McKinsey Solve Game: Guide, Updates & Free Practice [2025 Edition]

Table of Content:  

1. What is McKinsey Solve Game?
2. When does it appear in the McKinsey Interview Process?
3. How Does McKinsey Solve Game Work?
4. What traits is McKinsey assessing in McKinsey Solve Game?
5. What does McKinsey Solve Game include
   • Ecosystem Building
   • Red Rock Study  
   • Ocean Cleanup
6. The Importance of Practicing McKinsey Solve Game

Check out the only, fully-playable, and FREE McKinsey Solve Test (Problem-Solving Game) Simulation in the entire market!

What is McKinsey Solve Game?

McKinsey Solve Game, also known as the Problem Solving Game, PSG, Digital Assessment, or informally referred to as the "Imbellus Game," is a gamified assessment developed by Imbellus for McKinsey & Company. (Click to see all screening tests by McKinsey, BCG and Bain!)

The one and only existing platform to practice three McKinsey Solve simulation games for FREE!

When does it appear in the McKinsey Interview Process?

Within McKinsey's hiring process, the Solve Game is screening test, positioned between the application and the case interviews. Its primary objective remains consistent with the traditional Problem-Solving Test: to efficiently identify suitable candidates and streamline the resource-intensive case interview phase. This approach optimizes both time and resources in the recruitment process.

Please see the McKinsey interview process below:

Figure 1: McKinsey Interview Process

NOTE - MBBs constantly edit their hiring steps & tests. All possible steps are listed. You might not get all of them. The steps are indicative. You will get specifics from MBB recruitment. Follow those.

How Does McKinsey Solve Game Work?

The McKinsey Solve Test, also known as McKinsey Digital Assessment or McKinsey PSG, is subject to a total time of approximately 71 minutes. Candidates are given 2 out of 6 possible mini-games. The assessment evaluates both the final results and the solving process. If a candidate demonstrates skills and tendencies similar to those of a McKinsey consultant, they may receive an invitation for an interview.

The McKinsey Solve Test includes 6 confirmed mini-games: Ecosystem Building, Red Rock Study, Ocean Cleanup, Disaster Management, Disease Management, and Migration Management. It's worth noting that almost all candidates, nearly 100%, will start with the Ecosystem Building Game as their first challenge. In 2024, McKinsey added the third game - Ocean Cleanup. This game is still in beta phase and given after Ecosystem Building and Redrock Study.

Please note that the other three games, namely Disaster Management, Disease Management, and Migration Management, were previously used by McKinsey for beta testing purposes. However, they are no longer included in the McKinsey Solve test in 2023.

The time allocated for tutorials is not factored into the overall time limit. It's advisable for candidates to maximize this tutorial period by attempting to anticipate the mini-game's objectives and crafting a general approach before initiating the mini-game itself. This time can also be utilized for essential preparations, such as having pen, paper, and excel sheet readily available.

To familiarize yourself with the interface and how the McKinsey Solve Game works, sign up for our Free McKinsey PSG Simulation and give it a try!

Figure 2: McKinsey Solve Game Overview

What traits is McKinsey assessing in McKinsey Solve Game?

The McKinsey Solve game assesses five critical cognitive abilities:

1. Critical Thinking: Your ability to thoroughly analyze information.
2. Decision-Making: Your capacity to take appropriate actions based on your analysis.
3. Metacognition: How effectively you implement strategies to achieve the game's objective.
4. Situational Awareness: Your capacity to maintain focus on the environment and anticipate future changes.
5. Systems Thinking: How well you comprehend the cause-and-effect relationships among the elements within the system.

The positive aspect is that many of the assessed skills are interconnected, meaning that improving one area can also enhance performance in others. This is crucial because it allows you to avoid diving into every tiny detail just to achieve a higher score.

Additionally, while showcasing all abilities is essential for success, some skills carry more weight. Based on the insights from this Imbellus research paper, Critical Thinking, Situational Awareness, and Systems Thinking are the core competencies that top candidates must demonstrate.

Advanced abilities such as Decision-Making and Meta-Cognition, on the other hand, are what separate great candidates from the rest.

What does McKinsey Solve Game include?

Game 1: Ecosystem Building

Figure 3: Mountain (Left) & Reef (Right) Scenario of Ecosystem Building Game

What is Ecosystem Building Game?

