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Extensive Problem Solving

This article covers meaning, importance & example of Extensive Problem Solving from marketing perspective.

What is Extensive Problem Solving?

Extensive problem solving is the purchase decision marking in a situation in which the buyer has no information, experience about the products, services and suppliers. In extensive problem solving, lack of information also spreads to the brands for the product and also the criterion that they set for segregating the brands to be small or manageable subsets that help in the purchasing decision later. Consumers usually go for extensive problem solving when they discover that a need is completely new to them which requires significant effort to satisfy it.

The decision making process of a customer includes different levels of purchase decisions, i.e. extensive problem solving, limited problem solving and routinized choice behaviour.

Elements of Extensive Problem Solving

The various parameters which leads to extensive problem solving are:

1. Highly Priced Products: Like a car, house

2. Infrequent Purchases: Purchasing an automobile, HD TV

3. More Customer Participation: Purchasing a laptop with selection of RAM, ROM, display etc

4. Unfamiliar Product Category: Real-estate is a very unexplored category

5. Extensive Research & Time: Locality of buying house, proximity to hospital, station, market etc.

All these parameters or elements leads to extensive problem solving for the customer while taking a decision to make a purchase.

• Problem Recognition
• Problem Solution Approach

Importance of Extensive Problem Solving

It is very important for marketers to know the process that customers go through before purchasing. They cannot rely upon re-buys and word of mouth all the time for acquiring new customers. The customer in general goes through problem recognition, information search, evaluation, purchase decision and post-purchase evaluation. Closely related to a purchase decision is the problem solving phase. A new product with long term investment leads to extensive problem solving from a customer. This signifies that not all buying situations are same. A rebuy is very much different from a first choice purchase. The recognition that a brand enjoys in a customer’s mind helps the customer to make purchase decisions easily. If the brand has a dedicated marketing communication effort, whenever a consumer feels the need for a new product, they instantly go for it.

To help customers in extensive problem solving, companies must have clear transparent communication. It is thus very important for marketers to use a proper marketing mix so that they can have some cognition from their customers when they think of new products. With the advent of social media, the number of channels for promotion have hugely developed and they require a clear understanding on the segment of customer that each channel serves. The communication channels should lucidly differentiate themselves from other brands so that they are purchased quickly and easily.

Example of Extensive Problem Solving

Let us suppose, that Amber wants to buy a High Definition TV. The problem being, she has no idea regarding it. This is a case of extensive problem solving as the amount of information is low, the risk she is taking is high as she is going with the opinion that she gathers from her peers, the item is expensive and at the same time it also demands huge amount of involvement from the customer. Similarly, buying high price and long-term assets or products like car, motorcycle, house etc leads to extensive problem solving decision for the customers.

Hence, this concludes the definition of Extensive Problem Solving along with its overview.

This article has been researched & authored by the Business Concepts Team which comprises of MBA students, management professionals, and industry experts. It has been reviewed & published by the MBA Skool Team . The content on MBA Skool has been created for educational & academic purpose only.

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Individual Consumer Decision Making

29 Consumer Decision Making Process

An organization that wants to be successful must consider buyer behavior when developing the marketing mix. Buyer behavior is the actions people take with regard to buying and using products. Marketers must understand buyer behavior, such as how raising or lowering a price will affect the buyer’s perception of the product and therefore create a fluctuation in sales, or how a specific review on social media can create an entirely new direction for the marketing mix based on the comments (buyer behavior/input) of the target market.

The Consumer Decision Making Process

Once the process is started, a potential buyer can withdraw at any stage of making the actual purchase. The tendency for a person to go through all six stages is likely only in certain buying situations—a first time purchase of a product, for instance, or when buying high priced, long-lasting, infrequently purchased articles. This is referred to as complex decision making .

For many products, the purchasing behavior is a routine affair in which the aroused need is satisfied in a habitual manner by repurchasing the same brand. That is, past reinforcement in learning experiences leads directly to buying, and thus the second and third stages are bypassed. This is called simple decision making .

However, if something changes appreciably (price, product, availability, services), the buyer may re-enter the full decision process and consider alternative brands. Whether complex or simple, the first step is need identification (Assael, 1987).

When Inertia Takes Over

Need Recognition

Whether we act to resolve a particular problem depends upon two factors: (1) the magnitude of the discrepancy between what we have and what we need, and (2) the importance of the problem. A consumer may desire a new Cadillac and own a five-year-old Chevrolet. The discrepancy may be fairly large but relatively unimportant compared to the other problems they face. Conversely, an individual may own a car that is two years old and running very well. Yet, for various reasons, they may consider it extremely important to purchase a car this year. People must resolve these types of conflicts before they can proceed. Otherwise, the buying process for a given product stops at this point, probably in frustration.

Once the problem is recognized it must be defined in such a way that the consumer can actually initiate the action that will bring about a relevant problem solution. Note that, in many cases, problem recognition and problem definition occur simultaneously, such as a consumer running out of toothpaste. Consider the more complicated problem involved with status and image–how we want others to see us. For example, you may know that you are not satisfied with your appearance, but you may not be able to define it any more precisely than that. Consumers will not know where to begin solving their problem until the problem is adequately defined.

Marketers can become involved in the need recognition stage in three ways. First they need to know what problems consumers are facing in order to develop a marketing mix to help solve these problems. This requires that they measure problem recognition. Second, on occasion, marketers want to activate problem recognition. Public service announcements espousing the dangers of cigarette smoking is an example. Weekend and night shop hours are a response of retailers to the consumer problem of limited weekday shopping opportunities. This problem has become particularly important to families with two working adults. Finally, marketers can also shape the definition of the need or problem. If a consumer needs a new coat, do they define the problem as a need for inexpensive covering, a way to stay warm on the coldest days, a garment that will last several years, warm cover that will not attract odd looks from their peers, or an article of clothing that will express their personal sense of style? A salesperson or an ad may shape their answers

Information Search

After a need is recognized, the prospective consumer may seek information to help identify and evaluate alternative products, services, and outlets that will meet that need. Such information can come from family, friends, personal observation, or other sources, such as Consumer Reports, salespeople, or mass media. The promotional component of the marketers offering is aimed at providing information to assist the consumer in their problem solving process. In some cases, the consumer already has the needed information based on past purchasing and consumption experience. Bad experiences and lack of satisfaction can destroy repeat purchases. The consumer with a need for tires may look for information in the local newspaper or ask friends for recommendation. If they have bought tires before and was satisfied, they may go to the same dealer and buy the same brand.

Information search can also identify new needs. As a tire shopper looks for information, they may decide that the tires are not the real problem, that the need is for a new car. At this point, the perceived need may change triggering a new informational search. Information search involves mental as well as the physical activities that consumers must perform in order to make decisions and accomplish desired goals in the marketplace. It takes time, energy, money, and can often involve foregoing more desirable activities. The benefits of information search, however, can outweigh the costs. For example, engaging in a thorough information search may save money, improve quality of selection, or reduce risks. The Internet is a valuable information source.

Evaluation of Alternatives

After information is secured and processed, alternative products, services, and outlets are identified as viable options. The consumer evaluates these alternatives , and, if financially and psychologically able, makes a choice. The criteria used in evaluation varies from consumer to consumer just as the needs and information sources vary. One consumer may consider price most important while another puts more weight (importance) upon quality or convenience.

Using the ‘Rule of Thumb’

Consumers don’t have the time or desire to ponder endlessly about every purchase! Fortunately for us, heuristics , also described as shortcuts or mental “rules of thumb”, help us make decisions quickly and painlessly. Heuristics are especially important to draw on  when we are faced with choosing among products in a category where we don’t see huge differences or if the outcome isn’t ‘do or die’.

Heuristics are helpful sets of rules that simplify the decision-making process by making it quick and easy for consumers.

Common Heuristics in Consumer Decision Making

• Save the most money: Many people follow a rule like, “I’ll buy the lowest-priced choice so that I spend the least money right now.” Using this heuristic means you don’t need to look beyond the price tag to make a decision. Wal-Mart built a retailing empire by pleasing consumers who follow this rule.
• You get what you pay for: Some consumers might use the opposite heuristic of saving the most money and instead follow a rule such as: “I’ll buy the more expensive product because higher price means better quality.” These consumers are influenced by advertisements alluding to exclusivity, quality, and uncompromising performance.
• Stich to the tried and true: Brand loyalty also simplifies the decision-making process because we buy the brand that we’ve always bought before. therefore, we don’t need to spend more time and effort on the decision. Advertising plays a critical role in creating brand loyalty. In a study of the market leaders in thirty product categories, 27 of the brands that were #1 in 1930 were still at the top over 50 years later (Stevesnson, 1988)! A well known brand name is a powerful heuristic .
• National pride: Consumers who select brands because they represent their own culture and country of origin are making decision based on ethnocentrism . Ethnocentric consumers are said to perceive their own culture or country’s goods as being superior to others’. Ethnocentrism can behave as both a stereotype and a type of heuristic for consumers who are quick to generalize and judge brands based on their country of origin.
• Visual cues: Consumers may also rely on visual cues represented in product and packaging design. Visual cues may include the colour of the brand or product or deeper beliefs that they have developed about the brand. For example, if brands claim to support sustainability and climate activism, consumers want to believe these to be true. Visual cues such as green design and neutral-coloured packaging that appears to be made of recycled materials play into consumers’ heuristics .

The search for alternatives and the methods used in the search are influenced by such factors as: (a) time and money costs; (b) how much information the consumer already has; (c) the amount of the perceived risk if a wrong selection is made; and (d) the consumer’s predisposition toward particular choices as influenced by the attitude of the individual toward choice behaviour. That is, there are individuals who find the selection process to be difficult and disturbing. For these people there is a tendency to keep the number of alternatives to a minimum, even if they have not gone through an extensive information search to find that their alternatives appear to be the very best. On the other hand, there are individuals who feel it necessary to collect a long list of alternatives. This tendency can appreciably slow down the decision-making function.

Consumer Evaluations Made Easier

The evaluation of alternatives often involves consumers drawing on their evoke, inept, and insert sets to help them in the decision making process.

The brands and products that consumers compare—their evoked set – represent the alternatives being considered by consumers during the problem-solving process. Sometimes known as a “consideration” set, the evoked set tends to be small relative to the total number of options available. When a consumer commits significant time to the comparative process and reviews price, warranties, terms and condition of sale and other features it is said that they are involved in extended problem solving. Unlike routine problem solving, extended or extensive problem solving comprises external research and the evaluation of alternatives. Whereas, routine problem solving is low-involvement, inexpensive, and has limited risk if purchased, extended problem solving justifies the additional effort with a high-priced or scarce product, service, or benefit (e.g., the purchase of a car). Likewise, consumers use extensive problem solving for infrequently purchased, expensive, high-risk, or new goods or services.

As opposed to the evoked set, a consumer’s inept set represent those brands that they would not given any consideration too. For a consumer who is shopping around for an electric vehicle, for example, they would not even remotely consider gas-guzzling vehicles like large SUVs.

The inert set represents those brands or products a consumer is aware of, but is indifferent to and doesn’t consider them either desirable or relevant enough to be among the evoke set. Marketers have an opportunity here to position their brands appropriately so consumers move these items from their insert to evoke set when evaluation alternatives.

