Identify Goal
Define Problem
Define Problem
Gather Data
Define Causes
Identify Options
Clarify Problem
Generate Ideas
Evaluate Options
Generate Ideas
Choose the Best Solution
Implement Solution
Select Solution
Take Action
MacLeod offers her own problem solving procedure, which echoes the above steps:
“1. Recognize the Problem: State what you see. Sometimes the problem is covert. 2. Identify: Get the facts — What exactly happened? What is the issue? 3. and 4. Explore and Connect: Dig deeper and encourage group members to relate their similar experiences. Now you're getting more into the feelings and background [of the situation], not just the facts. 5. Possible Solutions: Consider and brainstorm ideas for resolution. 6. Implement: Choose a solution and try it out — this could be role play and/or a discussion of how the solution would be put in place. 7. Evaluate: Revisit to see if the solution was successful or not.”
Many of these problem solving techniques can be used in concert with one another, or multiple can be appropriate for any given problem. It’s less about facilitating a perfect CPS session, and more about encouraging team members to continually think outside the box and push beyond personal boundaries that inhibit their innovative thinking. So, try out several methods, find those that resonate best with your team, and continue adopting new techniques and adapting your processes along the way.
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In this episode of the McKinsey Podcast , Simon London speaks with Charles Conn, CEO of venture-capital firm Oxford Sciences Innovation, and McKinsey senior partner Hugo Sarrazin about the complexities of different problem-solving strategies.
Podcast transcript
Simon London: Hello, and welcome to this episode of the McKinsey Podcast , with me, Simon London. What’s the number-one skill you need to succeed professionally? Salesmanship, perhaps? Or a facility with statistics? Or maybe the ability to communicate crisply and clearly? Many would argue that at the very top of the list comes problem solving: that is, the ability to think through and come up with an optimal course of action to address any complex challenge—in business, in public policy, or indeed in life.
Looked at this way, it’s no surprise that McKinsey takes problem solving very seriously, testing for it during the recruiting process and then honing it, in McKinsey consultants, through immersion in a structured seven-step method. To discuss the art of problem solving, I sat down in California with McKinsey senior partner Hugo Sarrazin and also with Charles Conn. Charles is a former McKinsey partner, entrepreneur, executive, and coauthor of the book Bulletproof Problem Solving: The One Skill That Changes Everything [John Wiley & Sons, 2018].
Charles and Hugo, welcome to the podcast. Thank you for being here.
Hugo Sarrazin: Our pleasure.
Charles Conn: It’s terrific to be here.
Simon London: Problem solving is a really interesting piece of terminology. It could mean so many different things. I have a son who’s a teenage climber. They talk about solving problems. Climbing is problem solving. Charles, when you talk about problem solving, what are you talking about?
Charles Conn: For me, problem solving is the answer to the question “What should I do?” It’s interesting when there’s uncertainty and complexity, and when it’s meaningful because there are consequences. Your son’s climbing is a perfect example. There are consequences, and it’s complicated, and there’s uncertainty—can he make that grab? I think we can apply that same frame almost at any level. You can think about questions like “What town would I like to live in?” or “Should I put solar panels on my roof?”
You might think that’s a funny thing to apply problem solving to, but in my mind it’s not fundamentally different from business problem solving, which answers the question “What should my strategy be?” Or problem solving at the policy level: “How do we combat climate change?” “Should I support the local school bond?” I think these are all part and parcel of the same type of question, “What should I do?”
I’m a big fan of structured problem solving. By following steps, we can more clearly understand what problem it is we’re solving, what are the components of the problem that we’re solving, which components are the most important ones for us to pay attention to, which analytic techniques we should apply to those, and how we can synthesize what we’ve learned back into a compelling story. That’s all it is, at its heart.
I think sometimes when people think about seven steps, they assume that there’s a rigidity to this. That’s not it at all. It’s actually to give you the scope for creativity, which often doesn’t exist when your problem solving is muddled.
Simon London: You were just talking about the seven-step process. That’s what’s written down in the book, but it’s a very McKinsey process as well. Without getting too deep into the weeds, let’s go through the steps, one by one. You were just talking about problem definition as being a particularly important thing to get right first. That’s the first step. Hugo, tell us about that.
Hugo Sarrazin: It is surprising how often people jump past this step and make a bunch of assumptions. The most powerful thing is to step back and ask the basic questions—“What are we trying to solve? What are the constraints that exist? What are the dependencies?” Let’s make those explicit and really push the thinking and defining. At McKinsey, we spend an enormous amount of time in writing that little statement, and the statement, if you’re a logic purist, is great. You debate. “Is it an ‘or’? Is it an ‘and’? What’s the action verb?” Because all these specific words help you get to the heart of what matters.
Simon London: So this is a concise problem statement.
Hugo Sarrazin: Yeah. It’s not like “Can we grow in Japan?” That’s interesting, but it is “What, specifically, are we trying to uncover in the growth of a product in Japan? Or a segment in Japan? Or a channel in Japan?” When you spend an enormous amount of time, in the first meeting of the different stakeholders, debating this and having different people put forward what they think the problem definition is, you realize that people have completely different views of why they’re here. That, to me, is the most important step.
Charles Conn: I would agree with that. For me, the problem context is critical. When we understand “What are the forces acting upon your decision maker? How quickly is the answer needed? With what precision is the answer needed? Are there areas that are off limits or areas where we would particularly like to find our solution? Is the decision maker open to exploring other areas?” then you not only become more efficient, and move toward what we call the critical path in problem solving, but you also make it so much more likely that you’re not going to waste your time or your decision maker’s time.
How often do especially bright young people run off with half of the idea about what the problem is and start collecting data and start building models—only to discover that they’ve really gone off half-cocked.
Hugo Sarrazin: Yeah.
Charles Conn: And in the wrong direction.
Simon London: OK. So step one—and there is a real art and a structure to it—is define the problem. Step two, Charles?
Charles Conn: My favorite step is step two, which is to use logic trees to disaggregate the problem. Every problem we’re solving has some complexity and some uncertainty in it. The only way that we can really get our team working on the problem is to take the problem apart into logical pieces.
What we find, of course, is that the way to disaggregate the problem often gives you an insight into the answer to the problem quite quickly. I love to do two or three different cuts at it, each one giving a bit of a different insight into what might be going wrong. By doing sensible disaggregations, using logic trees, we can figure out which parts of the problem we should be looking at, and we can assign those different parts to team members.
Simon London: What’s a good example of a logic tree on a sort of ratable problem?
Charles Conn: Maybe the easiest one is the classic profit tree. Almost in every business that I would take a look at, I would start with a profit or return-on-assets tree. In its simplest form, you have the components of revenue, which are price and quantity, and the components of cost, which are cost and quantity. Each of those can be broken out. Cost can be broken into variable cost and fixed cost. The components of price can be broken into what your pricing scheme is. That simple tree often provides insight into what’s going on in a business or what the difference is between that business and the competitors.
If we add the leg, which is “What’s the asset base or investment element?”—so profit divided by assets—then we can ask the question “Is the business using its investments sensibly?” whether that’s in stores or in manufacturing or in transportation assets. I hope we can see just how simple this is, even though we’re describing it in words.
When I went to work with Gordon Moore at the Moore Foundation, the problem that he asked us to look at was “How can we save Pacific salmon?” Now, that sounds like an impossible question, but it was amenable to precisely the same type of disaggregation and allowed us to organize what became a 15-year effort to improve the likelihood of good outcomes for Pacific salmon.
Simon London: Now, is there a danger that your logic tree can be impossibly large? This, I think, brings us onto the third step in the process, which is that you have to prioritize.
Charles Conn: Absolutely. The third step, which we also emphasize, along with good problem definition, is rigorous prioritization—we ask the questions “How important is this lever or this branch of the tree in the overall outcome that we seek to achieve? How much can I move that lever?” Obviously, we try and focus our efforts on ones that have a big impact on the problem and the ones that we have the ability to change. With salmon, ocean conditions turned out to be a big lever, but not one that we could adjust. We focused our attention on fish habitats and fish-harvesting practices, which were big levers that we could affect.
People spend a lot of time arguing about branches that are either not important or that none of us can change. We see it in the public square. When we deal with questions at the policy level—“Should you support the death penalty?” “How do we affect climate change?” “How can we uncover the causes and address homelessness?”—it’s even more important that we’re focusing on levers that are big and movable.
Simon London: Let’s move swiftly on to step four. You’ve defined your problem, you disaggregate it, you prioritize where you want to analyze—what you want to really look at hard. Then you got to the work plan. Now, what does that mean in practice?
Hugo Sarrazin: Depending on what you’ve prioritized, there are many things you could do. It could be breaking the work among the team members so that people have a clear piece of the work to do. It could be defining the specific analyses that need to get done and executed, and being clear on time lines. There’s always a level-one answer, there’s a level-two answer, there’s a level-three answer. Without being too flippant, I can solve any problem during a good dinner with wine. It won’t have a whole lot of backing.
