problem solving methods in software development

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A Guide to Problem-Solving for Software Developers with Examples

If I ask you, out of the blue, what’s the role of a developer, what would you answer? Coding all day? Drinking coffee? Complaining about the management?

To me, a developer is first and foremost a problem solver, simply because solving problem is the most important (and the most difficult) part of our job. After all, even if our code is perfect, clear, performing great, a masterpiece of form and meaning, it’s useless if it doesn’t solve the problem it was meant to solve.

So, let’s dive into problem-solving today. More specifically, we’ll see in this article:

• How to define a problem, and the difference sometimes made between problem-solving and decision-making.
• Why some problems should not be solved.
• The two wide categories of problems you can encounter.
• Why it’s important to correctly define the problem, and how to do so.
• How to explore the solution space.
• Why deferring a problem might be the best decision to make in specific situations.
• Why reflecting on the whole process afterward can help you in the future.

This article is mostly based on my own experience, even if I apply here some ideas I found in books and papers.

We have our plan. Now, it’s time to dive deep into the difficult, but rewarding, process of problem-solving.

Problem-Solving and Decision-Making

“When I use a word,” Humpty Dumpty said in rather a scornful tone, “it means just what I choose it to mean — neither more nor less.” “The question is,” said Alice, “whether you can make words mean so many different things.” “The question is,” said Humpty Dumpty, “which is to be master — that’s all.” Lewis Caroll Source

Words are ambiguous; they can mean different things for each of us. So let’s first begin to agree on the definition of “problem-solving” here, to be sure we’re on the same page.

Let’s first look at the definition of the word “problem” in a dictionary:

• According to the American Heritage Dictionary , a problem is “a question to be considered, solved, or answered”.
• According to the Oxford Learner’s dictionary , a problem is “a thing that is difficult to deal with or to understand”.

In short, in any problem, there is some degree of uncertainty. If you’re certain of the solution, the problem is already solved. Nothing would need to be “considered, solved, or answered”.

Information is useful to reduce this uncertainty. The quantity is often not the most important, but the quality will be decisive. If I tell you that 90% of my readers are extremely intelligent, would it help you to solve a problem in your daily job? I bet it wouldn’t. It’s information nonetheless, but its usefulness for you is close to zero.

This is an extreme example, but it highlights an important point: before collecting any data, define your problem clearly; then, according to the problem, decide what data you need. Yet, many companies out there begin to collect the data and then decide what problem to solve. We’ll come back to that soon in this article.

So, to summarize, a problem is a situation with some degree of uncertainty. Sometimes, this uncertainty needs to be reduced to come up with an appropriate solution, or, at least, a decision to move forward to your specific goal.

Is there a Problem to Solve?

Whenever you (or somebody else) see a problem, you should always ask yourself this simple question first: is it really a problem, and should we solve it now ?

In other words, ask yourself the following questions:

• Why is this problem important to solve?
• Would be solving the problem creates some value? What value?
• What would happen if the problem was not solved?
• What desired outcome do we expect by solving the problem?

If the problem doesn’t bother anybody and solving it doesn’t create any value, why allocating effort and time to solve it?

It sounds obvious, but it’s an important point nonetheless. More often than not, I see developers heading first in solving problems without asking themselves if they should solve them at the first place.

The most common examples I can think of are useless refactoring. I saw developers refactoring parts of codebases which never change, or is rarely executed at runtime. In the mind of the developer, the code itself is the problem: refactoring is the solution.

I remember a similar case: a developer refactored part of the codebase which was basically never used. We discovered, months later, when we had more and more users using this specific part of the codebase, that the refactoring didn’t really simplify anything. To the contrary; we had to refactor the code again. The first refactoring tried to solve a problem which didn’t exists.

Of course, the developer could argue that the value created is a “cleaner” codebase, but it’s arguable, especially when the code is neither often modified nor used. The value created here is not clear, and it would have been easier if the first refactoring never happened. In this specific situation, I recommend refactoring when you actively change part of the codebase for another reason (implementing a new feature for example).

Whether a problem is worthy to be solved is subjective. It also depends on the problem: if the solution is clear and straightforward, it might be useful to solve it, if the consequences of the solution are also clearly known and the risks are low. Unfortunately, these kinds of problems, in practice, are quite rare.

Types of Problems

I would define here two wide categories of problems: the problems with a (or multiple) clear solution (what the literature call “problem-solving”), and the problems without clear solution (it’s sometimes called “decision-making” instead of “problem-solving”).

In fact, if the problem you’re trying to solve has a clear, accepted answer, it’s very likely it has been solved already. It’s often the case for mechanical, technical problems. For example, let’s say that you need to order a list; you just have to search on the wild Internet how to do so in your programming language of choice, and you’re done! You can ask an “AI” too, or stack overflow, or whatever.

In my experience, most technical problems have one (or multiple) accepted solution. I won’t speak about these kinds of problems at length in this article, since they’re the easiest to solve.

When you’re in front of a problem which has no clear solution (even after doing some research), it’s where things get more complicated. I’d argue that most problems you’ll face, as a software developer, are of this category. Problems which are directly linked to the domain of the company you work with are often specific (because they depend on the domain), and complex.

For example, I’m working for a company providing a learning platform for medical students who want to become doctors, among other services. This context is changing because the real world is changing; medicine is no exception.

Recently, we had to create new data structures for the knowledge we provide; these data structures are directly linked to the domain (medicine) here. But what data structures to create? How can they adapt to the ever-changing environment? How to capture the data in the most meaningful way, with understandable naming for other developers?

Decisions had to be made, and when there are no clear solutions, you need to come up with a couple of hypothesizes. They won’t feel necessary like solutions , but rather decisions to take to move forward toward the desired outcome. It often ends up in compromises, especially if you’re working in a team where the members have different opinions .

Also, architectural decisions have often no clear solutions because they depend, again, on the changing context. How to be sure that an architectural decision is good today and in three months? How can we make the architecture flexible enough to adapt to the blurry future?

As developers, we deal with complex codebases, which are somewhat linked to the even more complex real world. It’s difficult to know beforehand the consequences of our decisions, as well as the benefits, the drawback, and the potential bugs we introduce.

Before jumping into the solution space however, we first need a good detour in the problem space.

Defining the Problem

Correctly stating the problem.

After determining that we indeed have some kind of problem, it’s tempting to try to find a solution directly. Be patient: it’s better to look at the problem more closely first.

If you don’t specify well the problem, you might not solve it entirely. It’s also possible that you end up solving the wrong problem, or the symptoms of a problem, that is, other minor problems created by a root problem. Often, the ideal scenario is to find the root problem, even if you don’t want to tackle it first. In any case, it’s always useful information.

For example, not long ago, our users didn’t find the content they were searching for, using our search functionality on our learning platform.

We could have directly solved the problem by asking the search team to adjust that for us, but this problem was only a symptom. It wasn’t the first time that we had to spend time and energy trying to communicate to the search team what we wanted to fix; the real root problem here was that we didn’t have any ownership of our search results.

The solution: we created a better API communicating with the search team, to be able to adjust ourselves the search results in a more flexible manner.

When looking at a problem, a good first step is to write it down. Don’t do it once; try to find different formulations for the same problem.

Writing is nice (I love it!), but other ways to represent ideas can be really useful too. You can try to draw what you understand from the problem: a drawing, a diagram, or even a picture can help you understand the problem.

From there, you can ask yourself: do you have enough information to take a decision? The answer will be mostly based on the experience of the problem solver, there is no magical formula to be sure that you can and will solve the problem.

You should also try to look at the problem from different angles, to really frame it correctly. The best way to do so is to solve problems as a team.

Solving Problems in a Team

Trying to describe and think about a problem is a great beginning, but it’s even better if you do it as a team. You can exchange experience, opinions, and it’s easier to look at a problem from multiple angles when multiple developers are involved.

First, make sure that everybody in the team is aware of the problem. Defining it altogether is the best. If you have a doubt that somebody is not on the same page, you can re-explain it using different words. It might bring more insights and ideas to the discussion.

Don’t assume that everybody understands the problem equally. Words are powerful, but they are also ambiguous; never hesitate to ask questions (even if they seem stupid at first), and encourage the team to do the same. If your colleagues see that you’re not afraid to ask, it will give them confidence to do the same.

The ambiguity can also build overtime, after the problem was discussed. That’s why it’s really important to document the whole process, for anybody to be able to look at it again and fix the possible creeping misconceptions. Don’t try to describe everything, but try to be specific enough. It’s a delicate balance, and you’ll get better at it with experience.

If you don’t like writing, I’d recommend you to try anyway: this is a powerful skill which will be useful in many areas of your life.

Regarding the team of problem solvers, diversity is important. Diversity of opinion, experience, background, you name it. The more diverse the opinions and ideas are, the more chances you’ll have to solve the problem satisfyingly (more on that later). If the members of the team have enough respect, humility, and know how to listen to their colleagues , you’re in the perfect environment to solve problems.

As developers, we’re dealing with moving systems, because they need to reflect the ever-changing business domain of the company you’re working with. These problems are unique, and even if similar problems might have been solved in the past, they’re never the exactly same. The differences can have an impact on the solution, sometimes insignificant (allowing you to re-apply the solution found previously), sometimes important enough to change the solution entirely.

Exploring the Solution Space

Now that we’ve defined the problem, thought about it with our team, tried to look at it from different angles, it’s time to try to find solutions, or at least to make a decision.

What is a good decision? The one which will bring you closer to your desired outcome. It sounds obvious, but there can be some ego involved in discussions, which will push us to try to be right even if it’s not the best solution in the current context. Our personal incentives can conflict with the company’s best interest; it’s always good to try to stay aware of that.

The solution should also be the simplest possible, while still moving forward to the desired outcome. It should also have an acceptable level of risk when we decide to apply the solution. In my experience, complicated solutions are the ones which come up first: don’t stop there. Take some time trying to find the best solution with your team.

For example, here’s what we do with my actual team:

• We define the problem altogether.
• We try to think about different hypothesizes. Not only one, but a couple of them.
• We write the benefits and drawbacks of each hypothesis (which can lead to more ideas, and possibly more hypothesizes).
• We commit to a hypothesis, which then needs to be implemented.

What I meant by “hypothesis” here is a solution which might work; but only the implementation of the hypothesis can be considered as a solution. Before the implementation, it’s just an informed guess. Many things can go wrong during an implementation.

This process looks simple, but when you have multiple developers involved, it’s not. Again, if each member of the team have good soft skills and some experience, it can be an enjoyable and rewarding process. But you need a good team for it to work efficiently (that’s why it’s so important to ask the good questions when joining a company). It’s even better if the members of the team are used to swim in uncertainty, and take it as a challenge more than a chore.

The process described above is just an example; in practice it’s often more chaotic. For example, even when a decision is made, your brain might still continue to process the problem passively. If you find some flaws in the hypothesis you’ve committed to, congratulations! You have now a brand-new problem.

I can’t emphasize it enough: try to be as detached as possible from your ideas, opinions, and preferred hypothesizes. The goal is not for you to be right and feel good, but for your company to move in the good direction. It’s hard, but with practice it gets easier.

I also want to underline the importance of finding both benefits and drawbacks for the different hypothesizes you (and your team) came up with.

To find good solutions, we might also need to reduce the uncertainty around their possible consequences. Doing some external research can help, like gathering data around the problem and the possible hypothesizes. In the best case scenario, if you can find enough data, and if you feel confident that you can move forward with a hypothesis, that’s already a great victory.

If you don’t have enough external information to reduce the uncertainty to a level you feel comfortable with, look at your past experience. Try to find problems similar to the one your deal with in the present, and try to think about the solutions applied at the time, to see if they could also be applied in your current case. But be careful with this approach: complex problems are context-sensitive, and the context you were in the past will never be exactly the same as the present and future contexts.

For example, I recently changed the way we display search results in our system, because we had some data indicating that some users had difficulties to find what they really wanted to find. The problem: users have difficulties to find the good information; it’s a recurrent problem which might never be 100% solved. That said, thanks to the data gathered, we found an easy way to improve the situation.

The data was very clear and specific, but it’s not always the case. More often than not, your data won’t really prove anything. It might only show correlations without clear causality. It will be even more true if you begin by gathering data without defining first the problem you try to solve. You can find problems looking at some data, that’s true, but it needs care and deep understanding of what you’re doing; looking at data when you know exactly what you want to solve works better.

Using this kind of process, the hypothesis is often some sort of compromise. That’s fine; committing to a hypothesis is not the end of the process, and there will be other occasions to revisit and refine the solution.

If you don’t feel comfortable with the level of uncertainty of the problem (or the risk involved by applying your hypothesis), you need to dig more. Writing a prototype can be useful for example, if you hesitate between two or more approaches. If your prototype is convincing enough, it can also be useful to gather feedback from your users, even if the ones testing your hypothesis will always be more invested if they test a real-life functionality, instead of a prototype which might use dummy data, or be in a context which is too remote from the “real” context.

In my opinion, prototypes are not always useful for complex problems, because a prototype only test a new feature at time T, but doesn’t allow you to see if the solution stay flexible enough overtime. That’s often a big concern: how will the solution evolve?

But prototyping can still help gather information and reduce the uncertainty of the problem, even if the prototype doesn’t really give you the solution on a silver platter. It’s also great for A/B testing, when you’re in the (likely) case when you have not much information about the real needs of your users. You could ask them of course, but nothing guarantee that they know themselves what these needs are.

If you don’t find any satisfying hypothesis to your problem, you might also challenge the desired outcome. Maybe a similar, simplest hypothesis, with slightly different outcomes, could work better? If it makes things easier, faster, and less complex, it could be the best solution. Don’t hesitate to challenge your stakeholders directly on the desired outcomes.

Deferring the Problem

In some cases, you might be hesitant to try to solve a problem if there is still too much uncertainty around it. In that case, it might be best to defer solving the problem altogether.

Deferring the problem means that you don’t solve it now ; you keep things as they are, until you get more information to reduce the uncertainty enough.

We had a problem in the company I worked with some time ago: we have dosages which can be discovered in articles, but users didn’t really find them, and nobody really knew why. Because of this lack of information, the problem was not tackled right away, but differed. From there, data have been collected overtime, allowing us to understand the scope of the problem better.

Don’t forget that deferring a problem is already taking a decision. It might be the less disruptive decision for the application and its codebase, but it’s s decision nonetheless, and it can have consequences. Seeing a differed problem as a decision will push you to think about the possible consequences of your inaction, and you’ll look at it as a partial “solution”, with some uncertainty and risk associated to it.

In my experience, deferring the problem works well only when you try to actively seek more data to solve it later. It can be some monitoring to see how the problem evolves, or some data taken from users’ actions. Sometimes, simply waiting can also give you important information about the nature of the problem.

What you shouldn’t do is try to forget the problem. It might come back in force to haunt your sleepless nightmares later. Avoiding a problem is not deferring it.

Here’s another example: we began recently to build some CMS tooling for medical editors, for them to write and edit content on our learning platform. We had one GraphQL API endpoint at the beginning, providing data to two different part of the application:

• Our CMS for medical editors.
• Our learning platform for medical students.

We knew that using one single GraphQL endpoint for these two types of users could cause some problems.

But we didn’t do anything about it, mostly because we didn’t see any real, concrete problem, at least at first. When a minor symptom, related to this unique endpoint, popped up, we spoke about it, and we still chose not to do anything. We preferred deferring the problem once more, to try to solve the real problem (one API for two different kinds of applications) later.

Finally, when we had enough symptoms and some frustration, we decided to split our graphQL API in two different endpoints. It was the best moment to do so: we had enough information to come up with a good decision, we applied it, and we stayed vigilant, to see how our applied hypothesis would evolve.

Moving fast and breaking things is not always the best solution. In some situations, waiting a bit and see how things evolve can allow you to solve your problems in a more effective way. But, as always, it depends on the problem, its context, and so on.

Reading this article, you might have wondered: how much information is enough to be comfortable enough to apply a solution? Well, again, your experience will be the best judge here. You’ll also need to consider carefully risks, benefits, and drawbacks. It doesn’t mean that you need to chicken out if you don’t have 100% certainty about a problem and some hypothesizes; being a software developer implies to have some courage and accept that mistakes will be made. It’s not an easy task, and there is no general process to follow in any possible case.

In short: use your brain. Even if you’re totally wrong, you’ll have the opportunity to fix the bad decisions you’ve made before the implementation, during the implementation, and even after it. We don’t code in stone.

The Implementation: The Value of Iteration

You’ve gathered with your team, tried to define the problem, found multiple hypothesizes, and agreed to try one of them. Great! Problem solved.

Not so fast! We still need to apply the hypothesis, and hope that it will become a good solution to the problem. Doing so, you’ll gather more information along the way, which might change your perspective on the problem, on your hypothesizes, and can even create some baby problems on its own.

It’s where the agile methodology is useful: since we’ll never have 100% certainty regarding a problem and its possible solution, we’ll learn more about both while implementing the hypothesis. That’s why it’s so valuable to iterate on the implementation: it gives you more information to possibly adjust your code, or even the problem, or even switching hypothesizes altogether. Who knows? A solution which is not implemented is just a guess.

If the hypothesis applied is not the ones you would have personally preferred (compromising, or even giving up on your preferred solution is common in a team), only applying it will tell you if you’re right or wrong; that is, if the hypothesis can become a solution solving the problem, at least in the present context.

If you’re worried about how a specific solution will evolve overtime, it’s more complicated, because an implementation won’t give you the information you seek. Still, implementing a hypothesis can be a great source of learning (the most valuable to me is when I’m wrong, because I learn even more). If you think that your hypothesis can have better outcome at time T, you might also try to implement it and compare it. Again, it’s where prototyping is useful.

When applying the solution, you need to look at the details of the implementation, as well as the big picture, to judge if the solution you’re creating is appropriate (leading to the desired outcome). This is a difficult exercise. In general, a developer should be able to reason on different levels of abstraction, more or less at the same time. Again, if you’re aware of it, your experience will help you here, and you can also push yourself to think of all the possible risks and consequences at different levels.

If you work in a team, try to participate (at least a bit) into the implementation of the solution. It’s not good to create silos in teams (that is, only a couple of members have some information others don’t have).

You can go as far as looking at other projects, and ask yourselves these questions:

• Did we had similar problems on these other projects? How did we solve them?
• What was the context of these projects? Is it similar to our current context?
• What did we learn from these other problems, and their implementation? Is the implementation similar to what we’re doing now?

In any case, I would definitely recommend you to write a development journal. I write mine for years, and it has been valuable in many cases. I basically write in there:

• The interesting problems I had.
• The decisions made.
• How the implementation of the solution evolved overtime.
• The possible mistakes we made along the way.

It’s a great resource when you have a problem and you want to look at your past experience.

To evaluate your decisions overtime, nothing will beat a good monitoring process: logs, tests, and so on. It’s what the book Building Evolutionary Architecture call “fitness functions” for example, some monitoring allowing you to measure how healthy your architecture stays overtime. It doesn’t have to stop to the architecture; you can think about different monitoring system to see how something evolve, especially if the solution has still a lot of uncertainty regarding its benefits, drawbacks, and risks.

You can also do that retrospectively: looking at how the code complexity evolve overtime using Git for example.

Retrospective on the Process

We defined the problem, implemented a solution iteratively, and now the problem is gone. That’s it! We made it! Are we done now?

Decisions are sometimes not optimal, and implementing a solution successfully doesn’t mean that there wasn’t a better (simpler) one to begin with. That’s why it can be beneficial to look back and understand what went right, and what went wrong. For example, we can ask ourselves these questions:

• Looking at what we learned during the whole process, is there a potentially better hypothesis to solve the problem in a simpler, more robust way?
• What are the benefits and drawbacks we missed when speaking about the different hypothesizes, but we discovered during the implementation? Why we didn’t think about them beforehand?
• What other problems did we encounter during the implementation? Did we solve them? Did we differ some? What should be the next steps regarding these new problems?
• What kind of monitoring did we put in place to make sure that the solution won’t have undesired outcomes overtime? Can we learn something with this data?