The selection of an alternative, in many cases, will require additional evaluation. For example, a consumer may select a favorite brand and go to a convenient outlet to make a purchase. Upon arrival at the dealer, the consumer finds that the desired brand is out-of-stock. At this point, additional evaluation is needed to decide whether to wait until the product comes in, accept a substitute, or go to another outlet. The selection and evaluation phases of consumer problem solving are closely related and often run sequentially, with outlet selection influencing product evaluation, or product selection influencing outlet evaluation.

While many consumers would agree that choice is a good thing, there is such a thing as “too much choice” that inhibits the consumer decision making process. Consumer hyperchoice is a term used to describe purchasing situations that involve an excess of choice thus making selection for difficult for consumers. Dr. Sheena Iyengar studies consumer choice and collects data that supports the concept of consumer hyperchoice. In one of her studies, she put out jars of jam in a grocery store for shoppers to sample, with the intention to influence purchases. Dr. Iyengar discovered that when a fewer number of jam samples were provided to shoppers, more purchases were made. But when a large number of jam samples were set out, fewer purchases were made (Green, 2010). As it turns out, “more is less” when it comes to the selection process.

The Purchase Decision

After much searching and evaluating, or perhaps very little, consumers at some point have to decide whether they are going to buy.

Anything marketers can do to simplify purchasing will be attractive to buyers. This may include minimal clicks to online checkout; short wait times in line; and simplified payment options. When it comes to advertising marketers could also suggest the best size for a particular use, or the right wine to drink with a particular food. Sometimes several decision situations can be combined and marketed as one package. For example, travel agents often package travel tours with flight and hotel reservations.

To do a better marketing job at this stage of the buying process, a seller needs to know answers to many questions about consumers’ shopping behaviour. For instance, how much effort is the consumer willing to spend in shopping for the product? What factors influence when the consumer will actually purchase? Are there any conditions that would prohibit or delay purchase? Providing basic product, price, and location information through labels, advertising, personal selling, and public relations is an obvious starting point. Product sampling, coupons, and rebates may also provide an extra incentive to buy.

Actually determining how a consumer goes through the decision-making process is a difficult research task.

Post-Purchase Behaviour

All the behaviour determinants and the steps of the buying process up to this point are operative before or during the time a purchase is made. However, a consumer’s feelings and evaluations after the sale are also significant to a marketer, because they can influence repeat sales and also influence what the customer tells others about the product or brand.

Keeping the customer happy is what marketing is all about. Nevertheless, consumers typically experience some post-purchase anxiety after all but the most routine and inexpensive purchases. This anxiety reflects a phenomenon called cognitive dissonance . According to this theory, people strive for consistency among their cognitions (knowledge, attitudes, beliefs, values). When there are inconsistencies, dissonance exists, which people will try to eliminate. In some cases, the consumer makes the decision to buy a particular brand already aware of dissonant elements. In other instances, dissonance is aroused by disturbing information that is received after the purchase. The marketer may take specific steps to reduce post-purchase dissonance. Advertising that stresses the many positive attributes or confirms the popularity of the product can be helpful. Providing personal reinforcement has proven effective with big-ticket items such as automobiles and major appliances. Salespeople in these areas may send cards or may even make personal calls in order to reassure customers about their purchase.

Media Attributions

• The graphic of the “Consumer Decision Making Process” by Niosi, A. (2021) is licensed under CC BY-NC-SA and is adapted from Introduction to Business by Rice University.

Text Attributions

• The sections under the “Consumer Decision Making Process,” “Need Recognition” (edited), “Information Search,” “Evaluation of Alternatives”; the first paragraph under the section “Selection”; the section under “Purchase Decision”; and, the section under “Post-Purchase Behaviour” are adapted from Introducing Marketing [PDF] by John Burnett which is licensed under CC BY 3.0 .
• The opening paragraph and the image of the Consumer Decision Making Process is adapted from Introduction to Business by Rice University which is licensed under a Creative Commons Attribution 4.0 International License .
• The section under “Using the ‘Rule of Thumb'” is adapted (and edited) from Launch! Advertising and Promotion in Real Time [PDF] by Saylor Academy which is licensed under CC BY-NC-SA 3.0 .

Assael, H. (1987). Consumer Behavior and Marketing Action (3rd ed.), 84. Boston: Kent Publishing.

Green, P. (2010, March 17). An Expert on Choice Chooses. The New York Times. https://www.nytimes.com/2010/03/18/garden/18choice.html.

Consumer purchases made when a (new) need is identified and a consumer engages in a more rigorous evaluation, research, and alternative assessment process before satisfying the unmet need.

Consumer purchases made when a need is identified and a habitual ("routine") purchase is made to satisfy that need.

Purchasing decisions made out of habit.

The first stage of the Consumer Decision Making Process, need recognition takes place when a consumer identifies an unmet need.

The second stage of the Consumer Decision Making Process, information search takes place when a consumer seeks relative information that will help them identify and evaluate alternatives before deciding on the final purchase decision.

The third stage of the Consumer Decision Making Process, the evaluation of alternatives takes place when a consumer establishes criteria to evaluate the most viable purchasing option.

Also known as "mental shortcuts" or "rules of thumb", heuristics help consumers by simplifying the decision-making process.

A small set of "go-to" brands that consumers will consider as they evaluate the alternatives available to them before making a purchasing decision.

The brands a consumer would not pay any attention to during the evaluation of alternatives process.

The brands a consumer is aware of but indifferent to, when evaluating alternatives in the consumer decision making process. The consumer may deem these brands irrelevant and will therefore exclude them from any extensive evaluation or consideration.

A term that describes a purchasing situation in which a consumer is faced with an excess of choice that makes decision making difficult or nearly impossible.

A type of cognitive inconsistency, this term describes the discomfort consumers may feel when their beliefs, values, attitudes, or perceptions are inconsistent or contradictory to their original belief or understanding. Consumers with cognitive dissonance related to a purchasing decision will often seek to resolve this internal turmoil they are experiencing by returning the product or finding a way to justify it and minimizing their sense of buyer's remorse.

Introduction to Consumer Behaviour Copyright © 2021 by Andrea Niosi is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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What is Problem Solving? (Steps, Techniques, Examples)

What is problem solving, definition and importance.

Problem solving is the process of finding solutions to obstacles or challenges you encounter in your life or work. It is a crucial skill that allows you to tackle complex situations, adapt to changes, and overcome difficulties with ease. Mastering this ability will contribute to both your personal and professional growth, leading to more successful outcomes and better decision-making.

Problem-Solving Steps

The problem-solving process typically includes the following steps:

• Identify the issue : Recognize the problem that needs to be solved.
• Analyze the situation : Examine the issue in depth, gather all relevant information, and consider any limitations or constraints that may be present.
• Generate potential solutions : Brainstorm a list of possible solutions to the issue, without immediately judging or evaluating them.
• Evaluate options : Weigh the pros and cons of each potential solution, considering factors such as feasibility, effectiveness, and potential risks.
• Select the best solution : Choose the option that best addresses the problem and aligns with your objectives.
• Implement the solution : Put the selected solution into action and monitor the results to ensure it resolves the issue.
• Review and learn : Reflect on the problem-solving process, identify any improvements or adjustments that can be made, and apply these learnings to future situations.

Defining the Problem

To start tackling a problem, first, identify and understand it. Analyzing the issue thoroughly helps to clarify its scope and nature. Ask questions to gather information and consider the problem from various angles. Some strategies to define the problem include:

• Brainstorming with others
• Asking the 5 Ws and 1 H (Who, What, When, Where, Why, and How)
• Analyzing cause and effect
• Creating a problem statement

Generating Solutions

Once the problem is clearly understood, brainstorm possible solutions. Think creatively and keep an open mind, as well as considering lessons from past experiences. Consider:

• Creating a list of potential ideas to solve the problem
• Grouping and categorizing similar solutions
• Prioritizing potential solutions based on feasibility, cost, and resources required
• Involving others to share diverse opinions and inputs

Evaluating and Selecting Solutions

Evaluate each potential solution, weighing its pros and cons. To facilitate decision-making, use techniques such as:

• SWOT analysis (Strengths, Weaknesses, Opportunities, Threats)
• Decision-making matrices
• Pros and cons lists
• Risk assessments

After evaluating, choose the most suitable solution based on effectiveness, cost, and time constraints.

Implementing and Monitoring the Solution

Implement the chosen solution and monitor its progress. Key actions include:

• Communicating the solution to relevant parties
• Setting timelines and milestones
• Assigning tasks and responsibilities
• Monitoring the solution and making adjustments as necessary
• Evaluating the effectiveness of the solution after implementation

Utilize feedback from stakeholders and consider potential improvements. Remember that problem-solving is an ongoing process that can always be refined and enhanced.

Problem-Solving Techniques

During each step, you may find it helpful to utilize various problem-solving techniques, such as:

• Brainstorming : A free-flowing, open-minded session where ideas are generated and listed without judgment, to encourage creativity and innovative thinking.
• Root cause analysis : A method that explores the underlying causes of a problem to find the most effective solution rather than addressing superficial symptoms.
• SWOT analysis : A tool used to evaluate the strengths, weaknesses, opportunities, and threats related to a problem or decision, providing a comprehensive view of the situation.
• Mind mapping : A visual technique that uses diagrams to organize and connect ideas, helping to identify patterns, relationships, and possible solutions.

Brainstorming

When facing a problem, start by conducting a brainstorming session. Gather your team and encourage an open discussion where everyone contributes ideas, no matter how outlandish they may seem. This helps you:

• Generate a diverse range of solutions
• Encourage all team members to participate
• Foster creative thinking

When brainstorming, remember to:

• Reserve judgment until the session is over
• Encourage wild ideas
• Combine and improve upon ideas

Root Cause Analysis

For effective problem-solving, identifying the root cause of the issue at hand is crucial. Try these methods:

• 5 Whys : Ask “why” five times to get to the underlying cause.
• Fishbone Diagram : Create a diagram representing the problem and break it down into categories of potential causes.
• Pareto Analysis : Determine the few most significant causes underlying the majority of problems.

SWOT Analysis

SWOT analysis helps you examine the Strengths, Weaknesses, Opportunities, and Threats related to your problem. To perform a SWOT analysis:

• List your problem’s strengths, such as relevant resources or strong partnerships.
• Identify its weaknesses, such as knowledge gaps or limited resources.
• Explore opportunities, like trends or new technologies, that could help solve the problem.
• Recognize potential threats, like competition or regulatory barriers.

SWOT analysis aids in understanding the internal and external factors affecting the problem, which can help guide your solution.

Mind Mapping

A mind map is a visual representation of your problem and potential solutions. It enables you to organize information in a structured and intuitive manner. To create a mind map:

• Write the problem in the center of a blank page.
• Draw branches from the central problem to related sub-problems or contributing factors.
• Add more branches to represent potential solutions or further ideas.

Mind mapping allows you to visually see connections between ideas and promotes creativity in problem-solving.

