35 problem-solving techniques and methods for solving complex problems

Problem solving workshop

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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!

how to solve complex problems in life

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!

how to solve complex problems in life

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! 

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thank you very much for these excellent techniques

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Overview of the Problem-Solving Mental Process

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

how to solve complex problems in life

Rachel Goldman, PhD FTOS, is a licensed psychologist, clinical assistant professor, speaker, wellness expert specializing in eating behaviors, stress management, and health behavior change.

how to solve complex problems in life

  • Identify the Problem
  • Define the Problem
  • Form a Strategy
  • Organize Information
  • Allocate Resources
  • Monitor Progress
  • Evaluate the Results

Frequently Asked Questions

Problem-solving is a mental process that involves discovering, analyzing, and solving problems. The ultimate goal of problem-solving is to overcome obstacles and find a solution that best resolves the issue.

The best strategy for solving a problem depends largely on the unique situation. In some cases, people are better off learning everything they can about the issue and then using factual knowledge to come up with a solution. In other instances, creativity and insight are the best options.

It is not necessary to follow problem-solving steps sequentially, It is common to skip steps or even go back through steps multiple times until the desired solution is reached.

In order to correctly solve a problem, it is often important to follow a series of steps. Researchers sometimes refer to this as the problem-solving cycle. While this cycle is portrayed sequentially, people rarely follow a rigid series of steps to find a solution.

The following steps include developing strategies and organizing knowledge.

1. Identifying the Problem

While it may seem like an obvious step, identifying the problem is not always as simple as it sounds. In some cases, people might mistakenly identify the wrong source of a problem, which will make attempts to solve it inefficient or even useless.

Some strategies that you might use to figure out the source of a problem include :

  • Asking questions about the problem
  • Breaking the problem down into smaller pieces
  • Looking at the problem from different perspectives
  • Conducting research to figure out what relationships exist between different variables

2. Defining the Problem

After the problem has been identified, it is important to fully define the problem so that it can be solved. You can define a problem by operationally defining each aspect of the problem and setting goals for what aspects of the problem you will address

At this point, you should focus on figuring out which aspects of the problems are facts and which are opinions. State the problem clearly and identify the scope of the solution.

3. Forming a Strategy

After the problem has been identified, it is time to start brainstorming potential solutions. This step usually involves generating as many ideas as possible without judging their quality. Once several possibilities have been generated, they can be evaluated and narrowed down.

The next step is to develop a strategy to solve the problem. The approach used will vary depending upon the situation and the individual's unique preferences. Common problem-solving strategies include heuristics and algorithms.

  • Heuristics are mental shortcuts that are often based on solutions that have worked in the past. They can work well if the problem is similar to something you have encountered before and are often the best choice if you need a fast solution.
  • Algorithms are step-by-step strategies that are guaranteed to produce a correct result. While this approach is great for accuracy, it can also consume time and resources.

Heuristics are often best used when time is of the essence, while algorithms are a better choice when a decision needs to be as accurate as possible.

4. Organizing Information

Before coming up with a solution, you need to first organize the available information. What do you know about the problem? What do you not know? The more information that is available the better prepared you will be to come up with an accurate solution.

When approaching a problem, it is important to make sure that you have all the data you need. Making a decision without adequate information can lead to biased or inaccurate results.

5. Allocating Resources

Of course, we don't always have unlimited money, time, and other resources to solve a problem. Before you begin to solve a problem, you need to determine how high priority it is.

If it is an important problem, it is probably worth allocating more resources to solving it. If, however, it is a fairly unimportant problem, then you do not want to spend too much of your available resources on coming up with a solution.

At this stage, it is important to consider all of the factors that might affect the problem at hand. This includes looking at the available resources, deadlines that need to be met, and any possible risks involved in each solution. After careful evaluation, a decision can be made about which solution to pursue.

6. Monitoring Progress

After selecting a problem-solving strategy, it is time to put the plan into action and see if it works. This step might involve trying out different solutions to see which one is the most effective.

It is also important to monitor the situation after implementing a solution to ensure that the problem has been solved and that no new problems have arisen as a result of the proposed solution.

Effective problem-solvers tend to monitor their progress as they work towards a solution. If they are not making good progress toward reaching their goal, they will reevaluate their approach or look for new strategies .

7. Evaluating the Results

After a solution has been reached, it is important to evaluate the results to determine if it is the best possible solution to the problem. This evaluation might be immediate, such as checking the results of a math problem to ensure the answer is correct, or it can be delayed, such as evaluating the success of a therapy program after several months of treatment.

Once a problem has been solved, it is important to take some time to reflect on the process that was used and evaluate the results. This will help you to improve your problem-solving skills and become more efficient at solving future problems.

A Word From Verywell​

It is important to remember that there are many different problem-solving processes with different steps, and this is just one example. Problem-solving in real-world situations requires a great deal of resourcefulness, flexibility, resilience, and continuous interaction with the environment.

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You can become a better problem solving by:

  • Practicing brainstorming and coming up with multiple potential solutions to problems
  • Being open-minded and considering all possible options before making a decision
  • Breaking down problems into smaller, more manageable pieces
  • Asking for help when needed
  • Researching different problem-solving techniques and trying out new ones
  • Learning from mistakes and using them as opportunities to grow

It's important to communicate openly and honestly with your partner about what's going on. Try to see things from their perspective as well as your own. Work together to find a resolution that works for both of you. Be willing to compromise and accept that there may not be a perfect solution.

Take breaks if things are getting too heated, and come back to the problem when you feel calm and collected. Don't try to fix every problem on your own—consider asking a therapist or counselor for help and insight.

If you've tried everything and there doesn't seem to be a way to fix the problem, you may have to learn to accept it. This can be difficult, but try to focus on the positive aspects of your life and remember that every situation is temporary. Don't dwell on what's going wrong—instead, think about what's going right. Find support by talking to friends or family. Seek professional help if you're having trouble coping.

Davidson JE, Sternberg RJ, editors.  The Psychology of Problem Solving .  Cambridge University Press; 2003. doi:10.1017/CBO9780511615771

Sarathy V. Real world problem-solving .  Front Hum Neurosci . 2018;12:261. Published 2018 Jun 26. doi:10.3389/fnhum.2018.00261

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Bryan Lindsley

How To Solve Complex Problems

In today’s increasingly complex world, we are constantly faced with ill-defined problems that don’t have a clear solution. From poverty and climate change to crime and addiction, complex situations surround us. Unlike simple problems with a pre-defined or “right” answer, complex problems share several basic characteristics that make them hard to solve. While these problems can be frustrating and overwhelming, they also offer an opportunity for growth and creativity. Complex problem-solving skills are the key to addressing these tough issues.

In this article, I will discuss simple versus complex problems, define complex problem solving, and describe why it is so important in complex dynamic environments. I will also explain how to develop problem-solving skills and share some tips for effectively solving complex problems.

How is simple problem-solving different from complex problem-solving?

Solving problems is about getting from a currently undesirable state to an intended goal state. In other words, about bridging the gap between “what is” and “what ought to be”. However, the challenge of reaching a solution varies based on the kind of problem that is being solved. There are generally three different kinds of problems you should consider.

Simple problems have one problem solution. The goal is to find that answer as quickly and efficiently as possible. Puzzles are classic examples of simple problem solving. The objective is to find the one correct solution out of many possibilities.

Puzzles complex problem-solving

Problems are different from puzzles in that they don’t have a known problem solution. As such, many people may agree that there is an issue to be solved, but they may not agree on the intended goal state or how to get there. In this type of problem, people spend a lot of time debating the best solution and the optimal way to achieve it.

Messes are collections of interrelated problems where many stakeholders may not even agree on what the issue is. Unlike problems where there is agreement about what the problem is, in messes, there isn’t agreement amongst stakeholders. In other words, even “what is” can’t be taken for granted. Most complex social problems are messes, made up of interrelated social issues with ill-defined boundaries and goals.

Problems and messes can be complicated or complex

Puzzles are simple, but problems and messes exist on a continuum between complicated and complex. Complicated problems are technical in nature. There may be many involved variables, but the relationships are linear. As a result, complicated problems have step-by-step, systematic solutions. Repairing an engine or building a rocket may be difficult because of the many parts involved, but it is a technical problem we call complicated.

On the other hand, solving a complex problem is entirely different. Unlike complicated problems that may have many variables with linear relationships, a complex problem is characterized by connectivity patterns that are harder to understand and predict.

Characteristics of complex problems and messes

So what else makes a problem complex? Here are seven additional characteristics (from Funke and Hester and Adams ).

  • Lack of information. There is often a lack of data or information about the problem itself. In some cases, variables are unknown or cannot be measured.
  • Many goals. A complex problem has a mix of conflicting objectives. In some sense, every stakeholder involved with the problem may have their own goals. However, with limited resources, not all goals can be simultaneously satisfied.
  • Unpredictable feedback loops. In part due to many variables connected by a range of different relationships, a change in one variable is likely to have effects on other variables in the system. However, because we do not know all of the variables it will affect, small changes can have disproportionate system-wide effects. These unexpected events that have big, unpredictable effects are sometimes called Black Swans.
  • Dynamic. A complex problem changes over time and there is a significant impact based on when you act. In other words, because the problem and its parts and relationships are constantly changing, an action taken today won’t have the same effects as the same action taken tomorrow.
  • Time-delayed. It takes a while for cause and effect to be realized. Thus it is very hard to know if any given intervention is working.
  • Unknown unknowns. Building off the previous point about a lack of information, in a complex problem you may not even know what you don’t know. In other words, there may be very important variables that you are not even aware of.
  • Affected by (error-prone) humans. Simply put, human behavior tends to be illogical and unpredictable. When humans are involved in a problem, avoiding error may be impossible.

What is complex problem-solving?

“Complex problem solving” is the term for how to address a complex problem or messes that have the characteristics listed above.

Since a complex problem is a different phenomenon than a simple or complicated problem, solving them requires a different approach. Methods designed for simple problems, like systematic organization, deductive logic, and linear thinking don’t work well on their own for a complex problem.

And yet, despite its importance, there isn’t complete agreement about what exactly it is.

How is complex problem solving defined by experts?

Let’s look at what scientists, researchers, and system thinkers have come up with in terms of a definition for solving a complex problem. 

As a series of observations and informed decisions

For many employers, the focus is on making smart decisions. These must weigh the future effects to the company of any given solution. According to Indeed.com , it is defined as “a series of observations and informed decisions used to find and implement a solution to a problem. Beyond finding and implementing a solution, complex problem solving also involves considering future changes to circumstance, resources, and capabilities that may affect the trajectory of the process and success of the solution. Complex problem solving also involves considering the impact of the solution on the surrounding environment and individuals.”

As using information to review options and develop solutions

For others, it is more of a systematic way to consider a range of options. According to O*NET ,  the definition focuses on “identifying complex problems and reviewing related information to develop and evaluate options and implement solutions.”

As a self-regulated psychological process

Others emphasize the broad range of skills and emotions needed for change. In addition, they endorse an inspired kind of pragmatism. For example, Dietrich Dorner and Joachim Funke define it as “a collection of self-regulated psychological processes and activities necessary in dynamic environments to achieve ill-defined goals that cannot be reached by routine actions. Creative combinations of knowledge and a broad set of strategies are needed. Solutions are often more bricolage than perfect or optimal. The problem-solving process combines cognitive, emotional, and motivational aspects, particularly in high-stakes situations. Complex problems usually involve knowledge-rich requirements and collaboration among different persons.”

As a novel way of thinking and reasoning

Finally, some emphasize the multidisciplinary nature of knowledge and processes needed to tackle a complex problem. Patrick Hester and Kevin MacG. Adams have stated that “no single discipline can solve truly complex problems. Problems of real interest, those vexing ones that keep you up at night, require a discipline-agnostic approach…Simply they require us to think systemically about our problem…a novel way of thinking and reasoning about complex problems that encourages increased understanding and deliberate intervention.”

A synthesis definition

By pulling the main themes of these definitions together, we can get a sense of what complex problem-solvers must do:

Gain a better understanding of the phenomena of a complex problem or mess. Use a discipline-agnostic approach in order to develop deliberate interventions. Take into consideration future impacts on the surrounding environment.

Why is complex problem solving important?

Many efforts aimed at complex social problems like reducing homelessness and improving public health – despite good intentions giving more effort than ever before – are destined to fail because their approach is based on simple problem-solving. And some efforts might even unwittingly be contributing to the problems they’re trying to solve. 

Einstein said that “We can’t solve problems by using the same kind of thinking we used when we created them.” I think he could have easily been alluding to the need for more complex problem solvers who think differently. So what skills are required to do this?

What are complex problem-solving skills?

The skills required to solve a complex problem aren’t from one domain, nor are they an easily-packaged bundle. Rather, I like to think of them as a balancing act between a series of seemingly opposite approaches but synthesized. This brings a sort of cognitive dissonance into the process, which is itself informative.

It brings F. Scott Fitzgerald’s maxim to mind: 

“The test of a first-rate intelligence is the ability to hold two opposing ideas in mind at the same time and still retain the ability to function. One should, for example, be able to see that things are hopeless yet be determined to make them otherwise.” 

To see the problem situation clearly, for example, but also with a sense of optimism and possibility.

Here are the top three dialectics to keep in mind:

Thinking and reasoning

Reasoning is the ability to make logical deductions based on evidence and counterevidence. On the other hand, thinking is more about imagining an unknown reality based on thoughts about the whole picture and how the parts could fit together. By thinking clearly, one can have a sense of possibility that prepares the mind to deduce the right action in the unique moment at hand.

As Dorner and Funke explain: “Not every situation requires the same action,  and we may want to act this way or another to reach this or that goal. This appears logical, but it is a logic based on constantly shifting grounds: We cannot know whether necessary conditions are met, sometimes the assumptions we have made later turn out to be incorrect, and sometimes we have to revise our assumptions or make completely new ones. It is necessary to constantly switch between our sense of possibility and our sense of reality, that is, to switch between thinking and reasoning. It is an arduous process, and some people handle it well, while others do not.”

Analysis and reductionism combined with synthesis and holism

It’s important to be able to use scientific processes to break down a complex problem into its parts and analyze them. But at the same time, a complex problem is more than the sum of its parts. In most cases, the relationships between the parts are more important than the parts themselves. Therefore, decomposing problems with rigor isn’t enough. What’s needed, once problems are reduced and understood, is a way of understanding the relationships between various components as well as putting the pieces back together. However, synthesis and holism on their own without deductive analysis can often miss details and relationships that matter.  

What makes this balancing act more difficult is that certain professions tend to be trained in and prefer one domain over the other. Scientists prefer analysis and reductionism whereas most social scientists and practitioners default to synthesis and holism. Unfortunately, this divide of preferences results in people working in their silos at the expense of multi-disciplinary approaches that together can better “see” complexity.

seeing complex problem solving

Situational awareness and self-awareness 

Dual awareness is the ability to pay attention to two experiences simultaneously. In the case of complex problems, context really matters. In other words, problem-solving exists in an ecosystem of environmental factors that are not incidental. Personal and cultural preferences play a part as do current events unfolding over time. But as a problem solver, knowing the environment is only part of the equation. 

The other crucial part is the internal psychological process unique to every individual who also interacts with the problem and the environment. Problem solvers inevitably come into contact with others who may disagree with them, or be advancing seemingly counterproductive solutions, and these interactions result in emotions and motivations. Without self-awareness, we can become attached to our own subjective opinions, fall in love with “our” solutions, and generally be driven by the desire to be seen as problem solvers at the expense of actually solving the problem.

By balancing these three dialectics, practitioners can better deal with uncertainty as well as stay motivated despite setbacks. Self-regulation among these seemingly opposite approaches also reminds one to stay open-minded.

How do you develop complex problem-solving skills?

There is no one answer to this question, as the best way to develop them will vary depending on your strengths and weaknesses. However, there are a few general things that you can do to improve your ability to solve problems.

Ground yourself in theory and knowledge

First, it is important to learn about systems thinking and complexity theories. These frameworks will help you understand how complex systems work, and how different parts of a system interact with each other. This conceptual understanding will allow you to identify potential solutions to problems more quickly and effectively.

Practice switching between approaches

Second, practice switching between the dialectics mentioned above. For example, in your next meeting try to spend roughly half your time thinking and half your time reasoning. The important part is trying to get habituated to regularly switching lenses. It may seem disjointed at first, but after a while, it becomes second nature to simultaneously see how the parts interact and the big picture.

Focus on the specific problem phenomena

Third, it may sound obvious, but people often don’t spend very much time studying the problem itself and how it functions. In some sense, becoming a good problem-solver involves becoming a problem scientist. Your time should be spent regularly investigating the phenomena of “what is” rather than “what ought to be”. A holistic understanding of the problem is the required prerequisite to coming up with good solutions.

Stay curious

Finally, after we have worked on a problem for a while, we tend to think we know everything about it, including how to solve it. Even if we’re working on a problem, which may change dynamically from day to day, we start treating it more like a puzzle with a definite solution. When that happens, we can lose our motivation to continue learning about the problem. This is very risky because it closes the door to learning from others, regardless of whether we completely agree with them or not.

As Neils Bohr said, “Two different perspectives or models about a system will reveal truths regarding the system that are neither entirely independent nor entirely compatible.”

By staying curious, we can retain our ability to learn on a daily basis.

Tips for how to solve complex problems

Focus on processes over results.

It’s easy to get lost in utopian thinking. Many people spend so much time on “what ought to be” that they forget that problem solving is about the gap between “what is” and “what ought to be”. It is said that “life is a journey, not a destination.” The same is true for complex problem-solving. To do it well, a problem solver must focus on enjoying the process of gaining a holistic understanding of the problem. 

Adaptive and iterative methods and tools

A variety of adaptive and iterative methods have been developed to address complexity. They share a laser focus on gaining holistic understanding with tools that best match the phenomena of complexity. They are also non-ideological, trans-disciplinary, and flexible. In most cases, your journey through a set of steps won’t be linear. Rather, as you think and reason, analyze and synthesize, you’ll jump around to get a holistic picture.

adapting complex problem-solving

In my online course , we generally follow a seven-step method:

  • Get clear sight with a complex problem-solving frame
  • Establish a secure base of operation
  • Gain a deep understanding of the problem
  • Create an interactive model of the problem
  • Develop an impact strategy
  • Create an action plan and implement
  • Embed systemic solutions

Of course, each of these steps involves testing to see what works and consistently evaluating our process and progress.

Resolution is about systematically managing a problem over time

One last thing to keep in mind. Most social problems are not just solved one day, never to return. In reality,  most complex problems are managed, not solved. For all practical purposes, what this means is that “the solution” is a way of systematically dealing with the problem over time. Some find this disappointing, but it’s actually a pragmatic pointer to think about resolution – a way move problems in the right direction – rather than final solutions.

Problem solvers regularly train and practice

If you need help developing your complex problem-solving skills, I have an online class where you can learn everything you need to know. 

Sign up today and learn how to be successful at making a difference in the world!

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The psychological steps in solving complex personal problems

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how to solve complex problems in life

Complex personal and interpersonal problems are the main reason students present to counselling. Problems include: failing at studies, health and mental health concerns, relationship breakdowns and conflict, financial uncertainty, traumatic events, loss of meaning and purpose, and grief and loss.

What characterises ‘complex’ problems over everyday issues is that they tend to cause a lot of distress, they tend to hang around (don’t resolve on their own), they impact on multiple areas of a person’s life and they overwhelm our capacity to cope. In fact, the reason people reach out for help is because they feel like they can’t cope with the situation confronting them.

As much as I’d like to promise that you won’t experience such problems in your life, the reality is we will all face such problems at some point. Complex problems and challenges are an inevitable part of life. But there are very few problems that can’t be solved or at least addressed in some way. Even incredibly confronting problems like a severe mental illness, or significant trauma can be managed in positive constructive ways.

Depending on your background, personal experiences and current life situation, you may or may not feel confident in your own ability to confront such problems in your life in an effective way. One good way to improve your ability to cope with challenging situations is through counselling and therapy. Counselling/therapy can provide a guided process, with an expert problem-solver, through which you develop the capacity to self-reflect and make changes.

Another is to engage in self-directed reading and learning. This post falls into that category. This post is for those people who suspect they might not be the best problem solvers, or who want more concrete strategies for moving themselves forward in life during tough times.

Having spent some time reading and reflecting on how we solve problems, I believe there are 4 main components or stages to solving complex personal and interpersonal problems. Understanding and implementing these 4 stages can help make you a better problem solver.

These stages are:

  • Clearly describe your current situation
  • Describe what you would like your life to be like
  • Brainstorm and visualise strategies to get you from where you are to where you want to be
  • Implement and monitor those strategies.

Warning: this post is fairly long and explores each of these stages in some depth. I recommend reading it when you have 15-20 minutes to spare 🙂

Describe your current life

Stage 1 – clearly describe your current situation

To solve a complex problem, you need to really understand the problem.

When stuck in a tough place, I find there is a tendency to describe our problems in overly simplistic ways – ‘I am unhappy’, ‘I’m failing at my studies’, ‘my work sucks’, ‘I’ve got no friends’.

I think this is partly a strategy to avoid looking at the issue in detail – which might elicit more distress or a sense of shame or failure. For example, it is less distressing to say ‘my work sucks’ than owning up to the fact that I’ve lost direction and purpose, I’m not getting along with my colleagues and I’m being bullied.

It is also common to use other avoidance strategies when struggling with a complex problem or situation. We might withdraw from our friends and family, tell people ‘I don’t want to talk about it’ or have a few wines each night to try and forget the day. These are fine short-term if the problem will resolve on its own, but to effectively deal with a complex situation that won’t resolve on its own, you will need to take stock of your situation as it stands.

Reflecting, in detail, on your current situation and life can be confronting, so I don’t recommend doing this process whilst highly distressed. High levels of distress can cloud your judgement, prevent meaningful engagement with the process, and often lead to impulsive, poorly thought-out responses.

