9 smart ways to solve your problems
You only have so ̶m̶u̶c̶h̶ little energy in a day. And let’s face it, you would rather be doing something else than solving a problem. Even then, we often find ourselves floating from one problem to the next. Like a bee does moving from one flower to another, endlessly searching for that tasty nectar. We float about almost as though our entire existence is to solve problems. Smaller, less complicated problems occur more regularly. You probably face this kind several times a day. “What should I wear? What should I cook? Should I respond to that message now or later? When should I get this clogged sink checked?” While other problems, being far more complicated, thankfully are less regular. “Which contractor should I choose for this project? Are they the person I should marry? Should I quit my job? Should we turn off the life support machine?” I am sure you can think up many more examples. When I said smaller, less complicated problems earlier, I did not mean to belittle these problems. They inevitably add up, drawing vast amounts of energy from us over the years.
You see, each morning we wake with a reserve of energy from the night before. We add to this reserve when we feed our bodies. We draw from this reserve through the day as we solve problems by making decisions, choices, thinking and even while resting. The fewer the frivolous choices, the better says Sonke Ahrens who has looked deeply at the relationship between decision making and the quality of our thoughts and writing. Agnosing over small decisions degrades our productivity and the quality of our work. A simple decision like wearing a uniform set of clothes daily removes one such problem. The ‘what to wear’ problem; turtleneck donning Steve Jobs or grey-tee dressed Mark Zuckerberg come to mind. But before we get ahead of ourselves cutting at frivolous problems, perhaps we should start by simply asking “What exactly is a problem?”
What is a problem?
I think of a problem as simply an obstacle to achieving an intended outcome or goal. Say you are hungry, and you therefore want something to eat. Or that you would like to communicate with a friend thousands of miles away. The first case could be a problem if you have no food in your fridge or money to buy food. In the second case, no matter how loud you scream your friend will not be able to hear you. You know you have a problem when an obstacle stands in your way to getting what you want.
But this doesn’t not mean that any obstacle spawns a problem. Slightly modifying the hunger example, suppose instead that have food but cannot eat it because you are fasting. There is no longer a conflict that creates a problem. Slightly cheesy example I know. If, however, you have the food but do not know how to work the microwave to heat up the food. Does this knowledge gap create a problem? Yes it does.
A problem is well defined when presented as a conflict between two necessary conditions. — Eliyahu Goldratt
What are the common mistakes that people make when solving problems?
- Assuming that the problem is in fact a problem when it isn’t. In the modified hunger example you could double down on your resolve not to eat until the fast is over.
- Grappling with a problem that has already been solved by someone else. A quick search on Google can turn many problems into non-events.
- Solving symptoms of the problem and not the underlying problem cause(s). We’ll tackle this one, in depth, shortly.
- Taking the first solution that pops into your mind as the best approach. The brain works best when problems lurk just below the surface long enough to spawn fresh ideas. This is why it is bad idea to have a group brainstorming session and take the ideas generated in the one hour as sacrosanct. More on this too in a bit.
- Searching for a perfect answer instead of taking one that is good enough. Known as ‘Satisficing’ this is finding a solution that near enough meets the problem. Any more effort towards getting a single optimum solution does not change the outcome in a noteworthy way. Wikipedia is one such example. You get a really good answer without ploughing through hundreds of academic journals.
So, what are the smart ways to solving a problem?
Now we have a common understanding of what a problem is and the pitfalls to avoid, let’s take a look at the smart ways to solving them. There is an important caveat though. Do not take these approaches to be like a science; the same way you know that if you toss a ball up in the air it will return. Or that light when refracted will always arrange the colours of the rainbow in the exact same order. Think of these ways instead like you would tools in a toolbox or brushes in your mascara set if you will. They can be combined, used in parallel, one after the other and even iteratively. That is what makes them so powerful.