Simon London: Not going to have a lot of depth to it.
Hugo Sarrazin: No, but it may be useful as a starting point. If the stakes are not that high, that could be OK. If it’s really high stakes, you may need level three and have the whole model validated in three different ways. You need to find a work plan that reflects the level of precision, the time frame you have, and the stakeholders you need to bring along in the exercise.
Charles Conn: I love the way you’ve described that, because, again, some people think of problem solving as a linear thing, but of course what’s critical is that it’s iterative. As you say, you can solve the problem in one day or even one hour.
Charles Conn: We encourage our teams everywhere to do that. We call it the one-day answer or the one-hour answer. In work planning, we’re always iterating. Every time you see a 50-page work plan that stretches out to three months, you know it’s wrong. It will be outmoded very quickly by that learning process that you described. Iterative problem solving is a critical part of this. Sometimes, people think work planning sounds dull, but it isn’t. It’s how we know what’s expected of us and when we need to deliver it and how we’re progressing toward the answer. It’s also the place where we can deal with biases. Bias is a feature of every human decision-making process. If we design our team interactions intelligently, we can avoid the worst sort of biases.
Simon London: Here we’re talking about cognitive biases primarily, right? It’s not that I’m biased against you because of your accent or something. These are the cognitive biases that behavioral sciences have shown we all carry around, things like anchoring, overoptimism—these kinds of things.
Both: Yeah.
Charles Conn: Availability bias is the one that I’m always alert to. You think you’ve seen the problem before, and therefore what’s available is your previous conception of it—and we have to be most careful about that. In any human setting, we also have to be careful about biases that are based on hierarchies, sometimes called sunflower bias. I’m sure, Hugo, with your teams, you make sure that the youngest team members speak first. Not the oldest team members, because it’s easy for people to look at who’s senior and alter their own creative approaches.
Hugo Sarrazin: It’s helpful, at that moment—if someone is asserting a point of view—to ask the question “This was true in what context?” You’re trying to apply something that worked in one context to a different one. That can be deadly if the context has changed, and that’s why organizations struggle to change. You promote all these people because they did something that worked well in the past, and then there’s a disruption in the industry, and they keep doing what got them promoted even though the context has changed.
Simon London: Right. Right.
Hugo Sarrazin: So it’s the same thing in problem solving.
Charles Conn: And it’s why diversity in our teams is so important. It’s one of the best things about the world that we’re in now. We’re likely to have people from different socioeconomic, ethnic, and national backgrounds, each of whom sees problems from a slightly different perspective. It is therefore much more likely that the team will uncover a truly creative and clever approach to problem solving.
Simon London: Let’s move on to step five. You’ve done your work plan. Now you’ve actually got to do the analysis. The thing that strikes me here is that the range of tools that we have at our disposal now, of course, is just huge, particularly with advances in computation, advanced analytics. There’s so many things that you can apply here. Just talk about the analysis stage. How do you pick the right tools?
Charles Conn: For me, the most important thing is that we start with simple heuristics and explanatory statistics before we go off and use the big-gun tools. We need to understand the shape and scope of our problem before we start applying these massive and complex analytical approaches.
Simon London: Would you agree with that?
Hugo Sarrazin: I agree. I think there are so many wonderful heuristics. You need to start there before you go deep into the modeling exercise. There’s an interesting dynamic that’s happening, though. In some cases, for some types of problems, it is even better to set yourself up to maximize your learning. Your problem-solving methodology is test and learn, test and learn, test and learn, and iterate. That is a heuristic in itself, the A/B testing that is used in many parts of the world. So that’s a problem-solving methodology. It’s nothing different. It just uses technology and feedback loops in a fast way. The other one is exploratory data analysis. When you’re dealing with a large-scale problem, and there’s so much data, I can get to the heuristics that Charles was talking about through very clever visualization of data.
You test with your data. You need to set up an environment to do so, but don’t get caught up in neural-network modeling immediately. You’re testing, you’re checking—“Is the data right? Is it sound? Does it make sense?”—before you launch too far.
Simon London: You do hear these ideas—that if you have a big enough data set and enough algorithms, they’re going to find things that you just wouldn’t have spotted, find solutions that maybe you wouldn’t have thought of. Does machine learning sort of revolutionize the problem-solving process? Or are these actually just other tools in the toolbox for structured problem solving?
Charles Conn: It can be revolutionary. There are some areas in which the pattern recognition of large data sets and good algorithms can help us see things that we otherwise couldn’t see. But I do think it’s terribly important we don’t think that this particular technique is a substitute for superb problem solving, starting with good problem definition. Many people use machine learning without understanding algorithms that themselves can have biases built into them. Just as 20 years ago, when we were doing statistical analysis, we knew that we needed good model definition, we still need a good understanding of our algorithms and really good problem definition before we launch off into big data sets and unknown algorithms.
Simon London: Step six. You’ve done your analysis.
Charles Conn: I take six and seven together, and this is the place where young problem solvers often make a mistake. They’ve got their analysis, and they assume that’s the answer, and of course it isn’t the answer. The ability to synthesize the pieces that came out of the analysis and begin to weave those into a story that helps people answer the question “What should I do?” This is back to where we started. If we can’t synthesize, and we can’t tell a story, then our decision maker can’t find the answer to “What should I do?”
Simon London: But, again, these final steps are about motivating people to action, right?
Charles Conn: Yeah.
Simon London: I am slightly torn about the nomenclature of problem solving because it’s on paper, right? Until you motivate people to action, you actually haven’t solved anything.
Charles Conn: I love this question because I think decision-making theory, without a bias to action, is a waste of time. Everything in how I approach this is to help people take action that makes the world better.
Simon London: Hence, these are absolutely critical steps. If you don’t do this well, you’ve just got a bunch of analysis.
Charles Conn: We end up in exactly the same place where we started, which is people speaking across each other, past each other in the public square, rather than actually working together, shoulder to shoulder, to crack these important problems.
Simon London: In the real world, we have a lot of uncertainty—arguably, increasing uncertainty. How do good problem solvers deal with that?
Hugo Sarrazin: At every step of the process. In the problem definition, when you’re defining the context, you need to understand those sources of uncertainty and whether they’re important or not important. It becomes important in the definition of the tree.
You need to think carefully about the branches of the tree that are more certain and less certain as you define them. They don’t have equal weight just because they’ve got equal space on the page. Then, when you’re prioritizing, your prioritization approach may put more emphasis on things that have low probability but huge impact—or, vice versa, may put a lot of priority on things that are very likely and, hopefully, have a reasonable impact. You can introduce that along the way. When you come back to the synthesis, you just need to be nuanced about what you’re understanding, the likelihood.
Often, people lack humility in the way they make their recommendations: “This is the answer.” They’re very precise, and I think we would all be well-served to say, “This is a likely answer under the following sets of conditions” and then make the level of uncertainty clearer, if that is appropriate. It doesn’t mean you’re always in the gray zone; it doesn’t mean you don’t have a point of view. It just means that you can be explicit about the certainty of your answer when you make that recommendation.
Simon London: So it sounds like there is an underlying principle: “Acknowledge and embrace the uncertainty. Don’t pretend that it isn’t there. Be very clear about what the uncertainties are up front, and then build that into every step of the process.”
Hugo Sarrazin: Every step of the process.
Simon London: Yeah. We have just walked through a particular structured methodology for problem solving. But, of course, this is not the only structured methodology for problem solving. One that is also very well-known is design thinking, which comes at things very differently. So, Hugo, I know you have worked with a lot of designers. Just give us a very quick summary. Design thinking—what is it, and how does it relate?
Hugo Sarrazin: It starts with an incredible amount of empathy for the user and uses that to define the problem. It does pause and go out in the wild and spend an enormous amount of time seeing how people interact with objects, seeing the experience they’re getting, seeing the pain points or joy—and uses that to infer and define the problem.
Simon London: Problem definition, but out in the world.
Hugo Sarrazin: With an enormous amount of empathy. There’s a huge emphasis on empathy. Traditional, more classic problem solving is you define the problem based on an understanding of the situation. This one almost presupposes that we don’t know the problem until we go see it. The second thing is you need to come up with multiple scenarios or answers or ideas or concepts, and there’s a lot of divergent thinking initially. That’s slightly different, versus the prioritization, but not for long. Eventually, you need to kind of say, “OK, I’m going to converge again.” Then you go and you bring things back to the customer and get feedback and iterate. Then you rinse and repeat, rinse and repeat. There’s a lot of tactile building, along the way, of prototypes and things like that. It’s very iterative.
Simon London: So, Charles, are these complements or are these alternatives?
Charles Conn: I think they’re entirely complementary, and I think Hugo’s description is perfect. When we do problem definition well in classic problem solving, we are demonstrating the kind of empathy, at the very beginning of our problem, that design thinking asks us to approach. When we ideate—and that’s very similar to the disaggregation, prioritization, and work-planning steps—we do precisely the same thing, and often we use contrasting teams, so that we do have divergent thinking. The best teams allow divergent thinking to bump them off whatever their initial biases in problem solving are. For me, design thinking gives us a constant reminder of creativity, empathy, and the tactile nature of problem solving, but it’s absolutely complementary, not alternative.