Reflecting on past solutions is a difficult thing to do. There is no way to logically assess that the decision taken was better than others, since we didn’t implement the other hypothesizes, and we didn’t look at them overtime to appreciate their consequences. But you can still look at the implementation of the solution overtime, and write in your developer journal each time there is a bug which seems directly related to the solution. Would the bugs be the same if another solution would had been applied?

Bugs are often not an option; they will pop up, eventually. Nonetheless, it’s important to make sure that you can fix them in a reasonable amount of time, and that you don’t see them creeping back in the codebase after being solved. Some metrics, from the DevOps movement (like MTTR for example) can help here. Sometimes, bugs will show you a better, more refined solution to the original problem; after all, bugs can also give you some useful information. They are also the most direct result of the implementation of your solution.

If you want to know more about measuring complexity (which can be also used to measure complexity overtime after applying a solution), I wrote a couple of articles on the subject .

Humility in Problem-Solving

It’s time to do a little summary. What did we see in this article?

• We need to ensure that the problem we found is really a problem we need to solve. Is there any value to solve the problem? Is it even a problem?
• Try to determine what kind of problem you have: a problem which can have multiple, specific, known answers (like a technical problem), or a problem which depends on the real-life context, without known solutions?
• Defining the problem is important. Try to define it using different words. Write these definitions down. Does everybody in your team understand the problem equally?
• It’s time to explore the solution space. Draft a couple of hypothesizes, their benefits, drawbacks, and risks. You can also do some prototyping if you think it would give you more information to take the best decision.
• Do you have enough information to implement a hypothesis, becoming effectively a solution? If it’s not the case, it might be better to keep the status quo and try to solve the problem later, when you’ll have more information. But don’t forget the problem!
• If you decide to implement a solution, do it step by step, especially if you’re unsure about the consequences of your decisions. Implement an independent part of the hypothesis, look at the consequences, adjust if necessary, and re-iterate.
• When the solution is implemented, it’s time to reflect on the whole process: did we solve the problem? What other problems did we encounter? Maybe another solution would have been better? Why?

As I was writing above, most problems you’ll encounter will be complex ones, embedded into a changing environment with different moving parts. As a result, it’s difficult to train to solve problems in a vacuum; the only good training I know is solving real life problems. That’s why your experience is so important.

Experience build your intuition, which in turn increase your expertise.

You’ll never have 100% certainty that a solution will bring you the desired outcome, especially if you are in front of a complex problem with a blurry context. If you are absolutely convinced that you have the good solution without even beginning to implement it, I’d advise you to stay humber in front of the Gods of Complexity, or they will show you how little you know.

• How to solve it
• Hammock Driven Development
• When Deferring Decisions Leads to Better Codebases
• Lean Development - deferring decision

What Is Problem Solving? How Software Engineers Approach Complex Challenges

From debugging an existing system to designing an entirely new software application, a day in the life of a software engineer is filled with various challenges and complexities. The one skill that glues these disparate tasks together and makes them manageable? Problem solving . 

Throughout this blog post, we’ll explore why problem-solving skills are so critical for software engineers, delve into the techniques they use to address complex challenges, and discuss how hiring managers can identify these skills during the hiring process. 

What Is Problem Solving?

But what exactly is problem solving in the context of software engineering? How does it work, and why is it so important?

Problem solving, in the simplest terms, is the process of identifying a problem, analyzing it, and finding the most effective solution to overcome it. For software engineers, this process is deeply embedded in their daily workflow. It could be something as simple as figuring out why a piece of code isn’t working as expected, or something as complex as designing the architecture for a new software system. 

In a world where technology is evolving at a blistering pace, the complexity and volume of problems that software engineers face are also growing. As such, the ability to tackle these issues head-on and find innovative solutions is not only a handy skill — it’s a necessity. 

The Importance of Problem-Solving Skills for Software Engineers

Problem-solving isn’t just another ability that software engineers pull out of their toolkits when they encounter a bug or a system failure. It’s a constant, ongoing process that’s intrinsic to every aspect of their work. Let’s break down why this skill is so critical.

Driving Development Forward

Without problem solving, software development would hit a standstill. Every new feature, every optimization, and every bug fix is a problem that needs solving. Whether it’s a performance issue that needs diagnosing or a user interface that needs improving, the capacity to tackle and solve these problems is what keeps the wheels of development turning.

It’s estimated that 60% of software development lifecycle costs are related to maintenance tasks, including debugging and problem solving. This highlights how pivotal this skill is to the everyday functioning and advancement of software systems.

Innovation and Optimization

The importance of problem solving isn’t confined to reactive scenarios; it also plays a major role in proactive, innovative initiatives . Software engineers often need to think outside the box to come up with creative solutions, whether it’s optimizing an algorithm to run faster or designing a new feature to meet customer needs. These are all forms of problem solving.

Consider the development of the modern smartphone. It wasn’t born out of a pre-existing issue but was a solution to a problem people didn’t realize they had — a device that combined communication, entertainment, and productivity into one handheld tool.

Increasing Efficiency and Productivity

Good problem-solving skills can save a lot of time and resources. Effective problem-solvers are adept at dissecting an issue to understand its root cause, thus reducing the time spent on trial and error. This efficiency means projects move faster, releases happen sooner, and businesses stay ahead of their competition.

Improving Software Quality

Problem solving also plays a significant role in enhancing the quality of the end product. By tackling the root causes of bugs and system failures, software engineers can deliver reliable, high-performing software. This is critical because, according to the Consortium for Information and Software Quality, poor quality software in the U.S. in 2022 cost at least $2.41 trillion in operational issues, wasted developer time, and other related problems.

Problem-Solving Techniques in Software Engineering

So how do software engineers go about tackling these complex challenges? Let’s explore some of the key problem-solving techniques, theories, and processes they commonly use.

Decomposition

Breaking down a problem into smaller, manageable parts is one of the first steps in the problem-solving process. It’s like dealing with a complicated puzzle. You don’t try to solve it all at once. Instead, you separate the pieces, group them based on similarities, and then start working on the smaller sets. This method allows software engineers to handle complex issues without being overwhelmed and makes it easier to identify where things might be going wrong.

Abstraction

In the realm of software engineering, abstraction means focusing on the necessary information only and ignoring irrelevant details. It is a way of simplifying complex systems to make them easier to understand and manage. For instance, a software engineer might ignore the details of how a database works to focus on the information it holds and how to retrieve or modify that information.

Algorithmic Thinking

At its core, software engineering is about creating algorithms — step-by-step procedures to solve a problem or accomplish a goal. Algorithmic thinking involves conceiving and expressing these procedures clearly and accurately and viewing every problem through an algorithmic lens. A well-designed algorithm not only solves the problem at hand but also does so efficiently, saving computational resources.

Parallel Thinking

Parallel thinking is a structured process where team members think in the same direction at the same time, allowing for more organized discussion and collaboration. It’s an approach popularized by Edward de Bono with the “ Six Thinking Hats ” technique, where each “hat” represents a different style of thinking.

In the context of software engineering, parallel thinking can be highly effective for problem solving. For instance, when dealing with a complex issue, the team can use the “White Hat” to focus solely on the data and facts about the problem, then the “Black Hat” to consider potential problems with a proposed solution, and so on. This structured approach can lead to more comprehensive analysis and more effective solutions, and it ensures that everyone’s perspectives are considered.

This is the process of identifying and fixing errors in code . Debugging involves carefully reviewing the code, reproducing and analyzing the error, and then making necessary modifications to rectify the problem. It’s a key part of maintaining and improving software quality.

Testing and Validation

Testing is an essential part of problem solving in software engineering. Engineers use a variety of tests to verify that their code works as expected and to uncover any potential issues. These range from unit tests that check individual components of the code to integration tests that ensure the pieces work well together. Validation, on the other hand, ensures that the solution not only works but also fulfills the intended requirements and objectives.

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Evaluating Problem-Solving Skills

We’ve examined the importance of problem-solving in the work of a software engineer and explored various techniques software engineers employ to approach complex challenges. Now, let’s delve into how hiring teams can identify and evaluate problem-solving skills during the hiring process.

Recognizing Problem-Solving Skills in Candidates

How can you tell if a candidate is a good problem solver? Look for these indicators:

• Previous Experience: A history of dealing with complex, challenging projects is often a good sign. Ask the candidate to discuss a difficult problem they faced in a previous role and how they solved it.
• Problem-Solving Questions: During interviews, pose hypothetical scenarios or present real problems your company has faced. Ask candidates to explain how they would tackle these issues. You’re not just looking for a correct solution but the thought process that led them there.
• Technical Tests: Coding challenges and other technical tests can provide insight into a candidate’s problem-solving abilities. Consider leveraging a platform for assessing these skills in a realistic, job-related context.

Assessing Problem-Solving Skills

Once you’ve identified potential problem solvers, here are a few ways you can assess their skills:

• Solution Effectiveness: Did the candidate solve the problem? How efficient and effective is their solution?
• Approach and Process: Go beyond whether or not they solved the problem and examine how they arrived at their solution. Did they break the problem down into manageable parts? Did they consider different perspectives and possibilities?
• Communication: A good problem solver can explain their thought process clearly. Can the candidate effectively communicate how they arrived at their solution and why they chose it?
• Adaptability: Problem-solving often involves a degree of trial and error. How does the candidate handle roadblocks? Do they adapt their approach based on new information or feedback?

Hiring managers play a crucial role in identifying and fostering problem-solving skills within their teams. By focusing on these abilities during the hiring process, companies can build teams that are more capable, innovative, and resilient.

Key Takeaways

As you can see, problem solving plays a pivotal role in software engineering. Far from being an occasional requirement, it is the lifeblood that drives development forward, catalyzes innovation, and delivers of quality software. 

By leveraging problem-solving techniques, software engineers employ a powerful suite of strategies to overcome complex challenges. But mastering these techniques isn’t simple feat. It requires a learning mindset, regular practice, collaboration, reflective thinking, resilience, and a commitment to staying updated with industry trends. 

For hiring managers and team leads, recognizing these skills and fostering a culture that values and nurtures problem solving is key. It’s this emphasis on problem solving that can differentiate an average team from a high-performing one and an ordinary product from an industry-leading one.

At the end of the day, software engineering is fundamentally about solving problems — problems that matter to businesses, to users, and to the wider society. And it’s the proficient problem solvers who stand at the forefront of this dynamic field, turning challenges into opportunities, and ideas into reality.

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Problem-Solving Skills for Software Developers: Why & How to Improve

Problem-solving skills go hand-in-hand with software development. Learn some great problem-solving techniques and tips for improvement here!

Software developer jobs today require that you possess excellent problem-solving skills , and for good reason. Unfortunately, there seems to be a sort of talent gap when it comes to this one skill required of all software developers.

Troubleshooting and problem resolution are both informally and formally taught, but you mostly find that software developers have to learn problem-solving skills on their own. This is true for self-taught developers , obviously, but also even for those with software engineering degrees or who’ve graduated from coding boot camps.

This is why it’s necessary to acquaint yourself with the problem-solving process, whether you are a newbie or an experienced developer. In this article, we’ll explore everything you need to know about problem-solving so you can 10x your software development career.

What are Problem-Solving Skills?

As a developer, what do we mean by problem-solving? Let’s attempt a simple definition.

In software development, problem-solving is the process of using theories and research to find solutions to a problem domain, while testing different ideas and applying best practices to achieve a desired result. Problem-solving also has to do with utilizing creativity and logical thought processes to identify problems and resolve them with software.

Becoming a great software developer hinges more on learning algorithms than programming languages or frameworks . And algorithms are simply step-by-step instructions to solve a given problem.

Read More : How to Build a Software Engineer Portfolio (With Examples & Tips)

Why are impeccable problem-solving skills crucial?

Making good use of a computer language can be likened to being a skilled writer. An effective writer must know how to construct sentences and use grammar appropriately. There’s more to writing than just knowing all the words in the dictionary, and that’s how it works for developers, too.

You have different tasks to work on as a software developer, including perhaps designing, coding, and troubleshooting. Much of your time will be spent on identifying problems, spotting and correcting bugs, and making sense of codebases from before you started working there. Being ingenious at problem-solving is essential in creating incredible solutions to issues that arise throughout software development.

To demonstrate ingenuity, let’s consider Google’s autocomplete tool as an example.

The autocomplete tool is built to suggest related terms in the search bar as you type. The idea behind the tool is to reduce more than 200 years of time spent typing daily and to help users save time by up to 25% while typing.

Here’s what had to be done:

• To activate real-time completion of suggestions, the UI experience and JavaScript had to be implemented.
• Next, since users could type just about anything, the autocomplete suggestions had to be compiled into a sensible list dependent on user input.
• Then, Google had to create a back-end sustainability system for this function. Doing this meant massively increasing its infrastructure to accommodate all forms of data query and HTTP requests.
• Finally, the user interface had to be refined by software engineers in order to make sure that every user enjoyed a worthwhile experience. So they employed Google Trends to power the auto-completion tool while using algorithms to take out explicit or offensive predictions in line with Google’s auto-completion policy.

This is just one of Google’s innumerable problem-solving examples, but it’s clear to see that solving problems involves more than just telling a computer to do stuff. It’s about your ability to come up with parameters rightly tailored to target users so they can meet their goals.

So why must developers focus on problem-solving at work?

Software developers work with a wide range of people and departments, and it’s common to discover that some clients and teams find it difficult to define what they want. As a problem solver, it’s up to you to help them identify their needs and communicate their thoughts in an effective way.

Of course, you’ll need time and practice to develop your problem resolution ability. That’s because it’s less about solving problems faster but more about coming up with the best solution . And then you’ll need to deploy that solution.

Read More : Common Interview Questions for Software Developer Jobs (Non-Technical)

Types of problem-solving skills

Now let’s talk about four types of problem-solving skills for developers:

1.  Parallel thinking

As a software developer, parallel thinking is a crucial skill necessary to perform optimally. This makes it possible for you to carry out two tasks that complement each other at the same time (like an optimized form of multitasking skills). Being able to reorder tasks to boost parallel execution can help to improve your output and save valuable time .

2. Dissecting broad and/or complex goals

When it comes to building software, you will need to effectively outline the steps and tasks necessary to achieve your goal. Developers must learn to break large and complex tasks into smaller assignments because this is an important skill that will help you create results with precision.

3. Reimplementing existing solutions

You don’t always need to reinvent the wheel. Part of being an effective software developer comes with being able to use already existing tools before even thinking of creating new solutions. Developing problem-solving skills is very much connected to finding solutions that already exist and reusing them.

4. Abstraction

Keep in mind that goals tend to evolve. So if your client comes up with new ideas, that will mean changing your design goals and reordering your tasks. A good programmer must learn to create solutions in such a way that does not require a complete redesign from scratch.

You also have to become adept at abstracting problems so that your solutions can get them resolved so long as they aren’t entirely different from the original issue. You don’t necessarily have to abstract every aspect to avoid more complications being created. This calls for balance by abstracting only where necessary without making narrow decisions.

Read More : Learn 8 Great Benefits of Working From Home

4 Important Tips & Strategies for Improving Problem-Solving Skills

To keep your problem-solving skills and techniques from growing weaker over time, you need to exercise them non-stop. As they say: practice makes perfect!

To train the problem-solving side of your brain, these four tips and strategies can help you improve your abilities:

1. Make problem-solving a part of your life

Never restrict yourself to working on problems only during work hours. Don’t make it a chore, but, instead, do things that make problem-solving look fun. The game of chess, solving puzzles, and playing video games that compel you to think critically will help strengthen your problem-solving skills, and you can tell your significant other you are advancing your career! 🙂

When you come to a complex problem in your life, whether it’s budgeting for a home or renovating the downstairs bathroom, approach it both creatively and critically. Ask yourself: What would a great software engineer do in this situation?

2. Use different platforms to solve problems

Proffer solutions to a set of problems without restricting yourself to one platform. Using different platforms and tools regularly helps make sure you become flexible as a problem-solver. And it makes sense, because there really is no universal solution for the different problems that pop up in your line of work. Trying out different platforms to solve different problems helps you to keep an open mind and enables you to test out different techniques when looking to find solutions.

Read More : 12 Common Mistakes Keeping You From Landing Your First Developer Job

3. Be open to assistance from external sources

Part of being a good software developer comes with being able to ask for help and also accept all forms of feedback. You might need a different opinion or a new set of eyes to help find the most fitting solution to some problems. It makes sense to view building problem-solving skills as more of a team effort rather than a personal journey.

Have an open mind and heart to function not only as an individual but also as a collective. It’s a utopian working environment where everyone supports each other to become better versions of themselves. So if you come across an issue that keeps you stuck, get help! You may find someone who has a more refined framework or method you never knew existed or would have thought of using. You could then learn from them and add their solution to your toolkit.

Get feedback often, as well. This could be the catalyst to making improvements to your processes and evolving them into something truly refined.

4. Tackle new problems using lessons from past solutions

As you practice and finesse your ability to identify problems and find solutions, you’ll begin to notice patterns. It’s more like developing your toolbox armed with a wide range of solutions that have proved useful in the past. So when problems emerge, you will notice how easy it is to take some of those old solutions and apply them to the new problem.

The more you attempt to apply creativity in solving problems, the more you grow your skills. In the long run, that will help you find the right solutions faster and apply them to a wide range of problems more naturally. It’s all about improving the effectiveness and efficiency with which you tackle new problems while applying only the best possible solutions.

Read More : How to Stay Motivated at Work

3 Complementary Skills to Improve to Become a Good Problem Solver

Developing software is mostly about problem-solving at the very core before even writing your first lines of code. You have to identify problems that can be solved using software. Then you have to go on to understand how people try to solve such problems in real life.

It’s up to you to come up with a framework that allows you to take both the problem and the solution and convert them into computer code. And you have to do this in such a way that makes the software even more efficient and effective than a human.

While going through this process, developers also have to handle other problems such as deadline deliveries, checking for bugs and fixing them, and collaborate across teams. So, supporting skills must not be overlooked.

Software developers must build interpersonal skills and collaboration skills . Being able to empathize, accept feedback, handle criticism, listen intently, and show respect for others are all important characteristics and abilities necessary for teamwork, and, thus, necessary for solving problems on the job.

Read More : 5 Ways to Stand Out & Get Noticed in Your Current Development Job

Communication

No one is an island, and that’s true when you consider how software engineers work. Building software requires keeping up with clients and teammates and other departments. You can’t afford to be a Lone Ranger, at least not 100% of the time, and that’s why employers always look for good communication skills.

Being a good software developer also involves how well you can break down very complex concepts to laypeople. You want to be the kind of person who fixes a problem and is able to explain how you were able to do it. It’s all about your ability to be clear and articulate about every aspect of your work. And you want to be able to communicate not just verbally but also in written form.

To build your communication skills as a developer, you can learn from more experienced people and observe how they interact with their clients. And, don’t forget, with more and more companies becoming global enterprises and going remote, it’s important to brush up on your intercultural communication skills , as well.

Logical thinking

The difference between elite software developers and average ones is often said to be logical thinking. The ability to process thoughts logically is important, because you’ll often spend most of your time finding and fixing bugs rather than writing code.

Problems can show up from just about anywhere, even from what seems to be the most insignificant errors. So, your ability to detect software issues and solve these problems using deductive thought processes is a vital ingredient to your success as a software developer.

Read More : Questions to Ask at Interviews for Software Engineering Jobs

Problem-Solving Stages & Practices

There are countless problem-solving processes and various schools of thought regarding the best way to approach problems whenever they arise. To solve that problem, we’ve pooled some of these frameworks together to come up with a comprehensive approach to problem-solving.