Way #1: Marinate the problem
To solve a problem, we should become like bumble bees says Walter Isaacson, acclaimed American author and journalist. Stay long with — buzzing about — the problem. Simply spending more time with the problem, ideally in different formats. Writing it down, explaining it to others verbally, modelling it physically or even metaphorically. Bring to this problem ideas (pollen) from other problems. Doing this takes the problem from the conscious to the sub-conscious part of the brain that is better suited at making associative connections between what may initially seem to be disparate data points/ information. Seeking the lateral meaning to the problem. Albert Einstein is famously quoted as saying that when given a problem to solve in 6 hours he would spend the first 5 hours crafting the right question; finding the answer would then be easy. And there is something to be said of making the problem tangible, such as when you write it out or model it. Like a child playing around with Lego building blocks we stumble upon new designs. James Watson and Francis Crick, who became famous for their breakthrough of the DNA double helix in the 1950s, attribute their discovery to the improvised model they built and played around with in their office. Back with the bumble bees where we started, it turns out that they are especially finicky as to which flowers they visit. Buzzing about the flower before eventually deciding whether or not to stop by. For the flower that gets bumble bees staying long enough, getting pollinated is easy. Think about how much time has passed since your problem emerged. I know it sounds ironic, but the longer the time that you have spent mulling over the problem, the better.
Way #2: Peel back the problem’s layers
Taking the time to peel back the problem for what it really is and discovering its fundamental truths that need to be addressed. Let’s look at two methods to peeling a problem:
- Double diamond model: Exploring a variety of possible problems and honing to the primary issue and doing the same discovery process with the possible solutions before making an optimal choice. Don Norman calls this process the Double Diamond model [of design; Don is a design practitioner]. The model follows two iterative interrogation processes to make sure we are properly defining the problem and solution, as shown in the diagram below. This avoids the commitment bias of sticking to the first idea and not exploring further. Remember one of the pitfalls we mentioned earlier. This is how to avoid it.
First, we define the problem. Starting with an initial problem, we diverge outwards exploring the edges of the problem. The intention is that after exploring various possible problem angles, we converge at a coherently defined problem and not end up fixing just a symptom. When asked, most people will describe a symptom as the problem. Rushing to fix this will not address the underlying issue. This is why doctors, for instance, spend a few minutes at the beginning of each visit asking questions. Doctors call this a differential diagnosis. Just like the doctors, we should be doing the same when someone presents us with a problem… spending a moment to figure out “what is the real issue that needs to be fixed?”
The next step is to define the solution. Just like problem definition, this takes an outward (divergent) approach first to explore various possible solutions then an inward (convergent) approach to lock in on a preferred solution.
- Five Whys or root cause analysis: Root cause analysis is an approach to peeling back the layers to a problem by focusing on the underlying issue(s) that is cause the problem. Not just the problem or the symptoms exhibited by the problem. By asking the Five Whys; actually, it is more like asking the question ‘Why’ iteratively, each time interrogating the response previously provided.
A simplified example of this in practice could be while examining an event like a vehicle that crashed into a brick wall injuring the driver and destroying the property.
o Why did he drive into the wall? To avoid trampling on pedestrians the driver swerved into the building.
o Why was he going to trample on pedestrians? The driver had lost control of the vehicle.
o Why had he lost control of the car? Because he was driving too fast and missed his turn.
o Why was he driving too fast? He was distracted by his phone, which he was looking at while he drove, so he did not notice his excessive speed.
o Why was he using his phone while driving? He was trying to reschedule an appointment that he was running late for.
The Five Whys technique can be coupled with the earlier Double Diamond model; cyclically asking why to arrive at the problem that truly needs the fix or the solution that is best fit.
Way #3: Keep the new wine in new wineskins
In the Bible (Luke chapter 5 verses 33–39) Jesus tells the parable about how no one should pour new wine into old wineskins, otherwise the new wine will burst the old wineskins. There is something in this parable for problem solving too. We should not do the same with problems; giving new solutions to old problems and vice versa. Tracking the problem to when it first emerged is therefore important. Is it a new (modern) problem or not? The older the problem, likely, the older the solution. This approach eliminates previously solved problems. Another pitfall we touched upon earlier
“Those who cannot remember the past are condemned to repeat it.” — George Santayana
Perhaps this is why we feel like history keeps repeating itself. We approach problems thinking they are new, only to discover later that solutions have existed for ages. Once we have understood that a problem is old and therefore has an old solution this should not stop you from applying new thinking. Let’s consider a practical example. The problem of moving from place to another without getting lost is an old problem. But now have technological advances in digital maps that mean we no longer need to search the skies for direction. The problem is old, and so is the solution. But with a modern adaptation. How old, or new is the problem you are trying to solve?