This is a 35-minute time limit game. You will be placed randomly into either a mountain or a reef scenario. (Click here to sign up and play the game for FREE!)

Objective:

Your goal is to construct an ecosystem comprising 8 species from a selection of 39. There are three primary objectives to accomplish:

1. The ecosystem should establish a continuous food chain.
2. Ensure a calorie surplus for each predator-prey pair.
3. Align the ecosystem with the terrain specifications of your chosen location

What does Ecosystem Building Game include?

1. Terrain Specifications

Each location within the ecosystem is characterized by seven to eight terrain specifications, which can be selected by pinpointing a location.

In the Mountain scenario, there are 8 terrain specifications: Elevation, Soil pH, Precipitation, Temperature, Wind Speed, Air Pressure, Humidity, and Cloud Height.

In the Reef scenario, you'll find 7 terrain specifications: Depth, Water Current, Water Clarity, Temperature, Salt Content, Dissolved Oxygen, and Wind Speed. 

Each species has its own set of required terrain specifications, typically ranging from two to four. Failure to meet these terrain requirements will result in the species dying out. These requirements often come in ranges.

2. Food Chain Continuity

In the game, you will be given a total of 39 species, categorized into two main types: producers and consumers.

• Producers: These include plants and corals. Their sole source of food is typically sunlight or other natural elements. Consequently, they neither have prey nor consume calories.
• Consumers: This category comprises animals, which can further be classified as Herbivores (plant-eating animals), Carnivores (animal-eating animals), or Omnivores (consumers of both plants and animals). Additionally, some consumers hold the status of "apex animals," indicating that they do not have natural predators and are not consumed by any other species within the ecosystem.

3. Calories Balance

Each species in the ecosystem is characterized by two essential figures: Calories Needed and Calories Provided.

A species can thrive under the following conditions:

1. Sufficient Energy for Survival: The species' calorie needed is lower than the total calorie provided by the ecosystem.
2. Avoiding Extinction by Predation: The species' calorie provided surpasses the combined calorie consumption by the species that prey upon it.

In essence, for a species to thrive, it must have enough energy to sustain itself and should not be consumed to the point of extinction by its predators.

Figure 4: Overview of the Ecosystem Building Game Interface

Main Challenges of Ecosystem Building Game:

1. Information Overload: Handling a significant amount of data that requires absorption, calculation, analysis, and prioritization. This encompasses the specifications of 39 species, terrain characteristics of each location, and dietary rules.
2. Distracting and Irrelevant Information: Certain details provided may not be relevant and are included to divert your attention or lead you into making assumptions. It's essential to refrain from making any guesses or relying on any prior knowledge related to the environment, ecology, or zoology

Figure 5: CaseBasix Ecosystem Building Excel Solver

How to tackle Ecosystem Building Game:

Here's a breakdown of how to approach the game, following a 3-step process:

Step 1: Location Selection

1. Use a spreadsheet or scratch paper to record the terrain specifications and calorie provided data for the mini-game's producers.
2. Examine the data to identify which terrain specifications remain consistent across all species and which ones change. Focus only on the changing terrain specifications (usually 2 of them), while the others are intended to divert your attention.
3. Calculate the total calories provided for the producers in each group of terrain specifications. The group with the highest calorie provision is likely the easiest to construct the food chain.

Step 2: Food Chain Building

1. Examine the data to list consumers with compatible terrain requirements in your spreadsheet.
2. Select the apex predator with the lowest calorie requirement as the starting point for the food chain.
3. Construct the food chain starting from the apex predators and work your way down, listing the food sources for each top-level predator. Keep progressing in this manner until you reach the lowest tier, which includes corals and plants. Ideally, the food chain should encompass 3-4 levels and encompass 8 species.
4. Alternatively, you can build the food chain from the bottom up by examining the "Eaten By" specifications of each species, working your way up to the top predators.
5. Throughout the process, prioritize species with high calorie provision and low-calorie requirement. This should increase the chances of a calorie surplus in the food chain and allow room for additional species if the initial chain falls short of the required 8 species.
6. If your food chain doesn't reach the necessary 8 species, work from the bottom up to identify gaps of unused surplus calories and fill these gaps with predators or plant-eating animals.