Step 1 – Define the problem

You have to first start with problem identification. Knowing what you are dealing with is important, because you don’t want to risk spending valuable time applying wrong solutions. Avoid making automatic assumptions. Even when the symptoms look familiar, you want to investigate properly because such signs could be pointing to something else entirely.

Problems in software development come in different sizes and scopes. You could be having trouble getting some aspects of the product to respond in the desired way. Or maybe you’re having issues trying to decipher a codebase section where you can no longer communicate with the original developers. Sometimes, the problem could come in the form of an unfamiliar error message and you’re at loss.

Once you’re able to define the problem, make sure to document it.

Step 2 – Analyze the problem

Now it’s time to carry out problem analysis . Before deciding what problem resolution methods to adopt, it’s necessary to find out all there is to the issue, which builds on our first step. This will make it easier to come up with ideas and solutions later on.

Problem analysis isn’t always a walk in the park. There are times when the problem involves a very small mistake such as failing to import a package correctly or a small syntax error. Other times, however, it could be such a huge error, like the entire program acting differently than what you want. There might be no alarms or blinking red lights to tell you what the exact problem is.

If you encounter such situations, you can find answers by articulating the problem. Document what you intend to do, what you’ve done, the original intention for the program, and where you currently are. Communication comes in handy here, of course, not just in your documentation, but also in how you relay it to your teammates.

Read More : Got a Busy Developer Schedule? Here’s How to Keep Learning & Make Time

Step 3 – Brainstorm

This step has to do with generating ideas, and you can benefit from discussing the problem with a team and then coming up with ways to get it fixed. Keep in mind that problem-solving at work involves interacting with a diverse group of people where the individuals have unique skill sets and experiences.

Many developers tend to neglect the previous steps and rush straight into brainstorming. That’s definitely not a good way to go about problem-solving. The idea is not to skip the important steps in the process.

Once you get to the point where ideas need to be generated, do not discard any, because this step relies on a wide range of ideas. Only after gathering as many perspectives as possible should you then begin reviewing and narrowing down to the best possible solution.

Step 4 – Make a decision

At this point, all viable solutions have to be analyzed before selecting the most appropriate one to implement. Picking the best possible solution depends on its ability to meet certain criteria. It must be suitable, feasible, and then acceptable.

What it means is that the solution must be able to get the problem solved. It should also be easy to see how such a solution fits into the equation. And then every member of the team involved in the brainstorming process has to unanimously accept the solution.

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Step 5 – Implement

After identifying and choosing the solution, the next logical step is to plan out the implementation process and then execute it. Coming up with a detailed plan is crucial if the solution is to be a success.

Now this plan must detail all the necessary steps required to implement the solution. It will also explain the length of time and stages of work required. Once all of that is put in place, you can then move forward with the execution. The idea is not just to execute a solution but to do it the right way.

Implementation using automated tests can help to keep unexpected issues from arising in the future. Some other problem-solving practices or approaches begin the process with this step. So, whenever any changes are made to the project, tests asserting that the changes will perform as required will be written first before the changes are then made.

Step 6 – Evaluate

No problem-solving process can be deemed comprehensive enough if there is no room for evaluation. Whatever the solution may be, it has to undergo strict evaluation in order to see how it performs. That will also help determine whether the problem still exists and the extent to which such an issue keeps recurring.

In the event that the problem persists despite the implementation of a detailed plan, then the developer and team may even have to restart the problem-solving process. However discouraging that may sound, at least you’ll have caught it early enough. And, this also proves the process worked.

Read More : How to Become a Software Engineer: Education, Steps & Tips for Success

Final Thoughts

Developing problem-solving skills is quite necessary for software developers. To be a successful problem solver, you will need lots of years down the line to practice what you study.

Always remember that you are a problem solver first before anything else. There is more to building software than just understanding the tech behind it and writing lines of code. It’s all about improving your ability to identify problems and find solutions, and that will need lots of experience on your part.

Never shy away from problems, but learn to think critically and logically in any situation. By applying the six-step strategy for problem-solving at work discussed in this piece, you will be more equipped to come up with the most effective and efficient solutions.

We hope you enjoyed reading our guide on how to solve a problem as a software developer and ways to improve skills as a problem solver! If you have any questions, feedback, or other great problem-solving techniques or methods, let us know in the comments below 🙂

The Arc team publishes insightful articles and thought leadership pieces related to software engineering careers and remote work. From helping entry-level developers land their first junior role to assisting remote workers struggling with working from home to guiding mid-level programmers as they seek a leadership position, Arc covers it all and more!

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Posted on Aug 10, 2022

How to develop strong problem solving skills as a software developer

Introduction.

It is generally known that problem solving is an essential skill for software engineers.

Good problem solving skills involve being able to think creatively and analytically, breaking down problems into smaller parts and using a systematic approach to find solutions. Strong problem solving skills are essential for a successful career in software development. In this article we will review some approach.

Various Methods

Trial and error method.

The trial and error method is a common problem-solving technique in which potential solutions are tried out one by one until a working solution is found. This method can be used for both simple and complex problems.

Divide and conquer

Another approach is to use a more systematic method, such as divide and conquer or reduction. Divide and conquer is a software engineering technique for solving complex problems by breaking them down into smaller, more manageable pieces. This allows for more efficient and effective problem solving by breaking down a complex problem into smaller, more manageable sub-problems. Once these sub-problems have been solved, they can be combined to solve the larger, more complex problem.

One common example of divide and conquer is the use of recursion. Recursion involves breaking a problem down into smaller sub-problems, solving each sub-problem, and then combining the solutions to the sub-problems to solve the larger problem. Another common example is the use of algorithms, such as the quick sort algorithm, which break a problem down into smaller pieces, solving each piece, and then combining the solutions to the pieces to solve the larger problem.

Once a solution is found, it is important to learn from the experience and use that knowledge to improve future problem solving skills. This includes understanding what went wrong, what could have been done better, and how similar problems can be avoided in the future. By taking these steps, software developers can become more effective problem solvers.

Problem solving skills is important in its own way. As a software developer, you should try to develop all of these skills in order to be successful.

Analytical skills:

Analytical skills are the ability to collect and analyze data, identify patterns and trends, and make decisions based on that information. They involve both logical and creative thinking, as well as the ability to pay attention to detail. Strong analytical skills are important in many different fields. Some examples:

• Being able to break down a problem and identify the various components
• Being able to identify patterns and trends
• Being able to see relationships between different pieces of data
• Being able to make decisions based on data
• Being able to solve complex problems

Creative thinking

Creative thinking in computer science is all about coming up with new and innovative ways to solve problems. It’s about thinking outside the box and coming up with creative solutions that nobody has thought of before.

It’s important to be creative in computer science because it’s a constantly evolving field. If you’re not constantly coming up with new ideas, you’re going to fall behind. Creative thinking is what keeps computer science moving forward.

If you want to be successful in computer science, you need to be creative. It’s not enough to just learn the basics. You need to be constantly thinking of new and better ways to do things. So if you’re not a naturally creative person, don’t worry. Just keep working at it and you’ll get there.

Logical reasoning

Logical reasoning is a process of making deductions based on given information. In computer science, this process is often used to solve problems and to create new algorithms. To reason logically, one must first identify the premises and then use them to reach a valid conclusion.

Practice is one of the best ways to improve your problem solving skills. You can do this by working on coding challenges, participating in online coding contests, or simply trying to solve problems you encounter in your daytoday work. Collaboration is another great way to improve your problem solving skills. When you work with others, you can learn from their experiences and share your own insights. This can help you develop a more well rounded approach to problem solving.

If you're a software developer, congratulations! You have chosen one of the most mentally demanding professions there is. And if you want to be successful, you need to have strong problem solving skills.

My last tip: get comfortable with being stuck! It's normal to feel stuck when you're trying to solve a problem and don't be afraid to ask for help. We all need help from time to time, and there's no shame in admitting that you need help.

So there you have it! Follow these tips and you'll be well on your way to developing strong problem solving skills as a software developer.

Like this article? Join the discussion in our Discord channel .

Top comments (26)

Templates let you quickly answer FAQs or store snippets for re-use.

• Work Lead Dev
• Joined Jul 12, 2022

For students , don't underestimate the mathematics. You definitively don't need a master degrees in maths to be a successfull developer BUT , mathematics train your brain to think. All this theorems you probably never used in real world , all thoses equation you resolved in high school helped your logical reasoning.

Finally, to get better at resolving problem you definitely should resolve problem :P The more you resolve , the better you get !

• Joined Mar 14, 2022

I agree with you! I mentioned it, practice and practice.. About maths it is also another alternative

• Joined Sep 21, 2021

Science shows that there really is no knowledge transfer between unrelated fields. There is essentially no way to get overall better at thinking. You either can relate what you know already to the thing or you can't. In first case it's experience, not brain trained to thinking, in second it depends on if you learned how to learn.

Logical reasoning is a small part that everyone does even without thinking, but it doesn't transfer if you don't use abstractions to relate what you don't know with what you do know.

You can get better at resolving problems overall, but it's a tiny improvement if you don't focus on learning how to solve problems. Solving problems on it's own gives you experience you can use at solving similar things. But it won't help with different problems.

That being said if you can relate math you learned to problems you need to solve it can sometimes make something impossible into something very easy. That on it's own is a good reason to get good at maths. The other one is training on how to read information dense domain texts.

• Location Yenagoa, Nigeria
• Joined Feb 1, 2021

You're right, solving mathematical problems help increase logical reasoning, and I believe that's a major reason we do maths in Computer Science. Working with numbers is a top-tier ability if you want to become a successful "software engineer". Thanks.

You're right, solving mathematical problems help increase logical reasoning, and I believe that's a major reason we do maths in Computer Science. Working with numbers is a top-tier ability if you want to become a successful "software engineer". Thanks

• Location India
• Joined Aug 17, 2019

Just like Neil deGrasse Tyson said, It is not about finding the value of x, It is about process for finding the x.

• Location Munich, Germany
• Work Software Development Team Lead
• Joined Oct 4, 2019

I have to disagree, especially on the Maths->Logics path. I found it's a lot easier to go into Logics without Maths, even though the basic principles are similar (since both are just formal languages).

• Education Computer Science
• Work Senior Software Developer at Syskron GmbH
• Joined Jan 30, 2021

What he meant is that math trains your brain. Either way it’s math or not it’s necessary to think structured to solve programming problems. I have seen so many bad code written my mathematics (no offense 😃)

• Email [email protected]
• Location Living in the path between home and office
• Education The school of life and entry points
• Work 📖 Researching and learning everything about API Security and Business Logic
• Joined Jun 22, 2022

• Location Nashville
• Education Bootcamp Grad
• Work Fullstack Developer
• Joined Mar 5, 2017

You have to joke so you don't cry.

• Email [email protected]
• Location Budapest, Hungary
• Education engineering
• Work software developer @ itemis
• Joined Dec 25, 2021

what a cool drawing!

Hahaha @apimike humor is important!

I just said that math was a way , and because it's basically taught in every school of the world (contrary to other knowledge) it's important to embrace it and understand that what you are taught is not how to multiply 2 number but actually how to think.

I realized it way too late, I always hated math when I was young because I wasn't able to figure out the point of what I was taught.

The misconception is , that you have to be good at math to be a good developer. Indeed that completely false (unless your are developing for some specific field).

• Joined Nov 24, 2020

Being a successful software developer, one needs to be open to learning and unlearning. I've learnt and unlearnt and am grateful I did. Most of the time I share with colleagues and friends, I got to find out the knowledge that was most neglected, tends to be a challenge for someone else.

It's a mentally demanding field. It's not just a job, it's a way of life.

• Location Scotland, United Kingdom
• Joined Nov 13, 2020

this is spot on

Thanks for the article, it resonates.

I read most of the comments and can't stay quiet. From my years of experience, math can be a really powerful tool when it comes to solving problems. Ofcourse is only one of the tools out there that can empower a programmer. Another tool I found to be crucial are flow charts. Being able to construct them the right way can help a lot.

e. g. This problem I solved it using only math. And I have used many concepts of math and physics for game development. To understand algebra, arrays, matrixes, vectors, magnituds, forces, inertia, acceleration, etc... Can be crucial on the development of certain softwares. But it all depends the area in which you are coding.

• Location Dhaka, Bangladesh
• Education Dep. of Computer Science & Engineering(CSE), BAIUST
• Work Unemployed

A newbie here. I've a different problem . i.e. I face difficulty while implementing the code but I know the theory & logic behind it. Any suggestion/advice for me anyone ?

Hiiii maybe I will write an article about it ! Nice idea :)

• Email [email protected]
• Joined Apr 23, 2019

a great read

• Joined Jul 9, 2020

I wonder if there is literature about how to improve and train your problem solving skills. Could you recommend books about this topic?

Personnaly I don't know books on this topic, but if you have got something share it with us :)

• Joined Mar 11, 2022

this article and that comments below are good

• Email [email protected]
• Location Philippines
• Education Javascript Development with Clever Programmer
• Work Software Consultant at Servio Australia
• Joined Aug 29, 2020

Thank you. "Divide and conquer" works for me.

• Location Rwanda
• Joined Jul 30, 2022

I think, being open-mind is a way to simulate our brain when it comes to creative thinking. btw nice article

• Joined Sep 17, 2021

I have a short, simple rule: be creating and imaginary as much as possible. That's to say whatever others do you can do differently and/or more crazily.

• Joined Mar 13, 2023

Software quality assurance consulting services are specialized services offered by qualified experts who evaluate and examine software systems for flaws, weaknesses and potential threats. These qa company haberforever.com/ help companies improve the quality and reliability of their software products by providing extensive knowledge and skills in software testing methodology, automation technology and industry best practices.

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How to Enhance Problem-Solving Skills – A Guide for Software Developers

• April 09, 2024

Explore the art of problem-solving in software development with our insightful guide. Discover essential strategies for tackling challenges, including understanding the problem, strengthening mathematical foundations and practicing with coding challenges.

Problem-solving is the foundation when it comes to software development. Software developers must always have innovative solutions to face challenges appropriately. In this article, we will discover methods of problem-solving and also the improvement of the problem-solving technique itself. Let's consider all the key strategies and see how we can enhance our approach to overcoming developmental obstacles.

Understand the Problem Before You Solve It

The first and most crucial step in the problem-solving process is understanding the problem itself. This forms the foundation for everything that follows and ensures that you're not just looking for any solution, but the right one. The following five steps are key in the process of understanding a problem:

• Clear definition of the problem - break the problem into parts and define each of them.
• Gather all relevant information - view the problem from multiple perspectives and analyze all available information pertinent to the problem.
• Identify the fundamental causes of the problem - determine what triggers the problem and make it conscious so that in the future you can be prepared to avoid the occurrence of this problem or solve it more quickly.
• Visualize the problem - Use diagrams or data flows for clearer insight into the problem.
• Rephrase the problem - Sometimes, stating the problem differently can reveal new solutions.

Taking the time to truly understand the problem before attempting to solve it creates a solid foundation for your problem-solving efforts. This approach makes the solving process simpler and increases the chances of finding the best and most effective solution.

Dive into the essence of the problem, analyze, remember, and always think in the direction of solving. This will allow you, as a software developer, to be a step ahead of both problems and competitors in this field.

Strengthen Mathematical Foundations

At the core of the software development process lies a deep understanding of the problem, a process that is far more nuanced than it appears at first glance. The better you understand what you're dealing with, the easier it will be to find a solution. Mathematical foundations contribute to the thinking process, analytical perspective, and ultimately, problem-solving.

As software developers, you should take improving your mathematical knowledge seriously. Whether it's through courses, academic research, or practical application, the goal is to sharpen your analytical thinking. For software developers seeking a customized strategy to enhance their mathematical skills, seeking advice from experts, such as those found in various specialized courses, Denver math tutors , or through additional education, can be immensely beneficial for skill enhancement. 

Such resources can provide you with personalized attention and the nuanced understanding necessary to elevate your mathematical ability.

The benefits of strengthening mathematical foundations include:

• Improved logical thinking and analysis
• Enhanced ability to conceptualize complex problems
• Greater precision in coding and algorithm development
• Increased efficiency in identifying and solving problems
• Deeper understanding of computational complexity and optimization

Practice with Coding Challenges and Competitions

Engaging in coding challenges and competitions is a powerful way to sharpen your problem-solving skills. These platforms offer a wide range of problems, from simple algorithmic puzzles to complex software development tasks, pushing you to apply theoretical knowledge in practical scenarios.

Participating regularly exposes you to diverse problem types, encouraging adaptability and quick thinking. It's a practice arena where learning from mistakes is just as valuable as solving the problem. Beyond individual growth, these challenges often connect you with a community of like-minded individuals, offering peer learning opportunities and feedback.

This exposure to collective wisdom and diverse approaches enriches your problem-solving toolkit, making you a more versatile and competent software developer. Engage with these platforms to test your limits, learn efficiently, and prepare yourself for real-world software development challenges.

Adopt a Test-Driven Development (TDD) Approach

Test-Driven Development (TDD) is a software development methodology where tests are written before the actual code. This approach flips the traditional coding process on its head, prioritizing the creation of specific tests for functions before those functions are fully developed.

The idea is to refine and debug code in short, verifiable steps, enhancing both the quality of the software and the problem-solving skills of the developer. Here's how to adopt a TDD approach:

• Start by defining the requirements of the new feature or functionality you're developing.
• Write a test that fails because the feature doesn't exist yet.
• Write the minimum amount of code needed to pass the test.
• Refactor the code for optimization without changing its behavior.
• Repeat the process for each new piece of functionality, gradually building up the software in a controlled, error-minimizing manner.

Incorporating TDD into your workflow can significantly improve your problem-solving skills by encouraging a disciplined, thoughtful approach to coding. It forces you to consider all possible scenarios for your functions, leading to more robust and error-resistant software.

TDD can be particularly beneficial for software developers working on complex projects like an intranet search engine . This methodology ensures that every aspect of the search engine is tested and validated against real-world requirements, minimizing bugs and enhancing performance.

Breaking down the coding process into manageable steps and focusing on creating tests first can tackle intricate problems more effectively and deliver solutions that are both reliable and efficient.

Learn from Real-World Projects and Case Studies

Exploring real-world projects and dissecting case studies can dramatically boost your problem-solving prowess as a software developer. There's something incredibly valuable about stepping into the shoes of those who've navigated the complex maze of software development before you.

Choose projects or case studies that spark your curiosity or touch on areas you're keen to get better at. Delve into the tactics used, the hurdles that popped up, and the clever ways they were tackled. Focus intently on the thought process behind decisions and the specific technical fixes that were applied.

This hands-on learning method pushes you to think more critically and marry your book knowledge with the messy, unpredictable world of actual software projects . It’s about understanding the reasoning behind every move and seeing firsthand how different approaches can alter a project's trajectory. Immersing yourself in these stories of development brings to light the nuanced dance between solving problems creatively and sticking to tried-and-true technical principles.

You'll find yourself better prepared to foresee potential snags in your work and craft smarter, more innovative solutions. This provides you to mold into a more thoughtful, adaptable developer who can navigate the winds of change with grace.

Wrapping up, enhancing your problem-solving skills is a continuous journey, one that’s crucial for thriving as a software developer. By embracing practices like understanding problems deeply, engaging with coding challenges, adopting TDD, and learning from real-world projects, you’re setting yourself up for success. Remember, every challenge you overcome not only builds your skillset but also paves the way for future innovations. Keep pushing, keep learning, and let your curiosity lead the way.