If you are highly distressed, your first focus should be on safety (‘Am I safe, including from myself?’) and then second, bringing your distress level down. I’m sure you’ve had the same experience as me of being so emotionally overwhelmed by a problem or situation that you can barely think straight. During those moments, your best bet is to prioritise your safety and focus on simple soothing activities. For some this is about connecting with a close friend or family member. For others it is about engaging in some self-soothing activities (e.g. listening to music in bed, hot shower).

However, once you have your distress level down to a reasonable level (and it will come down), some significant life analysis is required. You might do this in one big chunk, or in smaller self-reflective episodes over the course of a week or months. Do it at a pace that suits you.

Your main job is to get a detailed description of your life at present, with a focus on the issues/ problems you are struggling with. To do so, consider your life from a number of different angles.

What is your life like? What does it involve? What does a typical day involve?

What are the main problems you are struggling with? What are the main interactions or situations that are troubling you?

What impact are these problems having on your life. How is your mood, your energy levels, your overall health?

Who are the main people in your life and how are they intertwined in these problems? Are other people in your life also being affected by these problems?

How did the problems develop? What is the relevant history? How did the problems come to be? What role did you, others, or ‘fate’ plan in the development of the problem? What aspects of you (e.g. personality, ability, thoughts, beliefs, feelings, reactions) are contributing to the problem?

How urgent is it that you solve these problems and why? Will these problems resolve on its own? If not, why?

What things have you tried to address the problem? Which things seemed to work? Which didn’t? Which ones did you only try half-heartedly?

What are you procrastinating on? If you haven’t taken any action on the problem to date, why?

As much as possible, break the main problems in your life down into component parts to help you identify what you can change. For example, a problem like ‘I’m depressed’, which is a bit nebulous, might be less overwhelming if broken down into more manageable parts – ‘my mood is low’, ‘I’m no longer exercising’, ‘I’m eating badly’, ‘I’ve not seen my doctor in a while cause I am busy’, ‘my schedule is too packed’, ‘I don’t enjoy my job’, and ‘my neighbour’s dog barks all the time’. Instead of trying to tackle something ill-defined, you will be addressing specific issues.

Generally I find that big issues do break down relatively easily into a set of smaller problems. One of the reasons problems become ‘complex’ is that they are the result of lots of smaller issues interacting to make a bigger problem.

At first it might seem counter-intuitive to break a big problem into parts (“you’ve just given me more things I need to work on”), but the process can actually help you realise that there are parts of the problem that you could realistically start addressing straight away.

A simple guide you can use to determine how far to break a problem down, is to do it until you get to a point where you start to identify smaller problems that you feel reasonably confident you can start working on.

I encourage you to be as honest in this process as possible. The more realistic you are about what is going on in your life, the better placed you will be to start changing it. You don’t need to share the results of your self-reflection with anyone, so you can keep it to yourself.

Having described the main things you are struggling with, then explore what has been getting in the way of you addressing these issues. What are the big barriers stopping you making improvements to your life?

Is it shame about having got yourself into this situation?

Is it your own fears and anxieties – fear of the unknown, fear of getting it wrong, fear of hurting other people, fear of disappointing others

Is it because of a feeling of being defeated?

Is it your own negative self-talk getting in the way (e.g. ‘why bother’, ‘I’m an idiot’, ‘I will never be able to fix it’)?

Is it the actions of others, wittingly or unwittingly getting in your way – or is the source of the problem another person or people?

Is it because you don’t know how to fix the problems?

Is it because you don’t have the resources (e.g. money, time, mental and physical energy) to fix them?

Are you worried that attempting to fix the problems with have other negative outcomes?

Is it something else altogether?

If you identify significant barriers, reframe these as additional problems that will need addressing in Stage 3. The nature of the barriers will give you clues as to what might be required. If the barriers are emotional you might need counselling/therapy or medication. If you don’t have the knowledge required, you might need to engage in further learning. If the barriers are a lack of resources, then your focus might need to be on obtaining those resources. If other people are getting in the way, you might have to strategise how to reduce their influence or get them to change their behaviour.

It is easy in a process like this where the main focus is on problems and barriers, to forget to appropriately acknowledge what is going right or well in your life at the moment. But is important that you do. Focusing on the good things in your life is not some cheap attempt to make you feel better, but very strategic. Specifically, you can leverage these strengths to help you address the issues. For example, you might have been working hard and have saved money, which you can use to support any changes you make. Or it might be that you have developed a strong network of friends whom you can ask for help. Or you might have particular talents or abilities that can be better used to your advantage. Make sure to capture these positives in the process.

I strongly recommend that you write this all stuff down. I base this on the assumption that, if things aren’t great for you at the moment, then your mind and memory aren’t going to be operating at 100%. Asking your brain to juggle all this information, without taking notes is unfair to your brain. If you aren’t a big fan of writing, consider drawing or illustrating the main issues. Regardless, get the details of your life, the main problems, the main barriers, and the things going right, down in some form.

A couple of things to be mindful that might derail the process.

You find yourself laying all the blame squarely at your own feet – Look it is possible that the situation you find yourself in is entirely your fault, but unlikely. Be careful that the process doesn’t degenerate into a self-criticism exercise. Self-criticism is not a very effective space from which to solve problems. Self-compassion is better. Self-compassion still acknowledges that you might be responsible for some aspects of the situation, but does so against a backdrop of ‘common humanity’ and ‘kindness’  – that is, that we all make mistakes, and deserve a chance to rectify those mistakes.

You find yourself blaming everyone else – The opposite situation can also occur where you hold everyone else responsible for your situation. You might even be correct, but be careful not to describe the situation in a way that leaves you with no role to play in improving your own life. If you are just waiting for other people to change, or for things to be more ‘fair’, you might remain stuck in the situation. This doesn’t mean ignoring the bad behaviour of others, but it does mean looking specifically at what you can do to change that behaviour or reduce its impact on your life.

You just find the whole process too hard – if you are not used to reflecting on your own life, then this process is going to be difficult. But persist with it, doing it in small chunks if necessary. If you have a trusted friend, family member or colleague, consider telling them that you are trying to make changes in your life and invite them to help you do this first stage. Or maybe consider seeing a counsellor and doing the process with them. They will be very used to this kind of self-reflection and can guide you.

If this stage goes to plan, you’ll end up with a detailed analysis of what is going wrong and right in your life, with your original problem broken down into potentially more manageable chunks. Don’t be alarmed if the process generates a lot of smaller problems. This is actually a good thing. It means that you’ve meaningfully engaged in the process. The critical output of Stage 1 is a thoughtful analysis of your situation and life. This, as you will see, forms the foundation on which Stages 2-4 are built on.

The final question to ask yourself in this stage is whether you are willing at this point to make an effort to address these problems and make changes in your life. This is an important question. Not taking action is a genuine option, especially if having done the reflection, you believe there are too many barriers to doing so currently. Revisit when you are ready.

make a wish

Stage 2 – describe what you’d like your life to be like

Having spent a significant amount of time describing your life as it is, in Stage 2, you switch gears to focus on describing how you want your life to be.

Driving this process is deceptively simple question taken from Solution Focused Therapy called “The Miracle Question”. The question goes something like this:

Imagine that tonight, whilst you sleep, a miracle happens, and all the things that are going wrong in your life are suddenly fixed. When you wake up tomorrow and start going about your day, how would you know that things had changed. What would be different?

Your job in Stage 2, is to describe, in as much detail as possible, what your life would look like, if the challenges facing you now, were fixed.

What would you be doing? What would a typical day look like? How would you spend your time?

What parts of your current life would be gone? What parts would be changed? What new things would be in your life?

Who would be in your life? What would your interactions with them be like? Who would no longer be in your life?

How do you think you would feel? What kind of person do you think you’d be? What new skills or abilities would you have? What values would you live by?

There are no rules about what to visualise. If you want a life that is just a little bit different than your existing life – that is OK. If you want a life that is drastically or outlandishly different from your existing one, that is OK too. It is even OK to wish for things that are not even possible.

What is important is to consider is why you want each of the things that you describe. Say for example that your vision of the perfect life involves $10 million dollars and a yacht. Ask yourself why those things? You might find that the reason you want $10 million dollars is because you want freedom from financial hardship, and the reason you want a yacht is because you want to explore the world, on your own terms. Consider each element of your vision of the future and what it would provide you at the deeper, conceptual level.

If you find it difficult to imagine a single well-defined future, don’t limit yourself to one. Imagine multiple different futures, all of which you suspect would make you happy and address the main issues you are struggling with at present. Look for commonalities between your different views of the ideal life. For example, you might discover that in all your versions of the ideal life that the things most important to you are good close friends, and engaging hobbies and interests. There will be common themes that connect your different versions of the ideal life.

Another approach is to take each of the problems and challenges you describe in Stage 1 and imagine each of them being fixed magically. What would happen after that? How would your typical day be different from how it is now?

Another way is to consider each of the following areas and what your life would look like in each area: family, marriage/couples/intimate partner, parenting, friends/social life, work, education/training, recreation/fun, spirituality, citizenship/community life, physical self-care (e.g. diet, exercise, sleep).

I personally find this process to be quite energising, but I’ve had people report to me that they find it quite depressing, because it highlights how ‘far away’ they are from their ideal life. If that is you, I encourage you to push through that initial discomfort. Why? Well because that discomfort is blocking you from visualising and hence planning a better life. That discomfort isn’t doing you any favours by doing that. If anything, it is keeping you trapped in your current life. Gently thank that discomfort for showing up, but push through the process of describing the ideal life.

brainstorm and visualise

Stage 3 – brainstorm and visualise all the possible strategies that could move you from your current life to your desired life.

In Stage 3, you are going to start practising a skill that is incredibly valuable, not just in solving problems but in many aspects of life. Put simply, that skill involves being able to outline and visualise the steps you need to take to get from where you are at the moment, to where you want to be.

To illustrate this skill, consider how athletes use visualisation. To win at any sport (as far as I can tell), athletes need to perform complex behavioural routines, done to perfection. For example, a high jumper needs to hone the run up, takeoff, bar clearance and landing in order to do the perfect high jump. In addition to practising multiple actual jumps, athletes can practise these routines in their head, through visualisation. They can rehearse, in incredible detail, every aspect of a jump. Doing so improves their actual jumps. Detailed mental rehearsal or visualisation allows athletes to modify their technique, predict the outcomes of these technique changes, and identify barriers to further improvement.

Your job is to do the same thing in relation to the issues facing you at the moment.

Doing so involves two parts: brainstorming and visualisation.

In the brainstorming part, you are going to take the problems and barriers identified in Stage 1, and try to develop as many ideas/strategies as you can (from the sensible to the ridiculous) for how you might address those problems, with the goal of achieving the life you described in Stage 2.

There are rules to brainstorming:

  • Aim for quantity and diversity of ideas – be imaginative
  • Resist the urge to criticise your ideas
  • Resist the urge to jump too quickly onto an idea
  • Mix and combine ideas freely
  • Include ideas even if they haven’t worked previously, just in case they simply need to be tweaked
  • The more ideas you develop, the more likely it is the successful strategy is in there

Be systematic. Take each problem and barrier and brainstorm strategies for each one.

Make sure your strategies are described behaviourally – by that I mean translate each idea into a specific action or set of actions. For example, your broad idea might be to ‘get treatment for my anxiety’, which you would further break down into: make a GP appointment, write down symptoms, tell GP symptoms, ask for assistance, ask for specific steps to do next, follow those steps. The more concrete the steps you describe, the easier it will be to do the next part.

In the visualisation part, you take each of these strategies and mentally rehearse carrying out the specific actions involved. The more detail you include in your mental rehearsal, the better.

There are a number of reasons to do this mental rehearsal.

  • Regular mental rehearsal increases your motivation to implement the strategy, because you imagine yourself succeeding.
  • Mental rehearsal is a type of practice that will mean you do a better job when you actually carry out the strategy.
  • Mental rehearsal allows you to identify knowledge or skills gaps that will need to be rectified before you carry out the strategy in the real world. For example, imagine that one of your strategies is to ‘approach your boss for a pay rise’. You might never have done this before, so when you go to mentally rehearse it, you realise you don’t really know how to. Addressing this skill deficit (e.g. going online to read about how other people have approached their boss for a pay rise) can get added to your list of strategies.
  • Mental rehearsal allows you to predict possible negative outcomes or consequences of your strategies and plan accordingly. For example, you might mentally rehearse going to see your doctor about your anxiety, and realise he/she might hassle you about other tests that you haven’t had done yet. This allows you to plan an appropriate response.

Don’t limit your visualisation to just successful outcomes, as the visualisation of negative outcomes can help you identify and prepare for the factors that might get in your way. But do focus on repeated visualisation of strategies working well, so you are motivated and feel more confident in actually carrying out the strategies.

In addition to improving performance, visualisation can also help you narrow down your list of strategies from the brainstorming part. This is particularly important if your brainstorming went well and you have way more ideas for improving your life than you can realistically implement. Use visualisation to identify those strategies you think have the greatest likelihood of success. These will be the ones you implement in Stage 4.

I’ll finish this section by noting that visualisation is a strategy that sometimes people ascribe magical qualities to ( e.g. The Secret ). But it isn’t magical. It is just a powerful form of mental rehearsal that activates the parts of the brain that need to be activated in order to carry out the action. If you view visualisation as a way of rehearsing future behaviours, you can use it many different areas of your life. A relevant example as a student, is waking up each day and visualising yourself having a successful day of study.

implement

Part 4 – start implementing the strategies and monitor the outcome

Phew! – this is a long post. If you need to have a toilet break or a quick drink be my guest 🙂

Ready to go? Don’t worry, this is the last section.

Ok, so if you’ve followed the logic of Stages 1-3, you will have a comprehensive description of your life as it stands, what you would like your life to look like, and a collection of strategies you think can move you towards that future. In Stage 4, you start putting these strategies into action.

Start by reviewing the main problems and barriers that you identified in Stage 1. Your first job is to select which of these you will start working on first. I generally recommend focusing your initial efforts on addressing the barriers. With these barriers addressed, you will be in a much better position to address the bigger picture issues.

I also tend to recommend that people start tackling barriers/problems that involve one-off actions (e.g. modify your study load), so you can have some immediate successes (‘wins on the board’), before tackling strategies that might involve establishing a new habit such as regular exercise or a change to your diet.

In this stage you can continue to use visualisation to rehearse the strategies before implementing them. In fact I recommend that you do.

Pacing is important in this stage. Pacing in this context refers to how many things you are trying to change at the same time. Pick too few, and you won’t get the encouragement of significant change. Pick too many, and you’ll be overwhelmed with the logistics of trying to transform your life too quickly. Remember that if you’ve been struggling with complex problems for a while, it might take some time to address these.

[Quick aside: if addressing your issues involves establishing new habits, educate yourself on what it takes to implement a new habit. I’ve written before about Habit Hacks and I also encourage you to pursue the writings of James Clear and BJ Fogg]

If you are implementing strategies for change, you will need to monitor the impacts of these strategies. Are they working? Is your life getting better? This is where all the work you did in Stage 2 becomes important. In that stage you envisioned a better future, in which your problems had been addressed. The core question you want to ask yourself on an ongoing basis is “Does this strategy get me closer to the life I imagined?” If you are moving towards the life you want, then the strategies are working.

Now i’d love to tell you that it will be a perfect straight line from your current life to your ideal life. It probably won’t be.

In fact, it is highly likely that in the process of making changes to your life, things will happen that you didn’t expect or predict. Where possible, treat this like a scientist might treat unusual data arising from an experiment. Use it to update the information in Stages 1-3.

Perhaps your current life changes in a way that makes it far more bearable, in which case you can update your vision of the future.

Perhaps you discover a strength or ability you didn’t know you had, which you can leverage to address your issues.

Maybe you discover that there were additional issues or problems not originally captured in Stage 1.

You might discover a personal need or desire that needs to be addressed in Stage 2.

Barriers might pop up which you didn’t forsee.  

Don’t be discouraged by the fact that you will need to update, or perhaps even radically change the personal self-assessments you did in Stage 1 and 2. It is perfectly normal. My concept of the ideal life is constantly shifting and changing, at least the surface description. The core themes however remain the same: creativity, writing, self-development, ongoing learning.

Also, don’t be surprised if the outcomes of your different strategies don’t match how you visualised them. Again, adopt the approach of a scientist and use this data to update the information developed in Stages 1-3.

Refine your strategies. Address skills gaps by purposefully seeking out professional (e.g. health and allied health professionals) or self-help (e.g. internet). .  help (e.g. professional help or self-help on the internet) or maybe professional help (e.g. health and allied health professionals). Don’t beat yourself up if you don’t get it right the first time. During a period when I was quite sick, I had a lot of doctor’s appointments before I really got good at describing what was happening to me, and asking clearly for what I needed.

Remind yourself regularly that you are moving forward, and even though the direction might change, and the methods to do so might shift over time, that you are consciously and deliberately pushing yourself forward. As you start making changes in your life, this is another place for self-compassion. Solving complex problems can be a messy process, with lots of trial and error and mistakes along the way. Expect this to happen, and don’t be hard on yourself if it doesn’t go to plan. Imagine you were coaching a friend through the process, and remember you would likely treat them with kindness and compassion as they tackled something difficult in their life.

Takeaway message

Solving complex personal and interpersonal problems, whilst challenging, can be assisted by attending to 4 key psychological processes – describing in detail your current life, describing your ideal life, brainstorming and visualising strategies for getting from your current life to your ideal life, and then implementing those strategies and monitoring the outcomes.

The strength of this approach is that it both pushes and pulls you towards a better future. The push comes from understanding what you don’t like about your current life and visualising ways to address it. The pull comes from imagining a better future and feeling it motivate you to change, during times when you might be struggling.

I can’t emphasise enough how important the visualisation component is making important changes in your life. Visualisation is the mechanism through which you will practice connecting how to get from where you are now, to where you want to be. Visualisation is how you identify some of the key barriers to change, prepare for different outcomes, and identify knowledge and skill gaps that you can address. Visualisation is a form of mental gymnastics that you will get better at, the more you try. I’ve started using regular mindfulness practice to improve my ability to visualise .

The final thing to keep in mind is that the process described above whilst self-guided, does not negate seeking professional help. In fact, it would highly complement it. The big difference is that you might be clearer about why you are seeking help, what you hope to get out of it and the nature of the help itself. For example, you might decide to see a counsellor, but instead of it being for a nebulous reason like ‘I’m not very happy’, you would be able to more clearly articulate the help you need (e.g. “I want to learn to be more assertive”).

If you want to connect with other like-minded students who are trying to make improvements in their life, consider joining Oasis Online. Oasis Online is a compendium of wellbeing programs, services, and resources here at Flinders. Also stay tuned to this blog because in 2022 I will be releasing Healthy Habits Hub, a FLO topic dealing specifically with how to improve one’s mental health and academic performance. It draws on many of the ideas discussed in this post.

Otherwise, thank you for taking the time read this very long post.

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Complex Problem Solving: What It Is and What It Is Not

Dietrich dörner.

1 Department of Psychology, University of Bamberg, Bamberg, Germany

Joachim Funke

2 Department of Psychology, Heidelberg University, Heidelberg, Germany

Computer-simulated scenarios have been part of psychological research on problem solving for more than 40 years. The shift in emphasis from simple toy problems to complex, more real-life oriented problems has been accompanied by discussions about the best ways to assess the process of solving complex problems. Psychometric issues such as reliable assessments and addressing correlations with other instruments have been in the foreground of these discussions and have left the content validity of complex problem solving in the background. In this paper, we return the focus to content issues and address the important features that define complex problems.

Succeeding in the 21st century requires many competencies, including creativity, life-long learning, and collaboration skills (e.g., National Research Council, 2011 ; Griffin and Care, 2015 ), to name only a few. One competence that seems to be of central importance is the ability to solve complex problems ( Mainzer, 2009 ). Mainzer quotes the Nobel prize winner Simon (1957) who wrote as early as 1957:

The capacity of the human mind for formulating and solving complex problems is very small compared with the size of the problem whose solution is required for objectively rational behavior in the real world or even for a reasonable approximation to such objective rationality. (p. 198)

The shift from well-defined to ill-defined problems came about as a result of a disillusion with the “general problem solver” ( Newell et al., 1959 ): The general problem solver was a computer software intended to solve all kind of problems that can be expressed through well-formed formulas. However, it soon became clear that this procedure was in fact a “special problem solver” that could only solve well-defined problems in a closed space. But real-world problems feature open boundaries and have no well-determined solution. In fact, the world is full of wicked problems and clumsy solutions ( Verweij and Thompson, 2006 ). As a result, solving well-defined problems and solving ill-defined problems requires different cognitive processes ( Schraw et al., 1995 ; but see Funke, 2010 ).

Well-defined problems have a clear set of means for reaching a precisely described goal state. For example: in a match-stick arithmetic problem, a person receives a false arithmetic expression constructed out of matchsticks (e.g., IV = III + III). According to the instructions, moving one of the matchsticks will make the equations true. Here, both the problem (find the appropriate stick to move) and the goal state (true arithmetic expression; solution is: VI = III + III) are defined clearly.

Ill-defined problems have no clear problem definition, their goal state is not defined clearly, and the means of moving towards the (diffusely described) goal state are not clear. For example: The goal state for solving the political conflict in the near-east conflict between Israel and Palestine is not clearly defined (living in peaceful harmony with each other?) and even if the conflict parties would agree on a two-state solution, this goal again leaves many issues unresolved. This type of problem is called a “complex problem” and is of central importance to this paper. All psychological processes that occur within individual persons and deal with the handling of such ill-defined complex problems will be subsumed under the umbrella term “complex problem solving” (CPS).