Simon London: I think, in a world of cross-functional teams, an interesting question is do people with design-thinking backgrounds really work well together with classical problem solvers? How do you make that chemistry happen?
Hugo Sarrazin: Yeah, it is not easy when people have spent an enormous amount of time seeped in design thinking or user-centric design, whichever word you want to use. If the person who’s applying classic problem-solving methodology is very rigid and mechanical in the way they’re doing it, there could be an enormous amount of tension. If there’s not clarity in the role and not clarity in the process, I think having the two together can be, sometimes, problematic.
The second thing that happens often is that the artifacts the two methodologies try to gravitate toward can be different. Classic problem solving often gravitates toward a model; design thinking migrates toward a prototype. Rather than writing a big deck with all my supporting evidence, they’ll bring an example, a thing, and that feels different. Then you spend your time differently to achieve those two end products, so that’s another source of friction.
Now, I still think it can be an incredibly powerful thing to have the two—if there are the right people with the right mind-set, if there is a team that is explicit about the roles, if we’re clear about the kind of outcomes we are attempting to bring forward. There’s an enormous amount of collaborativeness and respect.
Simon London: But they have to respect each other’s methodology and be prepared to flex, maybe, a little bit, in how this process is going to work.
Hugo Sarrazin: Absolutely.
Simon London: The other area where, it strikes me, there could be a little bit of a different sort of friction is this whole concept of the day-one answer, which is what we were just talking about in classical problem solving. Now, you know that this is probably not going to be your final answer, but that’s how you begin to structure the problem. Whereas I would imagine your design thinkers—no, they’re going off to do their ethnographic research and get out into the field, potentially for a long time, before they come back with at least an initial hypothesis.
Hugo Sarrazin: That is a great callout, and that’s another difference. Designers typically will like to soak into the situation and avoid converging too quickly. There’s optionality and exploring different options. There’s a strong belief that keeps the solution space wide enough that you can come up with more radical ideas. If there’s a large design team or many designers on the team, and you come on Friday and say, “What’s our week-one answer?” they’re going to struggle. They’re not going to be comfortable, naturally, to give that answer. It doesn’t mean they don’t have an answer; it’s just not where they are in their thinking process.
Simon London: I think we are, sadly, out of time for today. But Charles and Hugo, thank you so much.
Charles Conn: It was a pleasure to be here, Simon.
Hugo Sarrazin: It was a pleasure. Thank you.
Simon London: And thanks, as always, to you, our listeners, for tuning into this episode of the McKinsey Podcast . If you want to learn more about problem solving, you can find the book, Bulletproof Problem Solving: The One Skill That Changes Everything , online or order it through your local bookstore. To learn more about McKinsey, you can of course find us at McKinsey.com.
Charles Conn is CEO of Oxford Sciences Innovation and an alumnus of McKinsey’s Sydney office. Hugo Sarrazin is a senior partner in the Silicon Valley office, where Simon London, a member of McKinsey Publishing, is also based.
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June 14, 2022 - 10 min read
Solving complex problems may be difficult but it doesn't have to be excruciating. You just need the right frame of mind and a process for untangling the problem at hand.
Luckily for you, there are plenty of techniques available to solve whatever problems come at you in the workplace.
When faced with a doozy of a problem, where do you start? And what problem-solving techniques can you use right now that can help you make good decisions?
Today's post will give you tips and techniques for solving complex problems so you can untangle any complication like an expert.
At its core, problem-solving is a methodical four-step process. You may even recall these steps from when you were first introduced to the Scientific Method.
When applying problem-solving techniques, you will be using a variation of these steps as your foundation.
Takeaway: Before you can solve a problem, seek to understand it fully.
Time to get creative! You might think this will just be a list of out-of-the-box ways to brainstorm ideas. Not exactly.
Creative problem solving (CPS) is actually a formal process formulated by Sidney Parnes and Alex Faickney Osborn , who is thought of as the father of traditional brainstorming (and the "O" in famous advertising agency BBDO).
Their creative problem solving process emphasizes several things, namely:
Takeaway: When brainstorming solutions, generate ideas first by using questions and building off of existing ideas. Do all evaluating and judging later.
If you take a look at the history of problem-solving techniques in psychology, you'll come across a wide spectrum of interesting ideas that could be helpful.
In 1911, the American psychologist Edward Thorndike observed cats figuring out how to escape from the cage he placed them in. From this, Thorndike developed his law of effect , which states: If you succeed via trial-and-error, you're more likely to use those same actions and ideas that led to your previous success when you face the problem again.
Takeaway: Your past experience can inform and shed light on the problem you face now. Recall. Explore.
The Gestalt psychologists built on Thorndike's ideas when they proposed that problem-solving can happen via reproductive thinking — which is not about sex, but rather solving a problem by using past experience and reproducing that experience to solve the current problem.
What's interesting about Gestalt psychology is how they view barriers to problem-solving. Here are two such barriers:
Takeaway: Think outside of the box! And by box, we mean outside of the past experience you're holding on to, or outside any preconceived ideas on how a tool is conventionally used.
Hurson's productive thinking model.
In his book "Think Better," author and creativity guru Tim Hurson proposed a six-step model for solving problems creatively. The steps in his Productive Thinking Model are:
The most important part of defining the problem is looking at the possible root cause. You'll need to ask yourself questions like: Where and when is it happening? How is it occurring? With whom is it happening? Why is it happening?
You can get to the root cause with a fishbone diagram (also known as an Ishikawa diagram or a cause and effect diagram).
Basically, you put the effect on the right side as the problem statement. Then you list all possible causes on the left, grouped into larger cause categories. The resulting shape resembles a fish skeleton. Which is a perfect way to say, "This problem smells fishy."
Analogical thinking uses information from one area to help with a problem in a different area. In short, solving a different problem can lead you to find a solution to the actual problem. Watch out though! Analogies are difficult for beginners and take some getting used to.
An example: In the "radiation problem," a doctor has a patient with a tumor that cannot be operated on. The doctor can use rays to destroy the tumor but it also destroys healthy tissue.
Two researchers, Gick and Holyoak , noted that people solved the radiation problem much more easily after being asked to read a story about an invading general who must capture the fortress of a king but be careful to avoid landmines that will detonate if large forces traverse the streets. The general then sends small forces of men down different streets so the army can converge at the fortress at the same time and can capture it at full force.
In her book " The Architecture of All Abundance ," author Lenedra J. Carroll (aka the mother of pop star Jewel) talks about a question-and-answer technique for getting out of a problem.
When faced with a problem, ask yourself a question about it and brainstorm 12 answers ("12 what elses") to that problem. Then you can go further by taking one answer, turning it into a question and generating 12 more "what elses." Repeat until the solution is golden brown, fully baked, and ready to take out of the oven.
Hopefully you find these different techniques useful and they get your imagination rolling with ideas on how to solve different problems.
And if that's the case, then you have four different takeaways to use the next time a problem gets you tangled up:
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Do you have a problem-solving technique that has worked wonders for your organization? Hit the comments below and share your wisdom!
Lionel is a former Content Marketing Manager of Wrike. He is also a blogger since 1997, a productivity enthusiast, a project management newbie, a musician and producer of electronic downtempo music, a father of three, and a husband of one.
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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.
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.
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.
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.
So what else makes a problem complex? Here are seven additional characteristics (from Funke and Hester and Adams ).
“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.
Let’s look at what scientists, researchers, and system thinkers have come up with in terms of a definition for solving a complex problem.
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.”
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.”
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.”
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.”
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.
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?
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:
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.”
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.
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.
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.
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.
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.
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.
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.
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.
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.
In my online course , we generally follow a seven-step method:
Of course, each of these steps involves testing to see what works and consistently evaluating our process and progress.
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.
If you need help developing your complex problem-solving skills, I have an online class where you can learn everything you need to know.
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Effective problem solving is all about using the right process and following a plan tailored to the issue at hand. Recognizing your team or organization has an issue isn’t enough to come up with effective problem solving strategies.
To truly understand a problem and develop appropriate solutions, you will want to follow a solid process, follow the necessary problem solving steps, and bring all of your problem solving skills to the table. We’ll forst look at what problem solving strategies you can employ with your team when looking for a way to approach the process. We’ll then discuss the problem solving skills you need to be more effective at solving problems, complete with an activity from the SessionLab library you can use to develop that skill in your team.
Let’s get to it!
What skills do i need to be an effective problem solver, how can i improve my problem solving skills.
Problem solving strategies are methods of approaching and facilitating the process of problem-solving with a set of techniques , actions, and processes. Different strategies are more effective if you are trying to solve broad problems such as achieving higher growth versus more focused problems like, how do we improve our customer onboarding process?