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Problem-Solving Techniques for Software Developers

By Chevas Balloun

Last Updated: April 9th 2024

Too Long; Didn't Read:

Software developers must master problem-solving techniques to succeed in the tech industry. Debugging, critical thinking, and knowledge of algorithms are key. Problem-solving skills lead to promotions, higher salaries, and job security. Employers highly value these skills. Practicing diverse problem-solving methods is essential for professional growth and success.

In this crazy world of coding, being a problem-solving ninja isn't just a plus, it's an absolute must-have if you want to crush it. The big dogs like Google don't mess around; they're all about hiring folks who can take on complex challenges like a boss and make their products shine.

Across the board, from TechRepublic to ARC Dev , problem-solving skills are the golden ticket during hiring time.

These skills aren't just about fixing bugs or untangling code - they're about crafting epic solutions and communicating with your team like a pro. But it's not just about the immediate grind; mastering problem-solving is about developing a mindset that keeps you hungry for knowledge.

Like the legends at DEV Community say, it's about learning from your experiences, reflecting on your decisions, and embracing collaboration like a champ.

Get ready to level up, because we're about to dive deep into the art of problem-solving, the holy grail for devs. We'll show you how to sharpen these essential skills that Nucamp talks about, so you can slay any challenge that comes your way.

Table of Contents

Definition & importance of problem-solving, typical problems faced by software developers, effective problem-solving techniques, applying problem-solving techniques - examples, conclusion - the art of problem-solving, frequently asked questions, check out next:.

Discover the secret to project success through effective collaboration , the cornerstone of modern development work.

Problem-solving is the name of the game in coding, bro. It's like the beating heart of the whole dev scene. Figuring out how to tackle bugs, make shit run smoother, and just generally getting your code to do what you want it to – that's what it's all about.

According to some research , devs gotta be able to think outside the box and see the big picture if they want to slay those coding challenges.

Why is this skill so crucial, you ask? Well, software is like a never-ending maze of code, and with every new feature or update, fresh complexities pop up.

Coding ain't just about typing out lines – it's about understanding the logic, algorithms, and data structures behind it all, which falls under the problem-solving umbrella.

As one expert put it, "Programming is less about writing code and more about solving problems that make people's lives easier." HackerRank backs this up, saying that solid problem-solving skills lead to better software quality and keep dev projects moving forward.

Real talk, problem-solving skills are a must-have in the tech world.

Devs need to design user interfaces, understand what clients want, and be able to communicate their ideas clearly, according to this insight on software engineering problem-solving.

These kinds of skills are what's driving the 11% job growth in computer and IT fields from 2019 to 2029, according to the Bureau of Labor Statistics. Being a boss at problem-solving is practically synonymous with being a rockstar dev in today's rapidly evolving tech landscape.

In a nutshell:

• Technical Skills and Communication: Killer problem-solving skills are a combo of technical know-how and clear communication .
• Functional and Aesthetic Outcomes: How well devs can solve problems determines the functionality and look of software.
• Industry Growth: The tech industry's growth depends on having more skilled problem-solvers to navigate its complexities.

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Software development is a wild ride with mad challenges you gotta face every day. According to Stack Overflow , a whopping 38% of devs struggle with constraints like tight deadlines and dealing with legacy code.

On top of that, 34% face non-technical issues like communication breakdowns with managers or coworkers. As reported by Synoptek , one of the biggest technical headaches is the lack of a solid project infrastructure and keeping up with constantly changing requirements, which can mess up your delivery times and budgets.

With tech evolving at lightning speed, you gotta stay on top of the latest trends and make sure to implement tight security measures from the get-go to protect sensitive data, as Xperti points out.

Cybersecurity is a big deal, and it's on devs like you to keep that data privacy locked down. The 2020 Developer Survey revealed that a solid 29% of pros see collaboration as a major obstacle, especially with remote work becoming the norm, making effective communication tools and practices crucial.

And according to Casey McGuigan, product manager at Infragistics, technologies like low-code/no-code development tools could help address the shortage of developers, as highlighted in the Spiceworks survey .

To sum up the updated challenges in a visual way:

• Lack of established project infrastructure
• Adapting to changing project requirements and technologies
• Implementing robust security measures
• Non-technical and team collaboration issues

This field is constantly evolving, and mastering problem-solving skills is key.

As Mary Lee, a senior software engineer with a decade of experience, puts it, "Facing these challenges head-on, developers can grow in their careers and invent solutions that shape our future."

Developers these days have come up with some sick tricks to tackle the crazy coding challenges. Debugging is a major strategy, and it includes things like rubber duck debugging , where you explain your code line-by-line to an inanimate object, and somehow that helps you figure out the solution.

Crazy, right? Turns out, developers spend like 35-50% of their time debugging and validating code, so it's a big deal.

But it's not just about debugging.

Critical thinking methods like the Socratic questioning approach help break down problems into smaller, more manageable pieces. And let's not forget the POLYA method (Problem, Options, Learn, Act), which is basically a logic-based way to tackle problems and boost your coding skills.

This research from 7pace suggests six ways to level up your problem-solving game, like practicing diverse problems on different platforms and learning from past solutions.

Combining analytical skills, creativity, and logical reasoning is key to mastering the art of problem-solving, according to arc.dev. Being a pro at problem-solving can save you a ton of time and resources, because you can dissect issues like a boss.

Data shows that knowing your algorithms and data structures can make you up to 30% more efficient at solving problems.

So here are some dope heuristics to approach complex coding challenges:

• Understand the Fundamentals : Grasping the basics gives you a solid foundation to dissect problems .
• Break It Down : Divide big problems into smaller, more manageable chunks to avoid brain overload. Developers.dev recommends this for efficient problem-solving .
• Write Pseudocode : It makes you think through the logic before diving into the actual code .
• Seek Patterns : Recognizing recurring themes or algorithms can lead you to streamlined solutions .
• Iterative Testing : Incremental checks can catch errors early and ensure each component works as intended .

As one expert put it,

"Good programming is not about knowing all the answers; it's about knowing how to tackle the questions."

Incorporating these techniques into your workflow not only helps you conquer the current challenge but also sharpens your skills for future ones, making you a lifelong learner and a valuable asset to any team.

Coding can be a real pain sometimes, but the way you handle those problems can make or break a project. Take Google, for instance. Back in 2017, Chrome was hogging up a ton of memory, and users were getting frustrated.

But the dev team didn't just sit there scratching their heads. They used this technique called performance tuning to analyze what was going on, and they managed to cut Chrome's memory usage by like 20%! That's a huge deal.

But that's not the only cool example.

During the Apollo missions, when memory was tight, the developers had to get creative with priority scheduling to make sure the most important tasks could still run.

It just goes to show that sometimes you gotta think outside the box to solve a problem, especially when the stakes are high.

One social media firm had this nasty bug that kept crashing their servers during peak hours.

But instead of each developer trying to tackle it solo, they paired up and did some collaborative coding . Not only did they squash that bug in a few days, but their code quality improved too! Pretty slick, right?

Sometimes, real-world examples can inspire coding solutions too.

Like this dev who used go-karting races to understand race conditions and how to detect loops in linked lists. It's all about finding creative ways to apply concepts you already understand.

This health-tech startup used machine learning algorithms to integrate different healthcare systems, and it sped up their data processing by a whopping 40%! Talk about a game-changer.

At the end of the day, problem-solving is what separates the good coders from the great ones.

Whether it's performance tuning, collaborative coding, real-world inspirations, or leveraging new tech like machine learning, the key is being able to think creatively and adapt to whatever challenges come your way.

Problem-solving skills are the real MVP for any coder out there. It's not just some fancy buzzword; it's the key to unlocking a sick career trajectory. The stats don't lie – if you're a pro at tackling problems, you're 3.5 times more likely to snag promotions and leadership roles.

The folks at Indeed.com know what's up.

They're all about that structured problem-solving approach, which is the secret sauce for leveling up your skills and climbing that career ladder. A whopping 85% of software engineers give mad props to their problem-solving prowess for their career growth.

It's a game-changer.

But a whopping pay bump of 20%-30% – cha-ching! It's not just about the money, though. Tech companies are thirsty for this talent, with 90% of them doing whatever it takes to keep these problem-solving ninjas on board.

They know it's the secret sauce for innovation and efficiency within their squads.

And problem-solving skills are like a universal key that unlocks doors across different specializations and industries.

The Indeed UK crew has your back on this one.

You'll be a hot commodity!

Here's a quick rundown of the perks problem-solving skills bring to the table:

• More Job Opportunities: You'll be a coding chameleon, adapting to different programming environments and new tech like a boss.
• Negotiation Leverage: Your mad skills will give you some serious negotiating power when it comes to scoring that fat paycheck.
• Career Boost: Leadership roles will be within your grasp, thanks to your problem-solving prowess.
• Networking Goals: Crafting innovative solutions will make you the cool kid on the block, expanding your professional circle like crazy.

Don't just take my word for it.

Lisa Hernandez from Tech Innovations went from zero to hero all because of her problem-solving game. She's living proof that seeing every challenge as a learning opportunity can seriously upgrade your career trajectory.

In this ever-changing tech world, the ability to break down and conquer complex problems isn't just a nice-to-have – it's the key to success.

If you're looking to level up your critical thinking and decision-making skills, Nucamp's resources have got your back.

It's time to upgrade your problem-solving arsenal and dominate the tech game!

Why are problem-solving techniques important for software developers?

Problem-solving techniques are crucial for software developers as they enable them to dissect software issues, optimize performance, and implement effective solutions in a systematic manner. In the ever-evolving field of software development, problem-solving skills are essential for understanding logic, algorithms, data structures, and creating value through code.

What are some typical problems faced by software developers?

Software developers often face challenges such as working within constraints like time and legacy code, adapting to changing project requirements and technologies, implementing robust security measures, and dealing with non-technical issues like team collaboration and communication. Staying informed about new trends and integrating security measures early are also common challenges.

What are effective problem-solving techniques for software developers?

Effective problem-solving techniques for software developers include debugging methods like rubber duck debugging, critical thinking approaches like Socratic questioning, and utilizing problem-solving models like the POLYA method. It is essential to improve analytical skills, creativity, and logical reasoning, grasp algorithms and data structures knowledge, and follow strategies like breaking down problems, writing pseudocode, seeking patterns, and iterative testing.

How can problem-solving techniques be applied in real-world software development?

Problem-solving techniques can be applied in real-world software development scenarios by methods such as systematic profiling and performance tuning for software efficiency, innovative approaches like priority scheduling to manage resources effectively, collaborative methods like pair programming for complex problem-solving and improved quality, and using real-world inspiration for designing algorithms. Innovative integration of technologies like machine learning for data handling also showcases the practical application of problem-solving techniques.

What are the benefits of mastering problem-solving techniques for software developers?

Mastering problem-solving techniques opens up increased job opportunities in diverse programming environments, negotiation leverage for higher compensation, prospects for professional growth and ascension to leadership roles, and a networking edge through innovative solutions. Problem-solving skills are highly valued by employers, leading to premium salaries, job security, and retention by tech companies aiming to foster innovation and efficiency in their teams.

You may be interested in the following topics as well:

Master the art of problem-solving in tech by elevating your critical thinking approach.

Discover the importance of collaboration skills in thriving tech ecosystems.

Embrace the dynamic Agile approach and stay ahead in the ever-evolving field of software development.

Uncover the Five Components of Emotional Intelligence and see how they impact your career in technology.

Understand how a productive tech team leverages exceptional communication to streamline success.

Employ effective balancing strategies to ensure a smooth workflow between solitary coding and team tasks.

Chevas Balloun

Director of Marketing & Brand

Chevas has spent over 15 years inventing brands, designing interfaces, and driving engagement for companies like Microsoft. He is a practiced writer, a productivity app inventor, board game designer, and has a builder-mentality drives entrepreneurship.

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4 steps to solving any software problem

Problem-solving is a key skill for students, new programmers, and those who work with them.

I’ve noticed a gap in technical education which oddly coincides with a skill all software developers are expected to have: the problem-solving process. I started my software career with a combination of online tutorials and a coding bootcamp, but I’ve heard similar complaints about academic computer science programs.

I’m not saying no one formally teaches these skills, but it seems more common for developers to have to figure them out on their own. Many classic (and controversial ) parts of technical interviews, like whiteboard exercises and “brainteaser” questions, are attempts to test these skills.

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That’s why, whenever I’m helping beginners learn to code, I try to walk them through the process of solving problems in the same way I would at my job. I’d like to articulate those steps here, both for software newbies who are overwhelmed by this whole “coding” thing, and to see how it compares to the process other experienced developers use.

In general, I believe the process of solving a software development problem can be divided into four steps:

• Identify the problem
• Gather information

Iterate potential solutions

Test your solution.

While I’m writing these steps with students and less experienced developers in mind, I hope everyone who works in software will find them a useful reflection on our development process. Programming instructors and anyone who mentors new programmers should make sure their students or mentees have a firm grasp of this process along with any specific technical skills they may need.

What kind of problem?

Note that when I talk about a software development problem, I mean a problem of any size and scope:

• You’re trying to do a very specific thing and you can’t get some piece of it to behave as expected.
• You’re seeing a strange error message and you have no idea what it means.
• You’re trying to figure out some cryptic section of a legacy code base when the original developers have all left the organization.
• You know generally what you want to build, but you have no idea what the individual components of the project will look like.
• You’re trying to decide what software package to use and you don’t know which one is best.
• You know there’s a function to do exactly what you want, but you can’t remember what it’s called.

Identify and understand the problem

This is easier in some cases than in others. Sometimes you get a straightforward error message and you realize you made a simple mistake: a syntax error, forgetting to pass all the variables you need into a function, neglecting to import a package.

On the other hand, sometimes the error is totally baffling. Often a bug won’t present itself with flashing red lights—the program just doesn’t do what you want it to do.

Even when this is the case, you can try your best to articulate the problem. Ask yourself the following questions (and maybe even write down the answers):

• What am I trying to do?
• What have I done already?
• What do I think the program should be doing?
• What is it actually doing?

Gathering information

Sometimes I see people skipping straight to this step without having done the previous one. Examples include:

• Googling Stack Overflow as a first step.
• Copying and pasting code—whether from Stack Overflow, a tutorial, or elsewhere in your codebase—without understanding what it does.

I believe this practice leads to “solving” problems without fully understanding them. That’s not to say any of these resources—Stack Overflow, tutorials, any other examples you find—are bad. But they should be treated as a single tool in your toolbox, not the start and end of the problem-solving process.

How else can you use this toolbox? Think about the kind of information you’re looking for:

• If you know exactly what function, class, or API endpoint you’re using from an external package or service, you can go to the relevant page in its documentation to see all the various options when using it.
• If you’re having problems with an open-source package and you don’t know why, try reading the source code for the relevant feature to make sure it’s doing exactly what you assume it is.
• To get an overview of a new tool or framework, try searching for a tutorial or quickstart guide.
• If you don’t understand why something in your code base is designed the way it is, try looking at the commit history for the relevant file or files—often you can piece together a story of what past developers were trying to do.
• And yes, search engines. Sometimes you know exactly what you want to do but you don’t know what it’s called: “PHP assign two variables.” Sometimes you want ideas on how to do something: “JavaScript shuffle a deck of cards.” And sometimes you just have no idea, but looking at other people’s similar problems can help you figure out what to try next: “Django forms validation not working.” When you do this, try to read any links or relevant documentation you find to get a broader understanding of the issue.

If I’ve been using one of these methods for a while and I don’t seem to be making progress, I’ll often switch to another. I find that a lot of developers I know reach for the search engine first, but for me, intentionally using a variety of methods helps me gain a broader scope of understanding.

Try something. It doesn’t have to be perfect. If you see anything change as a result, that’s a success. You’ll improve on it soon. Then keep trying things until you’ve made substantial progress on the problem.

If you’re in unfamiliar territory, it can help to break down the “solution” into very small increments, and try them out piece by piece. Print your data to the console before you worry about how it’ll be rendered. Call a function you haven’t used before with simple hardcoded arguments, and get it to run as expected before replacing them with the actual data you’ll be using in your application.

This still applies if you’re using someone else’s code from Stack Overflow or a tutorial as an example. Don’t just copy and paste the code into your editor—type out the code line by line. This has two advantages. First, you’re forced to engage with the code and understand it in more detail. Second, you’ll have the chance to update anything that doesn’t translate perfectly to your application. Maybe you can leave out a variable you won’t use; maybe their example uses class Animal and you’re trying to sort Books , so you’d replace a variable called species with one called title .

Sometimes it’s harder to try out what you’re doing after every line of code; that’s ok. The idea is to avoid a situation where you’re typing away at code for hours, only to find that what you created doesn’t work and you have no idea why. Try to find a middle ground, and get to results you can see within a relatively short amount of time.

If you iterate like this for a long time and don’t seem to be getting anywhere, maybe it’s time to start back at step one and try something different. But if you can get something to work, even if it’s not exactly what you had in mind, now’s a good time to move on to the next step.

Often we do this by hand: load a web page and check that it contains all the elements we expect it to render. Try replicating the conditions that led to a bug, and confirm that the bug no longer happens. Try using the feature we added in a few different ways and see what happens.

Another way we do this is with automated tests. Adding a test that asserts a feature works as predicted or a bug no longer occurs helps prevent unexpected problems down the line.

Test-driven development is an alternate approach that starts with this step rather than leaving it to the end. For each change you make to your project, you start by writing a test that asserts the change will work as predicted, then make the change.

One advantage to the test-driven approach is that it forces you to think about what success means before you start working on a given section of the project. This is a good question to ask yourself whether you start by writing a test, write one at the end, or verify your change worked by some other means. It’s part of the first step defined here—identify and understand the problem—because it’s so fundamental to finding a solution.

Even if you are writing automated tests before you add any program code, you’ll be checking that a given portion of work satisfies what you’re trying to do: running the test suite, and trying the feature to make sure it works as expected.

What’s next?

These are the steps I take to solve problems when coding, and the ones I try to impart to students and junior developers when I’m helping them with an issue. I’d like to see more coding education programs—whether in academic computer science, bootcamps, or self-paced tutorials—provide their own instructions on this process. The exact process will depend on the person, the organization, and the work they’re doing—but knowing how to solve problems is a foundational skill to being a programmer. If you work with students or less experienced developers, see what you can do to help them develop this skill.

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A guide to problem-solving techniques, steps, and skills

You might associate problem-solving with the math exercises that a seven-year-old would do at school. But problem-solving isn’t just about math — it’s a crucial skill that helps everyone make better decisions in everyday life or work.

Problem-solving involves finding effective solutions to address complex challenges, in any context they may arise.

Unfortunately, structured and systematic problem-solving methods aren’t commonly taught. Instead, when solving a problem, PMs tend to rely heavily on intuition. While for simple issues this might work well, solving a complex problem with a straightforward solution is often ineffective and can even create more problems.

In this article, you’ll learn a framework for approaching problem-solving, alongside how you can improve your problem-solving skills.

The 7 steps to problem-solving

When it comes to problem-solving there are seven key steps that you should follow: define the problem, disaggregate, prioritize problem branches, create an analysis plan, conduct analysis, synthesis, and communication.

1. Define the problem

Problem-solving begins with a clear understanding of the issue at hand. Without a well-defined problem statement, confusion and misunderstandings can hinder progress. It’s crucial to ensure that the problem statement is outcome-focused, specific, measurable whenever possible, and time-bound.

Additionally, aligning the problem definition with relevant stakeholders and decision-makers is essential to ensure efforts are directed towards addressing the actual problem rather than side issues.

2. Disaggregate

Complex issues often require deeper analysis. Instead of tackling the entire problem at once, the next step is to break it down into smaller, more manageable components.

Various types of logic trees (also known as issue trees or decision trees) can be used to break down the problem. At each stage where new branches are created, it’s important for them to be “MECE” – mutually exclusive and collectively exhaustive. This process of breaking down continues until manageable components are identified, allowing for individual examination.

