What is hypothesis driven problem solving? How do I apply hypothesis driven problem solving to business? What are the steps to hypothesis driven problem solving? This blog post explores all of these questions - and then some.
What is hypothesis-driven problem solving?
Hypothesis driven problem solving also known as "top-down problem solving" or "hypothesis driven thinking" is a form of problem-solving that starts with the answer and works backward to prove or disprove that answer. Practiced by the biggest consulting firms around the globe for its effectiveness in getting to the heart of the matter, hypothesis-driven thinking is rooted in the scientific method.
Whereas bottoms-up problem solving (a non-hypothesis-driven approach) analyzes the data/information to arrive at your answer, top-down identifies an answer and looks to data/information to validate it. Comparatively speaking, bottoms-up problem solving can be a never-ending process, whereas top-down is laser-focused - and for that reason, effective.
In business leadership, the typical problem-solving approach practiced tends to be bottoms-up problem solving, however if you take the time to learn and apply it, top-down is often much more effective, particularly when you’re dealing with a problem that’s defined and a tight timeline.
What is a hypothesis driven approach or method?
A hypothesis-driven approach is one where you state your assumptions about what you think the answer is, and then fact-find to validate or refute. This helps focus your data gathering on exactly what you need vs. "boiling the ocean". It also helps to ensure you’ve thought through the entirety of the problem and that there is rigor and structure in your thinking.
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How do I apply hypothesis driven thinking?
The four steps to hypothesis-driven problem solving are simple. In a nutshell:
1) Define the problem
The first step is to define the problem. This may seem like an obvious step, but it's important to be clear about what you're trying to solve. Sometimes people jump right into solving a problem without taking the time to fully understand it. Defining the question you're trying to answer and your problem helps ensure that you're focusing on the right issue and prevents you from wasting time and energy. This may seem easy at first glance but to quote Albert the great “if I had an hour to solve a problem, I’d spend 55 minutes on the problem and 5 on the solution.” Defining your problem takes rumination and time.
2) Develop your initial hypothesis
The second step in hypothesis-driven thinking is to come up with an initial hypothesis. An initial hypothesis is a proposed explanation for an event or phenomenon that can be tested. It's important to note that a good hypothesis doesn't have to be correct – it just has to be plausible.
For example, let's say you're trying to improve customer satisfaction at your company. Your hypothesis could be that providing more customer service training will improve satisfaction, or perhaps hiring more seasoned employees/agents. This answer-driven approach gets you thinking early about the solution early on.
At this stage of the work, it's not uncommon to brainstorm multiple key hypotheses before you narrow the field.
From there, you're going to flesh out your logic taking a decision tree approach. That's thinking through what needs to be true for your hypothesis to be true. Fast forward and you will end up with a decision-tree with the 1st level being your hypothesis, the 2nd level being your supporting assumptions or logic and the 3rd level downward being the fact points that you'll need to uncover. This tree informs your work plan. Want a real world hypothesis tree to work from? Sign up to the right to claim your free hypothesis problem solving template.
3) Gather and analyze information to validate or refute your hypothesis
The third step is to gather information to validate or refute your hypothesis. This can be done in a number of ways, including surveys, interviews, focus groups, and data analysis.
It's important to note that you should constantly be gathering new information throughout the problem-solving process. You never want to stop learning – that's how you find the best solutions. In this step, ideally, you're looking for measurable evidence to validate or refute your assumptions. The term "acceptable evidence thresholds" is often used to describe the certainty you're looking to arrive at. Apply the 80/20 rule here - that’s enough evidence to get to 80% certainty. Many analytical approaches and methods can be used in this step.
Once you've gathered all of your information, it's time to analyze it and see if your hypothesis was correct.
4) Pivot your hypothesis and arrive at your solution
If the information you've gathered points to your hypothesis being correct, great! You can move on to step four. If not, don't worry – you can adjust your hypothesis and try again. Pivot to alternative hypotheses as many times as needed. Hypothesis-driven thinking is an iterative process.
With subsequent validation, eventually, you will arrive at your solution, backed by evidence. You've just shifted from many potential solutions to THE solution.
Hypothesis driven problem solving is a great way to solve complex problems. By breaking the problem into smaller parts, it's easier to develop and test hypotheses. And by analyzing the results, you can determine whether your hypothesis was correct.