Broadly, the problem solving steps outlined above should be included in any problem solving strategy though choosing where to focus your time and what approaches should be taken is where they begin to differ. You might find that some strategies ask for the problem identification to be done prior to the session or that everything happens in the course of a one day workshop.
The key similarity is that all good problem solving strategies are structured and designed. Four hours of open discussion is never going to be as productive as a four-hour workshop designed to lead a group through a problem solving process.
Good problem solving strategies are tailored to the team, organization and problem you will be attempting to solve. Here are some example problem solving strategies you can learn from or use to get started.
Often, the first step to solving problems or organizational challenges is bringing a group together effectively. Most teams have the tools, knowledge, and expertise necessary to solve their challenges – they just need some guidance in how to use leverage those skills and a structure and format that allows people to focus their energies.
Facilitated workshops are one of the most effective ways of solving problems of any scale. By designing and planning your workshop carefully, you can tailor the approach and scope to best fit the needs of your team and organization.
Workshops are an effective strategy for solving problems. By using tried and test facilitation techniques and methods, you can design and deliver a workshop that is perfectly suited to the unique variables of your organization. You may only have the capacity for a half-day workshop and so need a problem solving process to match.
By using our session planner tool and importing methods from our library of 700+ facilitation techniques, you can create the right problem solving workshop for your team. It might be that you want to encourage creative thinking or look at things from a new angle to unblock your groups approach to problem solving. By tailoring your workshop design to the purpose, you can help ensure great results.
One of the main benefits of a workshop is the structured approach to problem solving. Not only does this mean that the workshop itself will be successful, but many of the methods and techniques will help your team improve their working processes outside of the workshop.
We believe that workshops are one of the best tools you can use to improve the way your team works together. Start with a problem solving workshop and then see what team building, culture or design workshops can do for your organization!
Great for:
By using design thinking principles and methods, a design sprint is a great way of identifying, prioritizing and prototyping solutions to long term challenges that can help solve major organizational problems with quick action and measurable results.
Some familiarity with design thinking is useful, though not integral, and this strategy can really help a team align if there is some discussion around which problems should be approached first.
The stage-based structure of the design sprint is also very useful for teams new to design thinking. The inspiration phase, where you look to competitors that have solved your problem, and the rapid prototyping and testing phases are great for introducing new concepts that will benefit a team in all their future work.
It can be common for teams to look inward for solutions and so looking to the market for solutions you can iterate on can be very productive. Instilling an agile prototyping and testing mindset can also be great when helping teams move forwards – generating and testing solutions quickly can help save time in the long run and is also pretty exciting!
Organizational challenges and problems are often complicated and large scale in nature. Sometimes, trying to resolve such an issue in one swoop is simply unachievable or overwhelming. Try breaking down such problems into smaller issues that you can work on step by step. You may not be able to solve the problem of churning customers off the bat, but you can work with your team to identify smaller effort but high impact elements and work on those first.
This problem solving strategy can help a team generate momentum, prioritize and get some easy wins. It’s also a great strategy to employ with teams who are just beginning to learn how to approach the problem solving process. If you want some insight into a way to employ this strategy, we recommend looking at our design sprint template below!
Some problems are best solved by introducing a major shift in perspective or by using new methodologies that encourage your team to think differently.
Props and tools such as Methodkit , which uses a card-based toolkit for facilitation, or Lego Serious Play can be great ways to engage your team and find an inclusive, democratic problem solving strategy. Remember that play and creativity are great tools for achieving change and whatever the challenge, engaging your participants can be very effective where other strategies may have failed.
LEGO Serious Play is a problem solving methodology designed to get participants thinking differently by using 3D models and kinesthetic learning styles. By physically building LEGO models based on questions and exercises, participants are encouraged to think outside of the box and create their own responses.
Collaborate LEGO Serious Play exercises are also used to encourage communication and build problem solving skills in a group. By using this problem solving process, you can often help different kinds of learners and personality types contribute and unblock organizational problems with creative thinking.
Problem solving strategies like LEGO Serious Play are super effective at helping a team solve more skills-based problems such as communication between teams or a lack of creative thinking. Some problems are not suited to LEGO Serious Play and require a different problem solving strategy.
Card decks and method kids are great tools for those new to facilitation or for whom facilitation is not the primary role. Card decks such as the emotional culture deck can be used for complete workshops and in many cases, can be used right out of the box. Methodkit has a variety of kits designed for scenarios ranging from personal development through to personas and global challenges so you can find the right deck for your particular needs.
Having an easy to use framework that encourages creativity or a new approach can take some of the friction or planning difficulties out of the workshop process and energize a team in any setting. Simplicity is the key with these methods. By ensuring everyone on your team can get involved and engage with the process as quickly as possible can really contribute to the success of your problem solving strategy.
Looking to peers, experts and external facilitators can be a great way of approaching the problem solving process. Your team may not have the necessary expertise, insights of experience to tackle some issues, or you might simply benefit from a fresh perspective. Some problems may require bringing together an entire team, and coaching managers or team members individually might be the right approach. Remember that not all problems are best resolved in the same manner.
If you’re a solo entrepreneur, peer groups, coaches and mentors can also be invaluable at not only solving specific business problems, but in providing a support network for resolving future challenges. One great approach is to join a Mastermind Group and link up with like-minded individuals and all grow together. Remember that however you approach the sourcing of external advice, do so thoughtfully, respectfully and honestly. Reciprocate where you can and prepare to be surprised by just how kind and helpful your peers can be!
Problem solving in large organizations with lots of skilled team members is one thing, but how about if you work for yourself or in a very small team without the capacity to get the most from a design sprint or LEGO Serious Play session?
A mastermind group – sometimes known as a peer advisory board – is where a group of people come together to support one another in their own goals, challenges, and businesses. Each participant comes to the group with their own purpose and the other members of the group will help them create solutions, brainstorm ideas, and support one another.
Mastermind groups are very effective in creating an energized, supportive atmosphere that can deliver meaningful results. Learning from peers from outside of your organization or industry can really help unlock new ways of thinking and drive growth. Access to the experience and skills of your peers can be invaluable in helping fill the gaps in your own ability, particularly in young companies.
A mastermind group is a great solution for solo entrepreneurs, small teams, or for organizations that feel that external expertise or fresh perspectives will be beneficial for them. It is worth noting that Mastermind groups are often only as good as the participants and what they can bring to the group. Participants need to be committed, engaged and understand how to work in this context.
Receiving advice from a business coach or building a mentor/mentee relationship can be an effective way of resolving certain challenges. The one-to-one format of most coaching and mentor relationships can really help solve the challenges those individuals are having and benefit the organization as a result.
A great mentor can be invaluable when it comes to spotting potential problems before they arise and coming to understand a mentee very well has a host of other business benefits. You might run an internal mentorship program to help develop your team’s problem solving skills and strategies or as part of a large learning and development program. External coaches can also be an important part of your problem solving strategy, filling skills gaps for your management team or helping with specific business issues.
Now we’ve explored the problem solving process and the steps you will want to go through in order to have an effective session, let’s look at the skills you and your team need to be more effective problem solvers.
Problem solving skills are highly sought after, whatever industry or team you work in. Organizations are keen to employ people who are able to approach problems thoughtfully and find strong, realistic solutions. Whether you are a facilitator , a team leader or a developer, being an effective problem solver is a skill you’ll want to develop.
Problem solving skills form a whole suite of techniques and approaches that an individual uses to not only identify problems but to discuss them productively before then developing appropriate solutions.
Here are some of the most important problem solving skills everyone from executives to junior staff members should learn. We’ve also included an activity or exercise from the SessionLab library that can help you and your team develop that skill.
If you’re running a workshop or training session to try and improve problem solving skills in your team, try using these methods to supercharge your process!
Active listening is one of the most important skills anyone who works with people can possess. In short, active listening is a technique used to not only better understand what is being said by an individual, but also to be more aware of the underlying message the speaker is trying to convey. When it comes to problem solving, active listening is integral for understanding the position of every participant and to clarify the challenges, ideas and solutions they bring to the table.
Some active listening skills include:
Active Listening #hyperisland #skills #active listening #remote-friendly This activity supports participants to reflect on a question and generate their own solutions using simple principles of active listening and peer coaching. It’s an excellent introduction to active listening but can also be used with groups that are already familiar with it. Participants work in groups of three and take turns being: “the subject”, the listener, and the observer.
All problem solving models require strong analytical skills, particularly during the beginning of the process and when it comes to analyzing how solutions have performed.
Analytical skills are primarily focused on performing an effective analysis by collecting, studying and parsing data related to a problem or opportunity.
It often involves spotting patterns, being able to see things from different perspectives and using observable facts and data to make suggestions or produce insight.
Analytical skills are also important at every stage of the problem solving process and by having these skills, you can ensure that any ideas or solutions you create or backed up analytically and have been sufficiently thought out.
