of effects come from 20% of causes.
Is it accurate to six decimal places? Probably not. Does it describe cause & effect in 100% of situations? Probably not. Does it describe a large percentage of cause and effect in business and society? Pretty close, I’d say.
If a single, simple strategy or tactic solves 80% of a problem, I’d call that a pretty good start. You may not have implemented a perfect solution, but you’ve made a boatload of progress.
Managed expectations go a long way when solving problems.
Name the last time you solved a problem with a single solution and that solution performed perfectly 100% of the time, in every possible scenario so far – and can reasonably be expected to continue solving the problem in the foreseeable future.
A simple solution is often dismissed because it doesn’t solve the problem 100% of the time, or in 100% of scenarios where the problem can occur.
The “Do Not Call” system is a good example. Elected officials seem to agree that robocalls, cloaked and spoofed calls need to stop. Yet they’ve done nothing about it and continue to exempt themselves from existing robocall legislation.
While technology, laws, and a few vendors make it very difficult for us to solve 100% of this, you can solve 80% of it by using a Google Phone number when you don’t expect or want that party to call you. This is particularly true when the data is somewhat publicly accessible, such as voter or website domain registrations.
Google Phone will take those calls / texts, letting you avoid numerous unwanted interruptions via your cell.
Refining problem solving
Most solutions won’t resolve 100% of a problem’s scenarios. If they do, they’re often incredibly expensive, difficult to implement, hard to use, or all three. Even so, edge cases still find their way in.
Despite that, 80% isn’t always enough. Instead of looking for perfect solutions, try iteration. If your first simple solution solved 75 to 80% of the situation, look at what’s left.
What additional simple change can you make to fix the majority of the remaining situations? If you have 100 problem situations, your first 80 / 20 solution leaves 20 situations to resolve. Solving 80% of the leftovers leaves only FOUR percent.
Look at that again: Two simple solutions take you from 100% to four percent.
If you need to, refine again. At some point, the ROI of the next solution will tell you it’s time to move on to other problems.
Imagine that a single tweak to your sales process results in closing 80% of the sales you weren’t closing. Or that a single change in your manufacturing process reduces costs, in-use failure, or warranty claims by 80%. Neither are 100% solutions, but I doubt too many would object to that level of improvement.
If your approach to problem solving starts by looking for simple solutions, testing, implementing and iterating, the number of problems you face and the time and expense invested in dealing with them is going to shrink significantly.
What would you do with that newfound time and money?
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