How to Pass the McKinsey Solve Game [Imbellus] 2025: Complete Guide and Practice

Jump To:

• McKinsey Problem Solving Game General Overview

• The Ecosystem Building Game

• The RedRock Game

• The McKinsey Recruitment Process

• Tips, Strategies, and Preparation

• Problem-Solving According to McKinsey

• FAQs

You are in your home, facing your computer. On the screen is a vivid world controlled by you, the player. This isn't just a casual gaming session—it's a test of intellect, strategy, and composure. You are playing the McKinsey Solve Game, and success can be the key that unlocks the door to a career at McKinsey & Co.

Most applicants do not get past this stage of the hiring process, so the pressure is on. Let's discuss this digital assessment and what makes it so challenging.

The McKinsey Solve Game, sometimes called the McKinsey Problem Solving Game or the McKinsey Digital Assessment, is a modern, interactive way for McKinsey & Company to evaluate candidates before inviting them to case interviews.

Instead of answering multiple-choice questions on paper, you enter a simulated environment that feels more like a strategy game than a traditional test. Every move you make is tracked - from the data you choose to analyze to the sequence in which you take actions. McKinsey uses these insights to measure not just the accuracy of your final answer, but also how you think, adapt, and manage complex challenges.

The game was originally developed by Imbellus, a company specializing in scenario-based assessments, and was introduced at McKinsey in 2017 to replace the Problem Solving Test (PST). Over time, it has become one of the most distinctive pre-employment assessments in the consulting industry. Candidates worldwide now prepare specifically for it because the style, pace, and skills tested are unlike any other stage in the hiring process.

McKinsey positions the Solve Game as a fairer, more accurate measure of potential. Since it is not based on memorized formulas or business knowledge, the playing field is more even for candidates from diverse backgrounds. That said, the challenge lies in the fact that the scenarios are open-ended, with multiple possible solutions, and the scoring takes into account not just the result but how you arrived at it.

McKinsey is looking for consultants who can handle complex, ambiguous situations and break them down into actionable steps. The Solve Game’s scenarios mirror this by requiring you to:

• Collect and filter large amounts of data
• Identify patterns and relationships quickly
• Make strategic trade-offs with limited resources
• Adapt to new information as the scenario unfolds

In other words, the skills you need to succeed in the game are the same ones you will need when working with McKinsey clients - analytical thinking, resource management, creativity, and composure under pressure.

While the exact scoring algorithm is confidential, candidates and preparation experts have identified a few key competencies the game measures:

For most candidates, the Solve Game comes right after your initial application and before the first round of case interviews. Passing it is a requirement to move forward, and many applicants never get past this stage - not necessarily because they lack the skills, but because the format is so unfamiliar. This is why understanding the structure and practicing under realistic conditions is critical.

Understanding the format of the McKinsey Solve Game is essential if you want to perform well. I have worked with hundreds of candidates over the years, and the number one reason they struggled was because they went in without knowing exactly what to expect. Let’s break down how the assessment works from start to finish.

One of the most common questions candidates ask is “How is the McKinsey Solve Game scored?”. While McKinsey does not publish the official scoring algorithm, feedback from hundreds of test-takers and insider reports gives a good picture of how your performance is measured.

Weight of Each Game

While McKinsey doesn’t reveal exact weightings, reports suggest:

• Ecosystem Building – 35–40% of total score

• RedRock Case Study – 35–40% of total score

• Sea Wolf / Ocean Cleanup – 20–25% of total score

Performance in one game can offset weaker results in another, but consistently low scores across games will make progressing to interviews difficult.

Score Ranges & Benchmarks

Based on aggregated candidate feedback:

• Top Tier: Above ~75% – Very likely to move forward to case interview

• Competitive: ~60–75% – Still strong, but other parts of your application matter more

• Below Average: Under 60% – Less likely to progress unless you have exceptional credentials in other areas

⚠ Note: McKinsey doesn’t share your exact score with you — you’ll only know if you advance.

What Recruiters See

Recruiters typically see:

• Overall performance percentile

• Performance per skill category

• Qualitative insights from the game (e.g., “Strong at strategic planning but inconsistent in data analysis”)

From what I’ve seen, the top-performing candidates do three things:

1. Preview the entire scenario quickly before committing to actions. This helps you spot hidden connections early.

2. Track your reasoning steps in writing – McKinsey evaluates your process, not just your final answer.

3. Allocate time consciously – if you are stuck, move on and return later if possible.

The first section of the McKinsey Problem Solving Game places you, the candidate, in the middle of a harsh wilderness environment, either an underwater coral reef or a rocky mountain ridge.