Examples of Problem Solving in Various Contexts

In the business world, you might encounter problems related to finances, operations, or communication. Applying problem-solving skills in these situations could look like:

• Identifying areas of improvement in your company’s financial performance and implementing cost-saving measures
• Resolving internal conflicts among team members by listening and understanding different perspectives, then proposing and negotiating solutions
• Streamlining a process for better productivity by removing redundancies, automating tasks, or re-allocating resources

In educational contexts, problem-solving can be seen in various aspects, such as:

• Addressing a gap in students’ understanding by employing diverse teaching methods to cater to different learning styles
• Developing a strategy for successful time management to balance academic responsibilities and extracurricular activities
• Seeking resources and support to provide equal opportunities for learners with special needs or disabilities

Everyday life is full of challenges that require problem-solving skills. Some examples include:

• Overcoming a personal obstacle, such as improving your fitness level, by establishing achievable goals, measuring progress, and adjusting your approach accordingly
• Navigating a new environment or city by researching your surroundings, asking for directions, or using technology like GPS to guide you
• Dealing with a sudden change, like a change in your work schedule, by assessing the situation, identifying potential impacts, and adapting your plans to accommodate the change.
• How to Resolve Employee Conflict at Work [Steps, Tips, Examples]
• How to Write Inspiring Core Values? 5 Steps with Examples
• 30 Employee Feedback Examples (Positive & Negative)

Extensive Problem Solving

In the choice process, extensive problem solving includes those consumer decisions requiring considerable cognitive activity, thought, and behavioral effort as compared to routinized choice behavior and habitual decision making . [1]

This type of decision making is usually associated with high-involvement purchases and when the customer has limited experience with the product category. [2]

• ^ American Marketing Association. AMA Dictionary.
• ^ Govoni, N.A. Dictionary of Marketing Communications, Sage Publications, (2004)

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Struggling to overcome challenges in your life? We all face problems, big and small, on a regular basis.

So how do you tackle them effectively? What are some key problem-solving strategies and skills that can guide you?

Effective problem-solving requires breaking issues down logically, generating solutions creatively, weighing choices critically, and adapting plans flexibly based on outcomes. Useful strategies range from leveraging past solutions that have worked to visualizing problems through diagrams. Core skills include analytical abilities, innovative thinking, and collaboration.

Want to improve your problem-solving skills? Keep reading to find out 17 effective problem-solving strategies, key skills, common obstacles to watch for, and tips on improving your overall problem-solving skills.

Key Takeaways:

• Effective problem-solving requires breaking down issues logically, generating multiple solutions creatively, weighing choices critically, and adapting plans based on outcomes.
• Useful problem-solving strategies range from leveraging past solutions to brainstorming with groups to visualizing problems through diagrams and models.
• Core skills include analytical abilities, innovative thinking, decision-making, and team collaboration to solve problems.
• Common obstacles include fear of failure, information gaps, fixed mindsets, confirmation bias, and groupthink.
• Boosting problem-solving skills involves learning from experts, actively practicing, soliciting feedback, and analyzing others’ success.
• Onethread’s project management capabilities align with effective problem-solving tenets – facilitating structured solutions, tracking progress, and capturing lessons learned.

What Is Problem-Solving?

Problem-solving is the process of understanding an issue, situation, or challenge that needs to be addressed and then systematically working through possible solutions to arrive at the best outcome.

It involves critical thinking, analysis, logic, creativity, research, planning, reflection, and patience in order to overcome obstacles and find effective answers to complex questions or problems.

The ultimate goal is to implement the chosen solution successfully.

What Are Problem-Solving Strategies?

Problem-solving strategies are like frameworks or methodologies that help us solve tricky puzzles or problems we face in the workplace, at home, or with friends.

Imagine you have a big jigsaw puzzle. One strategy might be to start with the corner pieces. Another could be looking for pieces with the same colors. 

Just like in puzzles, in real life, we use different plans or steps to find solutions to problems. These strategies help us think clearly, make good choices, and find the best answers without getting too stressed or giving up.

Why Is It Important To Know Different Problem-Solving Strategies?

Knowing different problem-solving strategies is important because different types of problems often require different approaches to solve them effectively. Having a variety of strategies to choose from allows you to select the best method for the specific problem you are trying to solve.

This improves your ability to analyze issues thoroughly, develop solutions creatively, and tackle problems from multiple angles. Knowing multiple strategies also aids in overcoming roadblocks if your initial approach is not working.

Here are some reasons why you need to know different problem-solving strategies:

• Different Problems Require Different Tools: Just like you can’t use a hammer to fix everything, some problems need specific strategies to solve them.
• Improves Creativity: Knowing various strategies helps you think outside the box and come up with creative solutions.
• Saves Time: With the right strategy, you can solve problems faster instead of trying things that don’t work.
• Reduces Stress: When you know how to tackle a problem, it feels less scary and you feel more confident.
• Better Outcomes: Using the right strategy can lead to better solutions, making things work out better in the end.
• Learning and Growth: Each time you solve a problem, you learn something new, which makes you smarter and better at solving future problems.

Knowing different ways to solve problems helps you tackle anything that comes your way, making life a bit easier and more fun!

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. Collaboration with others can also provide diverse perspectives and ideas. 

By applying these strategies, you can tackle complex issues more effectively.

Now, consider a challenge you’re dealing with. Which strategy could help you find a solution? Here we will discuss key problem strategies in detail.

1. Use a Past Solution That Worked

This strategy involves looking back at previous similar problems you have faced and the solutions that were effective in solving them.

It is useful when you are facing a problem that is very similar to something you have already solved. The main benefit is that you don’t have to come up with a brand new solution – you already know the method that worked before will likely work again.

However, the limitation is that the current problem may have some unique aspects or differences that mean your old solution is not fully applicable.

The ideal process is to thoroughly analyze the new challenge, identify the key similarities and differences versus the past case, adapt the old solution as needed to align with the current context, and then pilot it carefully before full implementation.

An example is using the same negotiation tactics from purchasing your previous home when putting in an offer on a new house. Key terms would be adjusted but overall it can save significant time versus developing a brand new strategy.

2. Brainstorm Solutions

This involves gathering a group of people together to generate as many potential solutions to a problem as possible.

It is effective when you need creative ideas to solve a complex or challenging issue. By getting input from multiple people with diverse perspectives, you increase the likelihood of finding an innovative solution.

The main limitation is that brainstorming sessions can sometimes turn into unproductive gripe sessions or discussions rather than focusing on productive ideation —so they need to be properly facilitated.

The key to an effective brainstorming session is setting some basic ground rules upfront and having an experienced facilitator guide the discussion. Rules often include encouraging wild ideas, avoiding criticism of ideas during the ideation phase, and building on others’ ideas.

For instance, a struggling startup might hold a session where ideas for turnaround plans are generated and then formalized with financials and metrics.

3. Work Backward from the Solution

This technique involves envisioning that the problem has already been solved and then working step-by-step backward toward the current state.

This strategy is particularly helpful for long-term, multi-step problems. By starting from the imagined solution and identifying all the steps required to reach it, you can systematically determine the actions needed. It lets you tackle a big hairy problem through smaller, reversible steps.

A limitation is that this approach may not be possible if you cannot accurately envision the solution state to start with.

The approach helps drive logical systematic thinking for complex problem-solving, but should still be combined with creative brainstorming of alternative scenarios and solutions.

An example is planning for an event – you would imagine the successful event occurring, then determine the tasks needed the week before, two weeks before, etc. all the way back to the present.

4. Use the Kipling Method

This method, named after author Rudyard Kipling, provides a framework for thoroughly analyzing a problem before jumping into solutions.

It consists of answering six fundamental questions: What, Where, When, How, Who, and Why about the challenge. Clearly defining these core elements of the problem sets the stage for generating targeted solutions.

The Kipling method enables a deep understanding of problem parameters and root causes before solution identification. By jumping to brainstorm solutions too early, critical information can be missed or the problem is loosely defined, reducing solution quality.

Answering the six fundamental questions illuminates all angles of the issue. This takes time but pays dividends in generating optimal solutions later tuned precisely to the true underlying problem.

The limitation is that meticulously working through numerous questions before addressing solutions can slow progress.

The best approach blends structured problem decomposition techniques like the Kipling method with spurring innovative solution ideation from a diverse team. 

An example is using this technique after a technical process failure – the team would systematically detail What failed, Where/When did it fail, How it failed (sequence of events), Who was involved, and Why it likely failed before exploring preventative solutions.

5. Try Different Solutions Until One Works (Trial and Error)

This technique involves attempting various potential solutions sequentially until finding one that successfully solves the problem.

Trial and error works best when facing a concrete, bounded challenge with clear solution criteria and a small number of discrete options to try. By methodically testing solutions, you can determine the faulty component.

A limitation is that it can be time-intensive if the working solution set is large.

The key is limiting the variable set first. For technical problems, this boundary is inherent and each element can be iteratively tested. But for business issues, artificial constraints may be required – setting decision rules upfront to reduce options before testing.

Furthermore, hypothesis-driven experimentation is far superior to blind trial and error – have logic for why Option A may outperform Option B.

Examples include fixing printer jams by testing different paper tray and cable configurations or resolving website errors by tweaking CSS/HTML line-by-line until the code functions properly.

6. Use Proven Formulas or Frameworks (Heuristics)

Heuristics refers to applying existing problem-solving formulas or frameworks rather than addressing issues completely from scratch.

This allows leveraging established best practices rather than reinventing the wheel each time.

It is effective when facing recurrent, common challenges where proven structured approaches exist.

However, heuristics may force-fit solutions to non-standard problems.

For example, a cost-benefit analysis can be used instead of custom weighting schemes to analyze potential process improvements.

Onethread allows teams to define, save, and replicate configurable project templates so proven workflows can be reliably applied across problems with some consistency rather than fully custom one-off approaches each time.

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7. Trust Your Instincts (Insight Problem-Solving)

Insight is a problem-solving technique that involves waiting patiently for an unexpected “aha moment” when the solution pops into your mind.

It works well for personal challenges that require intuitive realizations over calculated logic. The unconscious mind makes connections leading to flashes of insight when relaxing or doing mundane tasks unrelated to the actual problem.

Benefits include out-of-the-box creative solutions. However, the limitations are that insights can’t be forced and may never come at all if too complex. Critical analysis is still required after initial insights.

A real-life example would be a writer struggling with how to end a novel. Despite extensive brainstorming, they feel stuck. Eventually while gardening one day, a perfect unexpected plot twist sparks an ideal conclusion. However, once written they still carefully review if the ending flows logically from the rest of the story.

8. Reverse Engineer the Problem

This approach involves deconstructing a problem in reverse sequential order from the current undesirable outcome back to the initial root causes.

By mapping the chain of events backward, you can identify the origin of where things went wrong and establish the critical junctures for solving it moving ahead. Reverse engineering provides diagnostic clarity on multi-step problems.

However, the limitation is that it focuses heavily on autopsying the past versus innovating improved future solutions.

An example is tracing back from a server outage, through the cascade of infrastructure failures that led to it finally terminating at the initial script error that triggered the crisis. This root cause would then inform the preventative measure.

9. Break Down Obstacles Between Current and Goal State (Means-End Analysis)

This technique defines the current problem state and the desired end goal state, then systematically identifies obstacles in the way of getting from one to the other.