Systematic research on CPS started in the 1970s with observations of the behavior of participants who were confronted with computer simulated microworlds. For example, in one of those microworlds participants assumed the role of executives who were tasked to manage a company over a certain period of time (see Brehmer and Dörner, 1993 , for a discussion of this methodology). Today, CPS is an established concept and has even influenced large-scale assessments such as PISA (“Programme for International Student Assessment”), organized by the Organization for Economic Cooperation and Development ( OECD, 2014 ). According to the World Economic Forum, CPS is one of the most important competencies required in the future ( World Economic Forum, 2015 ). Numerous articles on the subject have been published in recent years, documenting the increasing research activity relating to this field. In the following collection of papers we list only those published in 2010 and later: theoretical papers ( Blech and Funke, 2010 ; Funke, 2010 ; Knauff and Wolf, 2010 ; Leutner et al., 2012 ; Selten et al., 2012 ; Wüstenberg et al., 2012 ; Greiff et al., 2013b ; Fischer and Neubert, 2015 ; Schoppek and Fischer, 2015 ), papers about measurement issues ( Danner et al., 2011a ; Greiff et al., 2012 , 2015a ; Alison et al., 2013 ; Gobert et al., 2015 ; Greiff and Fischer, 2013 ; Herde et al., 2016 ; Stadler et al., 2016 ), papers about applications ( Fischer and Neubert, 2015 ; Ederer et al., 2016 ; Tremblay et al., 2017 ), papers about differential effects ( Barth and Funke, 2010 ; Danner et al., 2011b ; Beckmann and Goode, 2014 ; Greiff and Neubert, 2014 ; Scherer et al., 2015 ; Meißner et al., 2016 ; Wüstenberg et al., 2016 ), one paper about developmental effects ( Frischkorn et al., 2014 ), one paper with a neuroscience background ( Osman, 2012 ) 1 , papers about cultural differences ( Güss and Dörner, 2011 ; Sonnleitner et al., 2014 ; Güss et al., 2015 ), papers about validity issues ( Goode and Beckmann, 2010 ; Greiff et al., 2013c ; Schweizer et al., 2013 ; Mainert et al., 2015 ; Funke et al., 2017 ; Greiff et al., 2017 , 2015b ; Kretzschmar et al., 2016 ; Kretzschmar, 2017 ), review papers and meta-analyses ( Osman, 2010 ; Stadler et al., 2015 ), and finally books ( Qudrat-Ullah, 2015 ; Csapó and Funke, 2017b ) and book chapters ( Funke, 2012 ; Hotaling et al., 2015 ; Funke and Greiff, 2017 ; Greiff and Funke, 2017 ; Csapó and Funke, 2017a ; Fischer et al., 2017 ; Molnàr et al., 2017 ; Tobinski and Fritz, 2017 ; Viehrig et al., 2017 ). In addition, a new “Journal of Dynamic Decision Making” (JDDM) has been launched ( Fischer et al., 2015 , 2016 ) to give the field an open-access outlet for research and discussion.

This paper aims to clarify aspects of validity: what should be meant by the term CPS and what not? This clarification seems necessary because misunderstandings in recent publications provide – from our point of view – a potentially misleading picture of the construct. We start this article with a historical review before attempting to systematize different positions. We conclude with a working definition.

Historical Review

The concept behind CPS goes back to the German phrase “komplexes Problemlösen” (CPS; the term “komplexes Problemlösen” was used as a book title by Funke, 1986 ). The concept was introduced in Germany by Dörner and colleagues in the mid-1970s (see Dörner et al., 1975 ; Dörner, 1975 ) for the first time. The German phrase was later translated to CPS in the titles of two edited volumes by Sternberg and Frensch (1991) and Frensch and Funke (1995a) that collected papers from different research traditions. Even though it looks as though the term was coined in the 1970s, Edwards (1962) used the term “dynamic decision making” to describe decisions that come in a sequence. He compared static with dynamic decision making, writing:

  • simple  In dynamic situations, a new complication not found in the static situations arises. The environment in which the decision is set may be changing, either as a function of the sequence of decisions, or independently of them, or both. It is this possibility of an environment which changes while you collect information about it which makes the task of dynamic decision theory so difficult and so much fun. (p. 60)

The ability to solve complex problems is typically measured via dynamic systems that contain several interrelated variables that participants need to alter. Early work (see, e.g., Dörner, 1980 ) used a simulation scenario called “Lohhausen” that contained more than 2000 variables that represented the activities of a small town: Participants had to take over the role of a mayor for a simulated period of 10 years. The simulation condensed these ten years to ten hours in real time. Later, researchers used smaller dynamic systems as scenarios either based on linear equations (see, e.g., Funke, 1993 ) or on finite state automata (see, e.g., Buchner and Funke, 1993 ). In these contexts, CPS consisted of the identification and control of dynamic task environments that were previously unknown to the participants. Different task environments came along with different degrees of fidelity ( Gray, 2002 ).

According to Funke (2012) , the typical attributes of complex systems are (a) complexity of the problem situation which is usually represented by the sheer number of involved variables; (b) connectivity and mutual dependencies between involved variables; (c) dynamics of the situation, which reflects the role of time and developments within a system; (d) intransparency (in part or full) about the involved variables and their current values; and (e) polytely (greek term for “many goals”), representing goal conflicts on different levels of analysis. This mixture of features is similar to what is called VUCA (volatility, uncertainty, complexity, ambiguity) in modern approaches to management (e.g., Mack et al., 2016 ).

In his evaluation of the CPS movement, Sternberg (1995) compared (young) European approaches to CPS with (older) American research on expertise. His analysis of the differences between the European and American traditions shows advantages but also potential drawbacks for each side. He states (p. 301): “I believe that although there are problems with the European approach, it deals with some fundamental questions that American research scarcely addresses.” So, even though the echo of the European approach did not enjoy strong resonance in the US at that time, it was valued by scholars like Sternberg and others. Before attending to validity issues, we will first present a short review of different streams.

Different Approaches to CPS

In the short history of CPS research, different approaches can be identified ( Buchner, 1995 ; Fischer et al., 2017 ). To systematize, we differentiate between the following five lines of research:

  • simple (a) The search for individual differences comprises studies identifying interindividual differences that affect the ability to solve complex problems. This line of research is reflected, for example, in the early work by Dörner et al. (1983) and their “Lohhausen” study. Here, naïve student participants took over the role of the mayor of a small simulated town named Lohhausen for a simulation period of ten years. According to the results of the authors, it is not intelligence (as measured by conventional IQ tests) that predicts performance, but it is the ability to stay calm in the face of a challenging situation and the ability to switch easily between an analytic mode of processing and a more holistic one.
  • simple (b) The search for cognitive processes deals with the processes behind understanding complex dynamic systems. Representative of this line of research is, for example, Berry and Broadbent’s (1984) work on implicit and explicit learning processes when people interact with a dynamic system called “Sugar Production”. They found that those who perform best in controlling a dynamic system can do so implicitly, without explicit knowledge of details regarding the systems’ relations.
  • simple (c) The search for system factors seeks to identify the aspects of dynamic systems that determine the difficulty of complex problems and make some problems harder than others. Representative of this line of research is, for example, work by Funke (1985) , who systematically varied the number of causal effects within a dynamic system or the presence/absence of eigendynamics. He found, for example, that solution quality decreases as the number of systems relations increases.
  • simple (d) The psychometric approach develops measurement instruments that can be used as an alternative to classical IQ tests, as something that goes “beyond IQ”. The MicroDYN approach ( Wüstenberg et al., 2012 ) is representative for this line of research that presents an alternative to reasoning tests (like Raven matrices). These authors demonstrated that a small improvement in predicting school grade point average beyond reasoning is possible with MicroDYN tests.
  • simple (e) The experimental approach explores CPS under different experimental conditions. This approach uses CPS assessment instruments to test hypotheses derived from psychological theories and is sometimes used in research about cognitive processes (see above). Exemplary for this line of research is the work by Rohe et al. (2016) , who test the usefulness of “motto goals” in the context of complex problems compared to more traditional learning and performance goals. Motto goals differ from pure performance goals by activating positive affect and should lead to better goal attainment especially in complex situations (the mentioned study found no effect).

To be clear: these five approaches are not mutually exclusive and do overlap. But the differentiation helps to identify different research communities and different traditions. These communities had different opinions about scaling complexity.

The Race for Complexity: Use of More and More Complex Systems

In the early years of CPS research, microworlds started with systems containing about 20 variables (“Tailorshop”), soon reached 60 variables (“Moro”), and culminated in systems with about 2000 variables (“Lohhausen”). This race for complexity ended with the introduction of the concept of “minimal complex systems” (MCS; Greiff and Funke, 2009 ; Funke and Greiff, 2017 ), which ushered in a search for the lower bound of complexity instead of the higher bound, which could not be defined as easily. The idea behind this concept was that whereas the upper limits of complexity are unbound, the lower limits might be identifiable. Imagine starting with a simple system containing two variables with a simple linear connection between them; then, step by step, increase the number of variables and/or the type of connections. One soon reaches a point where the system can no longer be considered simple and has become a “complex system”. This point represents a minimal complex system. Despite some research having been conducted in this direction, the point of transition from simple to complex has not been identified clearly as of yet.

Some years later, the original “minimal complex systems” approach ( Greiff and Funke, 2009 ) shifted to the “multiple complex systems” approach ( Greiff et al., 2013a ). This shift is more than a slight change in wording: it is important because it taps into the issue of validity directly. Minimal complex systems have been introduced in the context of challenges from large-scale assessments like PISA 2012 that measure new aspects of problem solving, namely interactive problems besides static problem solving ( Greiff and Funke, 2017 ). PISA 2012 required test developers to remain within testing time constraints (given by the school class schedule). Also, test developers needed a large item pool for the construction of a broad class of problem solving items. It was clear from the beginning that MCS deal with simple dynamic situations that require controlled interaction: the exploration and control of simple ticket machines, simple mobile phones, or simple MP3 players (all of these example domains were developed within PISA 2012) – rather than really complex situations like managerial or political decision making.

As a consequence of this subtle but important shift in interpreting the letters MCS, the definition of CPS became a subject of debate recently ( Funke, 2014a ; Greiff and Martin, 2014 ; Funke et al., 2017 ). In the words of Funke (2014b , p. 495):

  • simple  It is funny that problems that nowadays come under the term ‘CPS’, are less complex (in terms of the previously described attributes of complex situations) than at the beginning of this new research tradition. The emphasis on psychometric qualities has led to a loss of variety. Systems thinking requires more than analyzing models with two or three linear equations – nonlinearity, cyclicity, rebound effects, etc. are inherent features of complex problems and should show up at least in some of the problems used for research and assessment purposes. Minimal complex systems run the danger of becoming minimal valid systems.

Searching for minimal complex systems is not the same as gaining insight into the way how humans deal with complexity and uncertainty. For psychometric purposes, it is appropriate to reduce complexity to a minimum; for understanding problem solving under conditions of overload, intransparency, and dynamics, it is necessary to realize those attributes with reasonable strength. This aspect is illustrated in the next section.

Importance of the Validity Issue

The most important reason for discussing the question of what complex problem solving is and what it is not stems from its phenomenology: if we lose sight of our phenomena, we are no longer doing good psychology. The relevant phenomena in the context of complex problems encompass many important aspects. In this section, we discuss four phenomena that are specific to complex problems. We consider these phenomena as critical for theory development and for the construction of assessment instruments (i.e., microworlds). These phenomena require theories for explaining them and they require assessment instruments eliciting them in a reliable way.

The first phenomenon is the emergency reaction of the intellectual system ( Dörner, 1980 ): When dealing with complex systems, actors tend to (a) reduce their intellectual level by decreasing self-reflections, by decreasing their intentions, by stereotyping, and by reducing their realization of intentions, (b) they show a tendency for fast action with increased readiness for risk, with increased violations of rules, and with increased tendency to escape the situation, and (c) they degenerate their hypotheses formation by construction of more global hypotheses and reduced tests of hypotheses, by increasing entrenchment, and by decontextualizing their goals. This phenomenon illustrates the strong connection between cognition, emotion, and motivation that has been emphasized by Dörner (see, e.g., Dörner and Güss, 2013 ) from the beginning of his research tradition; the emergency reaction reveals a shift in the mode of information processing under the pressure of complexity.

The second phenomenon comprises cross-cultural differences with respect to strategy use ( Strohschneider and Güss, 1999 ; Güss and Wiley, 2007 ; Güss et al., 2015 ). Results from complex task environments illustrate the strong influence of context and background knowledge to an extent that cannot be found for knowledge-poor problems. For example, in a comparison between Brazilian and German participants, it turned out that Brazilians accept the given problem descriptions and are more optimistic about the results of their efforts, whereas Germans tend to inquire more about the background of the problems and take a more active approach but are less optimistic (according to Strohschneider and Güss, 1998 , p. 695).

The third phenomenon relates to failures that occur during the planning and acting stages ( Jansson, 1994 ; Ramnarayan et al., 1997 ), illustrating that rational procedures seem to be unlikely to be used in complex situations. The potential for failures ( Dörner, 1996 ) rises with the complexity of the problem. Jansson (1994) presents seven major areas for failures with complex situations: acting directly on current feedback; insufficient systematization; insufficient control of hypotheses and strategies; lack of self-reflection; selective information gathering; selective decision making; and thematic vagabonding.

The fourth phenomenon describes (a lack of) training and transfer effects ( Kretzschmar and Süß, 2015 ), which again illustrates the context dependency of strategies and knowledge (i.e., there is no strategy that is so universal that it can be used in many different problem situations). In their own experiment, the authors could show training effects only for knowledge acquisition, not for knowledge application. Only with specific feedback, performance in complex environments can be increased ( Engelhart et al., 2017 ).

These four phenomena illustrate why the type of complexity (or degree of simplicity) used in research really matters. Furthermore, they demonstrate effects that are specific for complex problems, but not for toy problems. These phenomena direct the attention to the important question: does the stimulus material used (i.e., the computer-simulated microworld) tap and elicit the manifold of phenomena described above?

Dealing with partly unknown complex systems requires courage, wisdom, knowledge, grit, and creativity. In creativity research, “little c” and “BIG C” are used to differentiate between everyday creativity and eminent creativity ( Beghetto and Kaufman, 2007 ; Kaufman and Beghetto, 2009 ). Everyday creativity is important for solving everyday problems (e.g., finding a clever fix for a broken spoke on my bicycle), eminent creativity changes the world (e.g., inventing solar cells for energy production). Maybe problem solving research should use a similar differentiation between “little p” and “BIG P” to mark toy problems on the one side and big societal challenges on the other. The question then remains: what can we learn about BIG P by studying little p? What phenomena are present in both types, and what phenomena are unique to each of the two extremes?

Discussing research on CPS requires reflecting on the field’s research methods. Even if the experimental approach has been successful for testing hypotheses (for an overview of older work, see Funke, 1995 ), other methods might provide additional and novel insights. Complex phenomena require complex approaches to understand them. The complex nature of complex systems imposes limitations on psychological experiments: The more complex the environments, the more difficult is it to keep conditions under experimental control. And if experiments have to be run in labs one should bring enough complexity into the lab to establish the phenomena mentioned, at least in part.

There are interesting options to be explored (again): think-aloud protocols , which have been discredited for many years ( Nisbett and Wilson, 1977 ) and yet are a valuable source for theory testing ( Ericsson and Simon, 1983 ); introspection ( Jäkel and Schreiber, 2013 ), which seems to be banned from psychological methods but nevertheless offers insights into thought processes; the use of life-streaming ( Wendt, 2017 ), a medium in which streamers generate a video stream of think-aloud data in computer-gaming; political decision-making ( Dhami et al., 2015 ) that demonstrates error-proneness in groups; historical case studies ( Dörner and Güss, 2011 ) that give insights into the thinking styles of political leaders; the use of the critical incident technique ( Reuschenbach, 2008 ) to construct complex scenarios; and simulations with different degrees of fidelity ( Gray, 2002 ).

The methods tool box is full of instruments that have to be explored more carefully before any individual instrument receives a ban or research narrows its focus to only one paradigm for data collection. Brehmer and Dörner (1993) discussed the tensions between “research in the laboratory and research in the field”, optimistically concluding “that the new methodology of computer-simulated microworlds will provide us with the means to bridge the gap between the laboratory and the field” (p. 183). The idea behind this optimism was that computer-simulated scenarios would bring more complexity from the outside world into the controlled lab environment. But this is not true for all simulated scenarios. In his paper on simulated environments, Gray (2002) differentiated computer-simulated environments with respect to three dimensions: (1) tractability (“the more training subjects require before they can use a simulated task environment, the less tractable it is”, p. 211), correspondence (“High correspondence simulated task environments simulate many aspects of one task environment. Low correspondence simulated task environments simulate one aspect of many task environments”, p. 214), and engagement (“A simulated task environment is engaging to the degree to which it involves and occupies the participants; that is, the degree to which they agree to take it seriously”, p. 217). But the mere fact that a task is called a “computer-simulated task environment” does not mean anything specific in terms of these three dimensions. This is one of several reasons why we should differentiate between those studies that do not address the core features of CPS and those that do.

What is not CPS?

Even though a growing number of references claiming to deal with complex problems exist (e.g., Greiff and Wüstenberg, 2015 ; Greiff et al., 2016 ), it would be better to label the requirements within these tasks “dynamic problem solving,” as it has been done adequately in earlier work ( Greiff et al., 2012 ). The dynamics behind on-off-switches ( Thimbleby, 2007 ) are remarkable but not really complex. Small nonlinear systems that exhibit stunningly complex and unstable behavior do exist – but they are not used in psychometric assessments of so-called CPS. There are other small systems (like MicroDYN scenarios: Greiff and Wüstenberg, 2014 ) that exhibit simple forms of system behavior that are completely predictable and stable. This type of simple systems is used frequently. It is even offered commercially as a complex problem-solving test called COMPRO ( Greiff and Wüstenberg, 2015 ) for business applications. But a closer look reveals that the label is not used correctly; within COMPRO, the used linear equations are far from being complex and the system can be handled properly by using only one strategy (see for more details Funke et al., 2017 ).

Why do simple linear systems not fall within CPS? At the surface, nonlinear and linear systems might appear similar because both only include 3–5 variables. But the difference is in terms of systems behavior as well as strategies and learning. If the behavior is simple (as in linear systems where more input is related to more output and vice versa), the system can be easily understood (participants in the MicroDYN world have 3 minutes to explore a complex system). If the behavior is complex (as in systems that contain strange attractors or negative feedback loops), things become more complicated and much more observation is needed to identify the hidden structure of the unknown system ( Berry and Broadbent, 1984 ; Hundertmark et al., 2015 ).

Another issue is learning. If tasks can be solved using a single (and not so complicated) strategy, steep learning curves are to be expected. The shift from problem solving to learned routine behavior occurs rapidly, as was demonstrated by Luchins (1942) . In his water jar experiments, participants quickly acquired a specific strategy (a mental set) for solving certain measurement problems that they later continued applying to problems that would have allowed for easier approaches. In the case of complex systems, learning can occur only on very general, abstract levels because it is difficult for human observers to make specific predictions. Routines dealing with complex systems are quite different from routines relating to linear systems.

What should not be studied under the label of CPS are pure learning effects, multiple-cue probability learning, or tasks that can be solved using a single strategy. This last issue is a problem for MicroDYN tasks that rely strongly on the VOTAT strategy (“vary one thing at a time”; see Tschirgi, 1980 ). In real-life, it is hard to imagine a business manager trying to solve her or his problems by means of VOTAT.

What is CPS?

In the early days of CPS research, planet Earth’s dynamics and complexities gained attention through such books as “The limits to growth” ( Meadows et al., 1972 ) and “Beyond the limits” ( Meadows et al., 1992 ). In the current decade, for example, the World Economic Forum (2016) attempts to identify the complexities and risks of our modern world. In order to understand the meaning of complexity and uncertainty, taking a look at the worlds’ most pressing issues is helpful. Searching for strategies to cope with these problems is a difficult task: surely there is no place for the simple principle of “vary-one-thing-at-a-time” (VOTAT) when it comes to global problems. The VOTAT strategy is helpful in the context of simple problems ( Wüstenberg et al., 2014 ); therefore, whether or not VOTAT is helpful in a given problem situation helps us distinguish simple from complex problems.

Because there exist no clear-cut strategies for complex problems, typical failures occur when dealing with uncertainty ( Dörner, 1996 ; Güss et al., 2015 ). Ramnarayan et al. (1997) put together a list of generic errors (e.g., not developing adequate action plans; lack of background control; learning from experience blocked by stereotype knowledge; reactive instead of proactive action) that are typical of knowledge-rich complex systems but cannot be found in simple problems.

Complex problem solving is not a one-dimensional, low-level construct. On the contrary, CPS is a multi-dimensional bundle of competencies existing at a high level of abstraction, similar to intelligence (but going beyond IQ). As Funke et al. (2018) state: “Assessment of transversal (in educational contexts: cross-curricular) competencies cannot be done with one or two types of assessment. The plurality of skills and competencies requires a plurality of assessment instruments.”

There are at least three different aspects of complex systems that are part of our understanding of a complex system: (1) a complex system can be described at different levels of abstraction; (2) a complex system develops over time, has a history, a current state, and a (potentially unpredictable) future; (3) a complex system is knowledge-rich and activates a large semantic network, together with a broad list of potential strategies (domain-specific as well as domain-general).

Complex problem solving is not only a cognitive process but is also an emotional one ( Spering et al., 2005 ; Barth and Funke, 2010 ) and strongly dependent on motivation (low-stakes versus high-stakes testing; see Hermes and Stelling, 2016 ).

Furthermore, CPS is a dynamic process unfolding over time, with different phases and with more differentiation than simply knowledge acquisition and knowledge application. Ideally, the process should entail identifying problems (see Dillon, 1982 ; Lee and Cho, 2007 ), even if in experimental settings, problems are provided to participants a priori . The more complex and open a given situation, the more options can be generated (T. S. Schweizer et al., 2016 ). In closed problems, these processes do not occur in the same way.