The decomposition of the problem demands looking at the problem from various perspectives. That is why collaboration within a team often yields more valuable results, as diverse viewpoints lead to a richer pool of ideas and solutions.

3. Prioritize problem branches

The next step involves prioritization. Not all branches of the problem tree have the same impact, so it’s important to understand the significance of each and focus attention on the most impactful areas. Prioritizing helps streamline efforts and minimize the time required to solve the problem.

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4. Create an analysis plan

For prioritized components, you may need to conduct in-depth analysis. Before proceeding, a work plan is created for data gathering and analysis. If work is conducted within a team, having a plan provides guidance on what needs to be achieved, who is responsible for which tasks, and the timelines involved.

5. Conduct analysis

Data gathering and analysis are central to the problem-solving process. It’s a good practice to set time limits for this phase to prevent excessive time spent on perfecting details. You can employ heuristics and rule-of-thumb reasoning to improve efficiency and direct efforts towards the most impactful work.

6. Synthesis

After each individual branch component has been researched, the problem isn’t solved yet. The next step is synthesizing the data logically to address the initial question. The synthesis process and the logical relationship between the individual branch results depend on the logic tree used.

7. Communication

The last step is communicating the story and the solution of the problem to the stakeholders and decision-makers. Clear effective communication is necessary to build trust in the solution and facilitates understanding among all parties involved. It ensures that stakeholders grasp the intricacies of the problem and the proposed solution, leading to informed decision-making.

Exploring problem-solving in various contexts

While problem-solving has traditionally been associated with fields like engineering and science, today it has become a fundamental skill for individuals across all professions. In fact, problem-solving consistently ranks as one of the top skills required by employers.

Problem-solving techniques can be applied in diverse contexts:

• Individuals — What career path should I choose? Where should I live? These are examples of simple and common personal challenges that require effective problem-solving skills
• Organizations — Businesses also face many decisions that are not trivial to answer. Should we expand into new markets this year? How can we enhance the quality of our product development? Will our office accommodate the upcoming year’s growth in terms of capacity?
• Societal issues — The biggest world challenges are also complex problems that can be addressed with the same technique. How can we minimize the impact of climate change? How do we fight cancer?

Despite the variation in domains and contexts, the fundamental approach to solving these questions remains the same. It starts with gaining a clear understanding of the problem, followed by decomposition, conducting analysis of the decomposed branches, and synthesizing it into a result that answers the initial problem.

Real-world examples of problem-solving

Let’s now explore some examples where we can apply the problem solving framework.

Problem: In the production of electronic devices, you observe an increasing number of defects. How can you reduce the error rate and improve the quality?

Before delving into analysis, you can deprioritize branches that you already have information for or ones you deem less important. For instance, while transportation delays may occur, the resulting material degradation is likely negligible. For other branches, additional research and data gathering may be necessary.

Once results are obtained, synthesis is crucial to address the core question: How can you decrease the defect rate?

While all factors listed may play a role, their significance varies. Your task is to prioritize effectively. Through data analysis, you may discover that altering the equipment would bring the most substantial positive outcome. However, executing a solution isn’t always straightforward. In prioritizing, you should consider both the potential impact and the level of effort needed for implementation.

By evaluating impact and effort, you can systematically prioritize areas for improvement, focusing on those with high impact and requiring minimal effort to address. This approach ensures efficient allocation of resources towards improvements that offer the greatest return on investment.

Problem : What should be my next job role?

When breaking down this problem, you need to consider various factors that are important for your future happiness in the role. This includes aspects like the company culture, our interest in the work itself, and the lifestyle that you can afford with the role.

However, not all factors carry the same weight for us. To make sense of the results, we can assign a weight factor to each branch. For instance, passion for the job role may have a weight factor of 1, while interest in the industry may have a weight factor of 0.5, because that is less important for you.

By applying these weights to a specific role and summing the values, you can have an estimate of how suitable that role is for you. Moreover, you can compare two roles and make an informed decision based on these weighted indicators.

Key problem-solving skills

This framework provides the foundation and guidance needed to effectively solve problems. However, successfully applying this framework requires the following:

• Creativity — During the decomposition phase, it’s essential to approach the problem from various perspectives and think outside the box to generate innovative ideas for breaking down the problem tree
• Decision-making — Throughout the process, decisions must be made, even when full confidence is lacking. Employing rules of thumb to simplify analysis or selecting one tree cut over another requires decisiveness and comfort with choices made
• Analytical skills — Analytical and research skills are necessary for the phase following decomposition, involving data gathering and analysis on selected tree branches
• Teamwork — Collaboration and teamwork are crucial when working within a team setting. Solving problems effectively often requires collective effort and shared responsibility
• Communication — Clear and structured communication is essential to convey the problem solution to stakeholders and decision-makers and build trust

How to enhance your problem-solving skills

Problem-solving requires practice and a certain mindset. The more you practice, the easier it becomes. Here are some strategies to enhance your skills:

• Practice structured thinking in your daily life — Break down problems or questions into manageable parts. You don’t need to go through the entire problem-solving process and conduct detailed analysis. When conveying a message, simplify the conversation by breaking the message into smaller, more understandable segments
• Regularly challenging yourself with games and puzzles — Solving puzzles, riddles, or strategy games can boost your problem-solving skills and cognitive agility.
• Engage with individuals from diverse backgrounds and viewpoints — Conversing with people who offer different perspectives provides fresh insights and alternative solutions to problems. This boosts creativity and helps in approaching challenges from new angles

Final thoughts

Problem-solving extends far beyond mathematics or scientific fields; it’s a critical skill for making informed decisions in every area of life and work. The seven-step framework presented here provides a systematic approach to problem-solving, relevant across various domains.

Now, consider this: What’s one question currently on your mind? Grab a piece of paper and try to apply the problem-solving framework. You might uncover fresh insights you hadn’t considered before.

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• Dev Concepts

How to Build and Use Problem-solving Skills [Dev Concepts #41]

Home » News » Dev Concepts » How to Build and Use Problem-solving Skills [Dev Concepts #41]

• Author: Nikol Ruseva
• July 22, 2022
• No Comments
• algorithmicthinking , devconcept , developerskills , logicalthinking , problemsolving , programming , software engineering

To become a skilful developer means not only being familiar with a programming language or software but also having a set of skills that are fundamental to the software development process. These skills can be classified into four groups :

• Coding skills;
• Algorithmic thinking and problem solving skills;
• Fundamental software development concepts;
• Programming languages and software technologies.

Technical Skills

The skill of coding is knowledge of the basic concepts of programming. They are universal and once learned, can be applied in many programming languages. The programming language does not matter to the ability to code.

You need to know how to:

• Use development environments (the so-called IDEs) and developer tools;
• Work with variables and data, calculations, conditional statements, loops and data structures;
• Use functions, methods, classes and objects, programming APIs and libraries;
• Troubleshoot and debug code.

Now that you are familiar with the foundations of programming, you need to put that knowledge together and plan every step of finding a solution to a problem. This will require your algorithmic thinking and problem-solving skills . 

Algorithmic thinking is the ability to break a problem into a logical sequence of steps (called “algorithm”), to find a solution for every step (or break it further into sub-steps) and then assemble these steps into a working solution. 

Algorithmic thinking is similar to logical, engineering, mathematical, abstract, and problem solving. All these concepts are related to the ability to solve problems : to think logically, analyse the problems, and find and implement solutions. Problem solving is a more general skill , while algorithmic thinking is a more technical .

The fundamental computer science and software development concepts include many programming paradigms, essential software development knowledge and skills, and software engineering principles and concepts that developers typically acquire as they gain experience over time.

Some of these knowledge areas and concepts are:

• Object-oriented programming (OOP);
• Functional programming (FP);
• Asynchronous programming ;
• Relational and non-relational databases;
• The concepts behind the Web technologies.

To implement your knowledge you need to be familiar with programming languages, software development technologies, software platforms, software libraries, development frameworks and developer tools.

On the graphic below you can see an example technology stack for a Java developer.

Technologies are ever-changing and evolving , but these four groups of skills described above represent essential and stable knowledge since they will not change significantly over time. In fact, technologies are highly dependent on these skills.

Soft Skills

Soft skills are as important as the ones described above. They include the ability to communicate with people and work in a team which is essential since you as a developer will work on projects with your colleagues. You need to manage your time effectively, to be empathetic , adaptable and creative . Having attention to detail will increase your productivity at work and reduce the chances of error.

Tech Problem Solving

In the IT industry, a tech problem is often an assignment to design and implement a set of functionality which has certain input data and program state and produces output data and program state. 

Every tech problem has a goal . In programming, the goals are to design and write a working code , build an app or software system, which corresponds to the assignment and implement its requirements and functionality. Developers may encounter certain technical difficulties or limitations in designing and implementing the required functionality, like lack of resources, experience or knowledge. The process of problem solving includes finding a way to overcome these difficulties. This can be, for example, learning a new programming language, software library or framework.

Stages of Problem Solving

How to approach a tech problem? You can see in the graphic below seven stages of resolving a problem.

First of all, you need to define the problem. This involves gathering the requirements of the assignment.

After that, you analyse them. Here you should think about constraints, objects, processes and potential obstacles related to the problem. Based on a deeper understanding of the problem, you can extract the important information from the requirements and discard the non-important information, and explore its properties, which will be useful for building a solution.

The next step is to identify several solutions. You try to generate and explore different ideas and technical approaches on how to build a well-working solution. Then you analyse these ideas, their correctness, their strengths and weaknesses, their practical applicability and the costs of their implementation.   

After you have gathered some ideas you need to choose one of them. This is a decision-making process and depends mainly on the requirements, your capabilities and available resources.

After that, you need to plan and describe your actions for executing the chosen solution. You plan your algorithm. Technically, this means to write the definition of several functions, methods or classes, which will implement the chosen idea.

Sometimes planning of the algorithm is done together with its implementation, and there is no clear separation between the stages of algorithm design and algorithm implementation.

Once you have a clearly defined algorithm, you implement it . This means writing code to execute the planned steps. In software development, the implementation process includes also testing and debugging.

The last stage of problem solving is to review the results or test the solution with different input data and conditions. For software problems and apps, you need to perform testing of the code, feature by feature: to check for usual and unusual input data and conditions, check for edge cases and special cases.

Tips for Solving Problems

When it comes to solving a tech problem, the first and foremost important thing is understanding it. Take your time to read and analyse it thoroughly. Do not start to code immediately, because if you have not read the problem carefully, there is a chance of making hasty assumptions about the requirements.

Use a sheet of paper or other visualization tools . This will help you sketch your ideas fast and will improve your logical thinking. Squared paper is preferable. It works best for algorithmic problems. It helps build drawings, diagrams, tables and coordinate systems.

Write down the given input and the required output. For example, if your task is to find all odd numbers of a given array ask yourself some questions:

• What do I have?  →  An array and odd numbers.
• What is an array and how does it work? What is an odd number? What data type should I use to store it?  →  These questions will help you understand the problem .
• What is the end goal? → To filter odd numbers in the array and return it.
• How can I do it?  →  You may have multiple answers to this question and they are your potential solutions . Write them down, compare their advantages and disadvantages and then choose one of them.

After you implement the code test and debug it if needed. Make sure that you have covered all cases . Then look back and try to optimize and simplify your code making it easier to understand.

Lesson Topics

• Technical Skills;
• Soft Skills;
• Definition of a Tech Problem;
• Stages of Problem Solving;
• Tips for Solving Problems.

Lesson Slides

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35 problem-solving techniques and methods for solving complex problems

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All teams and organizations encounter challenges as they grow. There are problems that might occur for teams when it comes to miscommunication or resolving business-critical issues . You may face challenges around growth , design , user engagement, and even team culture and happiness. In short, problem-solving techniques should be part of every team’s skillset.

Problem-solving methods are primarily designed to help a group or team through a process of first identifying problems and challenges , ideating possible solutions , and then evaluating the most suitable .

Finding effective solutions to complex problems isn’t easy, but by using the right process and techniques, you can help your team be more efficient in the process.

So how do you develop strategies that are engaging, and empower your team to solve problems effectively?

In this blog post, we share a series of problem-solving tools you can use in your next workshop or team meeting. You’ll also find some tips for facilitating the process and how to enable others to solve complex problems.

Let’s get started! 

How do you identify problems?

How do you identify the right solution.

• Tips for more effective problem-solving

Complete problem-solving methods

• Problem-solving techniques to identify and analyze problems
• Problem-solving techniques for developing solutions

Problem-solving warm-up activities

Closing activities for a problem-solving process.

Before you can move towards finding the right solution for a given problem, you first need to identify and define the problem you wish to solve. 

Here, you want to clearly articulate what the problem is and allow your group to do the same. Remember that everyone in a group is likely to have differing perspectives and alignment is necessary in order to help the group move forward. 

Identifying a problem accurately also requires that all members of a group are able to contribute their views in an open and safe manner. It can be scary for people to stand up and contribute, especially if the problems or challenges are emotive or personal in nature. Be sure to try and create a psychologically safe space for these kinds of discussions.

Remember that problem analysis and further discussion are also important. Not taking the time to fully analyze and discuss a challenge can result in the development of solutions that are not fit for purpose or do not address the underlying issue.

Successfully identifying and then analyzing a problem means facilitating a group through activities designed to help them clearly and honestly articulate their thoughts and produce usable insight.

With this data, you might then produce a problem statement that clearly describes the problem you wish to be addressed and also state the goal of any process you undertake to tackle this issue.  

Finding solutions is the end goal of any process. Complex organizational challenges can only be solved with an appropriate solution but discovering them requires using the right problem-solving tool.

After you’ve explored a problem and discussed ideas, you need to help a team discuss and choose the right solution. Consensus tools and methods such as those below help a group explore possible solutions before then voting for the best. They’re a great way to tap into the collective intelligence of the group for great results!

Remember that the process is often iterative. Great problem solvers often roadtest a viable solution in a measured way to see what works too. While you might not get the right solution on your first try, the methods below help teams land on the most likely to succeed solution while also holding space for improvement.

Every effective problem solving process begins with an agenda . A well-structured workshop is one of the best methods for successfully guiding a group from exploring a problem to implementing a solution.

In SessionLab, it’s easy to go from an idea to a complete agenda . Start by dragging and dropping your core problem solving activities into place . Add timings, breaks and necessary materials before sharing your agenda with your colleagues.

The resulting agenda will be your guide to an effective and productive problem solving session that will also help you stay organized on the day!

Tips for more effective problem solving

Problem-solving activities are only one part of the puzzle. While a great method can help unlock your team’s ability to solve problems, without a thoughtful approach and strong facilitation the solutions may not be fit for purpose.

Let’s take a look at some problem-solving tips you can apply to any process to help it be a success!

Clearly define the problem

Jumping straight to solutions can be tempting, though without first clearly articulating a problem, the solution might not be the right one. Many of the problem-solving activities below include sections where the problem is explored and clearly defined before moving on.

This is a vital part of the problem-solving process and taking the time to fully define an issue can save time and effort later. A clear definition helps identify irrelevant information and it also ensures that your team sets off on the right track.

Don’t jump to conclusions

It’s easy for groups to exhibit cognitive bias or have preconceived ideas about both problems and potential solutions. Be sure to back up any problem statements or potential solutions with facts, research, and adequate forethought.

The best techniques ask participants to be methodical and challenge preconceived notions. Make sure you give the group enough time and space to collect relevant information and consider the problem in a new way. By approaching the process with a clear, rational mindset, you’ll often find that better solutions are more forthcoming.  

Try different approaches  

Problems come in all shapes and sizes and so too should the methods you use to solve them. If you find that one approach isn’t yielding results and your team isn’t finding different solutions, try mixing it up. You’ll be surprised at how using a new creative activity can unblock your team and generate great solutions.

Don’t take it personally 

Depending on the nature of your team or organizational problems, it’s easy for conversations to get heated. While it’s good for participants to be engaged in the discussions, ensure that emotions don’t run too high and that blame isn’t thrown around while finding solutions.

You’re all in it together, and even if your team or area is seeing problems, that isn’t necessarily a disparagement of you personally. Using facilitation skills to manage group dynamics is one effective method of helping conversations be more constructive.

Get the right people in the room

Your problem-solving method is often only as effective as the group using it. Getting the right people on the job and managing the number of people present is important too!

If the group is too small, you may not get enough different perspectives to effectively solve a problem. If the group is too large, you can go round and round during the ideation stages.

Creating the right group makeup is also important in ensuring you have the necessary expertise and skillset to both identify and follow up on potential solutions. Carefully consider who to include at each stage to help ensure your problem-solving method is followed and positioned for success.

Document everything

The best solutions can take refinement, iteration, and reflection to come out. Get into a habit of documenting your process in order to keep all the learnings from the session and to allow ideas to mature and develop. Many of the methods below involve the creation of documents or shared resources. Be sure to keep and share these so everyone can benefit from the work done!

Bring a facilitator 

Facilitation is all about making group processes easier. With a subject as potentially emotive and important as problem-solving, having an impartial third party in the form of a facilitator can make all the difference in finding great solutions and keeping the process moving. Consider bringing a facilitator to your problem-solving session to get better results and generate meaningful solutions!

Develop your problem-solving skills

It takes time and practice to be an effective problem solver. While some roles or participants might more naturally gravitate towards problem-solving, it can take development and planning to help everyone create better solutions.

You might develop a training program, run a problem-solving workshop or simply ask your team to practice using the techniques below. Check out our post on problem-solving skills to see how you and your group can develop the right mental process and be more resilient to issues too!

Design a great agenda

Workshops are a great format for solving problems. With the right approach, you can focus a group and help them find the solutions to their own problems. But designing a process can be time-consuming and finding the right activities can be difficult.

Check out our workshop planning guide to level-up your agenda design and start running more effective workshops. Need inspiration? Check out templates designed by expert facilitators to help you kickstart your process!

In this section, we’ll look at in-depth problem-solving methods that provide a complete end-to-end process for developing effective solutions. These will help guide your team from the discovery and definition of a problem through to delivering the right solution.

If you’re looking for an all-encompassing method or problem-solving model, these processes are a great place to start. They’ll ask your team to challenge preconceived ideas and adopt a mindset for solving problems more effectively.

• Six Thinking Hats
• Lightning Decision Jam
• Problem Definition Process
• Discovery & Action Dialogue

Design Sprint 2.0

• Open Space Technology

1. Six Thinking Hats

Individual approaches to solving a problem can be very different based on what team or role an individual holds. It can be easy for existing biases or perspectives to find their way into the mix, or for internal politics to direct a conversation.

Six Thinking Hats is a classic method for identifying the problems that need to be solved and enables your team to consider them from different angles, whether that is by focusing on facts and data, creative solutions, or by considering why a particular solution might not work.

Like all problem-solving frameworks, Six Thinking Hats is effective at helping teams remove roadblocks from a conversation or discussion and come to terms with all the aspects necessary to solve complex problems.

2. Lightning Decision Jam

Featured courtesy of Jonathan Courtney of AJ&Smart Berlin, Lightning Decision Jam is one of those strategies that should be in every facilitation toolbox. Exploring problems and finding solutions is often creative in nature, though as with any creative process, there is the potential to lose focus and get lost.

Unstructured discussions might get you there in the end, but it’s much more effective to use a method that creates a clear process and team focus.

In Lightning Decision Jam, participants are invited to begin by writing challenges, concerns, or mistakes on post-its without discussing them before then being invited by the moderator to present them to the group.

From there, the team vote on which problems to solve and are guided through steps that will allow them to reframe those problems, create solutions and then decide what to execute on. 

By deciding the problems that need to be solved as a team before moving on, this group process is great for ensuring the whole team is aligned and can take ownership over the next stages. 

