INTRODUCTION

In the last part, we began discussing problem solving. In this part, we’re going to continue that discussion. 

THE CONCEPT OF INSIGHT

Insight is basically a solution that suddenly pops into your head. There is no thought-trace. The solution just seems to come out of nowhere. Insights are a big part of creative thinking. But they can also occur with other problems. For example, with the purpose of life problem, an insight might be financial independence gives me freedom to explore solutions! This is an insight. It came out of nowhere. 

People aren’t good at estimating their insight problem solving capabilities. But they’re usually pretty good at estimating their non-insight problem solving capabilities. That’s why you see so many right-brained people who are unsure of their creativity while being sure of their mathematical skills. Similarly, it’s also why you see so many left-brained people who are unsure of their mathematical skills, but are sure of their creativity. 

Insight appears to come out of nowhere, but studies have identified some processes that work on insights in the background. These processes are as follows:

Selective encoding. Selecting information to consider as part of a problem. For example, while on the lookout for a new business idea, you might selectively consider your friend’s needs in the back of your mind without even knowing it, because unmet needs are often potential business ideas.

Selective combination. You selectively combine information to develop an idea, again, in the background, without being aware that you’re doing it. For example, you might combine estimates of available resources with a particular unmet need to develop an achievable idea.

Selective comparision. You selectively compare your idea to other similar ideas. For example, if your idea is maybe people heal through music, then you subconsciously begin to compare this idea with maybe, people heal through art forms in general, like TV shows or paintings. 

NATURE OF A PROBLEM

In the previous part, we saw the nature of problem solving. In this one, we’re going to discuss the nature of a typical problem. A problem can be summarized as follows:

  1. There is a goal.
  2. There is information, some of which is relevant, and some of which isn’t. 
  3. There is background knowledge/experience that comes into play. 
  4. There is a problem representation going on in your head, considering the goal, the relevant info and your background knowledge/experience. 

HOW WE GENERATE SOLUTIONS TO PROBLEMS

  1. We use past experience, present resources and critical thinking to come up with a solution.
  2. We test the solution. 
  3. If it fails, we repeat the process.
  4. We do this over and over again until the best/adequate solution is found. 

TWO STRATEGIES FOR SOLVING PROBLEMS

Algorithms

  1. Step-by-step procedure.
  2. Carefully thought-out with respect to time and resource constraints. 
  3. Carefully thought-out with respect to solution efficacy. 
  4. Explores as many alternate step-by-step paths as possible. 

Heuristics

  1. Heurisitcs are “cues” that simplify the process.
  2. For example, you may know the shortest distance to your destination is 7 km. So, as you travel toward your destination, you make sure that the total distance travelled does not exceed 7 km. If it does, then you are not on the shortest path, and you may need to retrace your steps. 
  3. Google maps is a real word example of heuristics. It gives us estimated time of arrival by car, bike or walk. These are heuristics when we’re trying to solve the problem of Am I going the right way? 

SOME SPECIFIC TECHNIQUES OF PROBLEM SOLVING

Generate and test solutions

Already discussed.

Means-ends analysis

There is an end (the goal) and there are means (ways to get to the goal). These means involve operations you can use to get to the goal, heuristics and assumptions that simplify the process, and intermediate problem states, which may show up on the way to the goal.  

For example, 2x + 6 = 10. 

  • Initial state: 2x + 6 = 10
  • Heuristic: Bring all non-x terms to one side.
  • Assumption: You’ll get a non-decimal answer for x.
  • Operation – move 6 to the right hand of the equation
  • Intermediate problem state: 2x = 10 – 6
  • Operation – subtract 6 from 10 and assign to 2x.
  • Intermediate problem state: 2x = 4
  • Operation – Send to 2 to the right hand of the equation.
  • Intermediate problem state: x = 4/2
  • Goal state: x = 2

Another example,

  1. Purpose of life = x.
  2. Purpose feels good.
  3. Things that make me feel good are drugs.
  4. I do drugs, but I don’t feel purpose. 
  • Initial state: Shown above. 
  • Heuristic: The 3 statements are logically connected. 
  • Assumption 1: The resolution of these statements will take me toward the solution. 
  • Assumption 2: At the end of this, I’m going to have a solution or piece of the solution to the purpose question.
  • Operation: Reconcile  (1) and (2)
  • Intermediate problem state: Whatever the purpose is must feel good.
  • Operation: Reconcile that with (3) 
  • Intermediate problem state: Drugs make me feel good, so drugs must be the purpose. 
  • Operation: Reconcile that with (4)
  • Intermediate problem state: I’m doing what feels good (drugs), but I don’t feel purpose. 
  • Goal state: Purpose = Definitely not drugs, and maybe it’s some other feel-good thing, or maybe it’s not about feeling good at all. 

Backward searching

This helps when there are many starting points (initial states), but only one goal state. Like a maze. So it helps to go backwards and trace a path from the goal to all the different origins, rather than the other way around. 

Planning strategy

This is useful when the problem is divided into simple aspects and complex aspects. You solve the simple aspects first, and then the complex aspect might become clearer, or at the very least, the problem becomes smaller. With life, for instance, you could first figure out your finances, accomplishments and relationships, and maybe then the purpose will become clearer, or at least seem like the last tiny bit of the problem. 

Thinking aloud

Thinking aloud involves concurrent vocalization. Vocalizing what’s known as the prototype. The prototype is formed using selected phrases, which when put together, highlight the problem’s behavior. For example, when you’re trying to get a holiday at work, you can vocalize as follows:

  1. Boss loves money bottomlines.
  2. I made good money for the company. 
  3. If I bring that up, I will soften him/her up.
  4. I have other opportunities lined up to make the company more money after the break. 
  5. I could bring those up as well. 
  6. Money in hand + bring it up + more potential money + boss’ thought-process = Request for holiday pretty much revolves around putting money on the boss’ mind. 

SUMMARY

In this post, we continued to discuss problem solving. We covered many more important aspects, and we do hope this series helps you. More goodies to come, down the road. Thank you for reading!