Way #4: Play the opposites game
Rory Sutherland argues that “the opposite of a good idea, can also be a good idea.” And to explain how, he uses the example of the wildly successful Red Bull beverage. One would have thought that the best commercial attack on the soft drink giants, Coca Cola and Pepsi, would have been another dark coloured, sweet tasting beverage. But quite the opposite since Red Bull, some argue, looks, and tastes like urine. Another good example he uses of the challenge the Eurotunnel team had in finding ways to reduce the duration of train rides between cities. He argues that instead of the near 3 billion euro the team planned to spend speeding up the trains, a fraction of that amount, say a few million euro, could get top male and female models to walking up and down the train serving snacks and drinks. People would ask for the trains to be slowed down he maintains. Still doubtful? Here is example you can try out yourself. Suppose you find yourself feeling a little cold. A good idea would be to jump into a hot shower and run the hot tub. The opposite to this idea, which is equally a good idea, is to have a cold shower instead. The increased blood circulation from the cold shower keeps your body warmer for longer after you have had the cold shower. This kind of thinking is not conventional, and neither are the solutions. But that is exactly what makes them so powerful and magical. What is the opposite of the good idea(s) you have to solving your problem?
Way #5: Borrow from another field
“Good artists copy, Great artists steal” — Pablo Picasso
The solution you are looking for may come from a different field. Like pollen from another flower that our earlier bumble bee brings when they stop for a visit. James Clear tells the story of John Boyd, a fighter pilot and military strategist, who created the thought experiment showcasing the power of adapting ideas from different fields. John Boyd took a motorboat, a military tank and bicycle, breaking them down to their constituent parts. A bicycle for example has a seat, handlebar, two wheels, a pedal and chain. He then combined a few parts from the three items to create a snowmobile. Once you have seen a snowmobile, imagining how the parts fit together seems obvious in retrospect. The problem you are trying to solve may not be one that your field has the answer for. New technologies, new ideas, new solutions only emerge from the convergence of other technologies, other ideas, other solutions especially those from fields other than the one with the problem.
Way #6: How does nature deal with the problem?
Look at how nature deals with the same problem. This technique is known as ‘Biomimicry’, by which we basically copy what happens in nature. Nature has a way of elegantly solving problems. By applying biomimicry, that is looking to how nature solved the said problem, we end up with a solution we would have otherwise not thought about. One of the more vivid examples is how aeroplanes mimic the flight of birds. Swim suits that mimic shark skin. Velco that mimics plant hooks or skyscraper cooling systems that mimic termite mounds. But even management theories have emerged this way. Eliyahu Goldratt is credited with developing a method, known as the Theory of Constraints, to improve factory production. He achieved this by turning management thinking on its head, not to focus on local efficiencies but on ‘throughput’; a term he used to describe the factory’s ability to meet market demand by producing finished products. He argued that in any factory, the throughput — that is, the factory’s ability to meet market demand — is determined by the slowest process in production. That is, the constraint in the production process. His solution was therefore to realign all factory processes such that their production capacity (you could say speed of completing their tasks) was determined by the capacity of the constraint. In nature, that is exactly what a pack of wolves do when on a trail. They order themselves such that the slowest wolves — usually the older, sickly wolves — are at the front of the pack and stronger, alpha wolves are at the back. This way the pack as a whole is able to ‘process’ (traverse) more ground together. When thinking about your problem, a good question to ask is “How does a similar problem in nature get solved?”