It's more and more common to see hypothesis thinking used in a variety of fields, including as an approach to software development.
Looking to improve your problem-solving skills? Give hypothesis driven problem solving a try. It's a great way to systematically solve complex problems using an analytical approach - and gets you to results that are both accurate and timely. That’s why it’s the bread and butter of the biggest consulting companies around the world from McKinsey & Company to Bain & Company to BCG, and many more.
What is hypothesis driven consulting?
Hypothesis-driven consulting is applying a hypothesis-driven approach to complex problems that arise in client engagements. It's commonly used and coveted by top consulting firms, including McKinsey, due to its effectiveness at solving business problems. It's core to the Consulting process and some expect their interviewees to approach case studies and case study interviews by applying a hypothesis approach. Amongst many consulting tools, hypothesis thinking is clutch. Trying to land a role on a top-tier Consulting Team? Prepping for a Consulting Interview? Learn this tool and you will be ahead of the game.
What problems can I apply hypothesis driven thinking to?
You can apply this thinking to a broad array of problems/opportunities. How do I diversify my revenue streams? What kind of business models should I optimize for? What's the market size of China? What's our market share in the US? Why are we seeing an increase in costs? How do we grow our customer base? What's our customer preference when it comes to returns? Why are business class ticket sales down? Why are we seeing a decline in revenue? Why are fuel costs rising? What color should we paint the fence?
A hypothesis-driven approach is a proven problem-solving process that will elevate your strategic thinking, help you craft power business strategies, accelerate your effectiveness, and is an agile practice that serves you well in today's rapidly changing climate.
Does hypothesis-driven problem solving training exist?
Due to an overwhelming need, we've created just that, a virtual training course on hypothesis-driven training that’s nested within our Strategic Thinking training. Student learning outcomes include improving your effectiveness, thinking and acting with impact, and levelling up your problem-solving skills. We call it problem-based learning at its finest. Enter your email below to download the free template and we will email you when the course becomes available!
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It’s training that teaches you to think more strategically about your work, business - and life. In the context of business, it teaches you how to make powerful and effective strategic decisions in the context of your business strategy.
Yes, it's an experimental approach that closely resembles the scientific method.
Hypothesis-Driven development is just another way to describe the process of taking a hypothesis-driven approach. Hypothesis-driven development is essentially a synonymous term.
Yes, resembling components of "agile thinking", hypothesis thinking is used as a common approach to software development. Frequent real-time feedback loops are applied to develop a product.
It's an easy four-step process - read the article above for more background knowledge.
Stay tuned for my next blog post - I’ll cover how the method is used in strategy and in strategic decision-making
Use cases range from macro to micro: identifying market trends, product development, crafting digital products, UX, driving customer demand, statistical analysis, statistical tests, continuous improvement, design sprints, and business development. Leadership teams often use it for solving organizational wide problems/issues and it can be applied to solve almost any typical strategy engagement.
Yes, it can used to help work through all of these questions/problems.
Most big firms, including Bain & Company, McKinsey & Company, BCG, etc. apply this tool in real life engagements.
Yes and it's accompanied by (un)formal discussion, hands-on practice, mini-cases and strategy cases, and inquiry-based learning. We've worked hard to create an engaging learning process designed to be delivered to you anytime, anywhere.
Learning and development outcomes can be found here
Any and all working professionals are welcome - we serve business leaders, individual contributors, executives and any team looking to level up their strategic thinking - come one come all.
Yes, it includes a module on narrative-driven story-telling, a natural derivative of hypothesis problem-solving.
An issue tree is a specific type of logic tree. See this blog post for issue trees, explained!
MECE stands for Mutually, Exclusive, Collectively Exhaustive and forms the core of hypothesis driven thinking and logic trees. See this post for an explanation and guide on MECE.
About the Author
Lindsay provides growth and advisory services to purpose-driven brands. Named a global innovation leader and Women to Watch, you will find her at the intersection of strategy, story-telling and innovation. When she’s not collaborating with clients, she’s hittingTEDxand other stages across North America to deliver keynotes on the future of consumerism, strategy and innovation. Prior to advising and providing brand and marketing consulting services, Lindsay spent six years at lululemon crafting their global growth strategy, exploring new marketplace opportunities and growing the company into the number one yoga wear player in the world. Her experiences culminate in what she refers to as her sweet spot - where strategy, innovation and insights intersect, where the rational meets the emotive, where facts meet insights and where logic meets creativity.