In analogy to the difference between formative (process-oriented) and summative (result-oriented) assessment ( Wiliam and Black, 1996 ; Bennett, 2011 ), CPS should not be reduced to the mere outcome of a solution process. The process leading up to the solution, including detours and errors made along the way, might provide a more differentiated impression of a person’s problem-solving abilities and competencies than the final result of such a process. This is one of the reasons why CPS environments are not, in fact, complex intelligence tests: research on CPS is not only about the outcome of the decision process, but it is also about the problem-solving process itself.

Complex problem solving is part of our daily life: finding the right person to share one’s life with, choosing a career that not only makes money, but that also makes us happy. Of course, CPS is not restricted to personal problems – life on Earth gives us many hard nuts to crack: climate change, population growth, the threat of war, the use and distribution of natural resources. In sum, many societal challenges can be seen as complex problems. To reduce that complexity to a one-hour lab activity on a random Friday afternoon puts it out of context and does not address CPS issues.

Theories about CPS should specify which populations they apply to. Across populations, one thing to consider is prior knowledge. CPS research with experts (e.g., Dew et al., 2009 ) is quite different from problem solving research using tasks that intentionally do not require any specific prior knowledge (see, e.g., Beckmann and Goode, 2014 ).

More than 20 years ago, Frensch and Funke (1995b) defined CPS as follows:

  • simple  CPS occurs to overcome barriers between a given state and a desired goal state by means of behavioral and/or cognitive, multi-step activities. The given state, goal state, and barriers between given state and goal state are complex, change dynamically during problem solving, and are intransparent. The exact properties of the given state, goal state, and barriers are unknown to the solver at the outset. CPS implies the efficient interaction between a solver and the situational requirements of the task, and involves a solver’s cognitive, emotional, personal, and social abilities and knowledge. (p. 18)

The above definition is rather formal and does not account for content or relations between the simulation and the real world. In a sense, we need a new definition of CPS that addresses these issues. Based on our previous arguments, we propose the following working definition:

  • simple  Complex problem solving is a collection of self-regulated psychological processes and activities necessary in dynamic environments to achieve ill-defined goals that cannot be reached by routine actions. Creative combinations of knowledge and a broad set of strategies are needed. Solutions are often more bricolage than perfect or optimal. The problem-solving process combines cognitive, emotional, and motivational aspects, particularly in high-stakes situations. Complex problems usually involve knowledge-rich requirements and collaboration among different persons.

The main differences to the older definition lie in the emphasis on (a) the self-regulation of processes, (b) creativity (as opposed to routine behavior), (c) the bricolage type of solution, and (d) the role of high-stakes challenges. Our new definition incorporates some aspects that have been discussed in this review but were not reflected in the 1995 definition, which focused on attributes of complex problems like dynamics or intransparency.

This leads us to the final reflection about the role of CPS for dealing with uncertainty and complexity in real life. We will distinguish thinking from reasoning and introduce the sense of possibility as an important aspect of validity.

CPS as Combining Reasoning and Thinking in an Uncertain Reality

Leading up to the Battle of Borodino in Leo Tolstoy’s novel “War and Peace”, Prince Andrei Bolkonsky explains the concept of war to his friend Pierre. Pierre expects war to resemble a game of chess: You position the troops and attempt to defeat your opponent by moving them in different directions.

“Far from it!”, Andrei responds. “In chess, you know the knight and his moves, you know the pawn and his combat strength. While in war, a battalion is sometimes stronger than a division and sometimes weaker than a company; it all depends on circumstances that can never be known. In war, you do not know the position of your enemy; some things you might be able to observe, some things you have to divine (but that depends on your ability to do so!) and many things cannot even be guessed at. In chess, you can see all of your opponent’s possible moves. In war, that is impossible. If you decide to attack, you cannot know whether the necessary conditions are met for you to succeed. Many a time, you cannot even know whether your troops will follow your orders…”

In essence, war is characterized by a high degree of uncertainty. A good commander (or politician) can add to that what he or she sees, tentatively fill in the blanks – and not just by means of logical deduction but also by intelligently bridging missing links. A bad commander extrapolates from what he sees and thus arrives at improper conclusions.

Many languages differentiate between two modes of mentalizing; for instance, the English language distinguishes between ‘thinking’ and ‘reasoning’. Reasoning denotes acute and exact mentalizing involving logical deductions. Such deductions are usually based on evidence and counterevidence. Thinking, however, is what is required to write novels. It is the construction of an initially unknown reality. But it is not a pipe dream, an unfounded process of fabrication. Rather, thinking asks us to imagine reality (“Wirklichkeitsfantasie”). In other words, a novelist has to possess a “sense of possibility” (“Möglichkeitssinn”, Robert Musil; in German, sense of possibility is often used synonymously with imagination even though imagination is not the same as sense of possibility, for imagination also encapsulates the impossible). This sense of possibility entails knowing the whole (or several wholes) or being able to construe an unknown whole that could accommodate a known part. The whole has to align with sociological and geographical givens, with the mentality of certain peoples or groups, and with the laws of physics and chemistry. Otherwise, the entire venture is ill-founded. A sense of possibility does not aim for the moon but imagines something that might be possible but has not been considered possible or even potentially possible so far.

Thinking is a means to eliminate uncertainty. This process requires both of the modes of thinking we have discussed thus far. Economic, political, or ecological decisions require us to first consider the situation at hand. Though certain situational aspects can be known, but many cannot. In fact, von Clausewitz (1832) posits that only about 25% of the necessary information is available when a military decision needs to be made. Even then, there is no way to guarantee that whatever information is available is also correct: Even if a piece of information was completely accurate yesterday, it might no longer apply today.

Once our sense of possibility has helped grasping a situation, problem solvers need to call on their reasoning skills. Not every situation requires the same action, and we may want to act this way or another to reach this or that goal. This appears logical, but it is a logic based on constantly shifting grounds: We cannot know whether necessary conditions are met, sometimes the assumptions we have made later turn out to be incorrect, and sometimes we have to revise our assumptions or make completely new ones. It is necessary to constantly switch between our sense of possibility and our sense of reality, that is, to switch between thinking and reasoning. It is an arduous process, and some people handle it well, while others do not.

If we are to believe Tuchman’s (1984) book, “The March of Folly”, most politicians and commanders are fools. According to Tuchman, not much has changed in the 3300 years that have elapsed since the misguided Trojans decided to welcome the left-behind wooden horse into their city that would end up dismantling Troy’s defensive walls. The Trojans, too, had been warned, but decided not to heed the warning. Although Laocoön had revealed the horse’s true nature to them by attacking it with a spear, making the weapons inside the horse ring, the Trojans refused to see the forest for the trees. They did not want to listen, they wanted the war to be over, and this desire ended up shaping their perception.

The objective of psychology is to predict and explain human actions and behavior as accurately as possible. However, thinking cannot be investigated by limiting its study to neatly confined fractions of reality such as the realms of propositional logic, chess, Go tasks, the Tower of Hanoi, and so forth. Within these systems, there is little need for a sense of possibility. But a sense of possibility – the ability to divine and construe an unknown reality – is at least as important as logical reasoning skills. Not researching the sense of possibility limits the validity of psychological research. All economic and political decision making draws upon this sense of possibility. By not exploring it, psychological research dedicated to the study of thinking cannot further the understanding of politicians’ competence and the reasons that underlie political mistakes. Christopher Clark identifies European diplomats’, politicians’, and commanders’ inability to form an accurate representation of reality as a reason for the outbreak of World War I. According to Clark’s (2012) book, “The Sleepwalkers”, the politicians of the time lived in their own make-believe world, wrongfully assuming that it was the same world everyone else inhabited. If CPS research wants to make significant contributions to the world, it has to acknowledge complexity and uncertainty as important aspects of it.

For more than 40 years, CPS has been a new subject of psychological research. During this time period, the initial emphasis on analyzing how humans deal with complex, dynamic, and uncertain situations has been lost. What is subsumed under the heading of CPS in modern research has lost the original complexities of real-life problems. From our point of view, the challenges of the 21st century require a return to the origins of this research tradition. We would encourage researchers in the field of problem solving to come back to the original ideas. There is enough complexity and uncertainty in the world to be studied. Improving our understanding of how humans deal with these global and pressing problems would be a worthwhile enterprise.

Author Contributions

JF drafted a first version of the manuscript, DD added further text and commented on the draft. JF finalized the manuscript.

Authors Note

After more than 40 years of controversial discussions between both authors, this is the first joint paper. We are happy to have done this now! We have found common ground!

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The authors thank the Deutsche Forschungsgemeinschaft (DFG) for the continuous support of their research over many years. Thanks to Daniel Holt for his comments on validity issues, thanks to Julia Nolte who helped us by translating German text excerpts into readable English and helped us, together with Keri Hartman, to improve our style and grammar – thanks for that! We also thank the two reviewers for their helpful critical comments on earlier versions of this manuscript. Finally, we acknowledge financial support by Deutsche Forschungsgemeinschaft and Ruprecht-Karls-Universität Heidelberg within their funding programme Open Access Publishing .

1 The fMRI-paper from Anderson (2012) uses the term “complex problem solving” for tasks that do not fall in our understanding of CPS and is therefore excluded from this list.

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SoftwareDominos

how to solve complex problems in life

The 7 Timeless Steps to Guide You Through Complex Problem Solving

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As we go through life, we inevitably encounter problems that require extensive forethought, critical thinking and creativity . Whether it’s a business challenge, a personal dilemma, or a societal issue, solving complex problems is a crucial skill for success.

This guide will explore the fundamentals of complex problem-solving and provide practical tips and strategies for mastering this critical skill.

1. What Is a Complex Problem?

1.1 generic definition of complex problems.

In crude terms, a complex problem presents no trivial or obvious solution. In other words, it shows the following characteristics:

Now that we have defined the general notion of a complex problem let’s look at some specific cases related to software development , business management , and complexity theory.

1.2 Complex Problems in Software Development

A complex software development problem involves intricate interactions between numerous system components and requires a sophisticated understanding of the business problem, computing , algorithms and data structures.

Source: “Domain-Driven Design: Tackling Complexity in the Heart of Software” by Eric Evans

1.3 Complex Problems in Business Management

In business management , a complex problem is characterized by interconnected elements, uncertainty, and dynamic interactions, making it challenging to predict outcomes and devise straightforward solutions. This is most obviously seen in formulating effective organisational strategies or leading successful enterprise transformations.

Source: “Strategic Management and Organisational Dynamics: The Challenge of Complexity” by Ralph D. Stacey

1.4 Complex Problems in Complexity Theory

From a complexity theory standpoint, a complex problem involves many interacting agents or components, often exhibiting emergent properties that cannot be easily deduced from the properties of individual agents.

Source: “The Quark and the Jaguar: Adventures in the Simple and the Complex” by Murray Gell-Mann

Complex problems are contrasted with complicated problems. Complicated problems have clear causes and effects, can be broken down into smaller parts, and have predictable solutions. Complex problems, however, are dynamic, have interconnected parts, and exhibit emergent properties (unpredictable outcomes from the interaction of parts).

Source:  “Cynefin Framework” (2007) by Dave Snowden

2. Solving Complex Problems: A Generic Approach

While developing a universal solution that works in any context would be very challenging, we will describe a generic approach consisting of seven steps that will work in most cases.

At the heart of this approach is logical decomposition , or breaking down a complex problem into smaller, more manageable ones and then developing and implementing effective solutions for each. It is a key skill essential for success in many areas of life, including business, education , and personal relationships.

Logical decomposition is at the heart of scientific thought, as described in Edsger W. Dijkstra’s paper “ On the Role of Scientific Thought “.

The seven steps to solving complex problems are listed below. We will go through them in great detail in the following sections.

Seven steps to complex problem solving. These involve identifying the problem, analysing any data to support the hypotheses, generating solutions, and implementing the best one.

In addition to the seven steps, we will cover the following topics:

With these topics in mind, let’s dive into complex problem-solving.

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3. What are Complex Problem Solving Skills?

Complex problem-solving skills refer to the ability to identify, analyze, and solve non-routine problems requiring high cognitive effort.

These problems typically involve a large number of variables and require the application of creative and critical thinking skills to identify potential solutions. Individuals with complex problem-solving skills can work through ambiguity and uncertainty and use logical reasoning to develop effective solutions.

4. Why are Complex Problem Solving Skills Essential?

In today’s rapidly changing world, individuals and organizations must possess complex problem-solving skills to succeed. These skills are essential for several reasons:

4.1 Dealing with Uncertainty

In many situations, there is no clear-cut solution to a problem. Complex problem-solving skills enable individuals to work through ambiguity and uncertainty and develop effective solutions.

4.2 Identifying Root Causes

Complex problems often have multiple causes that are difficult to identify. Individuals with complex problem-solving skills can identify and address the root causes of problems rather than just treating the symptoms.

4.3 Developing Creative Solutions

Complex problems require creative solutions that go beyond traditional approaches. Individuals who possess complex problem-solving skills can think outside the box and develop innovative solutions.

4.4 Achieving Business Success

Organizations with complex problem-solving skills are better equipped to overcome challenges, identify opportunities, and succeed in today’s competitive business environment.

5. How to Develop Complex Problem Solving Skills

While some individuals possess a natural aptitude for complex problem-solving, these skills can be developed and improved over time. Here are some tips to help you develop complex problem-solving skills:

5.1 Build Your Knowledge Base

Developing complex problem-solving skills requires a strong foundation of knowledge in your area of expertise. Stay updated on your field’s latest trends, research, and developments to enhance your problem-solving abilities.

5.2 Practice Critical Thinking

Developing critical thinking skills is essential for complex problem-solving. Practice questioning assumptions, analyzing information , and evaluating arguments to develop critical thinking skills.

5.3 Embrace Creativity

Complex problems require creative solutions. Embrace your creativity by exploring new ideas, brainstorming solutions, and seeking diverse perspectives.

5.4 Collaborate with Others

Collaborating with others can help you develop your complex problem-solving skills. Working in a team environment can expose you to new ideas and approaches, help you identify blind spots, and provide opportunities for feedback and support.

5.5 Seek Out Challenging Problems

Developing complex problem-solving skills requires practice. Seek out challenging problems and apply your problem-solving skills to real-world situations.

6. Understanding the Nature of Complex (vs Complicated) Problems

6.1 the cynefin framework.

Complex and complicated problems are two distinct types of challenges that require different approaches to solve. Dave Snowden, a management consultant and researcher, developed the Cynefin framework, a conceptual model used to understand complex systems and situations. The framework identifies five domains: simple, complicated, complex, chaotic, and disordered, and guides how to approach challenges in each domain.

6.2 Complicated Problems

Complicated problems are characterized by having many interrelated parts and require specialized knowledge and expertise to solve. They have a clear cause-and-effect relationship, and the solution can be discovered by systematically analysing the components. Complicated problems are best addressed through a top-down, expert-driven approach, where the experts can identify the best solution through analysis and evaluation.

6.3 Complex Problems

On the other hand , complex problems are characterized by uncertainty, ambiguity, and the involvement of multiple interconnected factors. There is no clear cause-and-effect relationship, and the solution cannot be found by simply analysing the components. Complex problems require a bottom-up, participatory approach, where multiple perspectives and ideas are considered to develop a solution. The solution may not be clear initially, but it involves experimentation, adaptation, and feedback.

The Cynefin framework proposes that complex problems belong to the complex domain, where emergent solutions cannot be predicted or prescribed. The complex domain should explore the problem, generate hypotheses, and test them through experimentation. The emphasis is on learning from the process , adapting to changing circumstances, and using feedback to guide the solution.

7. Identifying and Defining the Problem

The first step in problem-solving is identifying the problem. This step involves recognizing that a problem exists and understanding its nature. Some tips for identifying the problem include:

  • Observing the situation : Observe the situation and look for any signs that suggest a problem. This could be anything from an unexpected result to increased customer complaints.
  • Asking questions: Ask questions to gain a better understanding of the situation. This can help you identify the underlying issues and identify potential solutions.
  • Gathering information : Gather information about the problem by talking to people involved, researching the issue, and analyzing data.

Once you have identified the problem, the next step is to define it. This step involves breaking down the problem into smaller parts and better understanding its nature. Some tips for defining the problem include:

  • Writing it down: Write down the problem statement clearly and concisely. This will help you to focus on the specific issue and avoid confusion.
  • Breaking it down: Break the problem into smaller parts to better understand its nature. This can help you to identify the underlying causes and potential solutions. The logical decomposition of problems is vital, and we have dedicated the next section.
  • Identifying the scope: Identify the scope of the problem and determine its impact. This can help you to prioritize the problem and allocate resources accordingly.

In problem-solving, reliable data and statistical analysis skills are crucial in accurately identifying the problem. Data provides information and insights necessary for understanding the root cause of the problem. Statistical analysis allows us to make sense of the data and extract meaningful information. This article will discuss the importance of reliable data and statistical analysis skills in problem identification.

8. Problem Solving and Data

8.1 gathering reliable data.

In today’s fast-paced business environment, reliable data is more critical than ever. It is vital to have accurate and objective information to identify problems and determine their root cause.

Reliable data is the basis of any evidence-based decision-making, without which what we have is opinions and assumptions.

Without reliable data, it is difficult to make informed decisions that can lead to effective problem-solving. Here are some of the benefits of using reliable data in problem identification:

  • Objective information: Reliable data provides an objective perspective of the situation.
  • Evidence-based decision-making: Using reliable data ensures that decisions are based on evidence rather than assumptions or opinions.
  • Improved accuracy: Reliable data improves the accuracy of problem identification, leading to better solutions.
  • Better understanding: Reliable data provides a better understanding of the situation, leading to a more comprehensive and holistic approach to problem-solving.
  • Improved Risk Management : Reliable helps put problems into perspective by allowing analysts to calculate their occurrence probabilities and impacts. Risk can then be categorised and prioritized based on impact and probability .

8.2 Statistical Analysis Skills

Statistical analysis skills are necessary for making sense of the data and extracting meaningful information. These skills allow us to identify patterns and trends, understand the relationships between different variables, and (sometimes) predict future outcomes.

How statistical analysis can help with complex problem solving.

Some benefits of using statistical analysis skills in problem identification include the following:

  • Identifying patterns: Statistical analysis skills enable us to identify patterns and trends in the data, which can help identify the problem accurately.
  • Understanding relationships: Statistical analysis skills help us understand the relationships between different variables, which can help identify the problem’s root cause.
  • Predictive capabilities: Statistical analysis skills allow us to predict future outcomes based on the data, which can help develop effective solutions.
  • Objective analysis: Statistical analysis provides objective data analysis, which can help make evidence-based decisions.

Interpreting data, however, requires technical skills to avoid misinterpretations. The following is a common list of statistical analysis mistakes non-professionals can make.

  • Drawing conclusions based on small or biased sample sizes: Non-professionals often make the mistake of drawing conclusions based on small sample sizes, leading to inaccurate or biased results. Non-professionals may use biased samples, such as convenience or samples not representative of the population, leading to inaccurate results.
  • Ignoring outliers: Outliers are data points that lie far away from most data points. Ignoring outliers can lead to inaccurate results, as they may significantly impact the overall outcome.
  • Confusing correlation with causation: Non-professionals often make the mistake of assuming that correlation between two variables implies causation. However, correlation does not always imply causation, and looking for other factors contributing to the observed relationship is important.
  • Failing to consider confounding variables: A confounding variable is a variable that affects both the independent and dependent variables. Non-professionals often fail to consider confounding variables, leading to inaccurate or misleading results.
  • Using inappropriate statistical tests: Non-professionals may use statistical tests that are inappropriate for the analysed data. For example, using a t-test when the data is not normally distributed can lead to inaccurate results.
  • Overfitting models: Overfitting occurs when a statistical model is too complex, leading to a poor fit and generalization to new data. Non-professionals may overfit models by including too many variables or by selecting variables based on the results of statistical tests.
  • Misrepresenting data: Non-professionals may misrepresent data, such as using inappropriate scales or selectively presenting data that supports their conclusions, leading to incorrect interpretations of results.

8.3 How Software Team Leads Can Gather Reliable Data

Software team leads need reliable data on their performance to make informed decisions and identify areas for improvement. Here are some sources where software team leads can gather reliable data on their team’s performance:

  • Project management tools: Most project management tools have built-in reporting features allowing team leads to track performance metrics such as task completion rates, sprint velocity, and burn-down charts. This data can be used to identify areas for improvement and make data-driven decisions.
  • Team feedback: Gathering feedback from team members through one-on-one meetings or anonymous feedback forms can provide valuable insights into team performance . This data can help team leads identify areas where team members may struggle, or additional training or resources may be needed. Crucially, it also provides insights into the organisational culture .
  • Code analysis tools like SonarQube or Code Climate can provide insights into code quality , maintainability, and security. This data can help team leads identify needed code improvements and prioritize technical debt reduction.
  • Customer feedback: Customer feedback, such as ratings, reviews, and support tickets, can provide insights into the usability and functionality of deployed applications. This data can help team leads identify areas for improvement and prioritize feature development.

It’s important for software team leads to gather data from multiple sources and use that data to inform decisions and identify areas for improvement. Software team leads can drive continuous improvement and ensure project success by using reliable data sources and monitoring team performance metrics regularly.

9. Logical Decomposition in Problem Solving

Logical decomposition is a problem-solving technique that breaks down complex problems into smaller, more manageable pieces. It is a structured approach that enables individuals to examine a problem from multiple angles, identify key issues and sub-problems, and develop a solution that addresses each piece of the problem.

The process of logical decomposition involves breaking down the main problem into smaller sub-problems, which are then broken down into smaller pieces. Each piece is analyzed in detail to determine its underlying cause-and-effect relationships and potential solutions. By breaking down the problem into smaller pieces, the individual can better understand the overall problem, identify potential solutions more easily, and prioritize which sub-problems to address first.