Nine Whys #innovation #issue analysis #liberating structures With breathtaking simplicity, you can rapidly clarify for individuals and a group what is essentially important in their work. You can quickly reveal when a compelling purpose is missing in a gathering and avoid moving forward without clarity. When a group discovers an unambiguous shared purpose, more freedom and more responsibility are unleashed. You have laid the foundation for spreading and scaling innovations with fidelity.
Trying to solve problems on your own is difficult. Being able to collaborate effectively, with a free exchange of ideas, to delegate and be a productive member of a team is hugely important to all problem solving strategies.
Remember that whatever your role, collaboration is integral, and in a problem solving process, you are all working together to find the best solution for everyone.
Marshmallow challenge with debriefing #teamwork #team #leadership #collaboration In eighteen minutes, teams must build the tallest free-standing structure out of 20 sticks of spaghetti, one yard of tape, one yard of string, and one marshmallow. The marshmallow needs to be on top. The Marshmallow Challenge was developed by Tom Wujec, who has done the activity with hundreds of groups around the world. Visit the Marshmallow Challenge website for more information. This version has an extra debriefing question added with sample questions focusing on roles within the team.
Being an effective communicator means being empathetic, clear and succinct, asking the right questions, and demonstrating active listening skills throughout any discussion or meeting.
In a problem solving setting, you need to communicate well in order to progress through each stage of the process effectively. As a team leader, it may also fall to you to facilitate communication between parties who may not see eye to eye. Effective communication also means helping others to express themselves and be heard in a group.
Bus Trip #feedback #communication #appreciation #closing #thiagi #team This is one of my favourite feedback games. I use Bus Trip at the end of a training session or a meeting, and I use it all the time. The game creates a massive amount of energy with lots of smiles, laughs, and sometimes even a teardrop or two.
Creative problem solving skills can be some of the best tools in your arsenal. Thinking creatively, being able to generate lots of ideas and come up with out of the box solutions is useful at every step of the process.
The kinds of problems you will likely discuss in a problem solving workshop are often difficult to solve, and by approaching things in a fresh, creative manner, you can often create more innovative solutions.
Having practical creative skills is also a boon when it comes to problem solving. If you can help create quality design sketches and prototypes in record time, it can help bring a team to alignment more quickly or provide a base for further iteration.
The paper clip method #sharing #creativity #warm up #idea generation #brainstorming The power of brainstorming. A training for project leaders, creativity training, and to catalyse getting new solutions.
Critical thinking is one of the fundamental problem solving skills you’ll want to develop when working on developing solutions. Critical thinking is the ability to analyze, rationalize and evaluate while being aware of personal bias, outlying factors and remaining open-minded.
Defining and analyzing problems without deploying critical thinking skills can mean you and your team go down the wrong path. Developing solutions to complex issues requires critical thinking too – ensuring your team considers all possibilities and rationally evaluating them.
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.
Though it shares lots of space with general analytical skills, data analysis skills are something you want to cultivate in their own right in order to be an effective problem solver.
Being good at data analysis doesn’t just mean being able to find insights from data, but also selecting the appropriate data for a given issue, interpreting it effectively and knowing how to model and present that data. Depending on the problem at hand, it might also include a working knowledge of specific data analysis tools and procedures.
Having a solid grasp of data analysis techniques is useful if you’re leading a problem solving workshop but if you’re not an expert, don’t worry. Bring people into the group who has this skill set and help your team be more effective as a result.
All problems need a solution and all solutions require that someone make the decision to implement them. Without strong decision making skills, teams can become bogged down in discussion and less effective as a result.
Making decisions is a key part of the problem solving process. It’s important to remember that decision making is not restricted to the leadership team. Every staff member makes decisions every day and developing these skills ensures that your team is able to solve problems at any scale. Remember that making decisions does not mean leaping to the first solution but weighing up the options and coming to an informed, well thought out solution to any given problem that works for the whole team.
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
Most complex organizational problems require multiple people to be involved in delivering the solution. Ensuring that the team and organization can depend on you to take the necessary actions and communicate where necessary is key to ensuring problems are solved effectively.
Being dependable also means working to deadlines and to brief. It is often a matter of creating trust in a team so that everyone can depend on one another to complete the agreed actions in the agreed time frame so that the team can move forward together. Being undependable can create problems of friction and can limit the effectiveness of your solutions so be sure to bear this in mind throughout a project.
Team Purpose & Culture #team #hyperisland #culture #remote-friendly This is an essential process designed to help teams define their purpose (why they exist) and their culture (how they work together to achieve that purpose). Defining these two things will help any team to be more focused and aligned. With support of tangible examples from other companies, the team members work as individuals and a group to codify the way they work together. The goal is a visual manifestation of both the purpose and culture that can be put up in the team’s work space.
Emotional intelligence is an important skill for any successful team member, whether communicating internally or with clients or users. In the problem solving process, emotional intelligence means being attuned to how people are feeling and thinking, communicating effectively and being self-aware of what you bring to a room.
There are often differences of opinion when working through problem solving processes, and it can be easy to let things become impassioned or combative. Developing your emotional intelligence means being empathetic to your colleagues and managing your own emotions throughout the problem and solution process. Be kind, be thoughtful and put your points across care and attention.
Being emotionally intelligent is a skill for life and by deploying it at work, you can not only work efficiently but empathetically. Check out the emotional culture workshop template for more!
As we’ve clarified in our facilitation skills post, facilitation is the art of leading people through processes towards agreed-upon objectives in a manner that encourages participation, ownership, and creativity by all those involved. While facilitation is a set of interrelated skills in itself, the broad definition of facilitation can be invaluable when it comes to problem solving. Leading a team through a problem solving process is made more effective if you improve and utilize facilitation skills – whether you’re a manager, team leader or external stakeholder.
The Six Thinking Hats #creative thinking #meeting facilitation #problem solving #issue resolution #idea generation #conflict resolution The Six Thinking Hats are used by individuals and groups to separate out conflicting styles of thinking. They enable and encourage a group of people to think constructively together in exploring and implementing change, rather than using argument to fight over who is right and who is wrong.
Being flexible is a vital skill when it comes to problem solving. This does not mean immediately bowing to pressure or changing your opinion quickly: instead, being flexible is all about seeing things from new perspectives, receiving new information and factoring it into your thought process.
Flexibility is also important when it comes to rolling out solutions. It might be that other organizational projects have greater priority or require the same resources as your chosen solution. Being flexible means understanding needs and challenges across the team and being open to shifting or arranging your own schedule as necessary. Again, this does not mean immediately making way for other projects. It’s about articulating your own needs, understanding the needs of others and being able to come to a meaningful compromise.
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.
Working in any group can lead to unconscious elements of groupthink or situations in which you may not wish to be entirely honest. Disagreeing with the opinions of the executive team or wishing to save the feelings of a coworker can be tricky to navigate, but being honest is absolutely vital when to comes to developing effective solutions and ensuring your voice is heard.
Remember that being honest does not mean being brutally candid. You can deliver your honest feedback and opinions thoughtfully and without creating friction by using other skills such as emotional intelligence.
Explore your Values #hyperisland #skills #values #remote-friendly Your Values is an exercise for participants to explore what their most important values are. It’s done in an intuitive and rapid way to encourage participants to follow their intuitive feeling rather than over-thinking and finding the “correct” values. It is a good exercise to use to initiate reflection and dialogue around personal values.
The problem solving process is multi-faceted and requires different approaches at certain points of the process. Taking initiative to bring problems to the attention of the team, collect data or lead the solution creating process is always valuable. You might even roadtest your own small scale solutions or brainstorm before a session. Taking initiative is particularly effective if you have good deal of knowledge in that area or have ownership of a particular project and want to get things kickstarted.
That said, be sure to remember to honor the process and work in service of the team. If you are asked to own one part of the problem solving process and you don’t complete that task because your initiative leads you to work on something else, that’s not an effective method of solving business challenges.
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.
A particularly useful problem solving skill for product owners or managers is the ability to remain impartial throughout much of the process. In practice, this means treating all points of view and ideas brought forward in a meeting equally and ensuring that your own areas of interest or ownership are not favored over others.
There may be a stage in the process where a decision maker has to weigh the cost and ROI of possible solutions against the company roadmap though even then, ensuring that the decision made is based on merit and not personal opinion.
Empathy map #frame insights #create #design #issue analysis An empathy map is a tool to help a design team to empathize with the people they are designing for. You can make an empathy map for a group of people or for a persona. To be used after doing personas when more insights are needed.
Being a good leader means getting a team aligned, energized and focused around a common goal. In the problem solving process, strong leadership helps ensure that the process is efficient, that any conflicts are resolved and that a team is managed in the direction of success.
It’s common for managers or executives to assume this role in a problem solving workshop, though it’s important that the leader maintains impartiality and does not bulldoze the group in a particular direction. Remember that good leadership means working in service of the purpose and team and ensuring the workshop is a safe space for employees of any level to contribute. Take a look at our leadership games and activities post for more exercises and methods to help improve leadership in your organization.