As you move your mouse across the landscape, you will learn that different areas have differing statistics. Elevation, depth, temperature, humidity, etc. To make things more complicated, you can only view four stats at one time.

On your screen, you can see a flora and fauna almanac. Just as with the terrain, selecting any plant or animal will give you information about that species:

Your goal is to choose eight species and a location to place them, thereby creating a sustainable ecosystem and ensuring food chain continuity. This is achieved by carefully following the eating rules provided within the game. The key skills measured by the ecosystem-building mini-game are systems thinking, inductive logical thinking, decision-making under pressure, planning, and strategizing.

The rules are the same regardless of your ecosystem-building scenario. The only things that change between the coral reef and mountain ridge are the specific species in your guidebook.

On our McKinsey Problem Solving Game prep course, we recommend working with a five-step problem-solving system for maximum efficiency.

For this article, let's discuss several helpful tips for this part of the McKinsey Solve Game.

Part of this puzzle requires you to practice probabilistic thinking. This means a good way to start is by clustering your species into different groups that could create an ecosystem based on their environmental suitability. Then, choose the cluster you are most likely to succeed with. McKinsey calls this situational awareness, which is the ability to predict results based on the environment you are given.

You can do this by quickly going over the total calorie output of all species in the cluster, as well as checking the species' food sources to see how diverse they are so that food sources are not depleted.

After you've narrowed your options down to a specific cluster, you can start building your food chain one animal at a time. This will help you complete this part of the McKinsey digital assessment faster.

Once you are finished, submit your food chain, you will move on to the next section of the McKinsey Problem Solving Game Assessment - the RedRock Island Case Study.

After the ecosystem game comes the second part of the McKinsey Solve, which is often considered the more difficult one.

At the start of the game, you receive a phone call. The woman on the other end identifies herself as the chief researcher at RedRock Island and the head of RedRock Labs.

As a new Research Assistant, you are being asked to review data collected from the island and use it for studies and cases in the lab. This can be done by accessing the lab's computer and following four steps:

At this initial stage, you must review observations made by lab fieldworkers and collect only the most relevant data points.

How is this done within the game?

While you go over the data in its raw form, some verbal or numerical data points will be highlighted. You can drag and drop those data points into a section of the screen labelled "Research Journal" if you think they will be helpful to you in later stages. Once relevant data points have been saved to your on-screen research journal, you can reorder and rename them for your convenience.

Note that only a small part of the data is really relevant. After this phase, you will no longer be able to see any data points you did not save.

Once you move to this stage, you will be given numerical questions relevant to the study. You must answer these questions by dragging the significant data points collected into an onscreen calculator.

Though you can also use your own calculator or perform the calculations in your head, it is generally recommended not to stray from the game format and to use the in-game calculator so the software can track your process. You will need to make sure you are brushed up on basic operations, ratios, percentages, and compound growth before starting the McKinsey Problem Solving Game, so you can answer all the questions in this section.

Now that you have your results, create a textual and graphical report to explain them. The challenge here is to select the correct form of data visualization to represent the information, be it a bar chart, line chart, or pie chart.

After selecting your chosen graphic display, use the game interface to create the graphs so they accurately convey the data.

The first three steps all relate to a single study, with a single hypothesis and a single goal. Now that you have finished work on this study, you are bombarded with ten more minor cases. You will need to read these case questions, then repeat the first three phases with these research questions in mind.

A case is a single research question, unrelated to the larger study you have been researching until now.

This tends to be the most stressful part of the McKinsey Problem Solving Game. Candidates who just finished the main study, thinking they are close to the end, now must race against time to answer ten more questions. It is recommended that you leave about half of your RedRock Game time to the cases.

This part of the McKinsey Solve Game measures your numerical reasoning, understanding of data visualization, information filtering and prioritization, and critical reasoning skills.

It also evaluates candidates' reading comprehension.

It requires you to pre-select salient or important data points from all the data you are presented with based on your understanding of the study's objective and hypotheses, which are presented in writing.

Lastly, this part of the McKinsey Problem Solving Game ascertains your organizational skills. While you can drag and drop any data points you wish into your journal, it is recommended to label them, organize them in a logical order, and name them according to what they represent. This showcases your ability to turn chaos into order.

The McKinsey Solve Test is officially the second part of the recruitment process, which begins with submitting an application.

You will receive an email invitation to take the test soon after sending in your resume. Typically, you will be asked to take the assessment within 1-2 weeks of receiving the invite, though this can sometimes be more restrictive.