Logical decomposition is particularly useful for dealing with complex issues, as it allows individuals to break down a large, overwhelming problem into smaller, more manageable pieces. This not only makes the problem easier to understand and solve but also makes it less daunting and more approachable. Additionally, by breaking down the problem into smaller pieces, individuals can identify and focus on the underlying root causes of the problem rather than just treating the symptoms.

Logical decomposition is a vital stage of architecting large systems and solutions.

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10. Generating and Evaluating (Several) Potential Solutions

Generating multiple solutions to solve a problem is an effective way to increase creativity and innovation in problem-solving. By exploring different options, individuals can identify the strengths and weaknesses of each solution and determine the most effective approach to solving the problem. This section will discuss the advantages and techniques of generating multiple solutions to solve problems more effectively.

10.1 Advantages of Generating Multiple Solutions

The advantages of generating multiple solutions during problem solving are:

  • Increases creativity and innovation: Generating multiple solutions allows individuals to explore different approaches to solving a problem, which can lead to more creative and innovative solutions.
  • Increases the likelihood of finding an effective solution: By exploring multiple solutions, individuals are more likely to find a solution that addresses all aspects of the problem.
  • Increases engagement and ownership: Individuals who generate multiple solutions feel more ownership and engagement in problem-solving.
  • Avoid being locked or overcommitted to one solution that may prove suboptimal.

10.2 Techniques for Generating Multiple Solutions

Techniques for generating multiple solutions:

  • Brainstorming involves generating as many ideas as possible without evaluating them initially. This technique encourages individuals to be creative and open-minded, which can lead to the development of unique solutions.
  • Mind mapping involves visually organizing ideas and concepts around a central theme or problem. This technique can help individuals see connections between ideas and develop new solutions.
  • Reverse brainstorming involves identifying solutions that would make the problem worse rather than better. This technique can help individuals identify the underlying causes of the problem and develop more effective solutions.
  • SCAMPER is an acronym for Substitute, Combine, Adapt, Modify, Put to another use, Eliminate, and Reverse. This technique involves using these prompts to generate new ideas and solutions by altering existing ones.
  • The Six Thinking Hats technique involves assigning different roles to team members to encourage different perspectives and generate multiple solutions. The six roles are White (facts and information), Red (emotions and feelings), Black (potential problems and criticisms), Yellow (potential benefits and opportunities), Green (creativity and new ideas), and Blue (organizational and planning).

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11. Implementing and Assessing Solutions

Implementing solutions to complex problems requires a structured approach that considers the unique challenges and variables involved. Effective problem-solving involves implementing solutions that are practical, feasible, and sustainable.

This section will discuss two approaches to implementing solutions to complex problems: small safe-to-fail solutions and solving easy problems with large benefits first.

11.1 Implementing Many Safe-to-Fail Solutions

One effective approach to implementing solutions to complex problems is small safe-to-fail solutions. This technique involves implementing a small-scale solution that can be tested quickly and easily to gather feedback.

Exploring multiple paths allows analysts to avoid over-commitment to suboptimal solutions.

Individuals can gather feedback and adjust before investing significant resources in a larger solution by starting with small-scale solutions. This approach can save time and resources while ensuring that the final solution meets the needs of stakeholders .

Small safe-to-fail experiments effectively deal with complexity where an engineering solution is unknown priori.

11.2 Prioritizing High-Yield Solutions

Another effective approach to implementing solutions to complex problems is to first solve easy problems with large benefits. This technique involves identifying and solving simple, straightforward problems that significantly impact the overall problem.

Individuals can progress quickly and gain momentum towards solving the larger problem by prioritising easy problems. This approach can also help build trust and credibility with stakeholders, as progress is visible and measurable.

11.3 A Systematic Approach to Implementing Solutions

It is important to note that both approaches should be used with a broader problem-solving methodology . Effective problem-solving requires a systematic approach that involves identifying the problem, gathering information, analyzing data, developing and evaluating potential solutions, and implementing the best solution. By implementing small safe-to-fail solutions and solving easy problems with large benefits, individuals can enhance their problem-solving approach and increase the likelihood of success.

In conclusion, implementing solutions to complex problems requires a structured approach considering the unique challenges and variables involved. Implementing small safe-to-fail solutions and solving easy problems with large benefits are two effective techniques for enhancing problem-solving. These techniques should be used with a broader problem-solving methodology to ensure the final solution is practical, feasible, and sustainable.

12. Tips and Strategies for Effective Complex Problem Solving

The following steps will you solve any complicated issue you might face. To illustrate the main ideas, we will use the example of a software team grappling with a productivity issue.

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Step 1: Identify the Problem

Objective — Paint a full picture of the problem by laying out the details, preferably on a piece of paper, classifying the problem, and deciding on an approach to solving it.

How it’s done — Write down a complete description of the problem, including its scope and impact on the various stakeholders or aspects of the business. Use data as evidence to support initial hypotheses. Find out if the problem is localised and can be resolved locally or whether it might need escalation and support from higher levels of management.

Step 2: Identify a Framework for Thinking about the Solution

Objective — Classify the problem as complex, complicated, or disordered. This classification will determine the approach to be used.

How it’s done — You can do that by asking the following questions.

  • Do we have multiple, internally consistent, competing hypotheses explaining the issue?
  • Does the available data support both theories?

In this case, the problem lies in the complex domain, and the preferred approach is to identify good solutions and conduct safe-to-fail experiments. If it’s a complicated (but not complex) problem, the following questions can be answered in the affirmative:

  • Do we have a single view that explains the problem?
  • Do we know the engineering part of the solution?
  • Is the problem sufficiently familiar to be solved by an expert?

Step 3: Gathering Data to Support the Proposed Hypotheses

Objective — The availability of data can help place the problem into perspective. For example, a dollar figure of the losses due to process inefficiencies can help identify the potential solutions that management will deem feasible.

How it’s done — All modern project management and tracking tools have sophisticated built-in data capture tools that can be exported, cleaned, and analysed for insights.

For example, when evaluating a team’s productivity, you can export data from JIRA, Jenkins, or BitBucket and measure performance metrics such as team velocity, overruns, and time-to-market.

When evidence is insufficient, you can gather more data, abandon the hypothesis, or temporarily shelve it.

Step 4: Logical Decomposition in Problem-Solving

Objective — Most problems worth tackling are also overwhelming in size and complexity (or complicatedness). Luckily, a logical decomposition into specialized areas or modules will help focus the team’s efforts on a small enough subproblem or bring in the right expertise.

How it’s done — A preferred method of this author is mindmaps. A mindmap is a tree that starts with a single node and branches off into different areas, views, or perspectives of the problem. Mindmaps help analysts stay focused on a key area. They also ensure that all aspects of a problem are covered.

Once a mindmap has been created, potential solutions can be explored.

Step 5: Solution Generation and Selection

Objective — The key principle of solution generation is comprehensively exploring the solution space. This exploration allows teams to avoid local minima or overcommitting to a suboptimal solution.

How it’s done — The most effective approach is to bring in several people from different areas of expertise or seniority and to offer every suggestion the opportunity to be heard and thoroughly explored.

Also, different stakeholders might favour solutions that maximise their (potentially) narrow gains. If not consulted, they might actively block the implementation of the selected solution if it adversely impacts their interests.

The technical aspect of problem-solving is relatively easy to generate and implement without budgetary or scheduling constraints . It’s only when you consider the cost and impact of a solution that complexity arises.

Step 6: Implementing the Solution

Objective — This stage aims to efficiently and effectively implement the (optimal) selected solution(s).

How it’s done — Three principal techniques are required for the solution implementation to succeed. The first is conducting safe-to-fail experiments. The second is allocating resources to conduct each experiment. The third is to set up the criteria for success or failure.

Step 7: Evaluating the Solution

Objective — Solutions might work well under laboratory conditions but fail spectacularly in the field. Evaluating solutions after a trial is vital to avoid continued investment in failed solutions.

How it’s done — The best way to evaluate a solution is by monitoring the Key Performance Indicators (KPIs) originally in the problem diagnosis. Noticeable and measurable improvements should be observed when solutions are successful.

Measuring second-order effects or observing undesirable team or business dynamics changes is key to continuing or aborting initiatives.

Complex problem-solving refers to the ability to solve problems that are complex, ambiguous, and often require creative and innovative solutions. It involves identifying the root cause of a problem, analyzing different variables and factors, developing and evaluating possible solutions, and selecting the best course of action.

Complex problem-solving is essential because it allows individuals and organizations to overcome challenges and obstacles hindering their progress and success. It enables them to identify opportunities, improve processes, and innovate to stay ahead of the competition.

To develop your complex problem-solving skills, you can practice consistently, develop a systematic approach, and leverage the right tools and resources. You can also seek feedback from others, learn from your mistakes, and adopt a growth mindset that values continuous learning and improvement.

Some common obstacles to effective problem-solving include cognitive biases , lack of information, unclear objectives, and groupthink. These obstacles can hinder individuals and teams from developing effective solutions to complex problems.

Various tools and techniques for complex problem-solving include root cause analysis, fishbone diagrams, SWOT analysis, Pareto analysis, decision trees, and scenario planning. These tools can help individuals and teams to analyze complex problems, identify underlying causes, and develop effective solutions.

To improve your decision-making skills, you can develop a structured approach, gather and analyze relevant data, evaluate different options, and consider each alternative’s potential risks and benefits. You can also seek feedback from others and reflect on your past decisions to learn from your mistakes.

Complex problem-solving skills can be applied in various aspects of your personal life, such as improving your relationships, managing your finances, and achieving your goals. You can overcome obstacles and succeed personally by systematically analyzing different variables and factors and developing creative and innovative solutions.

To overcome cognitive biases in problem-solving, you can challenge your assumptions, seek diverse perspectives, and use data and evidence to inform your decisions. You can also use brainstorming and mind-mapping techniques to generate new ideas and avoid tunnel vision.

14. Final Words

In conclusion, complex problem-solving is a crucial skill that can significantly impact your professional and personal life. It allows you to navigate complex challenges, identify the root cause of a problem, and develop effective solutions.

By mastering the art of complex problem-solving, you can enhance your critical thinking, analytical skills, and decision-making abilities, which are essential for success in today’s fast-paced and dynamic business environment.

The key to mastering complex problem-solving is to practice consistently, develop a systematic approach, and leverage the right tools and resources. With patience, persistence, and a growth mindset, anyone can become a skilled problem solver and tackle even the most challenging problems.

Decision Making In a Professional Environment: Techniques and Pitfalls

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The Cynefin Framework

Using the most appropriate problem-solving process.

By the Mind Tools Content Team

how to solve complex problems in life

The most effective leaders understand that problem solving is not a "one-size-fits-all" process. They know that their actions depend on the situation, and they make better decisions by adapting their approach to changing circumstances.

But how do you know which approach you should use in a particular situation? And how can you avoid making the wrong decision?

In this article we'll look at the Cynefin framework, a tool that helps you make better decisions by assessing the situation you find yourself in.

About the Tool

Cynefin, pronounced "ku-nev-in," is a Welsh word that translates as "place" or "habitat." However, it can also be used to describe the elements of our situation and personal history that influence our thoughts and decisions in ways we don't understand.

Scholar David J. Snowden used the word to describe a framework he developed in 1999, based on concepts from knowledge management and organizational strategy. Along with his colleague Mary Boone, he published the framework in the November 2007 issue of the Harvard Business Review .

The Cynefin framework (Figure 1 below) is a problem-solving tool that helps you put situations into five "domains" defined by cause-and-effect relationships. This helps you assess your situation more accurately and respond appropriately.

Figure 1: The Cynefin Framework

how to solve complex problems in life

Based on the Cynefin framework diagram by David Snowden, see http://cognitive-edge.com . Reproduced with permission.

The "obvious" domain was originally called "simple," but this was updated in 2014.

You can use the Cynefin framework in a variety of situations to categorize a problem or decision and respond accordingly. For example, it is useful in product development, marketing and organizational strategy. It can also help you make better decisions in a crisis or emergency.

It helps you avoid using the same management style or decision-making approach in all situations – a mistake that can be costly to your team or organization– by encouraging you to be flexible and adaptable when making decisions, and to adjust your management style to fit your circumstances.

The Five Domains

Let's look at each of the five domains in greater detail.

Obvious Contexts – "The Domain of Best Practice"

In "obvious" contexts, your options are clear and cause-and-effect relationships are apparent to everyone involved.

Here, there are often explicit steps in place that dictate the next stage of the process. For example, problems encountered at help desks or call centers are often predictable, and there are processes in place to handle most of them.

Snowden argues that you need to "Sense – Categorize – Respond" to obvious decisions. Put simply, you should assess the situation, categorize its type, and then base your response on best practice. There is often one established "correct" answer, based on an existing process or procedure.

However, there is a danger that obvious contexts may be oversimplified. This often happens when leaders, or an entire organization, experience success and then become complacent. To avoid this, make sure that there are clear communication channels in place, so that team members can report any situations that don't fit with any established category.

Another challenge is that leaders may not be receptive to new ideas because of past experiences and success. For example, some people might automatically assume that previous solutions will work again. To overcome this, stay open to new ideas and be willing to pursue innovative suggestions.

Complicated Contexts – "The Domain of Experts"

"Complicated" problems might have several "correct" solutions. Here, there is a clear relationship between cause and effect, but it may not be visible to everyone, because the problem is... complicated. For example, you might see several symptoms of a problem but not know how to fix it.

The decision-making approach here is to "Sense – Analyze – Respond." In other words, you need to assess the situation, analyze what is known (often with the help of experts), and decide on the best response, using good practice.

Leaders may rely too heavily on experts in complicated situations, while dismissing or overlooking creative solutions from other people. To overcome this, assemble a team of people from a wide variety of backgrounds (including rebels and dissenters), and use tools such as Crawford's Slip Writing Method to ensure that everyone's views are heard.

Complex Contexts – "The Domain of Emergence"

It might be impossible to identify one "correct" solution, or spot cause-and-effect relationships, in "complex" situations. According to Snowden and Boone, many business situations fall into this category.

Complex contexts are often unpredictable, and the best approach here is to "Probe – Sense – Respond." Rather than trying to control the situation or insisting on a plan of action, it's often best to be patient, look for patterns, and encourage a solution to emerge.

It can be helpful to conduct business experiments in these situations, and accept failure as part of the learning process. Make sure that you have processes in place to guide your team's thinking – even a simple set of rules can lead to better solutions than no guidance at all.

Communication is essential here, too. Gather a diverse group of people to come up with innovative, creative solutions to complex problems. Use brainstorming tools such as Random Input or Provocation to generate new ideas, and encourage your team to debate the possibilities.

Complicated and complex situations are similar in some ways, and it can be challenging to tell which of them you're experiencing. However, if you need to make a decision based on incomplete data, for example, you're likely to be in a complex situation.

Chaotic Contexts – "The Domain of Rapid Response"

In "chaotic" situations, no relationship between cause and effect exists, so your primary goal is to establish order and stability. Crisis and emergency scenarios often fall into this domain.

The decision-making approach here is to "Act – Sense – Respond." You need to act decisively to address the most pressing issues, sense where there is stability and where there isn't, and then respond to move the situation from chaos to complexity.

To navigate chaotic situations successfully, conduct a Risk Analysis to identify possible risks, prioritize them with a Risk Impact/Probability Chart , and make sure that you have a comprehensive crisis plan in place. It's impossible to prepare for every situation, but planning for identifiable risks is often helpful.

Reliable information is critical in uncertain and chaotic situations, so make sure you know how to communicate in a crisis .

It can be extremely difficult to identify when you're in a "disorder" situation. Here, it isn't clear which of the other four domains is dominant, and people generally rely on decision-making techniques that are known and comfortable. Your primary goal in this situation is to gather more information , so that you can move into a known domain and then take the appropriate action.

José and his team recently rolled out an innovative new e-reader. However, it has developed an issue, and no one can agree on what's causing it. Dissatisfied customers are returning the product and the company's reputation has taken a hit. José is managing a number of issues. He has to help his team uncover the cause of the problem so it can be fixed, he's working with marketing to compensate customers, and he's answering questions from the media about the e-reader's issue.

He uses the Cynefin framework to gain a better understanding of the situation, and he categorizes it as "complicated," which means he needs to take a Sense – Analyze – Respond approach.

So, he brings in experts from research and development, IT and manufacturing to help him diagnose the problem. Working closely with his team, these experts list the quality concerns and then focus on each one individually to find the root cause of the problem.

After several days of analysis, everyone agrees that the problem is caused by dry solder joints. Working together, the consultants and José's team come up with a clear plan to address this and ensure that no more faulty e-readers are shipped.

The Cynefin framework was developed by David J. Snowden in 1999. It aims to help leaders understand that every situation is different and requires a unique approach to decision making.

The framework outlines five situational domains that are defined by cause-and-effect relationships. They are:

  • Complicated.

Each of these domains has a specific decision-making approach that helps you make better sense of the situation, and choose the most appropriate way forward.

Apply This to Your Life

Practice using the Cynefin framework the next time you have an important decision to make at work. Aim to identify the domain you're in correctly, and use the appropriate decision-making approach to process information and move forward.

Snowden, D. and Boone, M. (2007). 'A Leader’s Framework for Decision Making,' Harvard Business Review , November 2007. (Available here .)

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There are 4 main types of life and work problems we face every day. Here's how to solve each one

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When it comes to solving problems and making tough decisions , people love plans (especially their own plans), so they make a lot of them. And because they want the perfect plan, they demand more data to help them.

Inevitably, though, this takes longer and longer, and instead of the goal being to reach a decision, the process of making the decision becomes the goal.

There may be studies, hearings and debates, but nothing actually gets done. This can go on for quite a while, depending on the nature of the decision ... all because everyone wants the perfect plan.

The 'perfect plan' doesn't exist

More often than not, it's impossible to know the results of a dynamic system in advance. So any action is better than no action; it doesn't matter what you do, it just matters that you do, in order to learn and move forward.

Smart leaders know that in order to solve any major problem, the goal should be to get quick feedback on whether that decision was a good one or not. If it wasn't, then they know to pivot and seek a different path.

Each decision informs the next. The path emerges from the doing.

The 4 types of problems we encounter daily

In 1999, while working at IBM, a guy named Dave Snowden came up with a way of looking at problems to help people know what kind of problem they are facing, and what kind of solution they should be looking for.

He calls it the Cynefin framework — cynefin is a Welsh word that means "habitat" — because you need to know where you stand.

1. The simple problem

The first type of problem in Snowden's framework is simple and obvious . It has already been solved, and there actually is a best practice that works all the time.

Once you can determine that a problem is simple, you can apply a known recipe from your bag of tricks. If you're playing poker, never draw to an inside straight. A bank shouldn't make loans to people with X level of debt load.

With simple problems, the relationship between cause and effect is not only clear but obvious.

2. The complicated problem

This is the kind of problem where you have a known unknown. Take a giant oil company, for example: When geologists run a seismic survey to learn where they could drill for oil, they know they don't know the answer, but they know how to find it.

This is the domain of the expert. Once you have ascertained that the problem is solvable, you can work out a solution, even if it turns out to be tricky. If you're knowledgeable enough, you can figure out cause and effect.

I always think of this when I bring my car into the shop. It's making a weird noise and I'm worried. I know I don't know how to address this problem, but I know that my mechanic knows, or can figure it out.

3. The complex problem

The third type of problem is complex , where you can only figure out afterward why what happened happened. Here you have to take some sort of action to see what happens before you act again.

Most of us wrestle with complex problems. All the time. The answers aren't known, and all the forces aren't known. But we have to do something. And what happens will surprise us.

Let's examine the story of Twitch, a web service that allows people to stream themselves playing a video game so that other people can watch them do it. This isn't an obvious product except in retrospect. But Twitch is an incredible success story. Amazon acquired it for $970 million in 2014 .

This company's first product idea? A calendar that would integrate with Gmail. Of course, then Google came out with Google Calendar. So the company decided to go into live-streaming.

One of the founders would stream his entire life, 24/7. Camera on head and a big backpack with a computer — constantly live. They built an incredibly fast live-streaming service that a lot of people could use at the same time. But as it turns out, no one really wanted to watch that live-stream.

So they opened the idea up. Maybe people wanted to live-stream themselves? It really wasn't working in the marketplace, and they were running out of cash. Then, they noticed that a lot of people were watching live-streams of people playing video games. Weird.

But they went with that, and it turns out there is an avid audience of fans and recreational gamers who want to watch the top players play. People can make a small fortune just playing video games and streaming it for others to watch.

...any action is better than no action; it doesn't matter what you do, it just matters that you do, in order to learn and move forward. J.J. Sutherland CEO, Scrum Inc.

That's an extreme example of a solution to a need that no one knew existed. But the problems we're facing today in business, politics and society are tough ones. Often we simply do not know the solution. And sometimes we don't know how to even approach the solution.

So what you need to do is try something and then see what happens. Take the results of that and tweak what you're doing. Then try again. Tweak again. And let the solution emerge. That's all it is — a series of small experiments in short periods of time to find a solution to a complex problem.

4. The chaotic problem

The final type of problem in the Cynefin framework is chaotic. This is essentially a crisis.

Let's say there's a tsunami, or an oil rig blows up, or an uprising turns into a revolution, or there's a stock market crash. The first thing to do is to take action quickly, and begin to take steps to encapsulate the problem, to define its limits, to bring it out of the chaotic and into the realm of the merely complex.

One example I use to describe a chaotic problem is a riot. One night during the Arab Spring, I was in the middle of a crowd that decided to storm the parliament building. This crowd of tens of thousands lurched as one toward the parliament gates.

Here speed matters. Delaying the decision will only worsen the problem. J.J. Sutherland CEO, Scrum Inc.

Then screams broke out from one side and the whole crowd got chaotic. Everyone was running around unsure of what to do, and they turned from individuals into a mob. I was standing in the middle of all this with a young American student I'd hired because she spoke Arabic. I told her — and I'll tell you — exactly what to do in a riot.