The hypothesis-driven approach is a problem-solving method that is necessary at WHO because the environment around us is changing rapidly. WHO needs a new way of problem-solving to process large amounts of information from different fields and deliver quick, tailored recommendations to meet the needs of Member States.What is an example of hypothesis driven problem-solving? ›
For example, let's say you're trying to improve customer satisfaction at your company. Your hypothesis could be that providing more customer service training will improve satisfaction, or perhaps hiring more seasoned employees/agents. This answer-driven approach gets you thinking early about the solution early on.How does McKinsey do hypothesis driven problem-solving? ›
The McKinsey problem-solving process begins with the use of structured frameworks to generate fact-based hypotheses followed by data gathering and analysis to prove or disprove the hypotheses. Gut feeling at this stage is extremely important because we don't have many facts yet.What I learned at McKinsey how to be hypothesis driven? ›
McKinsey consultants follow three steps in this cycle: Form a hypothesis about the problem and determine the data needed to test the hypothesis. Gather and analyze the necessary data, comparing the result to the hypothesis.What is an example of hypothesis driven research? ›
Example: “Discovering the mechanism behind X will enable us to better detect the pathogen.” This tests the ability of the researchers to take information and use it. It is a result of successful hypothesis driven research.What are the 4 approaches of problem-solving? ›
From Francis Bacon who championed inductive methods to Buddha who championed meditative methods various people have proposed different approaches to solve problems. Here is an attempt to classify these approaches into 4 categories – system centric, problem centric, solution centric and solver centric approach.What are 3 examples of simple hypothesis? ›
|What are the health benefits of eating an apple a day?||Increasing apple consumption in over-60s will result in decreasing frequency of doctor's visits.|
|Which airlines have the most delays?||Low-cost airlines are more likely to have delays than premium airlines.|
The hypothesis is an educated guess as to what will happen during your experiment. The hypothesis is often written using the words "IF" and "THEN." For example, "If I do not study, then I will fail the test." The "if' and "then" statements reflect your independent and dependent variables.What is an example situation of how hypothesis testing can be applied in everyday life? ›
For example, suppose a doctor believes that a new drug is able to reduce blood pressure in obese patients. To test this, he may measure the blood pressure of 40 patients before and after using the new drug for one month.How do I prepare for the McKinsey problem solving test? ›
- First, practice your math computations. ...
- Second, practice data interpretation through other exams such as the GRE or GMAT. ...
- Third, practicing verbal cases with exhibits help hone your answer-first and analytical skills for McKinsey.
The advantage of using these data is that statistics can be applied to establish predictions without the consideration of the principles of designing a study, which is the fundamental requirement of a conventional hypothesis.What are the benefits of hypothesis based problem solving? ›
Taking an hypothesis driven approach to a problem means attempting to solve that problem by focussing on your best hypothesis as to the answer. This helps arrive at a solution quickly and efficiently.What is an example of a problem statement McKinsey? ›
Some of the best problem statements are simply goals formatted as questions. If you need to increase sales by 10%, a good problem statement is, “Within the next 12 months, what are the most effective options for the team to increase sales by 10%?”What are the key points of the McKinsey Way? ›
The McKinsey problem-solving process can be summarized in the 5 steps: define the problems, find the root cause, use “hypothesis-driven” process, analyze with “issue tree” and propose solutions. 1. Define the problem: Every consulting project revolves around a “problem”. But the “problem” is NOT always the problem!How do you know if a study is hypothesis-driven? ›
- It IS NOT discovery or descriptive research. Some research is not hypothesis-driven. ...
- It IS original. ...
- It IS NOT too general/global. ...
- It IS NOT too complex. ...
- It DOES NOT misdirect to the researcher.