Way #7: Reverse engineering the solution
This approach starts with a future state when the problem has been resolved and you then work backwards discovering challenges that may not be anticipated by a forward-looking solutioning process. John Rossman reveals how Amazon, the giant technology company, uses this technique in his book ‘Think like Amazon’. He argues that in Amazon, any product or service launch starts with presenting a write up called a Future Press Release. Written by the person (or team) leading the initiative, it puts them in a future state at which they are showcasing publicly the results of their hard work. Doing so, their write up touches on the hurdles encountered, decisions taken and fundamentally the benefits to the person consuming their product or service. This practice gives the team a fresh perspective on the nature of problems that could arise and even better frees them to come up with solutions that in future look obvious even though today they do not exist. Once written, the team uses the Future Press Release to guide their thinking with revisions being made where necessary for material developments. Greg McKeown writes in his book ‘Essentialism: the disciplined pursuit of less’ about how Michael Phelps — the swimming sensation who is also the most decorated Olympian of all time — used to play a mental videotape before going out for a race. His body responded naturally by reliving the experience during the race which allowed him to have an unmatched rhythmic consistency between races. Some may consider this a form of biohacking, which had him reverse engineer the race wins.
Way #8: Impermanence of the problem
Where the problem is temporal, lasting only a short time, the solution should not be permanent. Rahul Mehrotra and Felipe Vera wrote about this in their book ‘Kumbh Mela: Mapping the Ephemeral Megacity’. A city that forms over a week, fulfils the celebration, hosting up 20 million people, and is taken down just as fast. Impermanent problems like a convention centre for an Olympic event deserve impermanent solutions. Is the problem you seek to solve impermanent? If so, that last thing you should be doing is considering permanent solutions.
Way #9: Right vs correct solution to the problem
Decide on whether your solution needs to be ‘right’ or ‘correct’. My rule of thumb for this is simple. You can have many right answers but only one can be correct. Finding a correct solution means finding a solution that meets the belief system of the higher authorities who posed the problem. The way a teacher may pose a question with an exact answer in mind. That exact answer is the correct solution. Any other solution provided, even those that justifiably solve the problem, are therefore seen as incorrect. In organisations, the correct answer may not be the most optimal solution, or certainly the only right answer, but it is certainly one that will attract the most support. The pressure to find such correct solutions is especially so where the incentive scheme is stacked to favour such thinking. There is inherently a tension therefore between this ‘correct’ solution and an optimal solution. Hierarchical structures such as academic institutions and professional associations would typically take the ‘correct’ solution. Think about the problem you are trying to solve and ask yourself “Who defined this problem? Who will decide whether the solution I propose addresses the problem? Which of the solutions I have will be acceptable to them?” Knowing their view on the matter makes all the difference.
It is difficult to get a man to understand something when his salary depends upon his not understanding it. — Upton Sinclair
In closing
Solving a problem should only start when the problem is well understood. That is, when the conflict between two necessary conditions to achieve a goal is clear. You should not venture to solve a problem until you have such clarity, otherwise you end up wasting effort chasing about shifting issues.
Once the problem has been clearly defined, the approach to identifying a solution can use a range of methods: staying long with the problem, peeling back it’s layers, tracking its origins, playing the opposites game, imitating nature, reverse engineering a solution, timing the problem or choosing between a correct or right solution. Seen as tools, the good solution is crafted, not just because of a specific tool being used. Problem solving after all is not a science. Rather you take tools in turn, sometimes jointly, sometimes sequentially, crafting a solution that elegantly solves the problem. A problem approached this way is efficiently and effectively solved.
Bibliography
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Isaacson, W. (2014) The innovators: how a group of hackers, geniuses, and geeks created the digital revolution. First Simon&Schuster hardcover edition. New York: Simon & Schuster.
Mehrotra, R., Vera, F. and Harvard University (eds) (2015) Kumbh Mela: mapping the ephemeral megacity. New Delhi: Niyogi Books.
Rossman, J. (2019) Think like Amazon: 50 1/2 ideas to become a digital leader. New York: McGraw-Hill.
Sutherland, R. (2019) Alchemy: The Dark Art and Curious Science of Creating Magic in Brands, Business, and Life. William Morrow.