First, don't panic. I can't emphasize how important that is. Blind fear is what gets people trampled and killed. Second, find something hard that can't easily be knocked over, like a lamppost. It's bizarre — the crowd will part around you like a river around a stone.

What you've done is pulled the chaotic into the complex. Take a minute. Breathe. Figure out what the escape routes are. You have that freedom now. You can't do anything when you're just another body being flung about, but if you can get out of the noise and fear, you can start to come up with a plan.

Here speed matters. Delaying the decision will only worsen the problem. By rapidly iterating — trying something, seeing the response, trying again — you can ultimately succeed in bringing the crisis under control.

This trial-and-error approach can feel terrifying in the moment. But it's also an opportunity. New ways of doing things will emerge as people try to figure out how to work in an environment that didn't exist the day before.

J.J. Sutherland is the CEO of Scrum Inc. , a consulting and training firm, author of " The Scrum Fieldbook" and co-author of the best-selling book "Scrum: The Art of Doing Twice the Work in Half the Time." Previously, he was an award-winning correspondent and producer for NPR. Follow J.J. on LinkedIn .

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*This is an adapted excerpt from "The Scrum Fieldbook," by J.J. Sutherland. Copyright © 2019 by J.J. Sutherland. Excerpted by permission of Currency. All rights reserved.

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The Six Systems Thinking Steps to Solve Complex Problems

A quick overview of common problem solving techniques indicates that most of these methods focus on the problem rather than the whole eco-system where the problem exists. Along with the challenges of global economy , problems turn out to be more complicated and sometimes awakening problems. Climate change, traffic problems, and organizational problems that have developed through the years are all complex problems that we shouldn’t look at the same way as simple or linear problems. Part of the problem of thinking about a complex problem is the way we approach it, which may contribute to making the problem even more complex. As stated by Albert Einstein, “The problems cannot be solved using the same level of thinking that created them.” Systems thinking tends to focus on the broader ecosystem rather than the problem itself.

Systems thinking was developed by Jay Forrester and members of the Society for Organizational Learning at MIT. The idea is described in his book, The Fifth Discipline , as follows: “Systems thinking is a discipline for seeing wholes. It is a framework for seeing interrelationships rather than things, for seeing patterns of change rather than static ‘snapshots.’” A common example of the systems thinking method is the life around us where multiple systems interact with each other and are affected by each other. This wide perspective of systems thinking promotes it to solve complex problems that are dependent on external factors. Below are some of the stations that system thinking may contribute to solve.

  • Complex problems that involve different factors, which require understanding the big picture in order to be efficiently solved
  • Situations that are affecting, are being affected by, or affect the surrounding systems
  • Problems that have turned more complicated by previous attempts to solve them

Concepts of Systems Thinking

In order to understand systems thinking, a number of concepts should be highlighted in order to define the relation between the problem and the other elements in the system and how to observe this relation in order to reach an effective solution. These principles include the following.

  • All systems are composed of interconnected parts, and changing one part affects the entire system, including other parts.
  • The structure of a system determines its behavior, which means that the system depends on the connection between parts rather that the part themselves.
  • System behavior is an emergent phenomenon. System behavior is hard to predict due its continuously changing, non-linear relations and its time delay. It can’t be predicted by simply inspecting its elements or structure.
  • Feedback loops control a system’s major dynamic behavior. The feedback loop is a number of connections causing an output from one part to eventually influence input to that same part. The number of feedback loops are larger than the system parts, which contributes to increasing system complicity.
  • Complex social systems exhibit counterintuitive behavior. Solving complex problems can’t be achieved through everyday problem solving methods. They can be solved only through analytical methods and tools. Solving complex problems can be achieved through systems thinking, a process that fits the problem, and system dynamics , which is an approach to model systems by emphasizing their feedback loops.

Systems Thinking in Six Steps

In their paper Six Steps to Thinking Systemically , Michael Goodman and Richard Karash introduced six steps to apply systems thinking principles while solving complex problems. These steps were part of their case study to Bijou Bottling company’s problem of getting their orders shipped on time.

Set 1: Tell the Story

The first step in solving the problem is to understand it, and this can be achieved through looking deeply at the whole system rather than individual parts. This step requires meeting with the stakeholders to share their vision about the situation. One of the common tools to build this understanding is to utilize Concept Maps, which are graphical tools used to represent the organization or a structure of knowledge. Concept Maps visually present the system’s elements, concept links, proposition statements, cross-links, and examples.

concept maps

Step 2: Draw Behavior Over Time (BOT) Graphs

When thinking about a problem, we are influenced with the current situation that is reflected in our analysis, yet the problem follows a time dimension, which means that it should be tracked through the time. The Behavior Over Time graph draws a curve that presents a specific behavior (Y) through the time (X). This graph helps us to understanding whether or not the current solution is effective.

behavior over time

Step 3: Create a Focusing Statement

At this point, there should be a clear vision about the problem solving process, which is defined in the from of a statement that indicates the team’s target and why the problem occurs.

Step 4: Identify the Structure

After having clear vision about the problem through the proposed statement, the system structure should be described, including the behavior patterns. Building these patterns helps in understanding more about the problem, and it can be formed as a system archetype.

Step 5: Going Deeper into the Issues

After defining the problem and the system structure, this step tends to understand the underlying problems through clarifying four items: the purpose of the system (what we want), the mental models, the large system, and personal role in the situation.

Set 6: Plan an Intervention

The previously collected information is used to start the intervention phase, where modifications to the current problem relate parts to connections. This intervention attempts to reach the desirable behavior.

concept maps

Practice Example of Systems Thinking

One of the direct examples of adopting the systems thinking method was presented by Daniel Aronson highlighting insects who caused damage crops. Traditional thinking to solve crop damage is to apply more pesticides to reduce the number of insects and subsequently reduce the crop damage. However, this solution solves the problem for a short term. In the long run, the problem isn’t truly solved, as the original insect eating the crops are controlling the population of another species of insect in the environment either by preying on it or competing with it. Subsequently, the crop damage increases again due to the increasing numbers of other insect species.

systems thinking

Observing the ecosystem that includes both the insects and the crops, systems thinking suggests exploring a solution that ensures reducing the crop damage in the long run without affecting the environmental balance, such as deploying the Integrated Pest Management that has proven success based on MIT and the National Academy of Science. This solution tends to control the number of an insect species by introducing its predators in the area.

Unlike everyday problems, complex problems can’t be solved using traditional problem solving methods due to the nature of the problems and their complexity. One of the theories that attempts to understand complex problems is systems thinking, which is defined by a number of characters. Six steps are to be used to explore and solve complex problems under the umbrella of systems thinking, which help us to observe and think in a whole eco-system rather than individual parts. Systems thinking can be deployed in multiple domains to solve organization problem, or global problems such as energy, pollution, and poverty.

Dr Rafiq Elmansy

I'm an academic, author and design thinker, currently teaching design at the University of Leeds with a research focus on design thinking, design for health, interaction design and design for behaviour change. I developed and taught design programmes at Wrexham Glyndwr University, Northumbria University and The American University in Cairo. Additionally, I'm a published book author and founder of Designorate.com. I am a fellow for the Higher Education Academy (HEA), the Royal Society of Arts (FRSA), and an Adobe Education Leader. I write Adobe certification exams with Pearson Certiport. My design experience involves 20 years working with clients such as the UN, World Bank, Adobe, and Schneider. I worked with the Adobe team in developing many Adobe applications for more than 12 years.

how to solve complex problems in life

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3 thoughts on “ The Six Systems Thinking Steps to Solve Complex Problems ”

how to solve complex problems in life

“Systems thinking was developed by Jay Forrester and members of the Society for Organizational Learning at MIT. The idea is described in his book, The Fifth Discipline, as follows:” Peter Senge is the author of The Fifth Discipline

how to solve complex problems in life

Thank you so much Misi for the helpful information.

how to solve complex problems in life

Thank you for the valuable information. I believe that systems thinking can be applied to every aspect of our lives. When you teach yourself to spot patterns, cycles, and loops instead of individuals elements. You see behind the scenes. Understand what actually needs addressing to move forward and make progress faster with less damage.

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Complex Problems: How to Solve Them, the Simple Way

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This article is an excerpt from the Shortform summary of "The Checklist Manifesto" by Atul Gawande. Shortform has the world's best summaries of books you should be reading.

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Brenda Zimmerman and Sholom Glouberman, who study complexity, defined three kinds of problems: simple, complicated, and complex. What’s the difference? Particularly, what’s the difference between complicated problems and complex problems?

A complex problem is a problem that has many variables and for which the outcome is uncertain. An example of a complex problem is raising a child. You learn from raising one child, but the next child may require a different approach.

We’ll look at the nature of complex problems, how they differ from complicated problems, and how to solve complex problems in the workplace.

From Simple to Complex Problems

The successful experiences of using checklists in aviation decades ago suggest they could be applied widely. They protect even the most experienced from making mistakes in a whole range of tasks. They provide a mental safety net against typical human lapses in memory, focus, and attention to detail.

  • Simple Problem: An example of a simple problem is baking a cake from a mix — there’s a recipe and a few techniques, but once you’ve learned them, following the recipe usually works. 
  • Complicated Problem: An example of a complicated problem is sending a rocket to the moon. Complicated problems can be broken down into smaller problems. Solving the problem involves many people, teams, and specialists. Unexpected issues pop up, but you can learn, repeat the process, and perfect it. Timing and coordination are key. 
  • Complex Problem: An example of a complex problem is raising a child. Every child is unique. You learn from raising one child, but the next child may require a different approach. With complex problems like raising a child, the outcome is uncertain. Yet it’s possible to raise a child successfully.

In classifying the three problems described so far in this book — the bomber crash of 1935, the issue of central line infections, and the rescue of a drowning victim — the key problem and solution in each case were simple:

  • To avoid crashing the bomber, focus on the rudder and elevator controls.
  • To reduce central line infections, maintain sterility.
  • To saving a drowning victim, be ready to perform a cardiac bypass

All could be resolved by using a simple tool to compel the needed behavior — a checklist. We’re constantly confronted with similar simple problems that can be mitigated by checklists — for instance, a nurse’s failure to wear a mask while putting in a central line or a surgeon’s failure to recall that one cause of a cardiac arrest could be a potassium overdose.

But can checklists be used to address complicated or complex problems, such as ICU work, where there are many tasks performed by multiple people, dealing with individual patients with individual and complex problems? Medicine encompasses all three types of problems —  simple, complicated, and complex. It’s important to get basic things right, while allowing skill, judgment, and ability to react to the unexpected. 

The medical profession could learn from the construction industry, which handles the design and construction of huge and complicated structures with the help of sophisticated checklists addressing the full range of problems.

The Demise of the Master Builder 

Let’s look at an example of how checklists can solve complex problems.

People used to hire master builders, who designed, engineered, and oversaw the construction of large and small projects from start to finish. For instance, master builders built Notre Dame and the U.S. Capitol building.

However, by the mid-20 th -century master builders became obsolete because one person alone couldn’t master the advances occurring at every stage of the construction process . Architectural design and engineering design became separate specialties. Other specialties and subspecialties developed. Builders split further into areas of expertise such as finish carpenters and tower crane operators. Major projects now involve 16 different trades and hundreds of workers who must do their jobs in coordination with others. 

The construction process is orchestrated using sophisticated schedules and checkpoints that enforce roles, communication, and follow-through. The simple act of building has become a complex problem. The major advance in the industry over the last few decades has been perfecting this process of tracking and communication.

To manage increased complexity, the entire construction industry was forced to evolve. However, much of medicine is still structured like the master-builder era — with a lone physician executing all of a patient’s care — even though times have changed to the extent that a third of patients have at least 10 doctors involved in their care by the last year of their life. As a result, care can be uncoordinated and subject to error.

In construction, failure isn’t an option. Massive structures must stand up straight and withstand all kinds of pressures and potential disasters such as fires and earthquakes. 

Managing Complex Problems: The Rise of the Construction Checklist

To see how managing complex problems works, the author visited the Russian Wharf project in Boston while it was under construction in 2006. The project, completed in 2011, consisted of a high-rise, glass-and-steel waterfront building that incorporated commercial and residential space while retaining historic aspects of the original building on the site.

The nerve center for the project was a room where the construction schedule, essentially a huge checklist, was posted on the wall. This consisted of multiple, large sheets of paper containing numerous computer-created, color-coded lists. They listed every task by order and date — for instance concrete pouring and steel delivery for each story were scheduled at certain times. As each task was completed, the project executive noted it on the schedule and printed out the next phase of work. The construction schedule was designed to build the project in layers, using day-by-day checks to ensure that the knowledge and skills of hundreds of people were correctly applied at the right time and place.

Medicine and the Explosion of Complexity

Medicine is another field that’s continually dealing with complex problems. In trying to do the right things, the challenge of the 21st century is ineptitude , rather than ignorance. It used to be the reverse. For most of human history, we struggled with scientific ignorance. We didn’t understand how things worked or what caused illnesses and how to treat them.

For instance, doctors didn’t know how to treat heart attacks or how to prevent them as recently as the 1950s. Patients were prescribed morphine and bed rest and, if they survived, they lived as invalids. Today, however, we have a host of treatments and procedures that save lives and limit heart damage. Also, we can prevent many heart attacks because we understand and can mitigate the risks of high blood pressure, cholesterol, smoking, and diabetes.

But while science has increased our knowledge dramatically, we still often fail. The reason isn’t lack of money, malpractice, or government or insurance issues. It’s the enormous and ever-increasing complexity of many fields today . We struggle to apply knowledge the right way at the right moment. Under pressure, we make simple mistakes and overlook the obvious. 

For instance, authorities at all levels make numerous mistakes when disasters strike. Attorneys make mistakes in complex legal cases, most commonly administrative errors. We have foreign intelligence failures, cascading banking industry failures, and software design flaws that compromise the personal information of millions of people. Deciding the right treatment among the many options for a heart attack patient can be extremely difficult. Each one involves complexities and pitfalls. 

Getting the right thing done is a challenge too. From research, we know that heart attack patients who will benefit from cardiac balloon therapy should have it within 90 minutes of arriving at a hospital. After that, survival rates drop. But a 2006 study showed less than a 50 percent likelihood that a medical staff could get everything done that needed to be done in less than 90 minutes. Similarly, at least 30 percent of stroke patients get insufficient care, and the same is true for 45 percent of asthma patients and 60 percent of pneumonia patients. Knowing the right steps and trying hard aren’t enough.

A Different Strategy

Those on the receiving end of such failures naturally react with outrage. We can forgive ignorance and accept that others tried their best with what they knew. But when the experts know what to do and fail to do it, we’re likely to blame gross negligence, incompetence, or heartlessness. This ignores the complexity of many jobs today, and the complex problems that come with them.

The problem is that across numerous professions — medicine, engineering, finance, business, government — the level and complexity of our knowledge is more than any individual can apply correctly in all circumstances . Knowledge has saved and also overwhelmed us.

Most professions, especially medicine, have traditionally responded to failure by requiring more training and experience. Training of medical personnel, police, engineers, and others is more extensive than ever. Due to increased training requirements, doctors don’t practice independently until their mid-thirties. But while training and experience are important, expertise doesn’t address human fallibility. We need a different strategy for preventing failure that takes advantage of knowledge and experience but also compensates for human flaws .

The solution is a simple checklist. 

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Amanda Penn

Amanda Penn is a writer and reading specialist. She’s published dozens of articles and book reviews spanning a wide range of topics, including health, relationships, psychology, science, and much more. Amanda was a Fulbright Scholar and has taught in schools in the US and South Africa. Amanda received her Master's Degree in Education from the University of Pennsylvania.

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The Right Way to Solve Complex Business Problems

Corey Phelps, a strategy professor at McGill University, says great problem solvers are hard to find. Even seasoned professionals at the highest levels of organizations regularly...

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Corey Phelps, a strategy professor at McGill University, says great problem solvers are hard to find. Even seasoned professionals at the highest levels of organizations regularly fail to identify the real problem and instead jump to exploring solutions. Phelps identifies the common traps and outlines a research-proven method to solve problems effectively. He’s the coauthor of the book, Cracked it! How to solve big problems and sell solutions like top strategy consultants.

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Welcome to the IdeaCast from Harvard Business Review. I’m Curt Nickisch.

Problem-solving is in demand. It’s considered the top skill for success at management consulting firms. And it’s increasingly desired for everyone, not just new MBA’s.

A report from the World Economic Forum predicts that more than one-third of all jobs across all industries will require complex problem-solving as one of their core skills by 2020.

The problem is, we’re often really bad at problem-solving. Our guest today says even the most educated and experienced of senior leaders go about it the wrong way.

COREY PHELPS: I think this is one of the misnomers about problem-solving. There’s this belief that because we do it so frequently – and especially for senior leaders, they have a lot of experience, they solve problems for a living – and as such we would expect them to be quite good at it. And I think what we find is that they’re not. They don’t solve problems well because they fall prey to basically the foibles of being a human being – they fall prey to the cognitive biases and the pitfalls of problem-solving.

CURT NICKISCH: That’s Corey Phelps. He says fixing these foibles is possible and almost straightforward. You can improve your problem-solving skills by following a disciplined method.

Corey Phelps is a strategy professor at McGill University. He’s also the co-author of the book “Cracked It: How to Solve Big Problems and Sell Solutions like Top Strategy C onsultants.” Corey thanks for coming on the show.

COREY PHELPS: Thank you for the opportunity to talk.

CURT NICKISCH: Another probably many, many biases that prevent people from solving big problems well.

COREY PHELPS: Absolutely.

CURT NICKISCH: What are some of the most common, or your favorite stumbling blocks?

COREY PHELPS: Well, one of my favorites is essentially the problem of jumping to solutions or the challenge of jumping to solutions.

CURT NICKISCH: Oh, come on Corey. That’s so much fun.

COREY PHELPS: It is, and it’s very much a result of how our brains have evolved to process information, but it’s my favorite because we all do it. And especially I would say it happens in organizations because in organizations when you layer on these time pressures and you layer on these concerns about efficiency and productivity, it creates enormous, I would say incentive to say “I don’t have time to carefully define and analyze the problem. I got to get a solution. I got to implement it as quick as possible.” And the fundamental bias I think is, is illustrated beautifully by Danny Kahneman in his book “Thinking, Fast and Slow,” is that our minds are essentially hardwired to think fast.

We are able to pay attention to a tiny little bit of information. We can then weave a very coherent story that makes sense to us. And then we can use that story to jump very quickly to a solution that we just know will work. And if we just were able to move from that approach of what Kahneman and cognitive psychologists called “System 1 thinking” to “System 2 thinking” – that is to slow down, be more deliberative, be more structured – we would be able to better understand the problem that we’re trying to solve and be more effective and exhaustive with the tools that we want to use to understand the problem before we actually go into solution-generation mode.

CURT NICKISCH: Complex problems demand different areas of expertise and often as individuals we’re coming to those problems with one of them. And I wonder if that’s often the problem of problem-solving, which is that a manager is approaching it from their own expertise and because of that, they see the problem through a certain way. Is that one of the cognitive biases that stop people from being effective problem solvers?

COREY PHELPS: Yeah. That’s often referred to as the expertise trap. It basically colors and influences what we pay attention to with respect to a particular problem. And it limits us with respect to the tools that we can bring to bear to solve that problem. In the world of psychology, there’s famous psychologist, Abraham Maslow, who is famous for the hierarchy of needs. He’s also famous for something that was a also known as MaSlow’s axiom, Maslow’s law. It’s also called the law of the instrument, and to paraphrase Maslow, he basically said, “Look, I suppose if the only tool that you have in your toolkit is a hammer, everything looks like a nail.”

His point is that if you’re, for example, a finance expert and your toolkit is the toolkit of let’s say, discounted cash flow analysis for valuation, then you’re going to see problems through that very narrow lens. Now, one of the ways out of this, I think to your point is collaboration becomes fundamentally important. And collaboration starts with the recognition that I don’t have all of the tools, all of the knowledge in me to effectively solve this. So I need to recruit people that can actually help me.

CURT NICKISCH: That’s really interesting. I wonder how much the fact that you have solved a problem before it makes you have a bias for that same solution for future problems?

COREY PHELPS: Yeah, that’s a great question. What you’re alluding to is analogical reasoning, and we know that human beings, one of the things that allows us to operate in novel settings is that we can draw on our past experience. And we do so when it comes to problem solving, often times without being conscious or mentally aware of it. We reach into our memory and we ask ourselves a very simple question: “Have I seen a problem like this before?”

And if it looks familiar to me, the tendency then is to say, “Okay, well what worked in solving that problem that I faced before?” And then to say, “Well, if it worked in that setting, then it should work in this setting.” So that’s reasoning by analogy.

Reasoning by analogy has a great upside. It allows human beings to not become overwhelmed by the tremendous novelty that they face in their daily lives. The downside is that if we don’t truly understand it at sort of a deep level, whether or not the two problems are similar or different, then we can make what cognitive psychologists called surface-level analogies.

And we can then say, “Oh, this looks a lot like the problem I faced before, that solution that worked there is going to easily work here.” And we try that solution and it fails and it fails largely because if we dug a little bit deeper, the two problems actually aren’t much alike at all in terms of their underlying causes.

CURT NICKISCH: The starkest example of this, I think, in your book is Ron Johnson who left Apple to become CEO of JC Penney. Can you talk about that a little bit and what that episode for the company says about this?

COREY PHELPS: So yes, its – Ron Johnson had been hired away from Target in the United States to, by Steve Jobs to help create Apple stores. Apple stores are as many people know the most successful physical retailer on the planet measured by, for example, sales per square foot or per square meter. He’s got the golden touch. He’s created this tremendously successful retail format for Apple.