If you drop a ball, it will fall toward the ground. If you drink coffee before going to bed, then it will take longer to fall asleep. If you cover a wound with a bandage, then it will heal with less scarring.What is the opposite of hypothesis-driven? ›
The opposite of a hypothesis-driven project is a hypothesis-generating project. Here you also have a general research question (which could be need-driven or curiosity-driven – see part 1 of this post).What are the three main strategies for problem-solving? ›
Typical strategies include trial and error, applying algorithms, and using heuristics. To solve a large, complicated problem, it often helps to break the problem into smaller steps that can be accomplished individually, leading to an overall solution.What are the 7 problem-solving techniques? ›
- Identify and define the problem.
- Come up with possible solutions.
- Evaluate the options.
- Choose the best solution.
- Implement the solution.
- Evaluate the outcome.
A simple hypothesis suggests only the relationship between two variables: one independent and one dependent. Examples: If you stay up late, then you feel tired the next day. Turning off your phone makes it charge faster.
A hypothesis is an assumption that is made based on some evidence. This is the initial point of any investigation that translates the research questions into predictions. It includes components like variables, population and the relation between the variables.What is a key hypothesis example? ›
Here's an example of a hypothesis: If you increase the duration of light, (then) corn plants will grow more each day. The hypothesis establishes two variables, length of light exposure, and the rate of plant growth. An experiment could be designed to test whether the rate of growth depends on the duration of light.What are the 3 major types of hypothesis? ›
- Null Hypothesis. The null hypothesis states that there is no relationship between the two variables being studied (one variable does not affect the other). ...
- Nondirectional Hypothesis. ...
- Directional Hypothesis.
The common format is: If [CAUSE], then [EFFECT], because [RATIONALE]. In the world of experience optimization, strong hypotheses consist of three distinct parts: a definition of the problem, a proposed solution, and a result.What is an example of a one sample hypothesis test? ›
A one sample test of means compares the mean of a sample to a pre-specified value and tests for a deviation from that value. For example we might know that the average birth weight for white babies in the US is 3,410 grams and wish to compare the average birth weight of a sample of black babies to this value.What is an example of a hypothesis that can be tested? ›
Examples of a Testable Hypothesis
Students who attend class have higher grades than students who skip class. This is testable because it is possible to compare the grades of students who do and do not skip class and then analyze the resulting data.
The passing rate for the McKinsey Problem Solving Game is estimated at roughly 20-30%. As more candidates are invited to take the test, the proportion of those who pass is lower than the PST. Also, McKinsey uses the PSG for the recruitment of a wide range of candidates for various positions, not just consulting track.How do I pass an interview at McKinsey? ›
- Maintain structure throughout.
- McKinsey interviews require you to solve your McKinsey math to the ones place.
- Take 30 seconds or so in between each of the questions to prepare an answer.
- Give deeper second (and third) level McKinsey insights.
- Be answer first (think Pyramid Principle)
It is considered to be one of the most difficult recruitment tests because it tests a broad range of skills in a tight time constraint. The McKinsey PST is formulated to assess whether you have the critical skills to function effectively as an analyst/consultant.What are the five importance of hypothesis? ›
It helps to assume the probability of research failure and progress. It helps to provide link to the underlying theory and specific research question. It helps in data analysis and measure the validity and reliability of the research. It provides a basis or evidence to prove the validity of the research.
The purpose of hypothesis testing is to test whether the null hypothesis (there is no difference, no effect) can be rejected or approved. If the null hypothesis is rejected, then the research hypothesis can be accepted. If the null hypothesis is accepted, then the research hypothesis is rejected.What is the main purpose of a hypothesis? ›
Hypotheses are used to support scientific research and create breakthroughs in knowledge. These brief statements are what form the basis of entire research experiments. Thus, a flaw in the formulation of a hypothesis may cause a flaw in the design of an entire experiment.What are hypothesis-driven methods? ›
In research and data analysis, a hypothesis-driven approach is one of the main methods for using data to test and, ultimately, prove (or disprove) assertions. To do that, researchers collect a sufficient amount of data on the subject and then approach it with a specific hypothesis in mind.What are the four stages in testing hypotheses for learning? ›
Step 1: State the hypotheses. Step 2: Set the criteria for a decision. Step 3: Compute the test statistic. Step 4: Make a decision.What is the three step process for test driven development? ›
Red, Green and Refactor is the three phase of Test Driven Development and this the sequence that get followed while writing code. When followed, this order of steps helps ensure that you have tests for the code you are writing and you are writing only the code that you have to test for.What are some disadvantages of hypothesis driven entrepreneurship? ›
Acquiring a large numbers of customers before validating business model hypotheses can be expensive and can exacerbate damage to a startup's brand if a subsequent pivot confuses and alienates the early adopters. Instead, MVPs should be tested with just enough customers to provide reliable feedback.What is the difference between a problem and a hypothesis? ›
Whilst your problem statement identifies the problem you hope to solve, the hypothesis helps you decide on how you will try to solve it.What is the greatest benefit to using a problem-solving process? ›
Importance of a problem-solving process
Developing a process for solving problems improves your understanding of processes and how cause-and-effect relationships develop. By recognizing how a factor contributes to a certain result, you can determine how to optimize a process.