Lightning Decision Jam (LDJ)   #action   #decision making   #problem solving   #issue analysis   #innovation   #design   #remote-friendly   The problem with anything that requires creative thinking is that it’s easy to get lost—lose focus and fall into the trap of having useless, open-ended, unstructured discussions. Here’s the most effective solution I’ve found: Replace all open, unstructured discussion with a clear process. What to use this exercise for: Anything which requires a group of people to make decisions, solve problems or discuss challenges. It’s always good to frame an LDJ session with a broad topic, here are some examples: The conversion flow of our checkout Our internal design process How we organise events Keeping up with our competition Improving sales flow

3. Problem Definition Process

While problems can be complex, the problem-solving methods you use to identify and solve those problems can often be simple in design. 

By taking the time to truly identify and define a problem before asking the group to reframe the challenge as an opportunity, this method is a great way to enable change.

Begin by identifying a focus question and exploring the ways in which it manifests before splitting into five teams who will each consider the problem using a different method: escape, reversal, exaggeration, distortion or wishful. Teams develop a problem objective and create ideas in line with their method before then feeding them back to the group.

This method is great for enabling in-depth discussions while also creating space for finding creative solutions too!

Problem Definition   #problem solving   #idea generation   #creativity   #online   #remote-friendly   A problem solving technique to define a problem, challenge or opportunity and to generate ideas.

4. The 5 Whys 

Sometimes, a group needs to go further with their strategies and analyze the root cause at the heart of organizational issues. An RCA or root cause analysis is the process of identifying what is at the heart of business problems or recurring challenges. 

The 5 Whys is a simple and effective method of helping a group go find the root cause of any problem or challenge and conduct analysis that will deliver results. 

By beginning with the creation of a problem statement and going through five stages to refine it, The 5 Whys provides everything you need to truly discover the cause of an issue.

The 5 Whys   #hyperisland   #innovation   This simple and powerful method is useful for getting to the core of a problem or challenge. As the title suggests, the group defines a problems, then asks the question “why” five times, often using the resulting explanation as a starting point for creative problem solving.

5. World Cafe

World Cafe is a simple but powerful facilitation technique to help bigger groups to focus their energy and attention on solving complex problems.

World Cafe enables this approach by creating a relaxed atmosphere where participants are able to self-organize and explore topics relevant and important to them which are themed around a central problem-solving purpose. Create the right atmosphere by modeling your space after a cafe and after guiding the group through the method, let them take the lead!

Making problem-solving a part of your organization’s culture in the long term can be a difficult undertaking. More approachable formats like World Cafe can be especially effective in bringing people unfamiliar with workshops into the fold. 

World Cafe   #hyperisland   #innovation   #issue analysis   World Café is a simple yet powerful method, originated by Juanita Brown, for enabling meaningful conversations driven completely by participants and the topics that are relevant and important to them. Facilitators create a cafe-style space and provide simple guidelines. Participants then self-organize and explore a set of relevant topics or questions for conversation.

6. Discovery & Action Dialogue (DAD)

One of the best approaches is to create a safe space for a group to share and discover practices and behaviors that can help them find their own solutions.

With DAD, you can help a group choose which problems they wish to solve and which approaches they will take to do so. It’s great at helping remove resistance to change and can help get buy-in at every level too!

This process of enabling frontline ownership is great in ensuring follow-through and is one of the methods you will want in your toolbox as a facilitator.

Discovery & Action Dialogue (DAD)   #idea generation   #liberating structures   #action   #issue analysis   #remote-friendly   DADs make it easy for a group or community to discover practices and behaviors that enable some individuals (without access to special resources and facing the same constraints) to find better solutions than their peers to common problems. These are called positive deviant (PD) behaviors and practices. DADs make it possible for people in the group, unit, or community to discover by themselves these PD practices. DADs also create favorable conditions for stimulating participants’ creativity in spaces where they can feel safe to invent new and more effective practices. Resistance to change evaporates as participants are unleashed to choose freely which practices they will adopt or try and which problems they will tackle. DADs make it possible to achieve frontline ownership of solutions.

7. Design Sprint 2.0

Want to see how a team can solve big problems and move forward with prototyping and testing solutions in a few days? The Design Sprint 2.0 template from Jake Knapp, author of Sprint, is a complete agenda for a with proven results.

Developing the right agenda can involve difficult but necessary planning. Ensuring all the correct steps are followed can also be stressful or time-consuming depending on your level of experience.

Use this complete 4-day workshop template if you are finding there is no obvious solution to your challenge and want to focus your team around a specific problem that might require a shortcut to launching a minimum viable product or waiting for the organization-wide implementation of a solution.

8. Open space technology

Open space technology- developed by Harrison Owen – creates a space where large groups are invited to take ownership of their problem solving and lead individual sessions. Open space technology is a great format when you have a great deal of expertise and insight in the room and want to allow for different takes and approaches on a particular theme or problem you need to be solved.

Start by bringing your participants together to align around a central theme and focus their efforts. Explain the ground rules to help guide the problem-solving process and then invite members to identify any issue connecting to the central theme that they are interested in and are prepared to take responsibility for.

Once participants have decided on their approach to the core theme, they write their issue on a piece of paper, announce it to the group, pick a session time and place, and post the paper on the wall. As the wall fills up with sessions, the group is then invited to join the sessions that interest them the most and which they can contribute to, then you’re ready to begin!

Everyone joins the problem-solving group they’ve signed up to, record the discussion and if appropriate, findings can then be shared with the rest of the group afterward.

Open Space Technology   #action plan   #idea generation   #problem solving   #issue analysis   #large group   #online   #remote-friendly   Open Space is a methodology for large groups to create their agenda discerning important topics for discussion, suitable for conferences, community gatherings and whole system facilitation

Techniques to identify and analyze problems

Using a problem-solving method to help a team identify and analyze a problem can be a quick and effective addition to any workshop or meeting.

While further actions are always necessary, you can generate momentum and alignment easily, and these activities are a great place to get started.

We’ve put together this list of techniques to help you and your team with problem identification, analysis, and discussion that sets the foundation for developing effective solutions.

Let’s take a look!

• The Creativity Dice
• Fishbone Analysis
• Problem Tree
• SWOT Analysis
• Agreement-Certainty Matrix
• The Journalistic Six
• LEGO Challenge
• What, So What, Now What?
• Journalists

Individual and group perspectives are incredibly important, but what happens if people are set in their minds and need a change of perspective in order to approach a problem more effectively?

Flip It is a method we love because it is both simple to understand and run, and allows groups to understand how their perspectives and biases are formed. 

Participants in Flip It are first invited to consider concerns, issues, or problems from a perspective of fear and write them on a flip chart. Then, the group is asked to consider those same issues from a perspective of hope and flip their understanding.  

No problem and solution is free from existing bias and by changing perspectives with Flip It, you can then develop a problem solving model quickly and effectively.

Flip It!   #gamestorming   #problem solving   #action   Often, a change in a problem or situation comes simply from a change in our perspectives. Flip It! is a quick game designed to show players that perspectives are made, not born.

10. The Creativity Dice

One of the most useful problem solving skills you can teach your team is of approaching challenges with creativity, flexibility, and openness. Games like The Creativity Dice allow teams to overcome the potential hurdle of too much linear thinking and approach the process with a sense of fun and speed. 

In The Creativity Dice, participants are organized around a topic and roll a dice to determine what they will work on for a period of 3 minutes at a time. They might roll a 3 and work on investigating factual information on the chosen topic. They might roll a 1 and work on identifying the specific goals, standards, or criteria for the session.

Encouraging rapid work and iteration while asking participants to be flexible are great skills to cultivate. Having a stage for idea incubation in this game is also important. Moments of pause can help ensure the ideas that are put forward are the most suitable. 

The Creativity Dice   #creativity   #problem solving   #thiagi   #issue analysis   Too much linear thinking is hazardous to creative problem solving. To be creative, you should approach the problem (or the opportunity) from different points of view. You should leave a thought hanging in mid-air and move to another. This skipping around prevents premature closure and lets your brain incubate one line of thought while you consciously pursue another.

11. Fishbone Analysis

Organizational or team challenges are rarely simple, and it’s important to remember that one problem can be an indication of something that goes deeper and may require further consideration to be solved.

Fishbone Analysis helps groups to dig deeper and understand the origins of a problem. It’s a great example of a root cause analysis method that is simple for everyone on a team to get their head around. 

Participants in this activity are asked to annotate a diagram of a fish, first adding the problem or issue to be worked on at the head of a fish before then brainstorming the root causes of the problem and adding them as bones on the fish. 

Using abstractions such as a diagram of a fish can really help a team break out of their regular thinking and develop a creative approach.

Fishbone Analysis   #problem solving   ##root cause analysis   #decision making   #online facilitation   A process to help identify and understand the origins of problems, issues or observations.

12. Problem Tree 

Encouraging visual thinking can be an essential part of many strategies. By simply reframing and clarifying problems, a group can move towards developing a problem solving model that works for them. 

In Problem Tree, groups are asked to first brainstorm a list of problems – these can be design problems, team problems or larger business problems – and then organize them into a hierarchy. The hierarchy could be from most important to least important or abstract to practical, though the key thing with problem solving games that involve this aspect is that your group has some way of managing and sorting all the issues that are raised.

Once you have a list of problems that need to be solved and have organized them accordingly, you’re then well-positioned for the next problem solving steps.

Problem tree   #define intentions   #create   #design   #issue analysis   A problem tree is a tool to clarify the hierarchy of problems addressed by the team within a design project; it represents high level problems or related sublevel problems.

13. SWOT Analysis

Chances are you’ve heard of the SWOT Analysis before. This problem-solving method focuses on identifying strengths, weaknesses, opportunities, and threats is a tried and tested method for both individuals and teams.

Start by creating a desired end state or outcome and bare this in mind – any process solving model is made more effective by knowing what you are moving towards. Create a quadrant made up of the four categories of a SWOT analysis and ask participants to generate ideas based on each of those quadrants.

Once you have those ideas assembled in their quadrants, cluster them together based on their affinity with other ideas. These clusters are then used to facilitate group conversations and move things forward. 

SWOT analysis   #gamestorming   #problem solving   #action   #meeting facilitation   The SWOT Analysis is a long-standing technique of looking at what we have, with respect to the desired end state, as well as what we could improve on. It gives us an opportunity to gauge approaching opportunities and dangers, and assess the seriousness of the conditions that affect our future. When we understand those conditions, we can influence what comes next.

14. Agreement-Certainty Matrix

Not every problem-solving approach is right for every challenge, and deciding on the right method for the challenge at hand is a key part of being an effective team.

The Agreement Certainty matrix helps teams align on the nature of the challenges facing them. By sorting problems from simple to chaotic, your team can understand what methods are suitable for each problem and what they can do to ensure effective results. 

If you are already using Liberating Structures techniques as part of your problem-solving strategy, the Agreement-Certainty Matrix can be an invaluable addition to your process. We’ve found it particularly if you are having issues with recurring problems in your organization and want to go deeper in understanding the root cause. 

Agreement-Certainty Matrix   #issue analysis   #liberating structures   #problem solving   You can help individuals or groups avoid the frequent mistake of trying to solve a problem with methods that are not adapted to the nature of their challenge. The combination of two questions makes it possible to easily sort challenges into four categories: simple, complicated, complex , and chaotic .  A problem is simple when it can be solved reliably with practices that are easy to duplicate.  It is complicated when experts are required to devise a sophisticated solution that will yield the desired results predictably.  A problem is complex when there are several valid ways to proceed but outcomes are not predictable in detail.  Chaotic is when the context is too turbulent to identify a path forward.  A loose analogy may be used to describe these differences: simple is like following a recipe, complicated like sending a rocket to the moon, complex like raising a child, and chaotic is like the game “Pin the Tail on the Donkey.”  The Liberating Structures Matching Matrix in Chapter 5 can be used as the first step to clarify the nature of a challenge and avoid the mismatches between problems and solutions that are frequently at the root of chronic, recurring problems.

Organizing and charting a team’s progress can be important in ensuring its success. SQUID (Sequential Question and Insight Diagram) is a great model that allows a team to effectively switch between giving questions and answers and develop the skills they need to stay on track throughout the process. 

Begin with two different colored sticky notes – one for questions and one for answers – and with your central topic (the head of the squid) on the board. Ask the group to first come up with a series of questions connected to their best guess of how to approach the topic. Ask the group to come up with answers to those questions, fix them to the board and connect them with a line. After some discussion, go back to question mode by responding to the generated answers or other points on the board.

It’s rewarding to see a diagram grow throughout the exercise, and a completed SQUID can provide a visual resource for future effort and as an example for other teams.

SQUID   #gamestorming   #project planning   #issue analysis   #problem solving   When exploring an information space, it’s important for a group to know where they are at any given time. By using SQUID, a group charts out the territory as they go and can navigate accordingly. SQUID stands for Sequential Question and Insight Diagram.

16. Speed Boat

To continue with our nautical theme, Speed Boat is a short and sweet activity that can help a team quickly identify what employees, clients or service users might have a problem with and analyze what might be standing in the way of achieving a solution.

Methods that allow for a group to make observations, have insights and obtain those eureka moments quickly are invaluable when trying to solve complex problems.

In Speed Boat, the approach is to first consider what anchors and challenges might be holding an organization (or boat) back. Bonus points if you are able to identify any sharks in the water and develop ideas that can also deal with competitors!   

Speed Boat   #gamestorming   #problem solving   #action   Speedboat is a short and sweet way to identify what your employees or clients don’t like about your product/service or what’s standing in the way of a desired goal.

17. The Journalistic Six

Some of the most effective ways of solving problems is by encouraging teams to be more inclusive and diverse in their thinking.

Based on the six key questions journalism students are taught to answer in articles and news stories, The Journalistic Six helps create teams to see the whole picture. By using who, what, when, where, why, and how to facilitate the conversation and encourage creative thinking, your team can make sure that the problem identification and problem analysis stages of the are covered exhaustively and thoughtfully. Reporter’s notebook and dictaphone optional.

The Journalistic Six – Who What When Where Why How   #idea generation   #issue analysis   #problem solving   #online   #creative thinking   #remote-friendly   A questioning method for generating, explaining, investigating ideas.

18. LEGO Challenge

Now for an activity that is a little out of the (toy) box. LEGO Serious Play is a facilitation methodology that can be used to improve creative thinking and problem-solving skills. 

The LEGO Challenge includes giving each member of the team an assignment that is hidden from the rest of the group while they create a structure without speaking.

What the LEGO challenge brings to the table is a fun working example of working with stakeholders who might not be on the same page to solve problems. Also, it’s LEGO! Who doesn’t love LEGO! 

LEGO Challenge   #hyperisland   #team   A team-building activity in which groups must work together to build a structure out of LEGO, but each individual has a secret “assignment” which makes the collaborative process more challenging. It emphasizes group communication, leadership dynamics, conflict, cooperation, patience and problem solving strategy.

19. What, So What, Now What?

If not carefully managed, the problem identification and problem analysis stages of the problem-solving process can actually create more problems and misunderstandings.

The What, So What, Now What? problem-solving activity is designed to help collect insights and move forward while also eliminating the possibility of disagreement when it comes to identifying, clarifying, and analyzing organizational or work problems. 

Facilitation is all about bringing groups together so that might work on a shared goal and the best problem-solving strategies ensure that teams are aligned in purpose, if not initially in opinion or insight.

Throughout the three steps of this game, you give everyone on a team to reflect on a problem by asking what happened, why it is important, and what actions should then be taken. 

This can be a great activity for bringing our individual perceptions about a problem or challenge and contextualizing it in a larger group setting. This is one of the most important problem-solving skills you can bring to your organization.

W³ – What, So What, Now What?   #issue analysis   #innovation   #liberating structures   You can help groups reflect on a shared experience in a way that builds understanding and spurs coordinated action while avoiding unproductive conflict. It is possible for every voice to be heard while simultaneously sifting for insights and shaping new direction. Progressing in stages makes this practical—from collecting facts about What Happened to making sense of these facts with So What and finally to what actions logically follow with Now What . The shared progression eliminates most of the misunderstandings that otherwise fuel disagreements about what to do. Voila!

20. Journalists  

Problem analysis can be one of the most important and decisive stages of all problem-solving tools. Sometimes, a team can become bogged down in the details and are unable to move forward.

Journalists is an activity that can avoid a group from getting stuck in the problem identification or problem analysis stages of the process.

In Journalists, the group is invited to draft the front page of a fictional newspaper and figure out what stories deserve to be on the cover and what headlines those stories will have. By reframing how your problems and challenges are approached, you can help a team move productively through the process and be better prepared for the steps to follow.

Journalists   #vision   #big picture   #issue analysis   #remote-friendly   This is an exercise to use when the group gets stuck in details and struggles to see the big picture. Also good for defining a vision.

Problem-solving techniques for developing solutions 

The success of any problem-solving process can be measured by the solutions it produces. After you’ve defined the issue, explored existing ideas, and ideated, it’s time to narrow down to the correct solution.

Use these problem-solving techniques when you want to help your team find consensus, compare possible solutions, and move towards taking action on a particular problem.

• Improved Solutions
• Four-Step Sketch
• 15% Solutions
• How-Now-Wow matrix
• Impact Effort Matrix

21. Mindspin  

Brainstorming is part of the bread and butter of the problem-solving process and all problem-solving strategies benefit from getting ideas out and challenging a team to generate solutions quickly. 

With Mindspin, participants are encouraged not only to generate ideas but to do so under time constraints and by slamming down cards and passing them on. By doing multiple rounds, your team can begin with a free generation of possible solutions before moving on to developing those solutions and encouraging further ideation. 

This is one of our favorite problem-solving activities and can be great for keeping the energy up throughout the workshop. Remember the importance of helping people become engaged in the process – energizing problem-solving techniques like Mindspin can help ensure your team stays engaged and happy, even when the problems they’re coming together to solve are complex. 

MindSpin   #teampedia   #idea generation   #problem solving   #action   A fast and loud method to enhance brainstorming within a team. Since this activity has more than round ideas that are repetitive can be ruled out leaving more creative and innovative answers to the challenge.

22. Improved Solutions

After a team has successfully identified a problem and come up with a few solutions, it can be tempting to call the work of the problem-solving process complete. That said, the first solution is not necessarily the best, and by including a further review and reflection activity into your problem-solving model, you can ensure your group reaches the best possible result. 

One of a number of problem-solving games from Thiagi Group, Improved Solutions helps you go the extra mile and develop suggested solutions with close consideration and peer review. By supporting the discussion of several problems at once and by shifting team roles throughout, this problem-solving technique is a dynamic way of finding the best solution. 

Improved Solutions   #creativity   #thiagi   #problem solving   #action   #team   You can improve any solution by objectively reviewing its strengths and weaknesses and making suitable adjustments. In this creativity framegame, you improve the solutions to several problems. To maintain objective detachment, you deal with a different problem during each of six rounds and assume different roles (problem owner, consultant, basher, booster, enhancer, and evaluator) during each round. At the conclusion of the activity, each player ends up with two solutions to her problem.

23. Four Step Sketch

Creative thinking and visual ideation does not need to be confined to the opening stages of your problem-solving strategies. Exercises that include sketching and prototyping on paper can be effective at the solution finding and development stage of the process, and can be great for keeping a team engaged. 

By going from simple notes to a crazy 8s round that involves rapidly sketching 8 variations on their ideas before then producing a final solution sketch, the group is able to iterate quickly and visually. Problem-solving techniques like Four-Step Sketch are great if you have a group of different thinkers and want to change things up from a more textual or discussion-based approach.

