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Product Management

3 Step Problem solving approach for Product Managers

Problem Solving for Product Managers

As a product manager, your most important why is the customer problem that your product is trying to solve. Include your team and other stakeholders in understanding the customer problem and selecting the right goal metric to grow. This way, everyone can contribute, feel ownership, and stay motivated to solve the problem even if the product changes.

A problem well defined is a problem half-solved — Charles Kettering

Concept of problem-solving

Today’s businesses want employees who can adapt to new situations rapidly and effectively.

  • The ideal product manager is a master of basic skills such as reading, writing, and numeracy.
  • Product Manager is also a master of learning, communication, critical thinking, creative thinking, and problem-solving.
  • The ideal product manager can respond to a problem quickly, correctly, and with little or no supervision.

If you can solve problems, you can write your own ticket to whatever job you want.

Defining Problem Solving

Problems can be classified into puzzle problems, well-structured problems, and ill-structured problems.

Simple Problems

  • Many games contain puzzle problems and are not “serious” in nature, nor is there any real-life consequence for failing to solve them.

Well-structured Problems

  • Some problems which are simple and well-defined are called well-structured problems and include a set number of possible solutions – solutions are either 100% right or 100% wrong. An example of a well-structured problem is a typical mathematical (2 + 2 = 4) question. This question has a definitive correct answer.

Ill-structured Problems

  • In contrast to well-structured problems are ill-structured problems. In these cases, problems may have many possible answers because they are complex and poorly defined. The “best” solutions to ill-defined problems depend on the priorities underlying the situation. What is “best” today may not be “best” tomorrow. Ill-structured problems, because they are more difficult to “solve,” require the development of higher-order thinking skills and the ability to construct a convincing argument for a particular solution as opposed to all other possible solutions.

To summarize ill-structured problems:

  • ill-structured problems are complex and poorly defined.
  • They have many possible answers.
  • They do not have one best answer.

Here is an example of an ill-structured problem:

The population of your community is growing. Your water supply will not support many new people.

What do you do?

This is a complex problem. It affects the people, the environment, and the quality of life itself. To arrive at a good solution, you need to use math, science, political science, psychology, and probably more!

This problem actually occurs frequently in areas with a growing population. In one community facing this problem, more than 20 possible solutions were presented to the public. A solution was then chosen upon which the majority of the public agreed. It wasn’t the “right” solution because all of the 20 possible solutions had strengths and weaknesses.

The lesson here is that ill-structured problems usually have several workable solutions. Each solution has advantages and disadvantages that depend on who is affected by the solution. The solution chosen is often the one that has the best argument for it.


Problem-solving strategies

  • Abstraction: solving the problem in a model of the system before applying it to the real system
  • Analogy: using a solution that solves an analogous problem
  • Brainstorming: (especially among groups of people) suggesting a large number of solutions or ideas and combining and developing them until an optimum solution is found
  • Divide and conquer: breaking down a large, complex problem into smaller, solvable problems
  • Hypothesis testing: assuming a possible explanation to the problem and trying to prove (or, in some contexts, disprove) the assumption
  • Lateral thinking: approaching solutions indirectly and creatively
  • Means-ends analysis: choosing an action at each step to move closer to the goal
  • Method of focal objects: synthesizing seemingly non-matching characteristics of different objects into something new
  • Morphological analysis: assessing the output and interactions of an entire system
  • Proof: try to prove that the problem cannot be solved. The point where the proof fails will be the starting point for solving it
  • Reduction: transforming the problem into another problem for which solutions exist
  • Research: employing existing ideas or adapting existing solutions to similar problems
  • Root cause analysis: identifying the cause of a problem
  • Trial-and-error: testing possible solutions until the right one is found

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