Leadership Pizza #leadership #team #remote-friendly This leadership development activity offers a self-assessment framework for people to first identify what skills, attributes and attitudes they find important for effective leadership, and then assess their own development and initiate goal setting.
In the context of problem solving, mediation is important in keeping a team engaged, happy and free of conflict. When leading or facilitating a problem solving workshop, you are likely to run into differences of opinion. Depending on the nature of the problem, certain issues may be brought up that are emotive in nature.
Being an effective mediator means helping those people on either side of such a divide are heard, listen to one another and encouraged to find common ground and a resolution. Mediating skills are useful for leaders and managers in many situations and the problem solving process is no different.
Conflict Responses #hyperisland #team #issue resolution A workshop for a team to reflect on past conflicts, and use them to generate guidelines for effective conflict handling. The workshop uses the Thomas-Killman model of conflict responses to frame a reflective discussion. Use it to open up a discussion around conflict with a team.
Solving organizational problems is much more effective when following a process or problem solving model. Planning skills are vital in order to structure, deliver and follow-through on a problem solving workshop and ensure your solutions are intelligently deployed.
Planning skills include the ability to organize tasks and a team, plan and design the process and take into account any potential challenges. Taking the time to plan carefully can save time and frustration later in the process and is valuable for ensuring a team is positioned for success.
3 Action Steps #hyperisland #action #remote-friendly This is a small-scale strategic planning session that helps groups and individuals to take action toward a desired change. It is often used at the end of a workshop or programme. The group discusses and agrees on a vision, then creates some action steps that will lead them towards that vision. The scope of the challenge is also defined, through discussion of the helpful and harmful factors influencing the group.
As organisations grow, the scale and variation of problems they face multiplies. Your team or is likely to face numerous challenges in different areas and so having the skills to analyze and prioritize becomes very important, particularly for those in leadership roles.
A thorough problem solving process is likely to deliver multiple solutions and you may have several different problems you wish to solve simultaneously. Prioritization is the ability to measure the importance, value, and effectiveness of those possible solutions and choose which to enact and in what order. The process of prioritization is integral in ensuring the biggest challenges are addressed with the most impactful solutions.
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.
Some problem solving skills are utilized in a workshop or ideation phases, while others come in useful when it comes to decision making. Overseeing an entire problem solving process and ensuring its success requires strong project management skills.
While project management incorporates many of the other skills listed here, it is important to note the distinction of considering all of the factors of a project and managing them successfully. Being able to negotiate with stakeholders, manage tasks, time and people, consider costs and ROI, and tie everything together is massively helpful when going through the problem solving process.
Working out meaningful solutions to organizational challenges is only one part of the process. Thoughtfully documenting and keeping records of each problem solving step for future consultation is important in ensuring efficiency and meaningful change.
For example, some problems may be lower priority than others but can be revisited in the future. If the team has ideated on solutions and found some are not up to the task, record those so you can rule them out and avoiding repeating work. Keeping records of the process also helps you improve and refine your problem solving model next time around!
Personal Kanban #gamestorming #action #agile #project planning Personal Kanban is a tool for organizing your work to be more efficient and productive. It is based on agile methods and principles.
Conducting research to support both the identification of problems and the development of appropriate solutions is important for an effective process. Knowing where to go to collect research, how to conduct research efficiently, and identifying pieces of research are relevant are all things a good researcher can do well.
In larger groups, not everyone has to demonstrate this ability in order for a problem solving workshop to be effective. That said, having people with research skills involved in the process, particularly if they have existing area knowledge, can help ensure the solutions that are developed with data that supports their intention. Remember that being able to deliver the results of research efficiently and in a way the team can easily understand is also important. The best data in the world is only as effective as how it is delivered and interpreted.
Customer experience map #ideation #concepts #research #design #issue analysis #remote-friendly Customer experience mapping is a method of documenting and visualizing the experience a customer has as they use the product or service. It also maps out their responses to their experiences. To be used when there is a solution (even in a conceptual stage) that can be analyzed.
Managing risk is an often overlooked part of the problem solving process. Solutions are often developed with the intention of reducing exposure to risk or solving issues that create risk but sometimes, great solutions are more experimental in nature and as such, deploying them needs to be carefully considered.
Managing risk means acknowledging that there may be risks associated with more out of the box solutions or trying new things, but that this must be measured against the possible benefits and other organizational factors.
Be informed, get the right data and stakeholders in the room and you can appropriately factor risk into your decision making process.
Decisions, Decisions… #communication #decision making #thiagi #action #issue analysis When it comes to decision-making, why are some of us more prone to take risks while others are risk-averse? One explanation might be the way the decision and options were presented. This exercise, based on Kahneman and Tversky’s classic study , illustrates how the framing effect influences our judgement and our ability to make decisions . The participants are divided into two groups. Both groups are presented with the same problem and two alternative programs for solving them. The two programs both have the same consequences but are presented differently. The debriefing discussion examines how the framing of the program impacted the participant’s decision.
No single person is as good at problem solving as a team. Building an effective team and helping them come together around a common purpose is one of the most important problem solving skills, doubly so for leaders. By bringing a team together and helping them work efficiently, you pave the way for team ownership of a problem and the development of effective solutions.
In a problem solving workshop, it can be tempting to jump right into the deep end, though taking the time to break the ice, energize the team and align them with a game or exercise will pay off over the course of the day.
Remember that you will likely go through the problem solving process multiple times over an organization’s lifespan and building a strong team culture will make future problem solving more effective. It’s also great to work with people you know, trust and have fun with. Working on team building in and out of the problem solving process is a hallmark of successful teams that can work together to solve business problems.
9 Dimensions Team Building Activity #ice breaker #teambuilding #team #remote-friendly 9 Dimensions is a powerful activity designed to build relationships and trust among team members. There are 2 variations of this icebreaker. The first version is for teams who want to get to know each other better. The second version is for teams who want to explore how they are working together as a team.
The problem solving process is designed to lead a team from identifying a problem through to delivering a solution and evaluating its effectiveness. Without effective time management skills or timeboxing of tasks, it can be easy for a team to get bogged down or be inefficient.
By using a problem solving model and carefully designing your workshop, you can allocate time efficiently and trust that the process will deliver the results you need in a good timeframe.
Time management also comes into play when it comes to rolling out solutions, particularly those that are experimental in nature. Having a clear timeframe for implementing and evaluating solutions is vital for ensuring their success and being able to pivot if necessary.
Improving your skills at problem solving is often a career-long pursuit though there are methods you can use to make the learning process more efficient and to supercharge your problem solving skillset.
Remember that the skills you need to be a great problem solver have a large overlap with those skills you need to be effective in any role. Investing time and effort to develop your active listening or critical thinking skills is valuable in any context. Here are 7 ways to improve your problem solving skills.
Remember that your team is an excellent source of skills, wisdom, and techniques and that you should all take advantage of one another where possible. Best practices that one team has for solving problems, conducting research or making decisions should be shared across the organization. If you have in-house staff that have done active listening training or are data analysis pros, have them lead a training session.
Your team is one of your best resources. Create space and internal processes for the sharing of skills so that you can all grow together.
Once you’ve figured out you have a skills gap, the next step is to take action to fill that skills gap. That might be by asking your superior for training or coaching, or liaising with team members with that skill set. You might even attend specialized training for certain skills – active listening or critical thinking, for example, are business-critical skills that are regularly offered as part of a training scheme.
Whatever method you choose, remember that taking action of some description is necessary for growth. Whether that means practicing, getting help, attending training or doing some background reading, taking active steps to improve your skills is the way to go.
Problem solving can be complicated, particularly when attempting to solve large problems for the first time. Using a problem solving process helps give structure to your problem solving efforts and focus on creating outcomes, rather than worrying about the format.
Tools such as the seven-step problem solving process above are effective because not only do they feature steps that will help a team solve problems, they also develop skills along the way. Each step asks for people to engage with the process using different skills and in doing so, helps the team learn and grow together. Group processes of varying complexity and purpose can also be found in the SessionLab library of facilitation techniques . Using a tried and tested process and really help ease the learning curve for both those leading such a process, as well as those undergoing the purpose.
Effective teams make decisions about where they should and shouldn’t expend additional effort. By using a problem solving process, you can focus on the things that matter, rather than stumbling towards a solution haphazardly.
Some skills gaps are more obvious than others. It’s possible that your perception of your active listening skills differs from those of your colleagues.
It’s valuable to create a system where team members can provide feedback in an ordered and friendly manner so they can all learn from one another. Only by identifying areas of improvement can you then work to improve them.
Remember that feedback systems require oversight and consideration so that they don’t turn into a place to complain about colleagues. Design the system intelligently so that you encourage the creation of learning opportunities, rather than encouraging people to list their pet peeves.
While practice might not make perfect, it does make the problem solving process easier. If you are having trouble with critical thinking, don’t shy away from doing it. Get involved where you can and stretch those muscles as regularly as possible.