Four-Step Sketch   #design sprint   #innovation   #idea generation   #remote-friendly   The four-step sketch is an exercise that helps people to create well-formed concepts through a structured process that includes: Review key information Start design work on paper,  Consider multiple variations , Create a detailed solution . This exercise is preceded by a set of other activities allowing the group to clarify the challenge they want to solve. See how the Four Step Sketch exercise fits into a Design Sprint

24. 15% Solutions

Some problems are simpler than others and with the right problem-solving activities, you can empower people to take immediate actions that can help create organizational change. 

Part of the liberating structures toolkit, 15% solutions is a problem-solving technique that focuses on finding and implementing solutions quickly. A process of iterating and making small changes quickly can help generate momentum and an appetite for solving complex problems.

Problem-solving strategies can live and die on whether people are onboard. Getting some quick wins is a great way of getting people behind the process.   

It can be extremely empowering for a team to realize that problem-solving techniques can be deployed quickly and easily and delineate between things they can positively impact and those things they cannot change. 

15% Solutions   #action   #liberating structures   #remote-friendly   You can reveal the actions, however small, that everyone can do immediately. At a minimum, these will create momentum, and that may make a BIG difference.  15% Solutions show that there is no reason to wait around, feel powerless, or fearful. They help people pick it up a level. They get individuals and the group to focus on what is within their discretion instead of what they cannot change.  With a very simple question, you can flip the conversation to what can be done and find solutions to big problems that are often distributed widely in places not known in advance. Shifting a few grains of sand may trigger a landslide and change the whole landscape.

25. How-Now-Wow Matrix

The problem-solving process is often creative, as complex problems usually require a change of thinking and creative response in order to find the best solutions. While it’s common for the first stages to encourage creative thinking, groups can often gravitate to familiar solutions when it comes to the end of the process. 

When selecting solutions, you don’t want to lose your creative energy! The How-Now-Wow Matrix from Gamestorming is a great problem-solving activity that enables a group to stay creative and think out of the box when it comes to selecting the right solution for a given problem.

Problem-solving techniques that encourage creative thinking and the ideation and selection of new solutions can be the most effective in organisational change. Give the How-Now-Wow Matrix a go, and not just for how pleasant it is to say out loud. 

How-Now-Wow Matrix   #gamestorming   #idea generation   #remote-friendly   When people want to develop new ideas, they most often think out of the box in the brainstorming or divergent phase. However, when it comes to convergence, people often end up picking ideas that are most familiar to them. This is called a ‘creative paradox’ or a ‘creadox’. The How-Now-Wow matrix is an idea selection tool that breaks the creadox by forcing people to weigh each idea on 2 parameters.

26. Impact and Effort Matrix

All problem-solving techniques hope to not only find solutions to a given problem or challenge but to find the best solution. When it comes to finding a solution, groups are invited to put on their decision-making hats and really think about how a proposed idea would work in practice. 

The Impact and Effort Matrix is one of the problem-solving techniques that fall into this camp, empowering participants to first generate ideas and then categorize them into a 2×2 matrix based on impact and effort.

Activities that invite critical thinking while remaining simple are invaluable. Use the Impact and Effort Matrix to move from ideation and towards evaluating potential solutions before then committing to them. 

Impact and Effort Matrix   #gamestorming   #decision making   #action   #remote-friendly   In this decision-making exercise, possible actions are mapped based on two factors: effort required to implement and potential impact. Categorizing ideas along these lines is a useful technique in decision making, as it obliges contributors to balance and evaluate suggested actions before committing to them.

27. Dotmocracy

If you’ve followed each of the problem-solving steps with your group successfully, you should move towards the end of your process with heaps of possible solutions developed with a specific problem in mind. But how do you help a group go from ideation to putting a solution into action? 

Dotmocracy – or Dot Voting -is a tried and tested method of helping a team in the problem-solving process make decisions and put actions in place with a degree of oversight and consensus. 

One of the problem-solving techniques that should be in every facilitator’s toolbox, Dot Voting is fast and effective and can help identify the most popular and best solutions and help bring a group to a decision effectively. 

Dotmocracy   #action   #decision making   #group prioritization   #hyperisland   #remote-friendly   Dotmocracy is a simple method for group prioritization or decision-making. It is not an activity on its own, but a method to use in processes where prioritization or decision-making is the aim. The method supports a group to quickly see which options are most popular or relevant. The options or ideas are written on post-its and stuck up on a wall for the whole group to see. Each person votes for the options they think are the strongest, and that information is used to inform a decision.

All facilitators know that warm-ups and icebreakers are useful for any workshop or group process. Problem-solving workshops are no different.

Use these problem-solving techniques to warm up a group and prepare them for the rest of the process. Activating your group by tapping into some of the top problem-solving skills can be one of the best ways to see great outcomes from your session.

• Check-in/Check-out
• Doodling Together
• Show and Tell
• Constellations
• Draw a Tree

28. Check-in / Check-out

Solid processes are planned from beginning to end, and the best facilitators know that setting the tone and establishing a safe, open environment can be integral to a successful problem-solving process.

Check-in / Check-out is a great way to begin and/or bookend a problem-solving workshop. Checking in to a session emphasizes that everyone will be seen, heard, and expected to contribute. 

If you are running a series of meetings, setting a consistent pattern of checking in and checking out can really help your team get into a groove. We recommend this opening-closing activity for small to medium-sized groups though it can work with large groups if they’re disciplined!

Check-in / Check-out   #team   #opening   #closing   #hyperisland   #remote-friendly   Either checking-in or checking-out is a simple way for a team to open or close a process, symbolically and in a collaborative way. Checking-in/out invites each member in a group to be present, seen and heard, and to express a reflection or a feeling. Checking-in emphasizes presence, focus and group commitment; checking-out emphasizes reflection and symbolic closure.

29. Doodling Together  

Thinking creatively and not being afraid to make suggestions are important problem-solving skills for any group or team, and warming up by encouraging these behaviors is a great way to start. 

Doodling Together is one of our favorite creative ice breaker games – it’s quick, effective, and fun and can make all following problem-solving steps easier by encouraging a group to collaborate visually. By passing cards and adding additional items as they go, the workshop group gets into a groove of co-creation and idea development that is crucial to finding solutions to problems. 

Doodling Together   #collaboration   #creativity   #teamwork   #fun   #team   #visual methods   #energiser   #icebreaker   #remote-friendly   Create wild, weird and often funny postcards together & establish a group’s creative confidence.

30. Show and Tell

You might remember some version of Show and Tell from being a kid in school and it’s a great problem-solving activity to kick off a session.

Asking participants to prepare a little something before a workshop by bringing an object for show and tell can help them warm up before the session has even begun! Games that include a physical object can also help encourage early engagement before moving onto more big-picture thinking.

By asking your participants to tell stories about why they chose to bring a particular item to the group, you can help teams see things from new perspectives and see both differences and similarities in the way they approach a topic. Great groundwork for approaching a problem-solving process as a team! 

Show and Tell   #gamestorming   #action   #opening   #meeting facilitation   Show and Tell taps into the power of metaphors to reveal players’ underlying assumptions and associations around a topic The aim of the game is to get a deeper understanding of stakeholders’ perspectives on anything—a new project, an organizational restructuring, a shift in the company’s vision or team dynamic.

31. Constellations

Who doesn’t love stars? Constellations is a great warm-up activity for any workshop as it gets people up off their feet, energized, and ready to engage in new ways with established topics. It’s also great for showing existing beliefs, biases, and patterns that can come into play as part of your session.

Using warm-up games that help build trust and connection while also allowing for non-verbal responses can be great for easing people into the problem-solving process and encouraging engagement from everyone in the group. Constellations is great in large spaces that allow for movement and is definitely a practical exercise to allow the group to see patterns that are otherwise invisible. 

Constellations   #trust   #connection   #opening   #coaching   #patterns   #system   Individuals express their response to a statement or idea by standing closer or further from a central object. Used with teams to reveal system, hidden patterns, perspectives.

32. Draw a Tree

Problem-solving games that help raise group awareness through a central, unifying metaphor can be effective ways to warm-up a group in any problem-solving model.

Draw a Tree is a simple warm-up activity you can use in any group and which can provide a quick jolt of energy. Start by asking your participants to draw a tree in just 45 seconds – they can choose whether it will be abstract or realistic. 

Once the timer is up, ask the group how many people included the roots of the tree and use this as a means to discuss how we can ignore important parts of any system simply because they are not visible.

All problem-solving strategies are made more effective by thinking of problems critically and by exposing things that may not normally come to light. Warm-up games like Draw a Tree are great in that they quickly demonstrate some key problem-solving skills in an accessible and effective way.

Draw a Tree   #thiagi   #opening   #perspectives   #remote-friendly   With this game you can raise awarness about being more mindful, and aware of the environment we live in.

Each step of the problem-solving workshop benefits from an intelligent deployment of activities, games, and techniques. Bringing your session to an effective close helps ensure that solutions are followed through on and that you also celebrate what has been achieved.

Here are some problem-solving activities you can use to effectively close a workshop or meeting and ensure the great work you’ve done can continue afterward.

• One Breath Feedback
• Who What When Matrix
• Response Cards

How do I conclude a problem-solving process?

All good things must come to an end. With the bulk of the work done, it can be tempting to conclude your workshop swiftly and without a moment to debrief and align. This can be problematic in that it doesn’t allow your team to fully process the results or reflect on the process.

At the end of an effective session, your team will have gone through a process that, while productive, can be exhausting. It’s important to give your group a moment to take a breath, ensure that they are clear on future actions, and provide short feedback before leaving the space. 

The primary purpose of any problem-solving method is to generate solutions and then implement them. Be sure to take the opportunity to ensure everyone is aligned and ready to effectively implement the solutions you produced in the workshop.

Remember that every process can be improved and by giving a short moment to collect feedback in the session, you can further refine your problem-solving methods and see further success in the future too.

33. One Breath Feedback

Maintaining attention and focus during the closing stages of a problem-solving workshop can be tricky and so being concise when giving feedback can be important. It’s easy to incur “death by feedback” should some team members go on for too long sharing their perspectives in a quick feedback round. 

One Breath Feedback is a great closing activity for workshops. You give everyone an opportunity to provide feedback on what they’ve done but only in the space of a single breath. This keeps feedback short and to the point and means that everyone is encouraged to provide the most important piece of feedback to them. 

One breath feedback   #closing   #feedback   #action   This is a feedback round in just one breath that excels in maintaining attention: each participants is able to speak during just one breath … for most people that’s around 20 to 25 seconds … unless of course you’ve been a deep sea diver in which case you’ll be able to do it for longer.

34. Who What When Matrix 

Matrices feature as part of many effective problem-solving strategies and with good reason. They are easily recognizable, simple to use, and generate results.

The Who What When Matrix is a great tool to use when closing your problem-solving session by attributing a who, what and when to the actions and solutions you have decided upon. The resulting matrix is a simple, easy-to-follow way of ensuring your team can move forward. 

Great solutions can’t be enacted without action and ownership. Your problem-solving process should include a stage for allocating tasks to individuals or teams and creating a realistic timeframe for those solutions to be implemented or checked out. Use this method to keep the solution implementation process clear and simple for all involved. 

Who/What/When Matrix   #gamestorming   #action   #project planning   With Who/What/When matrix, you can connect people with clear actions they have defined and have committed to.

35. Response cards

Group discussion can comprise the bulk of most problem-solving activities and by the end of the process, you might find that your team is talked out! 

Providing a means for your team to give feedback with short written notes can ensure everyone is head and can contribute without the need to stand up and talk. Depending on the needs of the group, giving an alternative can help ensure everyone can contribute to your problem-solving model in the way that makes the most sense for them.

Response Cards is a great way to close a workshop if you are looking for a gentle warm-down and want to get some swift discussion around some of the feedback that is raised. 

Response Cards   #debriefing   #closing   #structured sharing   #questions and answers   #thiagi   #action   It can be hard to involve everyone during a closing of a session. Some might stay in the background or get unheard because of louder participants. However, with the use of Response Cards, everyone will be involved in providing feedback or clarify questions at the end of a session.

Save time and effort discovering the right solutions

A structured problem solving process is a surefire way of solving tough problems, discovering creative solutions and driving organizational change. But how can you design for successful outcomes?

With SessionLab, it’s easy to design engaging workshops that deliver results. Drag, drop and reorder blocks  to build your agenda. When you make changes or update your agenda, your session  timing   adjusts automatically , saving you time on manual adjustments.

Collaborating with stakeholders or clients? Share your agenda with a single click and collaborate in real-time. No more sending documents back and forth over email.

Explore  how to use SessionLab  to design effective problem solving workshops or  watch this five minute video  to see the planner in action!

Over to you

The problem-solving process can often be as complicated and multifaceted as the problems they are set-up to solve. With the right problem-solving techniques and a mix of creative exercises designed to guide discussion and generate purposeful ideas, we hope we’ve given you the tools to find the best solutions as simply and easily as possible.

Is there a problem-solving technique that you are missing here? Do you have a favorite activity or method you use when facilitating? Let us know in the comments below, we’d love to hear from you! 

thank you very much for these excellent techniques

Certainly wonderful article, very detailed. Shared!

Your list of techniques for problem solving can be helpfully extended by adding TRIZ to the list of techniques. TRIZ has 40 problem solving techniques derived from methods inventros and patent holders used to get new patents. About 10-12 are general approaches. many organization sponsor classes in TRIZ that are used to solve business problems or general organiztational problems. You can take a look at TRIZ and dwonload a free internet booklet to see if you feel it shound be included per your selection process.

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How to Improve Problem-Solving Skills as a Software Developer with SkillReactor

There’s more to software development than writing lines of code. In the first place, software developers exist to build applications that meet users’ needs. Netflix, for instance, was built to provide a steady stream of accessible entertainment to the masses. And Airbnb was created to give travelers the chance to lodge and get to know the local community better.

Put another way, true software developers are problem-solvers first and programmers second. Yet problem-solving is often the most overlooked skill among software developers . Too focused on gaining theoretical knowledge of various programming languages and frameworks, software developers today often forget to work out their problem-solving muscles.

One reason behind this is the abundance of programming videos, tutorials, books, and other learning resources available online, many of which use a spoonfeeding approach in teaching. As a result, students get lost when faced with real-world problems, unaware of where to start and how to apply the coding theories they learned. Where do they go from here?

Enter, SkillReactor .

SkillReactor helps software developers improve their coding skills and sharpens the highly underrated skill of problem-solving. How? Through its online learning platform, SkillIntern, users encounter short coding tasks that challenge them to diagnose and solve real-world industry problems.

Read on as we explore SkillReactor’s approach to training well-rounded software developers. You’ll also hear from Ryan Bell , SkillReactor’s Lead Engineer.

SkillReactor is a platform that helps deepen your understanding of programming tools and technologies, hone your coding skills, and develop core problem-solving skills vital for success in the tech industry.

How to Improve Problem-Solving Skills as a Coder with SkillReactor

SkillReactor’s approach to training is unique. It moves away from the traditional chalk-and-talk method, where teachers tell students how to code their way out of specific problems. The loophole with that approach is that students never really understand what goes on behind the code and what other methods they could take to approach a given scenario.

So, how does SkillReactor do it? SkillReactor uses the problem-based learning approach. In Ryan’s words, “This learning method helps users develop all necessary skills for software development: exposure to technologies, research and comprehension skills, and most importantly problem-solving.”

How Does SkillReactor’s Problem-Based Learning Approach Work?

As the name implies, SkillReactor’s problem-based learning approach involves presenting users with different challenges they need to solve using their coding skills. These challenges are accessible on SkillReactor’s proprietary learning platform, SkillIntern.

“The user has to analyze the requirements, research possible solutions, and then implement a working solution that fulfills the task’s acceptance criteria,” supplied Ryan.

Users get direction and pointers on the best way to approach the problem on each task, but they do not get an outright solution. Instead, they will use the clue to conduct simple research on Google or other search engines.

The platform also provides an automated validation system that lets users know if their solution is correct. If they input a wrong answer, the system provides feedback on why their response failed and what they need to do to fix it.

“This allows for an iterative approach to development that allows them to try again if they fail quickly,” explained Ryan. “The feedback from the validation allows you to act upon and improve your solution until it meets all requirements. This iterative approach further develops your problem-solving and analysis skills.”

You should also note that the tasks and projects on SkillIntern are industry-standard problems and represent a variety of unique situations you’ll likely face in the workplace. By solving these challenges, you practice your skills and gain firsthand insight into the puzzles that software developers encounter in the workplace.

Build Your Coding Skills

SkillIntern breaks these end-to-end projects into smaller tasks that you can complete with a few lines of code. Breaking large projects into smaller tasks of gradually increasing difficulty will help you better understand core back-end and front-end skills and tools and how they apply to the entire development lifecycle.

“Building a system requires you to first break down the task at hand into a series of smaller, easier to solve problems. Then, we identify the possible solutions for each problem, select the most appropriate solution, and then implement it. In essence, this means that software development is impossible without good problem-solving skills.”

What Do Software Developers Say About SkillReactor?

SkillReactor’s website features feedback from some of its users, and there seems to be no shortage of praises for the platform. Joshua Bins said, “As someone without a computer science background, this SkillReactor program was exactly what I needed to gain experience with developing a full-stack React application.”

Wajeeh Rehman also had positive things to say about his SkillReactor experience. He described SkillReactor to fit programmers of diverse experience, beginners, and experts alike. Having experienced other online courses, he spotted SkillReactor’s uniqueness.

“SkillReactor is not like a typical MOOC or learning platform in which you follow along with an instructor. Instead, you are provided with problems and a roadmap to explore and figure out how to solve them to create a functioning full-stack application. This instills problem-solving skills in beginners, which many severely lack.”

Develop Core Problem-Solving Skills with SkillReactor

SkillReactor is a platform where developers build core skills that improve their understanding of software development skills. Developers can engage in various full-stack software development projects using React, Node.js, TypeScript, and AWS Lambda programming languages.

Becoming a productive engineer also requires lots of practice and experience with independently developing solutions to many different problems. With SkillReactor, developers get that opportunity to hone their skills, gather work experience, and build projects that boost their portfolios.

Want to become a bona fide software developer and problem-solver? Register with SkillReactor today and complete a simple coding test to get started.

About us: Career Karma is a platform designed to help job seekers find, research, and connect with job training programs to advance their careers. Learn about the CK publication .

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Hybrid Approach to Problem Solving: The Knowledge-Based and Exploratory Methods

Introduction to problem-solving techniques.

Table of contents

The knowledge-based approach, the exploratory approach, the hybrid approach, key takeaways.

In the ever-evolving world of software development, problem-solving is a crucial skill. It is not just about finding the right solution, but also about understanding the problem and its context. In this article, we will explore two distinct methods of problem-solving that I've used before and suggest a hybrid approach to them.

The knowledge-based approach to problem-solving is based on crystalized memory. This approach is generally faster as it relies on pre-existing knowledge and solutions. It is like having a well-stocked library at your fingertips, ready to provide you with the answer to common problems.

However, this approach might not be suitable for new problems that aren't part of the background knowledge or are a bit different, making them difficult to recognize. It is like trying to find a specific book in a library that has never been built. You might need to build that library yourself, which is time-consuming and requires a lot of effort.

I am trying to illustrate in the image above the patterns that we just see and recognize, hopefully it won't be too abstract for readers. The geometric shapes in the image represent the patterns of knowledge and problem-solving.

The exploratory approach to problem-solving, on the other hand, involves turning chaos into order 🦞 by exploring the outcomes and understanding the heuristics. This approach is slower and might require some luck, but it provides valuable real-deal experience. It is like exploring a new city without a map, which can be frustrating and confusing, but also exciting and enlightening.

The exploratory approach is more about understanding the problem and its context, rather than just finding the right solution. It is about learning from the process, understanding the outcomes, documenting, and applying the heuristics to future problems.