Step 3: Sanity Check

1. Ensure that each species in your food chain aligns with the chosen location.
2. Verify that the food chain is continuous, meaning that the listed food sources match the descriptions of each species.
3. Confirm that each species in the food chain has an adequate calorie supply and isn't consumed to extinction based on the provided eating rules.
4. If any of the three checks are not met, make adjustments to the food chain.

Figure 6: Illustration of a food chain in Ecosystem Building game

Game 2: Red Rock Study

This is a game with a 35-minute time limit, during which you will complete the Red Rock Study, consisting of both Part 1 and Part 2. 

Experience the Redrock Study game firsthand by trying our FREE Simulation today.

The McKinsey Red Rock Study divides the tasks into 2 parts:

• Part 1: Study
• Part 2: Cases

Figure 7: McKinsey Redrock Study Game Interface

In Part 1, you'll get one study with a main goal and some data to support it. This part has three steps:

• Phase 1: Investigation
• Phase 2: Analysis
• Phase 3: Report

In Part 2, you'll receive 6 short cases that are related to the same topic but not directly connected to the Part 1 Study. Each case will come with two different types of questions:

1. Multiple choice questions
2. Numerical answer questions

You need to finish both tasks (Part 1 & Part 2) within a total time limit of 35 minutes. Although there are no specific time constraints for each part, it's advisable to allocate more time to the first part and less to the second part.

Now, let's delve into the specifics of Part 1 and Part 2 of the tasks.

Part 1: Study

Phase 1: Investigation

Figure 8: Objective & Data in the Study

Your goal is to read through the case description, recognize the main objective and essential data points, and then gather them in an on-screen Research Journal.

The data and information provided are divided into three sections, with each section containing the necessary information required to complete the study:

1. Objective
2. Exhibits
3. Study Information

How to tackle this phase:

1. Understanding the study
2. Collecting important data points

1. Understanding the study

Your objective here is to identify case’s objectives.

Every piece of information displayed on the screen is crucial for comprehending and resolving the case. However, some are more critical than others. Significant data points are highlighted and displayed in boxes on the screen, allowing you to click and drag these boxes to focus on them while working within the case.

The data provided comes in two formats:

1. Text-based data, which is divided into two types:
   • Movable data points: These text-based data points consist of case objectives and calculation instructions. They clarify the case's goal, specify the mathematical formulas to be applied, and outline which numbers need to be gathered. Typically, these are detailed sentences or paragraphs that describe the relationships (such as higher, lower, etc.) between the elements within the case.
   • Non-Movable data points: These text-based data points encompass background information and test instructions. They are not selectable or movable and are intended solely to provide an overview of the case. They do not need to be collected as their purpose is to offer context.
2. Number-based data: These typically consist of movable data points and comprise the majority of the data in the case. They can be found in two locations: within charts, diagrams (such as bar charts, pie charts, tables, etc.), or within the text. It's necessary to gather these numbers into the journal for calculations in the next phase.

2. Collecting important data points

You can drag any movable data point into the Research Journal to collect. In the Research Journal, each collected piece of information will appear as a card, with its own name and description. The data in the Research Journal can then be used in the Calculator or as answers in phase 2.

You have the option to change the labels for all the data yourself. We suggest doing this if the default label doesn't describe the contents well enough. Using the right labels will make your analysis faster because it helps you easily find the important data later on.

After you've collected the data, you can also include your own notes with each piece of information. This can assist you in explaining the information required during the Analysis phase.

Here’s a summary of our recommended approach:

1. Determine the objectives of the case.
2. Identify the mathematical formulas needed to address these objectives.
3. Collect in your Research Journal only the essential data points necessary for the calculations during the Analysis phase.

Phase 2 – Analysis

Figure 9: Example questions in Analysis Phase (with calculator)

Your objective here is to use the data points gathered during the Investigation phase to answer three quantitative questions using the provided calculator. These answers will be utilized to complete the report in Phase 3.

The three quantitative questions typically consist of 2 to 3 sub-questions, each with an answer input gap that requires a response from the calculator. To address these questions, you need to input the numerical data points you've collected into an on-screen calculator and then transfer the results to the corresponding gaps.

The calculator features a straightforward interface, resembling a digital calculator found on a phone, and includes basic operators such as multiplication (x), addition (+), subtraction (-), and division (÷).