By mapping the barriers or gaps, you can then develop solutions to address each one. This methodically connects the problem to solutions.

A limitation is that some obstacles may be unknown upfront and only emerge later.

For example, you can list down all the steps required for a new product launch – current state through production, marketing, sales, distribution, etc. to full launch (goal state) – to highlight where resource constraints or other blocks exist so they can be addressed.

Onethread allows dividing big-picture projects into discrete, manageable phases, milestones, and tasks to simplify execution just as problems can be decomposed into more achievable components. Features like dependency mapping further reinforce interconnections.

Using Onethread’s issues and subtasks feature, messy problems can be decomposed into manageable chunks.

10. Ask “Why” Five Times to Identify the Root Cause (The 5 Whys)

This technique involves asking “Why did this problem occur?” and then responding with an answer that is again met with asking “Why?” This process repeats five times until the root cause is revealed.

Continually asking why digs deeper from surface symptoms to underlying systemic issues.

It is effective for getting to the source of problems originating from human error or process breakdowns.

However, some complex issues may have multiple tangled root causes not solvable through this approach alone.

An example is a retail store experiencing a sudden decline in customers. Successively asking why five times may trace an initial drop to parking challenges, stemming from a city construction project – the true starting point to address.

11. Evaluate Strengths, Weaknesses, Opportunities, and Threats (SWOT Analysis)

This involves analyzing a problem or proposed solution by categorizing internal and external factors into a 2×2 matrix: Strengths, Weaknesses as the internal rows; Opportunities and Threats as the external columns.

Systematically identifying these elements provides balanced insight to evaluate options and risks. It is impactful when evaluating alternative solutions or developing strategy amid complexity or uncertainty.

The key benefit of SWOT analysis is enabling multi-dimensional thinking when rationally evaluating options. Rather than getting anchored on just the upsides or the existing way of operating, it urges a systematic assessment through four different lenses:

• Internal Strengths: Our core competencies/advantages able to deliver success
• Internal Weaknesses: Gaps/vulnerabilities we need to manage
• External Opportunities: Ways we can differentiate/drive additional value
• External Threats: Risks we must navigate or mitigate

Multiperspective analysis provides the needed holistic view of the balanced risk vs. reward equation for strategic decision making amid uncertainty.

However, SWOT can feel restrictive if not tailored and evolved for different issue types.

Teams should view SWOT analysis as a starting point, augmenting it further for distinct scenarios.

An example is performing a SWOT analysis on whether a small business should expand into a new market – evaluating internal capabilities to execute vs. risks in the external competitive and demand environment to inform the growth decision with eyes wide open.

12. Compare Current vs Expected Performance (Gap Analysis)

This technique involves comparing the current state of performance, output, or results to the desired or expected levels to highlight shortfalls.

By quantifying the gaps, you can identify problem areas and prioritize address solutions.

Gap analysis is based on the simple principle – “you can’t improve what you don’t measure.” It enables facts-driven problem diagnosis by highlighting delta to goals, not just vague dissatisfaction that something seems wrong. And measurement immediately suggests improvement opportunities – address the biggest gaps first.

This data orientation also supports ROI analysis on fixing issues – the return from closing larger gaps outweighs narrowly targeting smaller performance deficiencies.

However, the approach is only effective if robust standards and metrics exist as the benchmark to evaluate against. Organizations should invest upfront in establishing performance frameworks.

Furthermore, while numbers are invaluable, the human context behind problems should not be ignored – quantitative versus qualitative gap assessment is optimally blended.

For example, if usage declines are noted during software gap analysis, this could be used as a signal to improve user experience through design.

13. Observe Processes from the Frontline (Gemba Walk)

A Gemba walk involves going to the actual place where work is done, directly observing the process, engaging with employees, and finding areas for improvement.

By experiencing firsthand rather than solely reviewing abstract reports, practical problems and ideas emerge.

The limitation is Gemba walks provide anecdotes not statistically significant data. It complements but does not replace comprehensive performance measurement.

An example is a factory manager inspecting the production line to spot jam areas based on direct reality rather than relying on throughput dashboards alone back in her office. Frontline insights prove invaluable.

14. Analyze Competitive Forces (Porter’s Five Forces)

This involves assessing the marketplace around a problem or business situation via five key factors: competitors, new entrants, substitute offerings, suppliers, and customer power.

Evaluating these forces illuminates risks and opportunities for strategy development and issue resolution. It is effective for understanding dynamic external threats and opportunities when operating in a contested space.

However, over-indexing on only external factors can overlook the internal capabilities needed to execute solutions.

A startup CEO, for example, may analyze market entry barriers, whitespace opportunities, and disruption risks across these five forces to shape new product rollout strategies and marketing approaches.

15. Think from Different Perspectives (Six Thinking Hats)

The Six Thinking Hats is a technique developed by Edward de Bono that encourages people to think about a problem from six different perspectives, each represented by a colored “thinking hat.”

The key benefit of this strategy is that it pushes team members to move outside their usual thinking style and consider new angles. This brings more diverse ideas and solutions to the table.

It works best for complex problems that require innovative solutions and when a team is stuck in an unproductive debate. The structured framework keeps the conversation flowing in a positive direction.

Limitations are that it requires training on the method itself and may feel unnatural at first. Team dynamics can also influence success – some members may dominate certain “hats” while others remain quiet.

A real-life example is a software company debating whether to build a new feature. The white hat focuses on facts, red on gut feelings, black on potential risks, yellow on benefits, green on new ideas, and blue on process. This exposes more balanced perspectives before deciding.

Onethread centralizes diverse stakeholder communication onto one platform, ensuring all voices are incorporated when evaluating project tradeoffs, just as problem-solving should consider multifaceted solutions.

16. Visualize the Problem (Draw it Out)

Drawing out a problem involves creating visual representations like diagrams, flowcharts, and maps to work through challenging issues.

This strategy is helpful when dealing with complex situations with lots of interconnected components. The visuals simplify the complexity so you can thoroughly understand the problem and all its nuances.

Key benefits are that it allows more stakeholders to get on the same page regarding root causes and it sparks new creative solutions as connections are made visually.

However, simple problems with few variables don’t require extensive diagrams. Additionally, some challenges are so multidimensional that fully capturing every aspect is difficult.

A real-life example would be mapping out all the possible causes leading to decreased client satisfaction at a law firm. An intricate fishbone diagram with branches for issues like service delivery, technology, facilities, culture, and vendor partnerships allows the team to trace problems back to their origins and brainstorm targeted fixes.

17. Follow a Step-by-Step Procedure (Algorithms)

An algorithm is a predefined step-by-step process that is guaranteed to produce the correct solution if implemented properly.

Using algorithms is effective when facing problems that have clear, binary right and wrong answers. Algorithms work for mathematical calculations, computer code, manufacturing assembly lines, and scientific experiments.

Key benefits are consistency, accuracy, and efficiency. However, they require extensive upfront development and only apply to scenarios with strict parameters. Additionally, human error can lead to mistakes.

For example, crew members of fast food chains like McDonald’s follow specific algorithms for food prep – from grill times to ingredient amounts in sandwiches, to order fulfillment procedures. This ensures uniform quality and service across all locations. However, if a step is missed, errors occur.

The Problem-Solving Process

The problem-solving process typically includes defining the issue, analyzing details, creating solutions, weighing choices, acting, and reviewing results.

In the above, we have discussed several problem-solving strategies. For every problem-solving strategy, you have to follow these processes. Here’s a detailed step-by-step process of effective problem-solving:

Step 1: Identify the Problem

The problem-solving process starts with identifying the problem. This step involves understanding the issue’s nature, its scope, and its impact. Once the problem is clearly defined, it sets the foundation for finding effective solutions.

Identifying the problem is crucial. It means figuring out exactly what needs fixing. This involves looking at the situation closely, understanding what’s wrong, and knowing how it affects things. It’s about asking the right questions to get a clear picture of the issue. 

This step is important because it guides the rest of the problem-solving process. Without a clear understanding of the problem, finding a solution is much harder. It’s like diagnosing an illness before treating it. Once the problem is identified accurately, you can move on to exploring possible solutions and deciding on the best course of action.

Step 2: Break Down the Problem

Breaking down the problem is a key step in the problem-solving process. It involves dividing the main issue into smaller, more manageable parts. This makes it easier to understand and tackle each component one by one.

After identifying the problem, the next step is to break it down. This means splitting the big issue into smaller pieces. It’s like solving a puzzle by handling one piece at a time. 

By doing this, you can focus on each part without feeling overwhelmed. It also helps in identifying the root causes of the problem. Breaking down the problem allows for a clearer analysis and makes finding solutions more straightforward. 

Each smaller problem can be addressed individually, leading to an effective resolution of the overall issue. This approach not only simplifies complex problems but also aids in developing a systematic plan to solve them.

Step 3: Come up with potential solutions

Coming up with potential solutions is the third step in the problem-solving process. It involves brainstorming various options to address the problem, considering creativity and feasibility to find the best approach.

After breaking down the problem, it’s time to think of ways to solve it. This stage is about brainstorming different solutions. You look at the smaller issues you’ve identified and start thinking of ways to fix them. This is where creativity comes in. 

You want to come up with as many ideas as possible, no matter how out-of-the-box they seem. It’s important to consider all options and evaluate their pros and cons. This process allows you to gather a range of possible solutions. 

Later, you can narrow these down to the most practical and effective ones. This step is crucial because it sets the stage for deciding on the best solution to implement. It’s about being open-minded and innovative to tackle the problem effectively.

Step 4: Analyze the possible solutions

Analyzing the possible solutions is the fourth step in the problem-solving process. It involves evaluating each proposed solution’s advantages and disadvantages to determine the most effective and feasible option.

After coming up with potential solutions, the next step is to analyze them. This means looking closely at each idea to see how well it solves the problem. You weigh the pros and cons of every solution.

Consider factors like cost, time, resources, and potential outcomes. This analysis helps in understanding the implications of each option. It’s about being critical and objective, ensuring that the chosen solution is not only effective but also practical.

This step is vital because it guides you towards making an informed decision. It involves comparing the solutions against each other and selecting the one that best addresses the problem.

By thoroughly analyzing the options, you can move forward with confidence, knowing you’ve chosen the best path to solve the issue.

Step 5: Implement and Monitor the Solutions

Implementing and monitoring the solutions is the final step in the problem-solving process. It involves putting the chosen solution into action and observing its effectiveness, making adjustments as necessary.

Once you’ve selected the best solution, it’s time to put it into practice. This step is about action. You implement the chosen solution and then keep an eye on how it works. Monitoring is crucial because it tells you if the solution is solving the problem as expected. 

If things don’t go as planned, you may need to make some changes. This could mean tweaking the current solution or trying a different one. The goal is to ensure the problem is fully resolved. 

This step is critical because it involves real-world application. It’s not just about planning; it’s about doing and adjusting based on results. By effectively implementing and monitoring the solutions, you can achieve the desired outcome and solve the problem successfully.