Problem solving skills come more naturally to some than to others and that’s okay. Take opportunities to get involved and see where you can practice your skills in situations outside of a workshop context. Try collaborating in other circumstances at work or conduct data analysis on your own projects. You can often develop those skills you need for problem solving simply by doing them. Get involved!
Learn from the best. Our library of 700+ facilitation techniques is full of activities and methods that help develop the skills you need to be an effective problem solver. Check out our templates to see how to approach problem solving and other organizational challenges in a structured and intelligent manner.
There is no single approach to improving problem solving skills, but by using the techniques employed by others you can learn from their example and develop processes that have seen proven results.
Using tried and tested exercises that you know well can help deliver results, but you do run the risk of missing out on the learning opportunities offered by new approaches. As with the problem solving process, changing your mindset can remove blockages and be used to develop your problem solving skills.
Most teams have members with mixed skill sets and specialties. Mix people from different teams and share skills and different points of view. Teach your customer support team how to use design thinking methods or help your developers with conflict resolution techniques. Try switching perspectives with facilitation techniques like Flip It! or by using new problem solving methodologies or models. Give design thinking, liberating structures or lego serious play a try if you want to try a new approach. You will find that framing problems in new ways and using existing skills in new contexts can be hugely useful for personal development and improving your skillset. It’s also a lot of fun to try new things. Give it a go!
Encountering business challenges and needing to find appropriate solutions is not unique to your organization. Lots of very smart people have developed methods, theories and approaches to help develop problem solving skills and create effective solutions. Learn from them!
Books like The Art of Thinking Clearly , Think Smarter, or Thinking Fast, Thinking Slow are great places to start, though it’s also worth looking at blogs related to organizations facing similar problems to yours, or browsing for success stories. Seeing how Dropbox massively increased growth and working backward can help you see the skills or approach you might be lacking to solve that same problem. Learning from others by reading their stories or approaches can be time-consuming but ultimately rewarding.
A tired, distracted mind is not in the best position to learn new skills. It can be tempted to burn the candle at both ends and develop problem solving skills outside of work. Absolutely use your time effectively and take opportunities for self-improvement, though remember that rest is hugely important and that without letting your brain rest, you cannot be at your most effective.
Creating distance between yourself and the problem you might be facing can also be useful. By letting an idea sit, you can find that a better one presents itself or you can develop it further. Take regular breaks when working and create a space for downtime. Remember that working smarter is preferable to working harder and that self-care is important for any effective learning or improvement process.
Now we’ve explored some of the key problem solving skills and the problem solving steps necessary for an effective process, you’re ready to begin developing more effective solutions and leading problem solving workshops.
Need more inspiration? Check out our post on problem solving activities you can use when guiding a group towards a great solution in your next workshop or meeting. Have questions? Did you have a great problem solving technique you use with your team? Get in touch in the comments below. We’d love to chat!
James Smart is Head of Content at SessionLab. He’s also a creative facilitator who has run workshops and designed courses for establishments like the National Centre for Writing, UK. He especially enjoys working with young people and empowering others in their creative practice.
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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.
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.
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.
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.
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.
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.
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.
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As an academic and author, I've had the privilege of shaping the design landscape. I teach design at the University of Leeds and am the Programme Leader for the MA Design, focusing on design thinking, design for health, and behavioural design. I've developed and taught several innovative programmes at Wrexham Glyndwr University, Northumbria University, and The American University in Cairo. I'm also a published book author and the proud founder of Designorate.com, a platform that has been instrumental in fostering design innovation. My expertise in design has been recognised by prestigious organizations. I'm a fellow of the Higher Education Academy (HEA), the Design Research Society (FDRS), and an Adobe Education Leader. Over the course of 20 years, I've had the privilege of working with esteemed clients such as the UN, World Bank, Adobe, and Schneider, contributing to their design strategies. For more than 12 years, I collaborated closely with the Adobe team, playing a key role in the development of many Adobe applications.
3 thoughts on “ the six systems thinking steps to solve complex problems ”.
“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
Thank you so much Misi for the helpful information.
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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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...
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.
This article is about decision making and problem solving, partner center.
Harvard Business School Online's Business Insights Blog provides the career insights you need to achieve your goals and gain confidence in your business skills.
The importance of creativity in the workplace—particularly when problem-solving—is undeniable. Business leaders can’t approach new problems with old solutions and expect the same result.
This is where innovation-based processes need to guide problem-solving. Here’s an overview of what creative problem-solving is, along with tips on how to use it in conjunction with design thinking.
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Encountering problems with no clear cause can be frustrating. This occurs when there’s disagreement around a defined problem or research yields unclear results. In such situations, creative problem-solving helps develop solutions, despite a lack of clarity.
While creative problem-solving is less structured than other forms of innovation, it encourages exploring open-ended ideas and shifting perspectives—thereby fostering innovation and easier adaptation in the workplace. It also works best when paired with other innovation-based processes, such as design thinking .
Design thinking is a solutions-based mentality that encourages innovation and problem-solving. It’s guided by an iterative process that Harvard Business School Dean Srikant Datar outlines in four stages in the online course Design Thinking and Innovation :
Although user research is an essential first step in the design thinking process, there are times when it can’t identify a problem’s root cause. Creative problem-solving addresses this challenge by promoting the development of new perspectives.
Leveraging tools like design thinking and creativity at work can further your problem-solving abilities. Here are eight tips for doing so.
1. empathize with your audience.
A fundamental practice of design thinking’s clarify stage is empathy. Understanding your target audience can help you find creative and relevant solutions for their pain points through observing them and asking questions.
Practice empathy by paying attention to others’ needs and avoiding personal comparisons. The more you understand your audience, the more effective your solutions will be.
If a problem is difficult to define, reframe it as a question rather than a statement. For example, instead of saying, "The problem is," try framing around a question like, "How might we?" Think creatively by shifting your focus from the problem to potential solutions.
Consider this hypothetical case study: You’re the owner of a local coffee shop trying to fill your tip jar. Approaching the situation with a problem-focused mindset frames this as: "We need to find a way to get customers to tip more." If you reframe this as a question, however, you can explore: "How might we make it easier for customers to tip?" When you shift your focus from the shop to the customer, you empathize with your audience. You can take this train of thought one step further and consider questions such as: "How might we provide a tipping method for customers who don't carry cash?"
Whether you work at a coffee shop, a startup, or a Fortune 500 company, reframing can help surface creative solutions to problems that are difficult to define.
If you encounter an idea that seems outlandish or unreasonable, a natural response would be to reject it. This instant judgment impedes creativity. Even if ideas seem implausible, they can play a huge part in ideation. It's important to permit the exploration of original ideas.
While judgment can be perceived as negative, it’s crucial to avoid accepting ideas too quickly. If you love an idea, don’t immediately pursue it. Give equal consideration to each proposal and build on different concepts instead of acting on them immediately.
Cognitive fixedness is a state of mind that prevents you from recognizing a situation’s alternative solutions or interpretations instead of considering every situation through the lens of past experiences.
Although it's efficient in the short-term, cognitive fixedness interferes with creative thinking because it prevents you from approaching situations unbiased. It's important to be aware of this tendency so you can avoid it.
One of the key principles of creative problem-solving is the balance of divergent and convergent thinking. Divergent thinking is the process of brainstorming multiple ideas without limitation; open-ended creativity is encouraged. It’s an effective tool for generating ideas, but not every idea can be explored. Divergent thinking eventually needs to be grounded in reality.
Convergent thinking, on the other hand, is the process of narrowing ideas down into a few options. While converging ideas too quickly stifles creativity, it’s an important step that bridges the gap between ideation and development. It's important to strike a healthy balance between both to allow for the ideation and exploration of creative ideas.
Using creative tools is another way to foster innovation. Without a clear cause for a problem, such tools can help you avoid cognitive fixedness and abrupt decision-making. Here are several examples:
Creating a problem story requires identifying undesired phenomena (UDP) and taking note of events that precede and result from them. The goal is to reframe the situations to visualize their cause and effect.
To start, identify a UDP. Then, discover what events led to it. Observe and ask questions of your consumer base to determine the UDP’s cause.
Next, identify why the UDP is a problem. What effect does the UDP have that necessitates changing the status quo? It's helpful to visualize each event in boxes adjacent to one another when answering such questions.
The problem story can be extended in either direction, as long as there are additional cause-and-effect relationships. Once complete, focus on breaking the chains connecting two subsequent events by disrupting the cause-and-effect relationship between them.
The alternate worlds tool encourages you to consider how people from different backgrounds would approach similar situations. For instance, how would someone in hospitality versus manufacturing approach the same problem? This tool isn't intended to instantly solve problems but, rather, to encourage idea generation and creativity.
It's vital to maintain a positive mindset when problem-solving and avoid negative words that interfere with creativity. Positive language prevents quick judgments and overcomes cognitive fixedness. Instead of "no, but," use words like "yes, and."