The calculations required for the questions can be categorized into two types:

1. Basic Operations: This category includes addition, subtraction, multiplication, and division. While these operations are fundamental, you may need to use them in combination to perform more complex calculations.
2. Percentages/Ratios/Fractions: These calculations are used to address questions related to relationships, such as percentage differences, growth rates, and similar concepts.

We advise you to carry out all calculations using the provided calculator since all your actions are documented in a history log. It's safe to assume that the process you follow in arriving at the answers will also impact the final results.

It's crucial to keep in mind that the answers you obtain from these questions are almost always required in the Report phase. Therefore, it's essential to consistently record your answers in the journal.

How to tackle this phase:

1. Carefully read the questions to understand what is being asked.
2. Drag the relevant data points from your Research Journal into the calculator's input screen to perform the necessary calculations to answer the questions.
3. Drag the results and drop them into the empty spaces provided under the questions.
4. Ensure that you collect the answers in your Research Journal for use in the Report Phase.

Phase 3 - Report

Figure 10: Screenshot of Visual Report in Report Phase

Your objective here is to finalize the textual and graphical report. You will have the option to choose one of three types of graphs to include in the report, and these graphs will be based on the results calculated in Phase 2.

The Report phase is the final segment of Part 1 Study and comprises two sections: the Written Report and the Visual Report.

• Written Report: This summary report involves completing the text-format report by filling in the blanks with numbers obtained in the preceding phases, as well as using expressions like "higher," "lower," "equal to," and so on. The blanks in this phase are likely to resemble the answer inputs in the Analysis phase.
• Visual Report: This aspect involves data visualization, where you select the appropriate chart type and input the numbers to create a meaningful chart for the report.

Part 2: Cases

Your objective is to answer 6 cases, each featuring a question with instructions, textual information, and data exhibits.

In each of the 6 cases, there is an onscreen tool available to aid you. It's essential to solve the cases in a sequential manner, which means you cannot skip ahead and must address one case before proceeding to the next.

All 6 cases will revolve around the same theme or topic as Part 1 of the study, but they are not interconnected. These cases primarily demand a basic level of quantitative or reasoning skills and do not necessitate advanced mathematical abilities. 

However, it can be challenging to solve all 6 questions within a short time limit, so it's important to use your time wisely.

The question types in Part 2 can be grouped into four primary categories:

• Word problems: These involve mathematical exercises where candidates must read the text and interpret data to find solutions.
• Formulae: These questions are similar to word problems, but candidates only need to identify the formula used for calculation.
• Verbal Reasoning: These are single-select multiple-choice questions that ask candidates to determine which statement is true or false.
• Visualization: These questions require candidates to choose the appropriate chart type to represent the provided data.

Game 3: The Sea Wolf (Formerly Known as Ocean Cleanup)

What is Ocean Cleanup Game?

Introduced by McKinsey in 2024 as the newest addition to their Problem Solving Game series, the Ocean Cleanup Game—also known as the "McKinsey Ocean Treatment Game" or "The Sea Wolf"—requires players to manage and restore an ocean ecosystem. Players must strategically select and balance different microbial species to reduce plastic pollution effectively.

The primary objective is to identify the most adaptable microbes that can thrive across varying ocean sections, making "Microbe Management" a critical aspect of the game.

What are the details of this game?

• Time Limit: You have 20 minutes to complete both phases of the game.
• Game Order: The Ocean Cleanup Game follows the Ecosystem Building and Redrock Study games in the assessment series.
• Beta Status: The game is currently in beta, meaning player feedback is crucial and could lead to potential modifications.

How to play the Ocean Cleanup Game?

Step 1: Understanding the Game Structure

The game involves managing two distinct ocean sections, each with unique conditions like temperature, depth, and pollution type. The aim is to select microbes that can adapt well to both environments.
Microbial Attributes: Each microbe has five attributes:

• Numerical Attributes (Scale 1-10): This includes aspects like velocity, absorbency, and fluidity.
• Binary Attributes: Traits that are either present or absent, such as heat resistance or acid tolerance.