Why This Process is Important

Following a defined process to solve problems is important because it provides a systematic, structured approach instead of a haphazard one. Having clear steps guides logical thinking, analysis, and decision-making to increase effectiveness. Key reasons it helps are:

• Clear Direction: This process gives you a clear path to follow, which can make solving problems less overwhelming.
• Better Solutions: Thoughtful analysis of root causes, iterative testing of solutions, and learning orientation lead to addressing the heart of issues rather than just symptoms.
• Saves Time and Energy: Instead of guessing or trying random things, this process helps you find a solution more efficiently.
• Improves Skills: The more you use this process, the better you get at solving problems. It’s like practicing a sport. The more you practice, the better you play.
• Maximizes collaboration: Involving various stakeholders in the process enables broader inputs. Their communication and coordination are streamlined through organized brainstorming and evaluation.
• Provides consistency: Standard methodology across problems enables building institutional problem-solving capabilities over time. Patterns emerge on effective techniques to apply to different situations.

The problem-solving process is a powerful tool that can help us tackle any challenge we face. By following these steps, we can find solutions that work and learn important skills along the way.

Key Skills for Efficient Problem Solving

Efficient problem-solving requires breaking down issues logically, evaluating options, and implementing practical solutions.

Key skills include critical thinking to understand root causes, creativity to brainstorm innovative ideas, communication abilities to collaborate with others, and decision-making to select the best way forward. Staying adaptable, reflecting on outcomes, and applying lessons learned are also essential.

With practice, these capacities will lead to increased personal and team effectiveness in systematically addressing any problem.

 Let’s explore the powers you need to become a problem-solving hero!

Critical Thinking and Analytical Skills

Critical thinking and analytical skills are vital for efficient problem-solving as they enable individuals to objectively evaluate information, identify key issues, and generate effective solutions. 

These skills facilitate a deeper understanding of problems, leading to logical, well-reasoned decisions. By systematically breaking down complex issues and considering various perspectives, individuals can develop more innovative and practical solutions, enhancing their problem-solving effectiveness.

Communication Skills

Effective communication skills are essential for efficient problem-solving as they facilitate clear sharing of information, ensuring all team members understand the problem and proposed solutions. 

These skills enable individuals to articulate issues, listen actively, and collaborate effectively, fostering a productive environment where diverse ideas can be exchanged and refined. By enhancing mutual understanding, communication skills contribute significantly to identifying and implementing the most viable solutions.

Decision-Making

Strong decision-making skills are crucial for efficient problem-solving, as they enable individuals to choose the best course of action from multiple alternatives. 

These skills involve evaluating the potential outcomes of different solutions, considering the risks and benefits, and making informed choices. Effective decision-making leads to the implementation of solutions that are likely to resolve problems effectively, ensuring resources are used efficiently and goals are achieved.

Planning and Prioritization

Planning and prioritization are key for efficient problem-solving, ensuring resources are allocated effectively to address the most critical issues first. This approach helps in organizing tasks according to their urgency and impact, streamlining efforts towards achieving the desired outcome efficiently.

Emotional Intelligence

Emotional intelligence enhances problem-solving by allowing individuals to manage emotions, understand others, and navigate social complexities. It fosters a positive, collaborative environment, essential for generating creative solutions and making informed, empathetic decisions.

Leadership skills drive efficient problem-solving by inspiring and guiding teams toward common goals. Effective leaders motivate their teams, foster innovation, and navigate challenges, ensuring collective efforts are focused and productive in addressing problems.

Time Management

Time management is crucial in problem-solving, enabling individuals to allocate appropriate time to each task. By efficiently managing time, one can ensure that critical problems are addressed promptly without neglecting other responsibilities.

Data Analysis

Data analysis skills are essential for problem-solving, as they enable individuals to sift through data, identify trends, and extract actionable insights. This analytical approach supports evidence-based decision-making, leading to more accurate and effective solutions.

Research Skills

Research skills are vital for efficient problem-solving, allowing individuals to gather relevant information, explore various solutions, and understand the problem’s context. This thorough exploration aids in developing well-informed, innovative solutions.

Becoming a great problem solver takes practice, but with these skills, you’re on your way to becoming a problem-solving hero. 

How to Improve Your Problem-Solving Skills?

Improving your problem-solving skills can make you a master at overcoming challenges. Learn from experts, practice regularly, welcome feedback, try new methods, experiment, and study others’ success to become better.

Learning from Experts

Improving problem-solving skills by learning from experts involves seeking mentorship, attending workshops, and studying case studies. Experts provide insights and techniques that refine your approach, enhancing your ability to tackle complex problems effectively.

To enhance your problem-solving skills, learning from experts can be incredibly beneficial. Engaging with mentors, participating in specialized workshops, and analyzing case studies from seasoned professionals can offer valuable perspectives and strategies. 

Experts share their experiences, mistakes, and successes, providing practical knowledge that can be applied to your own problem-solving process. This exposure not only broadens your understanding but also introduces you to diverse methods and approaches, enabling you to tackle challenges more efficiently and creatively.

Improving problem-solving skills through practice involves tackling a variety of challenges regularly. This hands-on approach helps in refining techniques and strategies, making you more adept at identifying and solving problems efficiently.

One of the most effective ways to enhance your problem-solving skills is through consistent practice. By engaging with different types of problems on a regular basis, you develop a deeper understanding of various strategies and how they can be applied. 

This hands-on experience allows you to experiment with different approaches, learn from mistakes, and build confidence in your ability to tackle challenges.

Regular practice not only sharpens your analytical and critical thinking skills but also encourages adaptability and innovation, key components of effective problem-solving.

Openness to Feedback

Being open to feedback is like unlocking a secret level in a game. It helps you boost your problem-solving skills. Improving problem-solving skills through openness to feedback involves actively seeking and constructively responding to critiques. 

This receptivity enables you to refine your strategies and approaches based on insights from others, leading to more effective solutions. 

Learning New Approaches and Methodologies

Learning new approaches and methodologies is like adding new tools to your toolbox. It makes you a smarter problem-solver. Enhancing problem-solving skills by learning new approaches and methodologies involves staying updated with the latest trends and techniques in your field. 

This continuous learning expands your toolkit, enabling innovative solutions and a fresh perspective on challenges.

Experimentation

Experimentation is like being a scientist of your own problems. It’s a powerful way to improve your problem-solving skills. Boosting problem-solving skills through experimentation means trying out different solutions to see what works best. This trial-and-error approach fosters creativity and can lead to unique solutions that wouldn’t have been considered otherwise.

Analyzing Competitors’ Success

Analyzing competitors’ success is like being a detective. It’s a smart way to boost your problem-solving skills. Improving problem-solving skills by analyzing competitors’ success involves studying their strategies and outcomes. Understanding what worked for them can provide valuable insights and inspire effective solutions for your own challenges. 

Challenges in Problem-Solving

Facing obstacles when solving problems is common. Recognizing these barriers, like fear of failure or lack of information, helps us find ways around them for better solutions.

Fear of Failure

Fear of failure is like a big, scary monster that stops us from solving problems. It’s a challenge many face. Because being afraid of making mistakes can make us too scared to try new solutions. 

How can we overcome this? First, understand that it’s okay to fail. Failure is not the opposite of success; it’s part of learning. Every time we fail, we discover one more way not to solve a problem, getting us closer to the right solution. Treat each attempt like an experiment. It’s not about failing; it’s about testing and learning.

Lack of Information

Lack of information is like trying to solve a puzzle with missing pieces. It’s a big challenge in problem-solving. Because without all the necessary details, finding a solution is much harder. 

How can we fix this? Start by gathering as much information as you can. Ask questions, do research, or talk to experts. Think of yourself as a detective looking for clues. The more information you collect, the clearer the picture becomes. Then, use what you’ve learned to think of solutions. 

Fixed Mindset

A fixed mindset is like being stuck in quicksand; it makes solving problems harder. It means thinking you can’t improve or learn new ways to solve issues. 

How can we change this? First, believe that you can grow and learn from challenges. Think of your brain as a muscle that gets stronger every time you use it. When you face a problem, instead of saying “I can’t do this,” try thinking, “I can’t do this yet.” Look for lessons in every challenge and celebrate small wins. 

Everyone starts somewhere, and mistakes are just steps on the path to getting better. By shifting to a growth mindset, you’ll see problems as opportunities to grow. Keep trying, keep learning, and your problem-solving skills will soar!

Jumping to Conclusions

Jumping to conclusions is like trying to finish a race before it starts. It’s a challenge in problem-solving. That means making a decision too quickly without looking at all the facts. 

How can we avoid this? First, take a deep breath and slow down. Think about the problem like a puzzle. You need to see all the pieces before you know where they go. Ask questions, gather information, and consider different possibilities. Don’t choose the first solution that comes to mind. Instead, compare a few options. 

Feeling Overwhelmed

Feeling overwhelmed is like being buried under a mountain of puzzles. It’s a big challenge in problem-solving. When we’re overwhelmed, everything seems too hard to handle. 

How can we deal with this? Start by taking a step back. Breathe deeply and focus on one thing at a time. Break the big problem into smaller pieces, like sorting puzzle pieces by color. Tackle each small piece one by one. It’s also okay to ask for help. Sometimes, talking to someone else can give you a new perspective. 

Confirmation Bias

Confirmation bias is like wearing glasses that only let you see what you want to see. It’s a challenge in problem-solving. Because it makes us focus only on information that agrees with what we already believe, ignoring anything that doesn’t. 

How can we overcome this? First, be aware that you might be doing it. It’s like checking if your glasses are on right. Then, purposely look for information that challenges your views. It’s like trying on a different pair of glasses to see a new perspective. Ask questions and listen to answers, even if they don’t fit what you thought before.

Groupthink is like everyone in a group deciding to wear the same outfit without asking why. It’s a challenge in problem-solving. It means making decisions just because everyone else agrees, without really thinking it through. 

How can we avoid this? First, encourage everyone in the group to share their ideas, even if they’re different. It’s like inviting everyone to show their unique style of clothes. 

Listen to all opinions and discuss them. It’s okay to disagree; it helps us think of better solutions. Also, sometimes, ask someone outside the group for their thoughts. They might see something everyone in the group missed.

Overcoming obstacles in problem-solving requires patience, openness, and a willingness to learn from mistakes. By recognizing these barriers, we can develop strategies to navigate around them, leading to more effective and creative solutions.

What are the most common problem-solving techniques?

The most common techniques include brainstorming, the 5 Whys, mind mapping, SWOT analysis, and using algorithms or heuristics. Each approach has its strengths, suitable for different types of problems.

What’s the best problem-solving strategy for every situation?

There’s no one-size-fits-all strategy. The best approach depends on the problem’s complexity, available resources, and time constraints. Combining multiple techniques often yields the best results.

How can I improve my problem-solving skills?

Improve your problem-solving skills by practicing regularly, learning from experts, staying open to feedback, and continuously updating your knowledge on new approaches and methodologies.

Are there any tools or resources to help with problem-solving?

Yes, tools like mind mapping software, online courses on critical thinking, and books on problem-solving techniques can be very helpful. Joining forums or groups focused on problem-solving can also provide support and insights.

What are some common mistakes people make when solving problems?

Common mistakes include jumping to conclusions without fully understanding the problem, ignoring valuable feedback, sticking to familiar solutions without considering alternatives, and not breaking down complex problems into manageable parts.