Ideally, you should prepare for the McKinsey Solve before submitting your application, to give yourself time to prepare.

If you are one of the lucky test takers who passed the game, the next stage is the McKinsey Personal Experience Interviews (PEI) and Case Interviews. In the former, you will be asked to describe yourself, your fit to the company, and your growth and achievements in previous positions. In the latter, you will be asked to demonstrate your analytical skills by tackling a consultancy case along with your interviewer.

Mental math is an effective way to make calculations in the mini-games.

But as you’re only human, it’s not error-free. That’s why using a calculation tool, such as Excel formulas, can be a great way to make super fast and accurate calculations.

You can significantly cut down on calculation time by using external tools like Microsoft Excel. Our Preparation pack contains an Excel guide to teach you the most effective way of using a spreadsheet to ace the ecosystem-building mini-game.

The last thing you want during the assessment is a “blue screen of death.”

It may happen if your hardware is not strong enough, since the McKinsey PSG is pretty demanding in its system requirements.

Any computer that is more than five years old or without an HD screen will likely encounter lags and performance drops.

Also, you must have a fast and stable internet connection. If you get disconnected in the middle of the test, you might need to start all over again or even reschedule for another testing date.

On our preparation course, you can find simulations of both games, including comprehensive feedback reports. You can also find structured learning modules taking you through the most effective strategies to ace the test, including video and written guides.

The choice to use the McKinsey Problem Solving game as a primary and significant recruitment stage reflects McKinsey's organizational culture, which strongly emphasizes problem-solving as a core value.

The definition of problem-solving is, of course, subjective. However, McKinsey has its own version. This is the version they are trying to promote with their problem-solving game.

You can read more about Mckinsey's take on problem-solving and critical thinking here.

Here is a general overview of McKinsey's seven-stip problem-solving model:

• Problem Definition - understanding exactly what the problem is. This means more than just visualizing your desired outcome; it means understanding precisely what is standing in your way. In the McKinsey Problem Solving Game, this is reflected in the investigation phase of the RedRock Island task, as well as the data collection phase of the ecosystem-building mini-game.

• Problem Disaggregation - break up your problem into manageable parts. This can help you gain new perspectives into the problem itself and the solution.

• Prioritization - choose which action items will likely have the most significant impact and cost the least. You can find prioritization in the digital assessment when choosing which species bundle to look at, or which cases to read first.

• Build a Work Plan - Take your time limit and resources into account to create a solid plan to follow.

• Analyze - use any analytic tools at your disposal to turn the data you have into something workable. This is reflected in the Analysis phase, part of the RedRock section in the McKinsy Digital Assessment.

• Synthesize Findings – Combining insights from different analyses to form a coherent understanding of the problem and possible solutions.

• Develop Recommendation – Based on the synthesized findings, formulating a clear and actionable recommendation. This step is crucial in McKinsey’s consulting work, where structured, well-supported recommendations drive decision-making.

By incorporating these elements into the McKinsey digital Assessment, the recruiters are insuring candidates align with the firm's structured and data-driven approach to tackling challenges.

The McKinsey Problem Solving Game undergoes constant and regular updates. While Ecosystem building has been a staple of the game for years, the second mini-game has gone through several iterations like the Plant Defense game, Disease Management game, and Disaster Management game. The Redrock Island has officially been the second part of the McKinsey Assessment since 2023.

Let's go over past games in the McKinsey Digital Assessment:

• Disaster Management Mini-Game- Identify which natural disaster has struck an ecosystem, then relocate it to ensure its survival.

• Disease Management Mini-Game- predict which species is next to be affected by a contagious disease based on previous epidemiological data.

• Migration Management Mini-Game- Facilitate the safe transfer of an animal population from one environment to another.

• Plant Defense Mini-Game- a turn-based puzzle game in which you defend a plant from various invader species.

The game currently being piloted as a possible replacement for Redrock is the Ocean Cleanup Game, also known as the Sea Wolf Game.

The object of the Ocean Cleanup Game is to select 10 microbes out of a catalogue that can survive in an area of ocean you are trying to clean up. Three of these ten will create bond chains that will help remove plastic from that area of the ocean.

We are closely monitoring the decisions made at McKinsey to ensure our course remains up-to-date.

• Desktop or laptop with a stable connection and an HD screen

• Keyboard with numpad for faster calculator entry

• Quiet room, no interruptions, visible clock or timer

• Pen and paper for quick sketches and to track time boxes