Hypothesis driven problem solving also known as "top-down problem solving" or "hypothesis driven thinking" is a form of problem-solving that starts with the answer and works backward to prove or disprove that answer.What is the McKinsey Day 1 answer? ›
There is a McKinsey framework called “Day One Hypothesis” that many companies can use effectively. Basically, at McKinsey you meet with a client and after the first day of gathering information you make an initial hypothesis on what the solution may be.
The McKinsey problem-solving process begins with the use of structured frameworks to generate fact-based hypotheses followed by data gathering and analysis to prove or disprove the hypotheses. Gut feeling at this stage is extremely important because we don't have many facts yet.What is the McKinsey 3 rule? ›
One of the most simple tools of communicating a message among consultants is the often shared three step approach: Tell them what you will tell them. Tell them. Tell them what you told them.What is the McKinsey 5 Whys method? ›
The method is remarkably simple: when a problem occurs, you drill down to its root cause by asking "Why?" five times. Then, when a counter-measure becomes apparent, you follow it through to prevent the issue from recurring.What is hypothesis-driven vs discovery driven? ›
While hypothesis-driven research is based on established scientific theories, discovery-based research can be appropriate when so little is known about the topic of interest that a useful hypothesis cannot yet be made.What is descriptive vs hypothesis-driven? ›
Descriptive (or discovery) science, which is usually inductive, aims to observe, explore, and discover, while hypothesis-based science, which is usually deductive, begins with a specific question or problem and a potential answer or solution that can be tested.What are the three approaches to problem-solving? ›
There are 3 main approaches to solving a problem: Intuitive. Analytical. Experimental.How is hypothesis-driven approach different from data-driven? ›
In the data-driven approach, researchers just try every variable they are interested in, while in the hypothesis-driven approach, only variables that support their hypothesis are selected. The need to create a new variable is small for them. Therefore, they analyze the collected data without creating any new variables.What is the major benefit of hypothesis driven development? ›
Why we use hypothesis-driven development. For us, the hypothesis-driven approach provides a structured way to consolidate ideas and build hypotheses based on objective criteria. It's also less costly to test the prototype before production.What are hypothesis driven methods? ›
In research and data analysis, a hypothesis-driven approach is one of the main methods for using data to test and, ultimately, prove (or disprove) assertions. To do that, researchers collect a sufficient amount of data on the subject and then approach it with a specific hypothesis in mind.What are the benefits of hypothesis driven research? ›
The advantage of using these data is that statistics can be applied to establish predictions without the consideration of the principles of designing a study, which is the fundamental requirement of a conventional hypothesis.
The opposite of a hypothesis-driven project is a hypothesis-generating project. Here you also have a general research question (which could be need-driven or curiosity-driven – see part 1 of this post).What is descriptive hypothesis in simple words? ›
DESCRIPTIVE HYPOTHESIS • Propositions that state the existence, size, form or distribution of some variable. Variable can be object, person, organization, situation or event. Example: The rate of unemployment among arts students are high The education system is not oriented to the human resource needs of the country.What are the four 4 fundamental stages to effective problem-solving? ›
Analyze—Understand the root cause. Plan—Determine how to resolve the problem. Implement—Put the resolution in place. Evaluate—Determine if the resolution is producing the desired results.What is the most commonly used problem-solving strategy? ›
Trial and error
One of the most common problem-solving strategies is trial and error. In other words, you try different solutions until you find one that works.
- Share data across different channels. ...
- Use demographic data to plan campaigns. ...
- Personalize the customer journey. ...
- Target better with predictive analytics. ...
- Deepen audience insights with data onboarding.