Final Words

Mastering problem-solving strategies equips us with the tools to tackle challenges across all areas of life. By understanding and applying these techniques, embracing a growth mindset, and learning from both successes and obstacles, we can transform problems into opportunities for growth. Continuously improving these skills ensures we’re prepared to face and solve future challenges more effectively.

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What Are Problem-Solving Skills? Definition and Examples

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Forage puts students first. Our blog articles are written independently by our editorial team. They have not been paid for or sponsored by our partners. See our full  editorial guidelines .

Why do employers hire employees? To help them solve problems. Whether you’re a financial analyst deciding where to invest your firm’s money, or a marketer trying to figure out which channel to direct your efforts, companies hire people to help them find solutions. Problem-solving is an essential and marketable soft skill in the workplace. 

So, how can you improve your problem-solving and show employers you have this valuable skill? In this guide, we’ll cover:

Problem-Solving Skills Definition

Why are problem-solving skills important, problem-solving skills examples, how to include problem-solving skills in a job application, how to improve problem-solving skills, problem-solving: the bottom line.

Problem-solving skills are the ability to identify problems, brainstorm and analyze answers, and implement the best solutions. An employee with good problem-solving skills is both a self-starter and a collaborative teammate; they are proactive in understanding the root of a problem and work with others to consider a wide range of solutions before deciding how to move forward. 

Examples of using problem-solving skills in the workplace include:

• Researching patterns to understand why revenue decreased last quarter
• Experimenting with a new marketing channel to increase website sign-ups
• Brainstorming content types to share with potential customers
• Testing calls to action to see which ones drive the most product sales
• Implementing a new workflow to automate a team process and increase productivity

Problem-solving skills are the most sought-after soft skill of 2022. In fact, 86% of employers look for problem-solving skills on student resumes, according to the National Association of Colleges and Employers Job Outlook 2022 survey . 

It’s unsurprising why employers are looking for this skill: companies will always need people to help them find solutions to their problems. Someone proactive and successful at problem-solving is valuable to any team.

“Employers are looking for employees who can make decisions independently, especially with the prevalence of remote/hybrid work and the need to communicate asynchronously,” Eric Mochnacz, senior HR consultant at Red Clover, says. “Employers want to see individuals who can make well-informed decisions that mitigate risk, and they can do so without suffering from analysis paralysis.”

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Problem-solving includes three main parts: identifying the problem, analyzing possible solutions, and deciding on the best course of action.

>>MORE: Discover the right career for you based on your skills with a career aptitude test .

Research is the first step of problem-solving because it helps you understand the context of a problem. Researching a problem enables you to learn why the problem is happening. For example, is revenue down because of a new sales tactic? Or because of seasonality? Is there a problem with who the sales team is reaching out to? 

Research broadens your scope to all possible reasons why the problem could be happening. Then once you figure it out, it helps you narrow your scope to start solving it. 

Analysis is the next step of problem-solving. Now that you’ve identified the problem, analytical skills help you look at what potential solutions there might be.

“The goal of analysis isn’t to solve a problem, actually — it’s to better understand it because that’s where the real solution will be found,” Gretchen Skalka, owner of Career Insights Consulting, says. “Looking at a problem through the lens of impartiality is the only way to get a true understanding of it from all angles.”

Decision-Making

Once you’ve figured out where the problem is coming from and what solutions are, it’s time to decide on the best way to go forth. Decision-making skills help you determine what resources are available, what a feasible action plan entails, and what solution is likely to lead to success.

On a Resume

Employers looking for problem-solving skills might include the word “problem-solving” or other synonyms like “ critical thinking ” or “analytical skills” in the job description.

“I would add ‘buzzwords’ you can find from the job descriptions or LinkedIn endorsements section to filter into your resume to comply with the ATS,” Matthew Warzel, CPRW resume writer, advises. Warzel recommends including these skills on your resume but warns to “leave the soft skills as adjectives in the summary section. That is the only place soft skills should be mentioned.”

On the other hand, you can list hard skills separately in a skills section on your resume .

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In a Cover Letter or an Interview

Explaining your problem-solving skills in an interview can seem daunting. You’re required to expand on your process — how you identified a problem, analyzed potential solutions, and made a choice. As long as you can explain your approach, it’s okay if that solution didn’t come from a professional work experience.

“Young professionals shortchange themselves by thinking only paid-for solutions matter to employers,” Skalka says. “People at the genesis of their careers don’t have a wealth of professional experience to pull from, but they do have relevant experience to share.”

Aaron Case, career counselor and CPRW at Resume Genius, agrees and encourages early professionals to share this skill. “If you don’t have any relevant work experience yet, you can still highlight your problem-solving skills in your cover letter,” he says. “Just showcase examples of problems you solved while completing your degree, working at internships, or volunteering. You can even pull examples from completely unrelated part-time jobs, as long as you make it clear how your problem-solving ability transfers to your new line of work.”

Learn How to Identify Problems

Problem-solving doesn’t just require finding solutions to problems that are already there. It’s also about being proactive when something isn’t working as you hoped it would. Practice questioning and getting curious about processes and activities in your everyday life. What could you improve? What would you do if you had more resources for this process? If you had fewer? Challenge yourself to challenge the world around you.

Think Digitally

“Employers in the modern workplace value digital problem-solving skills, like being able to find a technology solution to a traditional issue,” Case says. “For example, when I first started working as a marketing writer, my department didn’t have the budget to hire a professional voice actor for marketing video voiceovers. But I found a perfect solution to the problem with an AI voiceover service that cost a fraction of the price of an actor.”

Being comfortable with new technology — even ones you haven’t used before — is a valuable skill in an increasingly hybrid and remote world. Don’t be afraid to research new and innovative technologies to help automate processes or find a more efficient technological solution.

Collaborate

Problem-solving isn’t done in a silo, and it shouldn’t be. Use your collaboration skills to gather multiple perspectives, help eliminate bias, and listen to alternative solutions. Ask others where they think the problem is coming from and what solutions would help them with your workflow. From there, try to compromise on a solution that can benefit everyone.

If we’ve learned anything from the past few years, it’s that the world of work is constantly changing — which means it’s crucial to know how to adapt . Be comfortable narrowing down a solution, then changing your direction when a colleague provides a new piece of information. Challenge yourself to get out of your comfort zone, whether with your personal routine or trying a new system at work.

Put Yourself in the Middle of Tough Moments

Just like adapting requires you to challenge your routine and tradition, good problem-solving requires you to put yourself in challenging situations — especially ones where you don’t have relevant experience or expertise to find a solution. Because you won’t know how to tackle the problem, you’ll learn new problem-solving skills and how to navigate new challenges. Ask your manager or a peer if you can help them work on a complicated problem, and be proactive about asking them questions along the way.

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Step 1 of 3

Companies always need people to help them find solutions — especially proactive employees who have practical analytical skills and can collaborate to decide the best way to move forward. Whether or not you have experience solving problems in a professional workplace, illustrate your problem-solving skills by describing your research, analysis, and decision-making process — and make it clear that you’re the solution to the employer’s current problems. 

Image Credit: Christina Morillo / Pexels 

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Module 4: Identifying and Understanding Customer Behavior

Increasing sales with extended problem solving, learning objectives.

• Describe how a retailer can increase sales from customers engaged in extended problem solving

Consumers with an extended problem solving mindset put a great deal of effort into their purchase decision, gathering information through research and taking care to evaluate all options, before arriving at a decision. Because of the time and energy committed to the search, this diligence is more likely dedicated to the selection and purchase of high-consideration or high-value items like cars, electronics and appliances. Or, it may be focused on something that is new or infrequently purchased. Thus, the consumer feels compelled to do more research to ensure their needs will be satisfied.

While it may be tempting to assume that these shoppers are mostly concerned with quantitative assessment of the alternatives, motivations can also be qualitative, building on external influences like cultural norms and family influences. Yet, it should be noted that these customers are deliberate in their process and are unlikely to be swayed directly by advertising, merchandising and promotion. As such, salespeople can be important in helping the consumer arrive at a decision.

For these shoppers, a salesperson will need to be able to engage the consumer to understand what their specific needs and concerns are, relative to the purchase. That is, what are they specifically hoping to get by buying the product– not the item itself, but what benefits it will provide? Further, the salesperson will need to be able to speak to how well specific features will meet the consumer’s stated needs. And, they will need to be educated on the features & benefits of both the goods they’re selling and those of competitive items, as they will likely need to compare and contract specific differences.

Because these consumers with an extended problem solving mindset are deliberate in their shopping process, salespeople should expect that they will not “close the sale,” during their first interaction. Instead, they may need to nurture the relationship with the customer, helping them arrive at their purchase decision over time. Thus, effective salespeople will be those who engage in follow-up with the shopper, making themselves available to answer questions or provide perspective.

Practice Questions

• Increasing Sales with Extended Problem Solving. Authored by : Patrick Williams. Provided by : Lumen Learning. License : CC BY: Attribution

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Consumer Motivation and Involvement

15 Involvement Levels

Depending on a consumer’s experience and knowledge, some consumers may be able to make quick purchase decisions and other consumers may need to get information and be more involved in the decision process before making a purchase. The level of involvement reflects how personally important or interested you are in consuming a product and how much information you need to make a decision. The level of involvement in buying decisions may be considered a continuum from decisions that are fairly routine (consumers are not very involved) to decisions that require extensive thought and a high level of involvement. Whether a decision is low, high, or limited, involvement varies by consumer, not by product.

Low Involvement Consumer Decision Making

At some point in your life you may have considered products you want to own (e.g. luxury or novelty items), but like many of us, you probably didn’t do much more than ponder their relevance or suitability to your life. At other times, you’ve probably looked at dozens of products, compared them, and then decided not to purchase any one of them. When you run out of products such as milk or bread that you buy on a regular basis, you may buy the product as soon as you recognize the need because you do not need to search for information or evaluate alternatives . As Nike would put it, you “just do it.” Low-involvement decisions are, however, typically products that are relatively inexpensive and pose a low risk to the buyer if a mistake is made in purchasing them.

Consumers often engage in routine response behaviour when they make low-involvement decisions — that is, they make automatic purchase decisions based on limited information or information they have gathered in the past. For example, if you always order a Diet Coke at lunch, you’re engaging in routine response behaviour. You may not even think about other drink options at lunch because your routine is to order a Diet Coke, and you simply do it. Similarly, if you run out of Diet Coke at home, you may buy more without any information search.

Some low-involvement purchases are made with no planning or previous thought. These buying decisions are called impulse buying . While you’re waiting to check out at the grocery store, perhaps you see a magazine with a notable celebrity on the cover and buy it on the spot simply because you want it. You might see a roll of tape at a check-out stand and remember you need one or you might see a bag of chips and realize you’re hungry or just want them. These are items that are typically low-involvement decisions. Low involvement decisions aren’t necessarily products purchased on impulse, although they can be.

High Involvement Consumer Decision Making

By contrast, high-involvement decisions carry a higher risk to buyers if they fail. These are often more complex purchases that may carry a high price tag, such as a house, a car, or an insurance policy. These items are not purchased often but are relevant and important to the buyer. Buyers don’t engage in routine response behaviour when purchasing high-involvement products. Instead, consumers engage in what’s called extended problem solving where they spend a lot of time comparing different aspects such as the features of the products, prices, and warranties.