Figure 11: 5 key microbial attributes in McKinsey Ocean Cleanup Game

Ocean Section Attributes vs. Microbes Attributes:

Ocean Section Attributes

At the start of the game, you’ll encounter five attributes that define each ocean section. These attributes remain constant and are divided as follows:

• Numerical Attributes: Three are represented as numerical intervals. For example:
  • Fluidity: 2-4
  • Velocity: 6-8
  • Absorbency: 7-9
• Binary Attributes: Two are binary, indicating whether they are desirable or undesirable traits:
  • Resistance to Acids: Desirable
  • Degradation from Heat: Undesirable

These attributes establish the requirements that the selected microbes must meet for effective performance in each section.

Figure 12: Ocean section attributes

Microbes Attributes

Each microbe has five attributes:

• Numerical Attributes: Three numerical attributes that can fall within or outside the defined ocean intervals. For instance:
  • Fluidity: 5
  • Velocity: 7
  • Absorbency: 8
• Binary Attributes: Two binary traits that may align (or not) with the desirable or undesirable conditions of the ocean. For example, a microbe could be resistant to acids but vulnerable to heat.

Matching the microbe attributes to the ocean section's attributes is crucial for achieving effective cleanup.

Step 2: Evaluating Microbes

The evaluation process involves two phases:

Phase 1: Selecting Attributes
Players select two out of the five attributes (numerical or binary) that will be prioritized across all microbes. This decision guides which microbes are most suitable for each ocean section.

Figure 13: Evaluating Microbes

Phase 2: Screening Microbes
After the attributes are set, players screen a total of 10 microbes and categorize them:

• Keep for Section 1: Microbes that align well with the first section's characteristics.
• Keep for Section 2: Microbes that fit better with the second section.
• Discard: Microbes that do not meet the required criteria.

Figure 14: Screening Microbes

Note: The relevance of this step to later stages of the game is currently uncertain and might be omitted in future versions.

Step 3: Selecting 10 Microbes

Players choose 10 microbes from a pool of 20, with the selection based on the microbes' alignment with the attributes of both ocean sections. Each microbe's description must be carefully analyzed to ensure compatibility with the conditions in both environments.

Step 4: Narrowing Down to 3 Microbes

From the selected 10, players further refine their selection to three microbes that best match the preferred range. Here are the key criteria:

• The average values of the selected microbes should fall within the desired range.
• Prioritize microbes with desirable traits while avoiding those with undesirable characteristics.

Figure 15: McKinsey Ocean Cleanup Game Steps Process

Main Challenges of the Ocean Cleanup Game

In this game, there are 3 main challenges:

• Randomness: The wide variety of microbes and their attributes can make the game feel unpredictable. To overcome this, focus on identifying patterns that lead to successful outcomes.
• Time Pressure: With a 20-minute time limit, players must manage time well. Practice quick decision-making to avoid getting bogged down.
• Balancing Two Ocean Sections: Managing two ocean sections simultaneously requires a careful approach. Players must continuously cross-check selections to ensure effective performance in both sections.

How to tackle the Ocean Cleanup Game?

Here are some strategies to improve your performance:

1. Understand the Game Rules: Familiarize yourself with the requirements and criteria for selecting microbes to make informed choices.
2. Aim for Balance: Choose microbes that complement each other, creating a balanced ecosystem. Avoid those that could disrupt the balance.
3. Manage Time Efficiently: Make quick, informed decisions to stay on track.
4. Leverage Tools: Use tools like Excel Solver to handle complex calculations, helping you optimize microbe selection more effectively and accurately.
5. Prioritize Both Sections: Ensure the selected microbes can perform well across both ocean sections, achieving optimal balance.

The Importance of Practicing McKinsey Solve Game

The McKinsey Solve Game is meant to assess your critical thinking skills. However, if you haven't practiced beforehand, you might not be familiar with these mini-games, including how they work and what you're supposed to do.

According to our survey, many candidates were surprised when they took the test, even if they had read guides and watched game walkthroughs. These mini-games have complicated interfaces and various functions. Most candidates, when they first encounter them, need to spend time just figuring out how they work, then what the goals are, and finally start playing the game. Going through all these steps in a very short time can be nearly impossible.

You might have the exact set of thinking skills McKinsey is looking for and still not do well in the mini-game. This could happen because you might not understand how the game works, struggle with time management, or get confused by some aspects of the game.

That's why practicing with the McKinsey Game is so helpful. With our FREE McKinsey PSG Simulation, you can become familiar with these types of mini-games and improve the thinking skills you need to do well.