So the day that it was announced that Ron Johnson was going to step into the CEO role at JC Penney, the stock price of JC Penney went up by almost 18 percent. So clearly he was viewed as the savior. Johnson moves very, very quickly. Within a few months, he announces that he has a strategic plan and it basically comes in three parts.

Part number one is he’s going to eliminate discount pricing. JC Penney had been a very aggressive sales promoter. The second piece of it is he’s going to completely change how they organize merchandise. It’s no longer going to be organized by function – so menswear, housewares, those sorts of things. It’s going to be organized by boutique, so there’s going to be a Levi’s boutique, a Martha Stewart Boutique, a Joe Fresh Boutique and so on.

And it would drop the JC P enney name, they would call it JCP. And he rolls this out over the course of about 12 months across the entire chain of over 1100 stores. What this tells us, he’s so confident in his solution, his strategic transformation, that he doesn’t think it’s worth it to test this out on one or two pilot stores.

CURT NICKISCH: Yeah, he was quoted as saying: “At Apple, we didn’t test anything.”

COREY PHELPS: We didn’t test. Yes. What worked at Apple, he assumed would work at JC Penney. And the critical thing that I think he missed is that JC Penney customers are very different from Apple store customers. In fact, JC Penney customers love the discount. They love the thrill of hunting for a deal.

CURT NICKISCH: Which seems so fundamental to business, right? Understanding your customer. It’s just kind of shocking, I guess, to hear the story.

COREY PHELPS: It is shocking and especially when you consider that Ron Johnson had spent his entire career in retail, so this is someone that had faced, had seen, problems in retailers for decades – for over three decades by the time that he got to JC Penney. So you would expect someone with that degree of experience in that industry wouldn’t make that leap of, well, what worked at Apple stores is going to work at JC Penney stores, but in fact that’s exactly what happened.

CURT NICKISCH: In your book, you essentially suggest four steps that you recommend people use. Tell us about the four steps then.

COREY PHELPS: So in the book we describe what we call the “Four S method,” so four stages, each of which starts with the letter “s”. So the first stage is “state the problem.” Stating the problem is fundamentally about defining what the problem is that you are attempting to solve.

CURT NICKISCH: And you probably would say don’t hurry over that first step or the other three are going to be kind of pointless.

COREY PHELPS: Yeah, that’s exactly the point of of laying out the four s’s. There’s a tremendous amount of desire even amongst senior executives to want to get in and fix the problem. In other words, what’s the trouble? What are the symptoms? What would define success? What are the constraints that we would be operating under? Who owns the problem? And then who are the key stakeholders?

Oftentimes that step is skipped over and we go right into, “I’ve got a hypothesis about what I think the solution is and I’m so obsessed with getting this thing fixed quickly, I’m not going to bother to analyze it particularly well or test the validity of my assumptions. I’m going to go right into implementation mode.”

The second step, what we call “structure the problem” is once you have defined the problem, you need to then start to identify what are the potential causes of that problem. So there are different tools that we talked about in the book that you can structure a problem for analysis. Once you’ve structured the problem for analysis and you’ve conducted the analysis that helps you identify what are the underlying causes that are contributing to it, which will then inform the third stage which is generating solutions for the problem and then testing and evaluating those solutions.

CURT NICKISCH: Is the danger that that third step – generating solutions – is the step that people spend the most time on or have the most fun with?

COREY PHELPS: Yeah. The danger is, is that what that’s naturally what people gravitate towards. So we want to skip over the first two, state and structure.

CURT NICKISCH: As soon as you said it, I was like, “let’s talk about that more.”

COREY PHELPS: Yeah. And we want to jump right into solutioning because people love to talk about their ideas that are going to fix the problem. And that’s actually a useful way to frame a discussion about solutions – we could, or we might do this – because it opens up possibilities for experimentation.

And the problem is that when we often talk about what we could do, we have very little understanding of what the problem is that we’re trying to solve and what are the underlying causes of that problem. Because as you said, solution generation is fun. Look, the classic example is brainstorming. Let’s get a bunch of people in a room and let’s talk about the ideas on how to fix this thing. And again, be deliberate, be disciplined. Do those first stages, the first two stages – state and structure – before you get into the solution generation phase.

CURT NICKISCH: Yeah. The other thing that often happens there is just the lack of awareness of just the cost of the different solutions – how much time, or what they would actually take to do.

COREY PHELPS: Yeah, and again, I’ll go back to that example I used of brainstorming where it’s fun to get a group of people together and talk about our ideas and how to fix the problem. There’s a couple challenges of that. One is what often happens when we do that is we tend to censor the solutions that we come up with. In other words, we ask ourselves, “if I say this idea, people are gonna, think I’m crazy, or people going to say: that’s stupid, that’ll never work, we can’t do that in our organization. It’s going to be too expensive, it’s going to take too much time. We don’t have the resources to do it.”

So brainstorming downside is we we self-sensor, so that’s where you need to have deep insight into your organization in terms of A. what’s going to be feasible, B. what’s going to be desirable on the part of the people that actually have the problem, who you’re trying to solve the problem for and C. from a business standpoint, is it going to be financially attractive for us?

So applying again a set of disciplined criteria that help you choose amongst those ideas for potential solutions. Then the last stage of the process which is selling – because it’s rare in any organization that someone or the group of people that come up with the solution actually have the power and the resources to implement it, so that means they’re going to have to persuade other people to buy into it and want to help.

CURT NICKISCH: Design thinking is another really different method essentially for solving problems or coming up with solutions that just aren’t arrived at through usual problem-solving or usual decision-making processes. I’m just wondering how design thinking comes to play when you’re also outlining these, you know, disciplined methods for stating and solving problems.

COREY PHELPS: For us it’s about choosing the right approach. You know what the potential causes of a problem are. You just don’t know which ones are operating in the particular problem you’re trying to solve. And what that means is that you’ve got a theory – and this is largely the world of strategy consultants – strategy consultants have theories. They have, if you hear them speak, deep understanding of different types of organizational problems, and what they bring is an analytic tool kit that says, “first we’re going to identify all the possible problems, all the possible causes I should say, of this problem. We’re going to figure out which ones are operating and we’re going to use that to come up with a solution.” Then you’ve got problems that you have no idea what the causes are. You’re in a world of unknown unknowns or unk-unks as the operations management people call them.

CURT NICKISCH: That’s terrible.

COREY PHELPS: In other words, you don’t have a theory. So the question is, how do you begin? Well, this is where design thinking can be quite valuable. Design thinking says: first off, let’s find out who are the human beings, the people that are actually experiencing this problem, and let’s go out and let’s talk to them. Let’s observe them. Let’s immerse ourselves in their experience and let’s start to develop an understanding of the causes of the problem from their perspective.

So rather than go into it and say, “I have a theory,” let’s go the design thinking route and let’s actually based upon interactions with users or customers, let’s actually develop a theory. And then we’ll use our new understanding or new insight into the causes of the problem to move into the solution generation phase.

CURT NICKISCH: Problem-solving – we know that that’s something that employers look for when they’re recruiting people. It is one of those phrases that, you know, I’m sure somebody out there has, has the title at a company Chief Problem Solver instead of CEO, right? So, it’s almost one of those phrases that so over used it can lose its meaning.

And if you are being hired or you’re trying to make a case for being on a team that’s tackling a problem, how do you make a compelling case that you are a good problem solver? How can you actually show it?

COREY PHELPS: It’s a great question and then I have two answers to this question. So one is, look at the end of the day, the proof is in the pudding. In other words, can you point to successful solutions that you’ve come up with – solutions that have actually been effective in solving a problem? So that’s one.

The second thing is can you actually articulate how you approach problem-solving? In other words, do you follow a method or are you reinventing the wheel every time you solve a problem? Is it an ad hoc approach? And I think this issue really comes to a head when it comes to the world of strategy consulting firms when they recruit. For example, Mckinsey, you’ve got the Mckinsey problem-solving test, which is again, a test that’s actually trying to elicit the extent to which people are good applicants are good at solving problems

And then you’ve got the case interview. And in the case interview, what they’re looking at is do you have a mastery over certain tools. But what they’re really looking at is, are you actually following a logical process to solve this problem? Because again, what they’re interested in is finding- to your point – people that are going to be good at solving complex organizational problems. So they’re trying to get some evidence that they can demonstrate that they’re good at it and some evidence that they follow a deliberate process.

CURT NICKISCH: So even if you’re not interviewing at a consulting firm, that’s a good approach, to show your thinking, show your process, show the questions you ask?

COREY PHELPS: Yeah, and to your point earlier, at least if we look at what recruiters of MBA students are saying these days, they’re saying, for example, according to the FT’s recent survey, they’re saying that we want people with really good problem solving skills, and by the same token, we find that that’s a skill that’s difficult for us to recruit for. And that reinforces our interest in this area because the fundamental idea for the book is to give people a method. We’re trying to equip not just MBA students but everybody that’s going to face complex problems with a toolkit to solve them better.

CURT NICKISCH: Corey, this has been really great. Thank you.

COREY PHELPS: Thanks for the opportunity. I appreciate it.

CURT NICKISCH: That’s Corey Phelps. He teaches strategy at McGill University, and he co-wrote the book “Cracked It: How to Solve Big Problems and Sell Solutions Like Top Strategy Consultants.”

This episode was produced by Mary Dooe. We got technical help from Rob Eckhardt. Adam Buchholz is our audio product manager.

Thanks for listening to the HBR IdeaCast. I’m Curt Nickisch.

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This article is about decision making and problem solving, partner center.

Career Sidekick

Interview Questions

Comprehensive Interview Guide: 60+ Professions Explored in Detail

26 Good Examples of Problem Solving (Interview Answers)

By Biron Clark

Published: November 15, 2023

Employers like to hire people who can solve problems and work well under pressure. A job rarely goes 100% according to plan, so hiring managers will be more likely to hire you if you seem like you can handle unexpected challenges while staying calm and logical in your approach.

But how do they measure this?

They’re going to ask you interview questions about these problem solving skills, and they might also look for examples of problem solving on your resume and cover letter. So coming up, I’m going to share a list of examples of problem solving, whether you’re an experienced job seeker or recent graduate.

Then I’ll share sample interview answers to, “Give an example of a time you used logic to solve a problem?”

Problem-Solving Defined

It is the ability to identify the problem, prioritize based on gravity and urgency, analyze the root cause, gather relevant information, develop and evaluate viable solutions, decide on the most effective and logical solution, and plan and execute implementation. 

Problem-solving also involves critical thinking, communication, listening, creativity, research, data gathering, risk assessment, continuous learning, decision-making, and other soft and technical skills.

Solving problems not only prevent losses or damages but also boosts self-confidence and reputation when you successfully execute it. The spotlight shines on you when people see you handle issues with ease and savvy despite the challenges. Your ability and potential to be a future leader that can take on more significant roles and tackle bigger setbacks shine through. Problem-solving is a skill you can master by learning from others and acquiring wisdom from their and your own experiences. 

It takes a village to come up with solutions, but a good problem solver can steer the team towards the best choice and implement it to achieve the desired result.

Watch: 26 Good Examples of Problem Solving

Examples of problem solving scenarios in the workplace.

  • Correcting a mistake at work, whether it was made by you or someone else
  • Overcoming a delay at work through problem solving and communication
  • Resolving an issue with a difficult or upset customer
  • Overcoming issues related to a limited budget, and still delivering good work through the use of creative problem solving
  • Overcoming a scheduling/staffing shortage in the department to still deliver excellent work
  • Troubleshooting and resolving technical issues
  • Handling and resolving a conflict with a coworker
  • Solving any problems related to money, customer billing, accounting and bookkeeping, etc.
  • Taking initiative when another team member overlooked or missed something important
  • Taking initiative to meet with your superior to discuss a problem before it became potentially worse
  • Solving a safety issue at work or reporting the issue to those who could solve it
  • Using problem solving abilities to reduce/eliminate a company expense
  • Finding a way to make the company more profitable through new service or product offerings, new pricing ideas, promotion and sale ideas, etc.
  • Changing how a process, team, or task is organized to make it more efficient
  • Using creative thinking to come up with a solution that the company hasn’t used before
  • Performing research to collect data and information to find a new solution to a problem
  • Boosting a company or team’s performance by improving some aspect of communication among employees
  • Finding a new piece of data that can guide a company’s decisions or strategy better in a certain area

Problem Solving Examples for Recent Grads/Entry Level Job Seekers

  • Coordinating work between team members in a class project
  • Reassigning a missing team member’s work to other group members in a class project
  • Adjusting your workflow on a project to accommodate a tight deadline
  • Speaking to your professor to get help when you were struggling or unsure about a project
  • Asking classmates, peers, or professors for help in an area of struggle
  • Talking to your academic advisor to brainstorm solutions to a problem you were facing
  • Researching solutions to an academic problem online, via Google or other methods
  • Using problem solving and creative thinking to obtain an internship or other work opportunity during school after struggling at first

You can share all of the examples above when you’re asked questions about problem solving in your interview. As you can see, even if you have no professional work experience, it’s possible to think back to problems and unexpected challenges that you faced in your studies and discuss how you solved them.

Interview Answers to “Give an Example of an Occasion When You Used Logic to Solve a Problem”

Now, let’s look at some sample interview answers to, “Give me an example of a time you used logic to solve a problem,” since you’re likely to hear this interview question in all sorts of industries.

Example Answer 1:

At my current job, I recently solved a problem where a client was upset about our software pricing. They had misunderstood the sales representative who explained pricing originally, and when their package renewed for its second month, they called to complain about the invoice. I apologized for the confusion and then spoke to our billing team to see what type of solution we could come up with. We decided that the best course of action was to offer a long-term pricing package that would provide a discount. This not only solved the problem but got the customer to agree to a longer-term contract, which means we’ll keep their business for at least one year now, and they’re happy with the pricing. I feel I got the best possible outcome and the way I chose to solve the problem was effective.

Example Answer 2:

In my last job, I had to do quite a bit of problem solving related to our shift scheduling. We had four people quit within a week and the department was severely understaffed. I coordinated a ramp-up of our hiring efforts, I got approval from the department head to offer bonuses for overtime work, and then I found eight employees who were willing to do overtime this month. I think the key problem solving skills here were taking initiative, communicating clearly, and reacting quickly to solve this problem before it became an even bigger issue.

Example Answer 3:

In my current marketing role, my manager asked me to come up with a solution to our declining social media engagement. I assessed our current strategy and recent results, analyzed what some of our top competitors were doing, and then came up with an exact blueprint we could follow this year to emulate our best competitors but also stand out and develop a unique voice as a brand. I feel this is a good example of using logic to solve a problem because it was based on analysis and observation of competitors, rather than guessing or quickly reacting to the situation without reliable data. I always use logic and data to solve problems when possible. The project turned out to be a success and we increased our social media engagement by an average of 82% by the end of the year.

Answering Questions About Problem Solving with the STAR Method

When you answer interview questions about problem solving scenarios, or if you decide to demonstrate your problem solving skills in a cover letter (which is a good idea any time the job description mention problem solving as a necessary skill), I recommend using the STAR method to tell your story.

STAR stands for:

It’s a simple way of walking the listener or reader through the story in a way that will make sense to them. So before jumping in and talking about the problem that needed solving, make sure to describe the general situation. What job/company were you working at? When was this? Then, you can describe the task at hand and the problem that needed solving. After this, describe the course of action you chose and why. Ideally, show that you evaluated all the information you could given the time you had, and made a decision based on logic and fact.

Finally, describe a positive result you got.

Whether you’re answering interview questions about problem solving or writing a cover letter, you should only choose examples where you got a positive result and successfully solved the issue.

Example answer:

Situation : We had an irate client who was a social media influencer and had impossible delivery time demands we could not meet. She spoke negatively about us in her vlog and asked her followers to boycott our products. (Task : To develop an official statement to explain our company’s side, clarify the issue, and prevent it from getting out of hand). Action : I drafted a statement that balanced empathy, understanding, and utmost customer service with facts, logic, and fairness. It was direct, simple, succinct, and phrased to highlight our brand values while addressing the issue in a logical yet sensitive way.   We also tapped our influencer partners to subtly and indirectly share their positive experiences with our brand so we could counter the negative content being shared online.  Result : We got the results we worked for through proper communication and a positive and strategic campaign. The irate client agreed to have a dialogue with us. She apologized to us, and we reaffirmed our commitment to delivering quality service to all. We assured her that she can reach out to us anytime regarding her purchases and that we’d gladly accommodate her requests whenever possible. She also retracted her negative statements in her vlog and urged her followers to keep supporting our brand.

What Are Good Outcomes of Problem Solving?

Whenever you answer interview questions about problem solving or share examples of problem solving in a cover letter, you want to be sure you’re sharing a positive outcome.

Below are good outcomes of problem solving:

  • Saving the company time or money
  • Making the company money
  • Pleasing/keeping a customer
  • Obtaining new customers
  • Solving a safety issue
  • Solving a staffing/scheduling issue
  • Solving a logistical issue
  • Solving a company hiring issue
  • Solving a technical/software issue
  • Making a process more efficient and faster for the company
  • Creating a new business process to make the company more profitable
  • Improving the company’s brand/image/reputation
  • Getting the company positive reviews from customers/clients

Every employer wants to make more money, save money, and save time. If you can assess your problem solving experience and think about how you’ve helped past employers in those three areas, then that’s a great start. That’s where I recommend you begin looking for stories of times you had to solve problems.

Tips to Improve Your Problem Solving Skills

Throughout your career, you’re going to get hired for better jobs and earn more money if you can show employers that you’re a problem solver. So to improve your problem solving skills, I recommend always analyzing a problem and situation before acting. When discussing problem solving with employers, you never want to sound like you rush or make impulsive decisions. They want to see fact-based or data-based decisions when you solve problems.

Next, to get better at solving problems, analyze the outcomes of past solutions you came up with. You can recognize what works and what doesn’t. Think about how you can get better at researching and analyzing a situation, but also how you can get better at communicating, deciding the right people in the organization to talk to and “pull in” to help you if needed, etc.

Finally, practice staying calm even in stressful situations. Take a few minutes to walk outside if needed. Step away from your phone and computer to clear your head. A work problem is rarely so urgent that you cannot take five minutes to think (with the possible exception of safety problems), and you’ll get better outcomes if you solve problems by acting logically instead of rushing to react in a panic.

You can use all of the ideas above to describe your problem solving skills when asked interview questions about the topic. If you say that you do the things above, employers will be impressed when they assess your problem solving ability.

If you practice the tips above, you’ll be ready to share detailed, impressive stories and problem solving examples that will make hiring managers want to offer you the job. Every employer appreciates a problem solver, whether solving problems is a requirement listed on the job description or not. And you never know which hiring manager or interviewer will ask you about a time you solved a problem, so you should always be ready to discuss this when applying for a job.

Related interview questions & answers:

  • How do you handle stress?
  • How do you handle conflict?
  • Tell me about a time when you failed

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  • 26 February 2024

To unravel the origin of life, treat findings as pieces of a bigger puzzle

  • Nick Lane   ORCID: http://orcid.org/0000-0002-5433-3973 0 &
  • Joana C. Xavier   ORCID: http://orcid.org/0000-0001-9242-8968 1

Nick Lane is professor of evolutionary biochemistry in the Division of Biosciences, University College London, UK.

You can also search for this author in PubMed   Google Scholar

Joana C. Xavier is a scientist in the Department of Chemistry, Imperial College London, UK.

One scenario suggests that life began in geothermal pools on land, such as this hot spring in Yellowstone National Park in Wyoming. Credit: Jeff Vanuga/Nature Picture Library

You have full access to this article via your institution.

The origin of life is one of the greatest challenges in science. It transcends conventional disciplinary boundaries, yet has been approached from within those confines for generations. Not surprisingly, these traditions have emphasized different aspects of the question.

Or rather, questions. The origin of life is really an extended continuum from the simplest prebiotic chemistry to the first reproducing cells, with molecular machines encoded by genes — machines such as ribosomes, the protein-building factories found in all cells. Most scientists agree that these nanomachines are a product of selection — but selection for what, where and how?

There is no consensus about what to look for, or where. Nor is there even agreement on whether all life must be carbon-based — although all known life on Earth is. Did meteorites deliver cells or organic material from outer space? Did life start on Earth in the hot waters of hydrothermal systems on land or in deep seas?

Observations alone cannot constrain these possibilities. The few geological traces that hint at early life are enigmatic. Is a bacterium-like imprint really a fossil, or some geochemical structure? Is a weak carbon isotope signature on the surface of a mineral a fingerprint of life (which accumulates the lighter carbon-12) or the result of another type of chemical activity?

Genes are not directly helpful either. Comparing gene sequences in modern organisms allows researchers to reconstruct a ‘tree of life’ going back to some of the earliest cells that have genes. Although the exact genetic make-up of this ancestral population is disputed, by definition it already had genes and proteins and so can tell us little about how they arose.

how to solve complex problems in life

How did life begin? One key ingredient is coming into view

None of this precludes understanding the origin of life, but it does make competing hypotheses hard to prove or disprove unambiguously. Combine that with the overarching importance of the question and it’s clear why the field is beset with over-claims and counter-claims, which in turn warp funding, attention and recognition.

This context has splintered the field. Strongly opposed viewpoints have coexisted for decades over basic questions such as the source of energy and carbon, the need for light and whether selection acts on genes, chemical networks or cells.

To understand how life might have begun, researchers must stop cherry-picking the most beautiful bits of data or the most apparently convincing isolated steps, and explore the implications of these deep differences in context. Depending on the starting point, each hypothesis has different testable predictions. For example, if life started in a warm pond on land, the succession of steps leading from prebiotic chemistry to cells with genes is surprisingly different from those that must be posited if the first cells emerged in deep-sea hydrothermal vents.

Building coherent frameworks — in which all the steps in the continuum fit together — is essential to making real progress. To see why, here we highlight two of the most prominent frameworks, which propose radically distinct environments for the origin of life.