High-involvement decisions can cause buyers a great deal of post-purchase dissonance, also known as cognitive dissonance which is a form of anxiety consumers experience if they are unsure about their purchases or if they had a difficult time deciding between two alternatives. Companies that sell high-involvement products are aware that post purchase dissonance can be a problem. Frequently, marketers try to offer consumers a lot of supporting information about their products, including why they are superior to competing brands and why the consumer won’t be disappointed with their purchase afterwards. Salespeople play a critical role in answering consumer questions and providing extensive support during and after the purchasing stage.

Limited Problem Solving

Limited problem solving falls somewhere between low-involvement (routine) and high-involvement (extended problem solving) decisions. Consumers engage in limited problem solving when they already have some information about a good or service but continue to search for a little more information. Assume you need a new backpack for a hiking trip. While you are familiar with backpacks, you know that new features and materials are available since you purchased your last backpack. You’re going to spend some time looking for one that’s decent because you don’t want it to fall apart while you’re traveling and dump everything you’ve packed on a hiking trail. You might do a little research online and come to a decision relatively quickly. You might consider the choices available at your favourite retail outlet but not look at every backpack at every outlet before making a decision. Or you might rely on the advice of a person you know who’s knowledgeable about backpacks. In some way you shorten or limit your involvement and the decision-making process.

Distinguishing Between Low Involvement and High Involvement

Products, such as chewing gum, which may be low-involvement for many consumers often use advertising such as commercials and sales promotions such as coupons to reach many consumers at once. Companies also try to sell products such as gum in as many locations as possible. Many products that are typically high-involvement such as automobiles may use more personal selling to answer consumers’ questions. Brand names can also be very important regardless of the consumer’s level of purchasing involvement. Consider a low-versus high-involvement decision — say, purchasing a tube of toothpaste versus a new car. You might routinely buy your favorite brand of toothpaste, not thinking much about the purchase (engage in routine response behaviour), but not be willing to switch to another brand either. Having a brand you like saves you “search time” and eliminates the evaluation period because you know what you’re getting.

When it comes to the car, you might engage in extensive problem solving but, again, only be willing to consider a certain brand or brands (e.g. your evoke set for automobiles). For example, in the 1970s, American-made cars had such a poor reputation for quality that buyers joked that a car that’s not foreign is “crap.” The quality of American cars is very good today, but you get the picture. If it’s a high-involvement product you’re purchasing, a good brand name is probably going to be very important to you. That’s why the manufacturers of products that are typically high-involvement decisions can’t become complacent about the value of their brands.

Ways to Increase Involvement Levels

Involvement levels – whether they are low, high, or limited – vary by consumer and less so by product. A consumer’s involvement with a particular product will depend on their experience and knowledge, as well as their general approach to gathering information before making purchasing decisions. In a highly competitive marketplace, however, brands are always vying for consumer preference, loyalty, and affirmation. For this reason, many brands will engage in marketing strategies to increase exposure, attention, and relevance; in other words, brands are constantly seeking ways to motivate consumers with the intention to increase consumer involvement with their products and services.

Some of the different ways marketers increase consumer involvement are: customization; engagement; incentives; appealing to hedonic needs; creating purpose; and, representation.

1. Customization

With Share a Coke, Coca-Cola made a global mass customization implementation that worked for them. The company was able to put the labels on millions of bottles in order to get consumers to notice the changes to the coke bottle in the aisle. People also felt a kinship and moment of recognition once they spotted their names or a friend’s name. Simultaneously this personalization also worked because of the printing equipment that could make it happen and there are not that many first names to begin with. These factors lead the brand to be able to roll this out globally ( Mass Customization #12 , 2017).

2. Engagement

Have you ever heard the expression, “content is king”? Without a doubt, engaging, memorable, and unique marketing content has a lasting impact on consumers. The marketing landscape is a noisy one, polluted with an infinite number of brands advertising extensively to consumers, vying for a fraction of our attention. Savvy marketers recognize the importance of sparking just enough consumer interest so they become motivated to take notice and process their marketing messages. Marketers who create content (that isn’t just about sales and promotion) that inspires, delights, and even serves an audience’s needs are unlocking the secret to engagement. And engagement leads to loyalty.

There is no trick to content marketing, but the brands who do it well know that stepping away – far away – from the usual sales and promotion lines is critical. While content marketing is an effective way to increase sales, grow a brand, and create loyalty, authenticity is at its core.

Bodyform and Old Spice are two brands who very cleverly applied just the right amount of self-deprecating humour to their content marketing that not only engaged consumers, but had them begging for more!

Content as a Key Driver to Consumer Engagement

Engaging customers through content might involve a two-way conversation online, or an entire campaign designed around a single customer comment.

In 2012, Richard Neill posted a message to Bodyform’s Facebook page calling out the brand for lying to and deceiving its customers and audiences for years. Richard went on to say that Bodyform’s advertisements failed to truly depict any sense of reality and that in fact he felt set up by the brand to experience a huge fall. Bodyform, or as Richard addressed the company, “you crafty bugger,” is a UK company that produces and sells feminine protection products to menstruating girls and women (Bodyform, n.d.). Little did Richard know that when he posted his humorous rant to Bodyform that the company would respond by creating a video speaking directly at Richard and coming “clean” on all their deceitful attempts to make having period look like fun. When Bodyform’s video went viral, a brand that would have otherwise continued to blend into the background, captured the attention of a global audience.

Xavier Izaguirre says that, “[a]udience involvement is the process and act of actively involving your target audience in your communication mix, in order to increase their engagement with your message as well as advocacy to your brand.” Bodyform gained global recognition by turning one person’s rant into a viral publicity sensation (even though Richard was not the customer in this case).

Despite being a household name, in the years leading up to Old Spice’s infamous “The Man Your Man Should Smell Like” campaign, sales were flat and the brand had failed to strike a chord in a new generation of consumers. Ad experts at Wieden + Kennedy produced a single 30-second ad (featuring a shirtless and self-deprecating Isaiah Mustafa) that played around the time of the 2010 Super Bowl game. While the ad quickly gained notoriety on YouTube, it was the now infamous, “ Response Campaign ” that made the campaign a leader of its time in audience engagement.

3. Incentives

Customer loyalty and reward programs successfully motivate consumers in the decision making process and reinforce purchasing behaviours ( a feature of instrumental conditioning ). The rationale for loyalty and rewards programs is clear: the cost of acquiring a new customer runs five to 25 times more than selling to an existing one and existing customers spend 67 per cent more than new customers (Bernazzani, n.d.). From the customer perspective, simple and practical reward programs such as Beauty Insider – a point-accumulation model used by Sephora – provides strong incentive for customer loyalty (Bernazzani, n.d.).

4. Appealing to Hedonic Needs

A particularly strong way to motivate consumers to increase involvement levels with a product or service is to appeal to their hedonic needs. Consumers seek to satisfy their need for fun, pleasure, and enjoyment through luxurious and rare purchases. In these cases, consumers are less likely to be price sensitive (“it’s a treat”) and more likely to spend greater processing time on the marketing messages they are presented with when a brand appeals to their greatest desires instead of their basic necessities.

5. Creating Purpose

Millennial and Digital Native consumers are profoundly different than those who came before them. Brands, particularly in the consumer goods category, who demonstrate (and uphold) a commitment to sustainability grow at a faster rate (4 per cent) than those who do not (1 per cent) (“Consumer-Goods…”, 2015). In a 2015 poll, 30,000 consumers were asked how much the environment, packaging, price, marketing, and organic or health and wellness claims had on their consumer-goods’ purchase decisions, and to no surprise, 66 per cent said they would be willing to pay more for sustainable brands. (Nielsen, 2015). A rising trend and important factor to consider in evaluating consumer involvement levels and ways to increase them. So while cruelty-free, fair trade, and locally-sourced may all seem like buzz words to some, they are non-negotiable decision-making factors to a large and growing consumer market.

6. Representation

Celebrity endorsement can have a profound impact on consumers’ overall attitude towards a brand. Consumers who might otherwise have a “neutral” attitude towards a brand (neither positive nor negative) may be more noticed to take notice of a brand’s messages and stimuli if a celebrity they admire is the face of the brand.

When sportswear and sneaker brand Puma signed Rihanna on to not just endorse the brand but design an entire collection, sales soared in all the regions and the brand enjoyed a new “revival” in the U.S. where Under Armour and Nike had been making significant gains (“Rihanna Designs…”, 2017). “Rihanna’s relationship with us makes the brand actual and hot again with young consumers,” said chief executive Bjorn Gulden (“Rihanna Designs…”, 2017).

Media Attributions

• The image of two different coloured sneakers is by Raka Rachgo on Unsplash .
• The image of a coffee card in a wallet is by Rebecca Aldama on Unsplash .
• The image of an island resort in tropical destination is by Ishan @seefromthesky on Unsplash .
• The image of a stack of glossy magazine covers is by Charisse Kenion on Unsplash .

Text Attributions

• The introductory paragraph; sections on “Low Involvement Consumer Decision Making”, “High Involvement Consumer Decision Making”, and “Limited Problem Solving” are adapted from Principles of Marketing which is licensed under CC BY-NC-SA 3.0.

About Us . (n.d.). Body Form. Retrieved February 2, 2019, from https://www.bodyform.co.uk/about-us/.

Kalamut, A. (2010, August 18). Old Spice Video “Case Study” . YouTube [Video]. https://youtu.be/Kg0booW1uOQ.

Bernazzani, S. (n.d.). Customer Loyalty: The Ultimate Guide [Blog post]. https://blog.hubspot.com/service/customer-loyalty.

Bodyform Channel. (2012, October 16). Bodyform Responds: The Truth . YouTube [Video]. https://www.youtube.com/watch?v=Bpy75q2DDow&feature=youtu.be.

Consumer-Goods’ Brands That Demonstrate Commitment to Sustainability Outperform Those That Don’t. (2015, October 12). Nielsen [Press Release]. https://www.nielsen.com/us/en/press-room/2015/consumer-goods-brands-that-demonstrate-commitment-to-sustainability-outperform.html.

Curtin, M. (2018, March 30). 73 Per Cent of Millennials are Willing to Spend More Money on This 1 Type of Product . Inc. https://www.inc.com/melanie-curtin/73-percent-of-millennials-are-willing-to-spend-more-money-on-this-1-type-of-product.html.

Izaguirre, X. (2012, October 17). How are brands using audience involvement to increase reach and engagement?   EConsultancy. https://econsultancy.com/how-are-brands-using-audience-involvement-to-increase-reach-and-engagement/.

Rihanna Designs Help Lift Puma Sportswear Sales . (2017, October 24). Reuters. https://www.businessoffashion.com/articles/news-analysis/rihanna-designs-help-lift-puma-sportswear-sales.

Tarver, E. (2018, October 20). Why the ‘Share a Coke’ Campaign Is So Successful . Investopedia. https://www.investopedia.com/articles/markets/100715/what-makes-share-coke-campaign-so-successful.asp.

Low involvement decision making typically reflects when a consumer who has a low level of interest and attachment to an item. These items may be relatively inexpensive, pose low risk (can be exchanged, returned, or replaced easily), and not require research or comparison shopping.