I am trying to illustrate in the image above simple shapes on the bottom-left, which represent basic knowledge and solutions, to slightly more complex shapes in the middle to the top-right of the image, which represent advanced knowledge and problem-solving techniques. This progression mirrors the learning process, where we start with simple patterns and gradually develop more complex ones as we gain more knowledge and experience.

The hybrid approach to problem-solving begins with the exploratory method, which is especially useful when you have a significant amount of time and the problem at hand is of high importance. In this phase, you solve the problem yourself, diving deep into the problem, understanding its semantics, and breaking it down into smaller, more manageable pieces. This approach is like having a well-stocked library and also exploring a new city without a map.

The exploratory phase is crucial when you can afford it in terms of time. It's akin to conducting a thorough investigation, gathering as much information as possible, and understanding the problem in its entirety. This phase involves research, trial-and-error, asking questions, and testing various hypotheses. It's during this phase that you might interact with AI solutions like ChatGPT to explore potential solutions and understand the design and semantics behind them.

Once you have a solution, you can then compare it with the best solution out there. This is the knowledge-based approach. It's like having a well-stocked library and reading the best books on the topic. You're not just learning about the problem, but also understanding the reasons behind the solution or design. This phase is crucial as it helps you understand the problems that were faced and the solutions that have been provided.

This hybrid approach combines the speed of the knowledge-based approach with the depth of understanding of the exploratory approach. It allows for a more comprehensive understanding of the problem and its solution.

Problem-solving is a crucial skill in software development, requiring an understanding of the problem and its context.

The knowledge-based approach to problem-solving relies on pre-existing knowledge and solutions, making it generally faster but less suitable for new problems.

The exploratory approach involves understanding the problem and its context and learning from the process. It is slower and might require some luck, but provides valuable experience whatever the outcome.

The hybrid approach to problem-solving combines the knowledge-based and exploratory approaches. It begins with the exploratory method, which is especially useful when you have a significant amount of time and the problem at hand is of high importance. After finding a solution, you can then compare it with the best solution out there, which is the knowledge-based approach. This hybrid approach combines the speed of the knowledge-based approach with the depth of understanding of the exploratory approach, allowing for a more comprehensive understanding of the problem and its solution.

The hybrid approach to problem-solving is a powerful tool that combines the exploratory and knowledge-based methods. It allows you to solve problems comprehensively and efficiently, leveraging the best of both worlds. Whether you're dealing with a complex programming task or a personal challenge, this approach can help you find the best solution.

https://youtu.be/UfcAVejslrU 🎶 MUSIC BIT: Problem-solving in software development is not merely about finding solutions, but also about understanding the problem and its context. This exploration is enriched when we incorporate elements from the realm of music, such as the song 'Weightless' by Marconi Union. 'Weightless' is a renowned instrumental track known for its calming effect. It features dreamy synths, soothing melodies, and instrumentation that includes piano, guitar, and electronic samples of natural soundscapes. Scientific research has validated its effectiveness, indicating that it can slow heart rate, reduce blood pressure, and decrease cortisol levels, a hormone released in response to stress . The calming nature of 'Weightless' can be likened to the peace and relaxation we experience when we solve a complex problem. Our journey of problem-solving is filled with ups and downs, but ultimately, we find satisfaction when we find the right solution. In our next meeting in two weeks, keep exploring, keep learning, and find your 'Weightless' moments. Goodbye for now!

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What is root cause analysis (RCA) in software development?

Root cause analysis definition.

Root cause analysis (RCA) is a proven troubleshooting technique used by software development teams to identify and resolve problems at their core, rather than attempting to treat symptoms. Root cause analysis is a structured, step-by-step process designed to seek out primary, underlying causes by gathering and analyzing relevant data and testing solutions that address them.

Why is root cause analysis important?

Root cause analysis is essential in software development because the systematic approach allows teams to troubleshoot more efficiently and develop long-term solutions that prevent issues from recurring. By addressing the root causes of errors and defects, developers can ensure their systems are stable, reliable, and efficient, reducing costly downtime and speeding up the development process. RCA also helps developers prioritize issues based on their impact and severity, empowering them to tackle the most critical problems first.

How to conduct a root cause analysis

Applied as a problem-solving method across industries and disciplines— from science and engineering to manufacturing and healthcare— root cause analysis requires following a specific series of steps to isolate and understand the fundamental factors contributing to a flaw or failure in a system. The steps involved in conducting root cause analysis in software development follow the same universal RCA principles:

• Step 1: Define the problem and set up alerts (if possible) The first step in RCA is to define the problem and make sure it’s clearly understood. This could include setting up alerts to monitor for potential issues like abnormal application behavior, system performance degradation, or security incidents.
• Step 2: Gather and analyze data to determine potential causal factors Once the problem has been defined, the next step is to gather and analyze data. This may include reviewing system logs, application performance metrics, user feedback, and other relevant data sources. The data evaluation should lead to a list of potential causal factors that could be contributing to the problem.
• Step 3: Determine root causes Once the data analysis in Step 2 is complete, use one of several RCA methods to analyze the data and potential causal factors to discover the actual root cause (or causes) of the problem. The root cause analysis should suggest corrective actions.
• Step 4: Implement solutions and document actions After the root cause has been identified, the last step is implementing solutions to address the problem. This may include changes to code, configuration settings, or any number of system adjustments. It’s important to document all actions taken to address the problem to ensure they’re effective and can be repeated if necessary.

Methods and techniques for root cause analysis outside of the software world

There are many useful tools developed to aid in achieving effective RCA. When brainstorming and analyzing potential causes, these methods allow you to visualize and organize information into a usable framework for solving problems. Popular techniques for root cause analysis include:

• 5 Whys The 5 Whys is a problem-solving strategy that helps get to root causes by iterating on “Why” questions until the immediate causes of a problem are identified. When teams ask" why" multiple times, with each question leading logically to the next, it encourages critical thinking and deeper digging, helping to prevent superficial or surface-level solutions.
• Pareto chart A Pareto Chart is a combination bar chart and line chart that maps out the frequency of the most common root causes of problems, starting with the most probable. Based on the Pareto principle, which states that 80% of the effects come from 20% of the causes, the chart lists causes in order of importance and shows the cumulative impact of each, helping teams prioritize the causes that have the most significant impact on the problem.
• Scatter plot diagram A scatter plot diagram uses dots to help teams identify patterns in data that could be contributing to a problem. Plotting two numeric variables on a graph makes it easier to find any correlation between them. The technique can help you quickly identify any significant relationships between variables and identify outliers, which could be the potential causes you're looking for.
• Fishbone diagram Resembling a fish skeleton, this visual tool provides a graphic representation of the factors that could be contributing to a problem, with the head representing the issue and the bones representing the categories of potential causes. It is particularly effective at fostering collaboration among teams and can help lead to a more comprehensive understanding of the problem.
• Failure Mode and Effects Analysis (FMEA) FMEA is a structured, empirical approach that helps to identify potential failures and their effects. It is a systematic method that involves identifying potential failure modes, evaluating their severity, and determining the likelihood of occurrence and detection — then ranking them by their potential risk score. It can help teams focus on the most important issues to tackle first and also help prevent problems before they occur.

Root cause analysis tools for software developers

In the software world, RCA can expose root problems deep in the code. But the use of cloud-native technologies and the complexity of today's modern applications make it increasingly difficult to determine the root cause of issues. Teams can use observability and security tools to achieve powerful RCA results, for example:

Observability Observability provides real-time insight into software performance and behavior through data collection and analysis, allowing you to identify issues and gain visibility into root causes by monitoring metrics, logs, and traces, and through AIOps and observability tools like:

• Machine learning and AIOps Search, visualization, and machine learning can help identify anomalies and surface the root cause of an issue. This can help you make informed decisions and take corrective action quickly.
• Distributed tracing Tracking and analyzing the flow of requests through complex distributed systems with distributed tracing provides insight into the interactions between components and services, which can help identify bottlenecks and other issues that could be causing problems.
• Log pattern analysis Analyzing log patterns and trends generated by applications and infrastructure to identify the root cause of a problem—as well as detect anomalies, errors, and other issues that could be impacting software performance.
• Service dependency mapping By identifying the relationships and dependencies between different components in a system, you can automatically map service dependencies that might be causing issues and understand how changes in one component impact the rest of the system.
• Latency and error correlations Analyzing data related to latency and error rates to identify correlations between the two, you can spot patterns and relationships between errors and performance issues that can help pinpoint root causes.

Security Analyzing security-related data to identify vulnerabilities and weaknesses in the system is an important aspect of root cause analysis. It can help prevent security breaches and other issues that could impact software performance.

• Unsupervised anomaly detection provides an additional layer of defense Comprehensive security requires multiple layers of threat protection. Unsupervised machine learning identifies deviations from normal activity in your data, without having to specify what's abnormal, and can catch attacks that standard approaches to threat hunting are likely to miss.
• Investigating threats and exploring correlations Analyzing security data related to detected events helps determine whether they represent actual threats, or can be ignored. Security analysts recognize malicious activity by looking at patterns in sessions, event timelines, and diagnostic information from hosts.

Common mistakes to avoid with root cause analysis

Root cause analysis can be incredibly effective for identifying and resolving problems, but there are several common mistakes teams should be aware of:

• Lack of data validation: Failing to validate the data used in your analysis can lead to incorrect conclusions and ineffective solutions.
• Selecting solutions as causes: Issues like lack of training and support or budget constraints are rarely the root cause of a problem. They're far more often the solutions. It's critical to dive deeper to trace a problem to its origins.
• Need to find one cause: There can be many contributing factors that lead to a problem, and it's important to identify all of them, rather than landing on one that's convenient.
• Not involving the right people: Valid, truly effective RCA requires input from all relevant stakeholders, including software developers, testers, and business analysts.

Benefits of root cause analysis

The benefits of root cause analysis in software development are enhanced troubleshooting, reduced costs, and greater efficiency — all of which lead to a better product and a happier customer. Root cause analysis is a critical component of software development, helping teams identify the origins of fundamental errors and how to fix them. RCA also allows teams to stop problems from happening again.

• Helps to prevent problems from recurring: RCA enables teams to implement solutions that address root causes rather than just symptoms. By preventing problems from recurring, teams can save time, reduce costs, and improve the overall quality of their software. For example, a software team may notice that a particular feature of an application is consistently crashing. By performing RCA, they might discover the issue stems from a particular set of user inputs that aren’t being handled properly. With this information, they can implement a correct solution that stops the issue in its tracks.
• Improves process efficiency: By identifying root causes, teams can optimize their processes to prevent similar issues from occurring, leading to increased efficiency, reduced downtime, and a more streamlined development process. If a dev team finds their continuous integration pipeline repeatedly failing due to issues with their test suite, they can perform RCA to find out if the problem is slow-running tests causing the pipeline to time out. Now they can optimize their test suite to avoid similar problems in the future.
• Prevents customer dissatisfaction: Root cause analysis helps teams address issues that could impact customer satisfaction. If, for example, a team receives user complaints about a feature being too slow to load, they might use RCA to determine that the issue is a poorly optimized database query. By implementing solutions to prevent that problem from recurring, like optimizing the query to improve performance, they can deliver a more positive user experience. When software consistently meets customer expectations, it goes a long way in building trust and loyalty, which can ultimately lead to increased revenue and long-term growth.

Tips for performing root cause analysis

• Pull information from multiple sources, and understand your data When performing root cause analysis, data quality, visibility, and comprehension are paramount. Elastic offers a solution that consolidates all your data in one system. You get data visualization in Kibana and interactive tools that allow you to dig deep into observability issues and investigate security incidents.
• Get multiple eyes on the data and the problem by working with a team Elastic features extended support for personalized collaboration in Kibana and O11y, helping you streamline workflows and facilitate escalations with your team.
• Take notes Elastic offers streamlined alerts and case management , allowing you to reach insights faster with richer context for your data and visualizations, including sourcing annotations dynamically from Elasticsearch queries in Kibana. For query-based annotations, you also have the ability to manually annotate Kibana Lens visualization with notes.

Root cause analysis with Elastic

The Elasticsearch Platform and its built-in solutions — Elastic Enterprise Search , Elastic Observability , and Elastic Security — act collectively as a jet engine for facilitating root cause analysis. As the most widely deployed solution for transforming metrics, logs, and traces into actionable IT insights — Elastic Observability enables you to unify observability across your entire digital ecosystem. Further, analysts recognized Elastic Security as a leader in security analytics and SIEM.

Specifically, the following capabilities accelerate root cause analysis in its various phases:

• Ingest your data with Elastic Agent and hundreds of integrations .
• Receive automated notifications of potential issues using pre-configured alerts and anomaly detection, effectively putting your monitoring on "auto pilot"
• Apply machine learning and AIOps to process large data sets at scale, with interactive features tailor-made to facilitate RCA for observability, including APM correlations and Explain log rate spikes , and for security investigations with features like Session View , Event timeline , and query hosts for diagnostic information using Osquery .
• Determine causal factors using guided journeys and collaborate on root cause and appropriate solutions to fix and prevent the problems using Elastic case management .

To help your team get the most out of root cause analysis, start a free trial and discover what Elastic can do for you.

Root cause analysis resources

• Root cause analysis for logs
• Automate anomaly detection and accelerate root cause analysis with AIOps
• Why you need AIOps as part of your observability strategy
• Elastic Security for SIEM & security analytics
• Elastic Security for automated threat protection
• Accelerate security investigations with machine learning and interactive root cause analysis in Elastic
• Apply Elastic to root cause analysis in manufacturing
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Nine essential problem solving tools: The ultimate guide to finding a solution

October 26, 2023 by MindManager Blog

Problem solving may unfold differently depending on the industry, or even the department you work in. However, most agree that before you can fix any issue, you need to be clear on what it is, why it’s happening, and what your ideal long-term solution will achieve.

Understanding both the nature and the cause of a problem is the only way to figure out which actions will help you resolve it.

Given that most problem-solving processes are part inspiration and part perspiration, you’ll be more successful if you can reach for a problem solving tool that facilitates collaboration, encourages creative thinking, and makes it easier to implement the fix you devise.

The problem solving tools include three unique categories: problem solving diagrams, problem solving mind maps, and problem solving software solutions.

They include:

• Fishbone diagrams
• Strategy maps
• Mental maps
• Concept maps
• Layered process audit software
• Charting software
• MindManager

In this article, we’ve put together a roundup of versatile problem solving tools and software to help you and your team map out and repair workplace issues as efficiently as possible.

Let’s get started!

Problem solving diagrams

Mapping your way out of a problem is the simplest way to see where you are, and where you need to end up.

Not only do visual problem maps let you plot the most efficient route from Point A (dysfunctional situation) to Point B (flawless process), problem mapping diagrams make it easier to see:

• The root cause of a dilemma.
• The steps, resources, and personnel associated with each possible solution.
• The least time-consuming, most cost-effective options.

A visual problem solving process help to solidify understanding. Furthermore, it’s a great way for you and your team to transform abstract ideas into a practical, reconstructive plan.

Here are three examples of common problem mapping diagrams you can try with your team:

1. Fishbone diagrams

Fishbone diagrams are a common problem solving tool so-named because, once complete, they resemble the skeleton of a fish.

With the possible root causes of an issue (the ribs) branching off from either side of a spine line attached to the head (the problem), dynamic fishbone diagrams let you:

• Lay out a related set of possible reasons for an existing problem
• Investigate each possibility by breaking it out into sub-causes
• See how contributing factors relate to one another

Fishbone diagrams are also known as cause and effect or Ishikawa diagrams.

2. Flowcharts

A flowchart is an easy-to-understand diagram with a variety of applications. But you can use it to outline and examine how the steps of a flawed process connect.

Made up of a few simple symbols linked with arrows indicating workflow direction, flowcharts clearly illustrate what happens at each stage of a process – and how each event impacts other events and decisions.

3. Strategy maps

Frequently used as a strategic planning tool, strategy maps also work well as problem mapping diagrams. Based on a hierarchal system, thoughts and ideas can be arranged on a single page to flesh out a potential resolution.

Once you’ve got a few tactics you feel are worth exploring as possible ways to overcome a challenge, a strategy map will help you establish the best route to your problem-solving goal.

Problem solving mind maps

Problem solving mind maps are especially valuable in visualization. Because they facilitate the brainstorming process that plays a key role in both root cause analysis and the identification of potential solutions, they help make problems more solvable.

Mind maps are diagrams that represent your thinking. Since many people struggle taking or working with hand-written or typed notes, mind maps were designed to let you lay out and structure your thoughts visually so you can play with ideas, concepts, and solutions the same way your brain does.

By starting with a single notion that branches out into greater detail, problem solving mind maps make it easy to:

• Explain unfamiliar problems or processes in less time
• Share and elaborate on novel ideas
• Achieve better group comprehension that can lead to more effective solutions

Mind maps are a valuable problem solving tool because they’re geared toward bringing out the flexible thinking that creative solutions require. Here are three types of problem solving mind maps you can use to facilitate the brainstorming process.

4. Mental maps

A mental map helps you get your thoughts about what might be causing a workplace issue out of your head and onto a shared digital space.

Because mental maps mirror the way our brains take in and analyze new information, using them to describe your theories visually will help you and your team work through and test those thought models.

5. Idea maps

Idea maps let you take advantage of a wide assortment of colors and images to lay down and organize your scattered thought process. Idea maps are ideal brainstorming tools because they allow you to present and explore ideas about the best way to solve a problem collaboratively, and with a shared sense of enthusiasm for outside-the-box thinking.

6. Concept maps

Concept maps are one of the best ways to shape your thoughts around a potential solution because they let you create interlinked, visual representations of intricate concepts.

By laying out your suggested problem-solving process digitally – and using lines to form and define relationship connections – your group will be able to see how each piece of the solution puzzle connects with another.

Problem solving software solutions

Problem solving software is the best way to take advantage of multiple problem solving tools in one platform. While some software programs are geared toward specific industries or processes – like manufacturing or customer relationship management, for example – others, like MindManager , are purpose-built to work across multiple trades, departments, and teams.

Here are three problem-solving software examples.

7. Layered process audit software

Layered process audits (LPAs) help companies oversee production processes and keep an eye on the cost and quality of the goods they create. Dedicated LPA software makes problem solving easier for manufacturers because it helps them see where costly leaks are occurring and allows all levels of management to get involved in repairing those leaks.

8. Charting software

Charting software comes in all shapes and sizes to fit a variety of business sectors. Pareto charts, for example, combine bar charts with line graphs so companies can compare different problems or contributing factors to determine their frequency, cost, and significance. Charting software is often used in marketing, where a variety of bar charts and X-Y axis diagrams make it possible to display and examine competitor profiles, customer segmentation, and sales trends.

9. MindManager

No matter where you work, or what your problem-solving role looks like, MindManager is a problem solving software that will make your team more productive in figuring out why a process, plan, or project isn’t working the way it should.

Once you know why an obstruction, shortfall, or difficulty exists, you can use MindManager’s wide range of brainstorming and problem mapping diagrams to:

• Find the most promising way to correct the situation
• Activate your chosen solution, and
• Conduct regular checks to make sure your repair work is sustainable

MindManager is the ultimate problem solving software.

Not only is it versatile enough to use as your go-to system for puzzling out all types of workplace problems, MindManager’s built-in forecasting tools, timeline charts, and warning indicators let you plan, implement, and monitor your solutions.

By allowing your group to work together more effectively to break down problems, uncover solutions, and rebuild processes and workflows, MindManager’s versatile collection of problem solving tools will help make everyone on your team a more efficient problem solver.

Download a free trial today to get started!

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MindManager helps boost collaboration and productivity among remote and hybrid teams to achieve better results, faster.

Why choose MindManager?

MindManager® helps individuals, teams, and enterprises bring greater clarity and structure to plans, projects, and processes. It provides visual productivity tools and mind mapping software to help take you and your organization to where you want to be.

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