Prebiotic soup

Most people have heard of prebiotic soup. That’s in part because the hypothesis is grounded in the chemistry that works best for making many of the building blocks of living things. In the modern version of this idea, the synthesis of organic molecules begins with derivatives of cyanide, energized by ultraviolet radiation. This chemistry can produce relevant products, such as the nucleotide building blocks of genes, in high yields — although different reactions occur in distinct environments, ranging from laboratory equivalents of the atmosphere to geothermal ponds and streams 1 .

Where did all this cyanide come from? Meteorite impacts might be one source, but there is little agreement about that among geologists. Nor does this approach explain just how these “reservoirs of material … come to life when conditions change” 2 . That is, how compounds that formed under disparate conditions could persist for long periods (potentially millions of years) before somehow coming together and self-assembling into growing cells.

how to solve complex problems in life

It’s time to admit that genes are not the blueprint for life

This framework posits that nucleotides are concentrated in a small pond. To form RNA, the simplest and most versatile genetic material, nucleotides must polymerize. That is most easily achieved by drying them out (polymerization is a type of dehydration reaction). Proponents imagine a succession of wet–dry cycles, in which the pond dries out to form polymers of RNA, then fills again with water containing more nucleotides and so on, cycle after cycle, making more and more RNA 3 .

But this concept raises some difficult questions. It places the onus on an ‘RNA world’, in which RNA acts both as a catalyst (in a similar way to enzymes) and as a genetic template that can be copied. The problems are that there is little evidence that RNA can catalyse many of the reactions attributed to it (such as those required for metabolism); and copying ‘naked’ RNA (that is not enclosed in compartments such as cells) favours the RNA strands that replicate the fastest. Far from building complexity, these tend to get smaller and simpler over time. Worse, by regularly drying everything out, wet–dry cycles keep forming random groupings of RNA (in effect, randomized genomes). The best combinations, which happen to encode multiple useful catalysts, are immediately lost again by re-randomization in the next generation, precluding the ‘vertical inheritance’ that is needed for evolution to build novelty.

If selection on RNA in drying ponds could somehow be made to generate greater complexity, what must it achieve? To make cells that grow and reproduce, RNA must encode metabolism: the network of hundreds of reactions that keeps all cells alive. Modern-day metabolic reactions bear no resemblance to the cyanide chemistry that makes nucleotides in this model. Evolution would therefore need to replace each and every step in metabolism, and there is no evidence that such a wholesale replacement is possible.

Unlike evolving an eye, a process in which intermediates have function, encoding only half the steps of a metabolic pathway (or half the pathways needed for a free-living cell) has little, if any, benefit. Can genes that encode multiple metabolic pathways have arisen at once? The odds against this are so great that the astrophysicist Fred Hoyle once compared it to a tornado blowing through a junkyard and assembling a jumbo jet. It is not good enough to counter that evolution will find a way: a real explanation needs to specify how.

On balance, we would say that prebiotic chemistry starting with cyanide can produce the building blocks of life, but most of the downstream steps predicted by this framework remain problematic.

Hydrothermal systems

Our own favoured scenario is that the chemistry of life reflects the conditions under which life began, in deep-sea hydrothermal systems on the early Earth 4 . In broad brush strokes, this means that gases such as carbon dioxide (the near-universal source of carbon in cells today) and hydrogen feed a network of reactions with a topology resembling metabolism. Genes and proteins arise within this spontaneous protometabolism and promote the flux of materials through the network, leading to cell growth and reproduction. There are plenty of problems here, too, but they differ from those in the prebiotic soup framework.

how to solve complex problems in life

Origin of life theory involving RNA–protein hybrid gets new support

The first problem is that H 2 and CO 2 are not particularly reactive — indeed, their chemistry was largely ignored for decades, although rising interest in green chemistry is changing that. But deep-sea vents are labyrinths of interconnected pores, which have a topology resembling cells — acidic outside and alkaline inside. The flow of protons from the outside to the inside of these pores can drive work in much the same way that the inward flow of protons can drive CO 2 fixation in cells today 5 . Research in the past few years shows that these conditions can drive the synthesis of carboxylic acids 6 and long-chain fatty acids 7 , which can self-assemble into cell-like structures bounded by lipid bilayer membranes 5 .

But many chemists are troubled by the idea that, in the absence of enzymes to serve as catalysts, hydrothermal flow could drive scores of reactions through a network that prefigures metabolism, from CO 2 right up to nucleotides. The chemist Leslie Orgel once dismissed this scenario as an “appeal to magic”. Certainly, further data are required, supporting or otherwise. Multiple steps have now been shown to occur spontaneously in core metabolic pathways (such as the Krebs cycle and amino-acid biosynthesis) without being driven by enzymes 8 , but this is still far from demonstrating flux through the entire network.

Polymerization is another stumbling block. Nucleotides have been polymerized in water on mineral surfaces 9 , but this raises similar questions to those noted for wet–dry cycles about how selection could act. If the problem is solved by polymerizing nucleotides inside growing protocells, mineral surfaces would not have been available. Polymerization would then have needed to happen in cell-like (aqueous gel) conditions, but without enzymes. If serious attempts to synthesize RNA under those conditions fail, the overall framework would need to be modified.

A 13m tall carbonate chimney in the Lost City Hydrothermal Field

A 13-metre-tall carbonate chimney in the Lost City hydrothermal field in the Atlantic Ocean. Credit: Deborah Kelley and Mitch Elend, University of Washington

Conversely, if these difficult problems are resolved, then the hydrothermal scenario offers a promising route to the emergence of genetic information, overcoming Hoyle’s jumbo-jet argument. Patterns in the genetic code suggest direct physical interactions between amino acids and the nucleotides that encode them, especially for those formed most easily by metabolism 5 . Such associations mean that random RNA sequences could act as templates for non-random peptides that have a function in growing protocells. The first genes wouldn’t have had to encode metabolism, but just enhance flux through a spontaneous protometabolism — for example, by enabling the reaction between H 2 and CO 2 .

Thus, in short, the two frameworks have different advantages and disadvantages, and it is premature to dismiss either.

Findings can be true but irrelevant

Similarly probing questions apply to other origins-of-life scenarios. If organic molecules were delivered from space — for instance, in carbonaceous chondrites such as the Murchison meteorite 10 — then how and where did they come together, how did they polymerize, and so on? The delivery of organics from space simply stocks a soup and doesn’t solve most of the downstream problems — with the further issue that such a delivery method is unlikely to have been reliable and consistent at specific locations.

If life started out as droplets known as coacervates, in which immiscible liquids separate into distinct phases that promote different types of chemistry, then one must ask where all the precursors to feed their growth came from. And how did these phase-separated droplets morph into cells with different topology, in which these distinct chemistries now mostly occur under aqueous-gel conditions?

how to solve complex problems in life

Prebiotic chemistry

Similar questions can be asked about ‘eutectic freezing’ (in which growing ice crystals concentrate the surrounding soup) and layered minerals or pores in volcanic rocks, such as basalt or floating pumice, that catalyse organic synthesis.

All of these fragments of scenarios are ‘true’, in that there is empirical evidence supporting each snapshot moment. But the fact that it is possible to make amino acids by passing electrical discharges through a Jovian mixture of gases, as the US chemist Stanley Miller famously did 70 years ago, does not mean that is how life began — merely that this chemistry is possible. Likewise, the fact that analogous chemistry can occur in hydrothermal systems, or from cyanide in terrestrial geothermal systems, or in interstellar space, does not mean that all of these environments were required for life to start, just that this chemistry is favoured under many conditions. The question is always: what happens next?

If none of these scenarios is ‘wrong’, then there is space in the field to pursue multiple frameworks. No one needs to abandon their favoured positions (yet). But brash claims for a breakthrough on the origin of life are unhelpful noise if they do not come in the context of a wider framework. The problem is ultimately answerable only if the whole question is taken seriously.

Look for convergence points

An important feature of these competing frameworks is that they must ultimately converge on cells with genes and proteins — on life as we know it on Earth. This convergence offers new possibilities for collaboration, because any answer will probably feature aspects of more than one framework. Exactly where these convergences occur will depend on which hypothetical steps are disproved.

Cofactors offer a possible convergence point. They got their name because they work together with an enzyme to catalyse a reaction. But from an origins-of-life perspective, the term is misleading because cofactors usually catalyse the same reaction on their own, albeit more slowly. Many cofactors derive from nucleotides, such as nicotinamide adenine dinucleotide. These might prove hard to make when starting with CO 2 . Could it be that cofactors were initially synthesized from cyanide, but, once in circulation, tended to catalyse CO 2 chemistry, now driving a lifelike protometabolism that included their own synthesis 11 ?

how to solve complex problems in life

Bringing space rocks back to Earth could answer some of life’s biggest questions

Perhaps, but this idea also shows how important it is to test predictions within a specific framework first. In the simplest scenario, all of biochemistry begins from CO 2 in a hydrothermal system, whereas the alternative scenario calls for at least two places and two types of chemistry — adding up to much more uncertainty. Occam’s razor says that the simplest scenario should be tested thoroughly first. If the simplest chemistry is shown not to work — that is, if it is not possible to synthesize cofactors from CO 2 without cofactors — then the alternative can be taken seriously.

This question could be approached experimentally or using modern computational chemistry tools, but either way, the best way to make progress is to test the simplest idea to destruction first. If it can be shown not to work, then the convergence point might be real, and should be explored seriously.

Towards an answer

The origins-of-life field faces the same problems with culture and incentives that afflict all of science — overselling ideas towards publication and funding, too little common ground between competing groups and perhaps too much pride: too strong an attachment to favoured scenarios, and too little willingness to be proved wrong. These incentives are amplified by the difficulty of disproving complex interrelated hypotheses involving different disciplines when there is so little direct evidence — no ‘smoking gun’ to be discovered.

Changing this culture will take some work, given the political reality of science — the relentless pressure to publish, to secure funding, tenure or promotion — but it is necessary if the field wishes to continue attracting students. This requires that scientists, but also editors and funders, are aware of the issues that fragmented the field and work to overcome them. We highlight four priorities to begin to move in the right direction.

Train interdisciplinary scientists. Pursuing hypotheses across conventional disciplinary boundaries calls for a new generation of scientists — PhD students, postdoctoral researchers and early-career principal investigators (PIs) — with wide-ranging expertise and a willingness to test specific hypotheses within coherent wider frameworks. The field will clearly benefit from doctoral training that stresses collegiality, interdisciplinarity and the rigorous, open-minded testing of competing hypotheses.

Foster good communication. To promote such a culture, one of us (J.C.X.) co-founded the Origin of Life Early-career Network (OoLEN) in 2020, which has grown to more than 200 international researchers, from students to early-career PIs. It is run by volunteers and has no institutional ties, financial or otherwise. Members engage in debates through regular meetings (online or in-person), disseminate research and write articles together. There is still no shortage of disagreements, but that is part of scientific research and OoLEN promotes a healthy approach to them 12 .

For later-career researchers, conferences could help to reach across divides in similar ways. Physics meetings have provided examples. In one, proponents of loop quantum gravity and string theory switched sides in a debate, framing good-humoured but strong arguments against their own position in a constructive form of ‘steel manning’.

Embrace open science. Accepting that specific hypotheses will be disproved and that frameworks will be reshaped requires the publication of negative results — too often undervalued and unpublished. But it is clearly important for the field to know whether, for example, attempts to synthesize cofactors from CO 2 fail — and, specifically, under what conditions.

Dissemination of negative data could be promoted in several ways. Most valuable is a more systematic use of open-access, community-driven knowledge bases that would host and curate data. These would help to collate experimental conditions, highlight genuine gaps in empirical evidence and enable analysis of large data sets through machine-learning studies.

Improve publishing practices. Researchers should aspire to contextualize their findings in cover letters, papers and press releases, to give a sense of how the work fits into a wider framework. Refraining from hype might seem unrealistic but could work if researchers implemented this practice in their roles as peer reviewers for papers and grants as well as authors.

Journal editors and grant-awarding bodies should also consider how polarized the field is to ensure fair reviews. One way to improve the peer-review process would be to enlist more early-career researchers, who tend to be less entrenched in their positions. Transparent peer review (in which anonymous reports are published with a paper) could also curb bias, because it enables constructive criticism without concealing prejudice.

It is too soon to aim for consensus or unity, and the question is too big; the field needs constructive disunity. Embracing multiple rigorous frameworks for the origin of life, as we advocate here, will promote objectivity, cooperation and falsifiability — good science — while still enabling researchers to focus on what they care most about. Without that, science loses its sparkle and creativity, never more important than here. With it, the field might one day get close to an answer.

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3 Quantum Computing Stocks to Buy on the Dip: February 2024

Quantum computing is a scientific field that uses quantum mechanics to solve complex problems faster than traditional computers. It’s a lesser-known are of technology that is growing by leaps and bounds.

In fact, consulting firm McKinsey & Co. forecasts that the market for quantum computing could reach $1.3 trillion by 2035. Industries within automotive, chemicals, financial services, and life sciences would be the main beneficiaries of the technological advances. Given the huge, largely untapped market, it should come as no surprise that companies are racing to capitalize on the opportunity. Both small start-ups and the most powerful tech firms worldwide are competing to develop the most advanced quantum computers of today and tomorrow.

Let’s explore the top three quantum computing stocks to buy while they are on the dip this month.

IonQ (IONQ)

IonQ (NYSE: IONQ ) is a pure-play quantum computer concern. The company is developing a trapped ion quantum computer and also makes quantum circuits for use by third parties.

IonQ is widely viewed as one of the best ways for investors to gain exposure to the quantum computing sector. Evidence lies in the 93% gain in the company’s share price over the last 12 months. However, IONQ stock has pulled back 14% year to date ( YTD ). Therefore, a prime buying opportunity for investors is present.

The decrease in IONQ stock can be blamed on the fact that the company remains unprofitable. It reported a net loss of $44.8 million in last year’s Q3. However, sales grew 122% year over year ( YOY ) to $6.1 million, and its customer bookings now exceed $100 million. Also, rumors circulate that IonQ could become a takeover target as larger tech companies look for ways to capitalize on the emergence of quantum computing.

IBM (NYSE: IBM ) has its hands in a lot of pots. One of the biggest pots is quantum computing. Last December, IBM unveiled what is being called the world’s most advanced quantum computer at its Thomas J. Watson Research Center.

Called the “The IBM Quantum System Two,” the computer is capable of solving the most complex mathematical problems. Further, this would be achieved in a fraction of the time that it would take the world’s fastest supercomputers.

Also, IBM unveiled a new quantum computing chip in December. Taken together, the Quantum System Two and chip, combined with new code, could lead to IBM producing a series of quantum machines by 2033. Recently, IBM’s Director of Research Dario Gil appear on the TV show 60 Minutes . He believes the IBM’s quantum computers could solve problems in physics, chemistry, engineering, and medicine within minutes. That would take today’s silicon-based supercomputers millions of years to compute.

IBM stock has gained 35% in the last 12 months, including a 14% year-to-date increase.

Alphabet (GOOG/GOOGL)

In addition to being an artificial intelligence ( AI ) leader, Alphabet (NASDAQ: GOOG /NASDAQ: GOOGL ) leads the pack in quantum computing.

The company’s scientists and engineers have been responsible for several major breakthroughs in quantum computing over the years. In 2019, the company announced that it had achieved what’s known as “quantum supremacy.” That’s when a quantum computer solves a problem that a traditional computer couldn’t.

In Alphabet’s case, one of its quantum computers solved a calculation in three minutes and 20 seconds. In contrast, today’s most powerful supercomputers would need thousands of years to achieve it. Additionally, Alphabet has successfully demonstrated for the first time that errors in quantum computing could be reduced by increasing the number of qubits used in processing. This overcomes what was previously viewed as a major stumbling block for quantum computers. GOOGL stock has risen 34% in the last 12 months.

On the date of publication, Joel Baglole held a long position in GOOGL. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.

Joel Baglole has been a business journalist for 20 years. He spent five years as a staff reporter at The Wall Street Journal, and has also written for The Washington Post and Toronto Star newspapers, as well as financial websites such as The Motley Fool and Investopedia.

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    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 How do you identify problems?

  5. Problem-Solving Strategies and Obstacles

    Problem-solving is a vital skill for coping with various challenges in life. This webpage explains the different strategies and obstacles that can affect how you solve problems, and offers tips on how to improve your problem-solving skills. Learn how to identify, analyze, and overcome problems with Verywell Mind.

  6. The Problem-Solving Process

    The best strategy for solving a problem depends largely on the unique situation. In some cases, people are better off learning everything they can about the issue and then using factual knowledge to come up with a solution. In other instances, creativity and insight are the best options.

  7. How To Solve Complex Problems

    Built with ConvertKit How is simple problem-solving different from complex problem-solving? Solving problems is about getting from a currently undesirable state to an intended goal state. In other words, about bridging the gap between "what is" and "what ought to be".

  8. The psychological steps in solving complex personal problems

    Stage 1 - clearly describe your current situation To solve a complex problem, you need to really understand the problem. When stuck in a tough place, I find there is a tendency to describe our problems in overly simplistic ways - 'I am unhappy', 'I'm failing at my studies', 'my work sucks', 'I've got no friends'.

  9. Solve Complex Problems by Expanding Your Thinking

    Too many leaders approach complex problems with either-or thinking: The answer is right or wrong, good or bad, win or lose. To cultivate a nuanced perspective, challenge your understanding of the ...

  10. Complex Problem Solving: What It Is and What It Is Not

    The capacity of the human mind for formulating and solving complex problems is very small compared with the size of the problem whose solution is required for objectively rational behavior in the real world or even for a reasonable approximation to such objective rationality. (p. 198)

  11. Complex Problem-Solving: Definition and Steps

    Ways of implementing solutions When solving complex problems, the considerations often include: The scope of the problem The impact of the problem The resources available to solve the problem Potential changes to the situation Potential solutions Optimal solutions The impact of optimal solutions Ways of implementing solutions

  12. How to Solve Complex Problems: A Step-by-Step Guide

    Here are some more detailed steps you can follow to help solve complex problems: Define the problem clearly: The first step in solving any problem is to define it clearly and understand exactly what you are trying to solve. Gather all the necessary information and identify the root cause of the problem. This may involve conducting research ...

  13. Solving Complex Problems

    Regardless of topic, the students in a section of Solving Complex Problems all work together in the first few class sessions to predict what challenges will arise and to parse the overall problem into a series of 5 to 10 themes. For example, themes might include the environmental context of the problem, engineering challenges, public relations ...

  14. The 7 Timeless Steps to Guide You Through Complex Problem Solving

    1. What Is a Complex Problem? 1.1 Generic Definition of Complex Problems In crude terms, a complex problem presents no trivial or obvious solution. In other words, it shows the following characteristics: Accepts alternative solutions: Complex problems often accept multiple competing solutions.

  15. The Cynefin Framework

    Along with his colleague Mary Boone, he published the framework in the November 2007 issue of the Harvard Business Review. The Cynefin framework (Figure 1 below) is a problem-solving tool that helps you put situations into five "domains" defined by cause-and-effect relationships. This helps you assess your situation more accurately and respond ...

  16. The 4 main types of problems you'll face in life—and how to solve them

    1. The simple problem. The first type of problem in Snowden's framework is simple and obvious. It has already been solved, and there actually is a best practice that works all the time. Once you ...

  17. The Six Systems Thinking Steps to Solve Complex Problems

    Solving complex problems can be achieved through systems thinking, a process that fits the problem, and system dynamics, which is an approach to model systems by emphasizing their feedback loops. Systems Thinking in Six Steps

  18. How to Solve Complex Problems: Embrace Imperfection

    Rule #1: Temporarily change the rules to gain information about the true solution. Even after accepting an imperfect solution, you may find it still isn't good enough. In this case, Christian and Griffiths describe other ways of embracing imperfection to get closer to perfection. First, by adjusting the rules of impossible problems, you can ...

  19. Complex Problems: How to Solve Them, the Simple Way

    Timing and coordination are key. Complex Problem: An example of a complex problem is raising a child. Every child is unique. You learn from raising one child, but the next child may require a different approach. With complex problems like raising a child, the outcome is uncertain. Yet it's possible to raise a child successfully.

  20. How to solve complex problems

    How to solve complex problems efficiently In any scientific project, including data science, if you want strong added value and innovation, you will have to deal with complexity. Nicolas MARTIN · Follow Published in Towards Data Science · 6 min read · Apr 9, 2021 --

  21. Solving Complex Problems Specialization

    To solve complex problems, whether it is the challenge of developing a new product, or Einstein's task of trying to explain how gravity worked - and literally everything else in between - it is not enough to take the problem and apply already existing skills. The skill that has always led to big breakthroughs in any field or industry is the ...

  22. The Right Way to Solve Complex Business Problems

    All episodes. Details. Transcript. December 04, 2018. Corey Phelps, a strategy professor at McGill University, says great problem solvers are hard to find. Even seasoned professionals at the ...

  23. 26 Good Examples of Problem Solving (Interview Answers)

    Examples of Problem Solving Scenarios in the Workplace. Correcting a mistake at work, whether it was made by you or someone else. Overcoming a delay at work through problem solving and communication. Resolving an issue with a difficult or upset customer. Overcoming issues related to a limited budget, and still delivering good work through the ...

  24. To unravel the origin of life, treat findings as pieces of a ...

    Explaining isolated steps on the road from simple chemicals to complex living organisms is not enough. ... solve most of the downstream problems — with the further issue that such a delivery ...

  25. 3 Quantum Computing Stocks to Buy on the Dip: February 2024

    Called the "The IBM Quantum System Two," the computer is capable of solving the most complex mathematical problems. Further, this would be achieved in a fraction of the time that it would take ...

  26. Generalizing Beyond the Training Distribution through Compositional

    This is especially limiting in the embodied setting - where an agent must solve new tasks in new environments. In this talk, I'll introduce the idea of compositional generative modeling, which enables generalization beyond the training data by building complex generative models from smaller constituents.