Positive language makes others feel heard and valued rather than shut down. This practice doesn’t necessitate agreeing with every idea but instead approaching each from a positive perspective.
Using “yes, and” as a tool for further idea exploration is also effective. If someone presents an idea, build upon it using “yes, and.” What additional features could improve it? How could it benefit consumers beyond its intended purpose?
While it may not seem essential, this small adjustment can make a big difference in encouraging creativity.
Practicing design thinking can make you a more creative problem-solver. While commonly associated with the workplace, adopting a design thinking mentality can also improve your everyday life. Here are several ways you can practice design thinking:
Though creativity comes naturally to some, it's an acquired skill for many. Regardless of which category you're in, improving your ability to innovate is a valuable endeavor. Whether you want to bolster your creativity or expand your professional skill set, taking an innovation-based course can enhance your problem-solving.
If you're ready to become a more creative problem-solver, explore Design Thinking and Innovation , one of our online entrepreneurship and innovation courses . If you aren't sure which course is the right fit, download our free course flowchart to determine which best aligns with your goals.
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Dietrich dörner.
1 Department of Psychology, University of Bamberg, Bamberg, Germany
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.
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:
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.
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:
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.
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):
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.
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.
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.
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:
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:
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.
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.
JF drafted a first version of the manuscript, DD added further text and commented on the draft. JF finalized the manuscript.
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!
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.
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.
Six tips for solving complex problems.
Adam Stott is an entrepreneur, author, business coach and founder of Big Business Events.
Problems will always present themselves, and you need to be able to keep yourself on track, ask yourself the right questions and solve problems fast and efficiently. When you’re able to get things done more quickly, you will have more time to guide your business, more time for your personal relationships and more time to create more wealth.
Complex problems often put you in a place where you feel stuck. They can make you feel fearful, overwhelmed and like you just don't know what to do, which can slow your reaction in solving the issue. This happens to business owners who are at the height of their careers as well as leaders of new startups. The answer is really about making sure you ask yourself the right questions because those questions will help you see that you'll be able to overcome the challenges and the issues that you have and come up with answers quickly.
When things start to stack up on top of you and someone brings a new challenge to you, you might decide to put it off and deal with it later. What happens next? You get another challenge, and that only adds to what you have to deal with. Challenges never stop coming and, eventually, you have ten or eleven problems because you didn't deal with the things that were coming to you at that moment. Procrastinating leads to not getting things done and, eventually, you become overwhelmed and don’t know where to start.
Here are some things you can do to improve your ability to solve complex problems:
1. Always be learning.
Prepare your mind to be a bit faster and deal with things in a better way by constantly learning. Get your brain to go places you haven’t asked it to go before. When you’re challenging your brain and expanding your knowledge, you can also expand your ability to solve problems.
Believe it or not, this is something you need to prepare for. How do you have a fast mind and why does it matter? It matters because you're running a business, becoming more successful in your career and things are developing for you. You are becoming busier and being asked more and more questions. You have more decisions to make. You are responsible for more people, and if you're slow in your decision-making and in getting stuff done, what you'll find is things can start to pile up.
2. Try to solve problems more quickly.
One of the best ways to do this is with coaching because you have someone guiding you when an issue comes up, and you're able to ask questions of someone who has already been through what you're going through. This can allow you to get results much more quickly, and at the same time, you can learn from another's experiences.
3. Ask yourself what needs to happen.
When you have a complex challenge and you don't know what to do, ask yourself, “If I was to solve this problem, what would need to happen?”
When you do that, you're actively directing your thoughts toward a solution and you are more likely to start coming up with answers. Then ask yourself, “How can I benefit from this complex problem or challenge?” If you can come up with some sort of benefit, you can attach an incentive around completing it.
4. Ask a qualified person for help.
If you can't find the answer, ask a person who you think is best qualified to deal with the situation you have. Don't get advice from people who haven't been in situations similar to yours and who haven’t dealt with problems like yours. You are probably more qualified to answer the question yourself.
5. Ask yourself the best thing that can happen.
If you're struggling, ask yourself, “What is the best thing that can happen in this situation?” This gives you a best-case scenario. Then ask yourself, “What is the very worst thing that can happen?” Now you also know the worst-case scenario. Then ask yourself, “What’s the most likely thing that can happen?” Now you've covered all your bases.
6. Consider your current mindset.
Do you feel positive or are you in a place where you are feeling negative? If you're in a state where you're feeling negative, it can be very hard to come up with the right answers. Whereas if you're feeling positive, it can be easier to come up with the right answers. If you’re not in the right place to make a decision and you need to take a short break, do that. But be careful of ignoring problems and burying your head in the sand.
Try to make small decisions instantly and move forward. More complex problems might require a little more time and energy to think them through, so don't expend unnecessary energy on the small things.
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7. Solution evaluation. 1. Problem identification. The first stage of any problem solving process is to identify the problem (s) you need to solve. This often looks like using group discussions and activities to help a group surface and effectively articulate the challenges they're facing and wish to resolve.
In this article, we define complex problem-solving, discuss the key differences between complex and simple problem solving, talk about the necessary steps to solve complex problems and offer a list of jobs that may benefit from developing complex problem-solving skills. Related: Problem-Solving Skills: Definition and Examples
17 Effective Problem-Solving Strategies. Effective problem-solving strategies include breaking the problem into smaller parts, brainstorming multiple solutions, evaluating the pros and cons of each, and choosing the most viable option. Critical thinking and creativity are essential in developing innovative solutions.
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. Seek Out Challenging Problems.
And third, pay attention to how you're feeling. Embracing complexity means learning to better manage tough emotions like fear and anger. The problems we're facing often seem as complex as they ...
The 7 steps to problem-solving. When it comes to problem-solving there are seven key steps that you should follow: define the problem, disaggregate, prioritize problem branches, create an analysis plan, conduct analysis, synthesis, and communication. 1. Define the problem. Problem-solving begins with a clear understanding of the issue at hand.
Most problem solving techniques look for a balance between the following binaries: ... Complex Problem Solving. Soft Systems Methodology (SSM): For extremely complex problems, SSM can help you identify how factors interact, and determine the best course of action. SSM was borne out of organizational process modeling and general systems theory ...
How to Solve Problems. To bring the best ideas forward, teams must build psychological safety. Teams today aren't just asked to execute tasks: They're called upon to solve problems. You'd ...
In this episode of the McKinsey Podcast, Simon London speaks with Charles Conn, CEO of venture-capital firm Oxford Sciences Innovation, and McKinsey senior partner Hugo Sarrazin about the complexities of different problem-solving strategies.. Podcast transcript. Simon London: Hello, and welcome to this episode of the McKinsey Podcast, with me, Simon London.
Solving complex problems may be difficult but it doesn't have to be excruciating. You just need the right frame of mind and a process for untangling the problem at hand. ... When applying problem-solving techniques, you will be using a variation of these steps as your foundation. Takeaway: Before you can solve a problem, seek to understand it ...
Phase 4: Elevate. This phase involves exploring how the problem connects to broader organizational issues. It's like zooming out on a map to understand where a city lies in relation to the whole ...
14 types of problem-solving strategies. Here are some examples of problem-solving strategies you can practice using to see which works best for you in different situations: 1. Define the problem. Taking the time to define a potential challenge can help you identify certain elements to create a plan to resolve them.
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.".
Planning skills are vital in order to structure, deliver and follow-through on a problem solving workshop and ensure your solutions are intelligently deployed. Planning skills include the ability to organize tasks and a team, plan and design the process and take into account any potential challenges.
In insight problem-solving, the cognitive processes that help you solve a problem happen outside your conscious awareness. 4. Working backward. Working backward is a problem-solving approach often ...
Complex problem solving is a skill you can continue to improve with each new complex problem. The more you test your assumptions, open your mind, put feedback into practice, and test new ideas ...
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 ...
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 ...
8. Practice Design Thinking. Practicing design thinking can make you a more creative problem-solver. While commonly associated with the workplace, adopting a design thinking mentality can also improve your everyday life. Here are several ways you can practice design thinking: Learn from others: There are many examples of design thinking in ...
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 ...
5. Implement a solution. 6. Evaluate a solution. 7. Here's what else to consider. Complex problems can challenge your creativity, logic, and perseverance. They may have multiple variables ...
Go to: 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.
Specialization - 4 course series. SOLVING COMPLEX PROBLEMS will teach you revolutionary new problem-solving skills. Involving lectures from over 50 experts from all faculties at Macquarie University, we look at solving complex problems in a way that has never been done before. Please note that this specialisation will be discontinued on Monday ...
Here are some things you can do to improve your ability to solve complex problems: 1. Always be learning. Prepare your mind to be a bit faster and deal with things in a better way by constantly ...
This complex problem-solving course introduces participants to MIT's unique, powerful, and integrative System Dynamics approach to assess problems that will not go away and to produce the results they want. Through exercises and simulation models, participants experience the long-term side effects and impacts of decisions and understand the ...