This concept describes when consumers make low-involvement decisions that are "automatic" in nature and reflect a limited amount of information the consumer has gathered in the past.

A type of purchase that is made with no previous planning or thought.

High involvement decision making typically reflects when a consumer who has a high degree of interest and attachment to an item. These items may be relatively expensive, pose a high risk to the consumer (can't be exchanged or refunded easily or at all), and require some degree of research or comparison shopping.

Also known as "consumer remorse" or "consumer guilt", this is an unsettling feeling consumers may experience post-purchase if they feel their actions are not aligned with their needs.

Consumers engage in limited problem solving when they have some information about an item, but continue to gather more information to inform their purchasing decision. This falls between "low" and "high" involvement on the involvement continuum.

Introduction to Consumer Behaviour Copyright © by Andrea Niosi is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Problem-Solving Strategies and Obstacles

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• Application
• Improvement

From deciding what to eat for dinner to considering whether it's the right time to buy a house, problem-solving is a large part of our daily lives. Learn some of the problem-solving strategies that exist and how to use them in real life, along with ways to overcome obstacles that are making it harder to resolve the issues you face.

What Is Problem-Solving?

In cognitive psychology , the term 'problem-solving' refers to the mental process that people go through to discover, analyze, and solve problems.

A problem exists when there is a goal that we want to achieve but the process by which we will achieve it is not obvious to us. Put another way, there is something that we want to occur in our life, yet we are not immediately certain how to make it happen.

Maybe you want a better relationship with your spouse or another family member but you're not sure how to improve it. Or you want to start a business but are unsure what steps to take. Problem-solving helps you figure out how to achieve these desires.

The problem-solving process involves:

• Discovery of the problem
• Deciding to tackle the issue
• Seeking to understand the problem more fully
• Researching available options or solutions
• Taking action to resolve the issue

Before problem-solving can occur, it is important to first understand the exact nature of the problem itself. If your understanding of the issue is faulty, your attempts to resolve it will also be incorrect or flawed.

Problem-Solving Mental Processes

Several mental processes are at work during problem-solving. Among them are:

• Perceptually recognizing the problem
• Representing the problem in memory
• Considering relevant information that applies to the problem
• Identifying different aspects of the problem
• Labeling and describing the problem

Problem-Solving Strategies

There are many ways to go about solving a problem. Some of these strategies might be used on their own, or you may decide to employ multiple approaches when working to figure out and fix a problem.

An algorithm is a step-by-step procedure that, by following certain "rules" produces a solution. Algorithms are commonly used in mathematics to solve division or multiplication problems. But they can be used in other fields as well.

In psychology, algorithms can be used to help identify individuals with a greater risk of mental health issues. For instance, research suggests that certain algorithms might help us recognize children with an elevated risk of suicide or self-harm.

One benefit of algorithms is that they guarantee an accurate answer. However, they aren't always the best approach to problem-solving, in part because detecting patterns can be incredibly time-consuming.

There are also concerns when machine learning is involved—also known as artificial intelligence (AI)—such as whether they can accurately predict human behaviors.

Heuristics are shortcut strategies that people can use to solve a problem at hand. These "rule of thumb" approaches allow you to simplify complex problems, reducing the total number of possible solutions to a more manageable set.

If you find yourself sitting in a traffic jam, for example, you may quickly consider other routes, taking one to get moving once again. When shopping for a new car, you might think back to a prior experience when negotiating got you a lower price, then employ the same tactics.

While heuristics may be helpful when facing smaller issues, major decisions shouldn't necessarily be made using a shortcut approach. Heuristics also don't guarantee an effective solution, such as when trying to drive around a traffic jam only to find yourself on an equally crowded route.

Trial and Error

A trial-and-error approach to problem-solving involves trying a number of potential solutions to a particular issue, then ruling out those that do not work. If you're not sure whether to buy a shirt in blue or green, for instance, you may try on each before deciding which one to purchase.

This can be a good strategy to use if you have a limited number of solutions available. But if there are many different choices available, narrowing down the possible options using another problem-solving technique can be helpful before attempting trial and error.

In some cases, the solution to a problem can appear as a sudden insight. You are facing an issue in a relationship or your career when, out of nowhere, the solution appears in your mind and you know exactly what to do.

Insight can occur when the problem in front of you is similar to an issue that you've dealt with in the past. Although, you may not recognize what is occurring since the underlying mental processes that lead to insight often happen outside of conscious awareness .

Research indicates that insight is most likely to occur during times when you are alone—such as when going on a walk by yourself, when you're in the shower, or when lying in bed after waking up.

How to Apply Problem-Solving Strategies in Real Life

If you're facing a problem, you can implement one or more of these strategies to find a potential solution. Here's how to use them in real life:

• Create a flow chart . If you have time, you can take advantage of the algorithm approach to problem-solving by sitting down and making a flow chart of each potential solution, its consequences, and what happens next.
• Recall your past experiences . When a problem needs to be solved fairly quickly, heuristics may be a better approach. Think back to when you faced a similar issue, then use your knowledge and experience to choose the best option possible.
• Start trying potential solutions . If your options are limited, start trying them one by one to see which solution is best for achieving your desired goal. If a particular solution doesn't work, move on to the next.
• Take some time alone . Since insight is often achieved when you're alone, carve out time to be by yourself for a while. The answer to your problem may come to you, seemingly out of the blue, if you spend some time away from others.

Obstacles to Problem-Solving

Problem-solving is not a flawless process as there are a number of obstacles that can interfere with our ability to solve a problem quickly and efficiently. These obstacles include:

• Assumptions: When dealing with a problem, people can make assumptions about the constraints and obstacles that prevent certain solutions. Thus, they may not even try some potential options.
• Functional fixedness : This term refers to the tendency to view problems only in their customary manner. Functional fixedness prevents people from fully seeing all of the different options that might be available to find a solution.
• Irrelevant or misleading information: When trying to solve a problem, it's important to distinguish between information that is relevant to the issue and irrelevant data that can lead to faulty solutions. The more complex the problem, the easier it is to focus on misleading or irrelevant information.
• Mental set: A mental set is a tendency to only use solutions that have worked in the past rather than looking for alternative ideas. A mental set can work as a heuristic, making it a useful problem-solving tool. However, mental sets can also lead to inflexibility, making it more difficult to find effective solutions.

How to Improve Your Problem-Solving Skills

In the end, if your goal is to become a better problem-solver, it's helpful to remember that this is a process. Thus, if you want to improve your problem-solving skills, following these steps can help lead you to your solution:

• Recognize that a problem exists . If you are facing a problem, there are generally signs. For instance, if you have a mental illness , you may experience excessive fear or sadness, mood changes, and changes in sleeping or eating habits. Recognizing these signs can help you realize that an issue exists.
• Decide to solve the problem . Make a conscious decision to solve the issue at hand. Commit to yourself that you will go through the steps necessary to find a solution.
• Seek to fully understand the issue . Analyze the problem you face, looking at it from all sides. If your problem is relationship-related, for instance, ask yourself how the other person may be interpreting the issue. You might also consider how your actions might be contributing to the situation.
• Research potential options . Using the problem-solving strategies mentioned, research potential solutions. Make a list of options, then consider each one individually. What are some pros and cons of taking the available routes? What would you need to do to make them happen?
• Take action . Select the best solution possible and take action. Action is one of the steps required for change . So, go through the motions needed to resolve the issue.
• Try another option, if needed . If the solution you chose didn't work, don't give up. Either go through the problem-solving process again or simply try another option.

You can find a way to solve your problems as long as you keep working toward this goal—even if the best solution is simply to let go because no other good solution exists.

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

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

Dietrich dörner.

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

Joachim Funke

2 Department of Psychology, Heidelberg University, Heidelberg, Germany

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

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

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

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

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

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

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

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

Historical Review

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

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

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

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

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

Different Approaches to CPS

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

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

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

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

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

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

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

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

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

Importance of the Validity Issue

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

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

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

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

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

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

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

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

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

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

What is not CPS?

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

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

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

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

What is CPS?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

CPS as Combining Reasoning and Thinking in an Uncertain Reality

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

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

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

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

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

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

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

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

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

Author Contributions

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

Authors Note

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

Conflict of Interest Statement

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

Acknowledgments

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

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

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Consumer Decision Making Process: Meaning, Stages, Levels, Models

Meaning of consumer decision making process.

Consumer decision making process involves the consumers to identify their needs, gather information, evaluate alternatives and then make their buying decision.

It is simply a process which depicts the journey of the consumer from starting to end for making buying decisions. Marketers use this process as a source of information for acquiring all important data related to consumers.

Stages of Consumer Decision Making Process

Levels of Consumer Decision Making

Models of consumer decision making  , consumer decision rules, related posts:, add commercemates to your homescreen.

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Consumer Behavior - Decision Making

An understanding of consumer behavior is necessary for the long-term success and survival of a firm. Consumer decision making is viewed as the edifice of the marketing concept, an important orientation in marketing management.

The marketer should be able to determine needs and wants of the target segment and provide product and service offerings more effectively and efficiently than competitors.

Types of Consumer Decision Making

The following are the types of decision making methods which can be used to analyze consumer behavior −

Extensive Problem Solving

In extensive decision making, the consumers have no established or set criteria for evaluating a product in a particular category. Here the consumers have not narrowed the number of brands from which they would like to consider and so their decision making efforts can be classified as extensive problem solving. In this particular set of problem solving phase, the consumer needs a lot of information to set a criteria on the basis of specific brands could be judged.

Limited Problem Solving

In limited problem solving, the consumers have already set the basic criteria or standard for evaluating the products. However, they have not fully set the established preferences and they search for additional information to discriminate among other products or brands.

Routinized Response Behavior

Here, in routinized response behavior, consumers have experience with the product and they have set the criteria for which they tend to evaluate the brands they are considering. In some situations, they may want to collect a small amount of additional information, while in others they may simply review what they are aware about. In extensive problem solving, consumer seeks for more information to make a choice, in limited problem solving consumers have the basic idea or the criteria set for evaluation, whereas in routinized response behavior consumers need only little additional information.

Views of Consumer Decision Making

An economic view.

Consumers have generally been assumed to make rational decisions. The economic view of consumer decision making is being criticized by researchers because a consumer is assumed to posses the following traits to behave rationally −

Firstly, they need to be aware of all the alternatives present in the market

Secondly, they must be able to efficiently rank the products as per their benefits.

Lastly, they must also know the best alternative that suits them as per their requirements.

In the world of perfect competition, consumers rarely have all the information to make the so called ‘perfect decision.’

A Passive View

Passive view is totally opposite to the economic view. Here, it is assumed that consumers are impulsive and irrational while making a purchase. The main limitation of this view is that consumers also seek information about the alternatives available and make rational or wise decisions and purchase the products or services that provides the greatest satisfaction.

A Cognitive View

The cognitive model helps individuals to focus on the processes through which they can get information about selected brands. In the framework of cognitive view, the consumer very actively searches for such products or services that can fulfill all their requirements.

An Emotional View

Consumers are associated with deep feelings or emotions such as, fear, love, hope etc. These emotions are likely to be highly involving.

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Meaning of extensive problem solving in English

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to delay until you are ready

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