McKinsey Solve Game: How to Pass the Digital Assessment in 2025

Jump To:

• What is the McKinsey Solve Game?

• McKinsey Solve Game Mechanics Explained

• McKinsey Solve Game Tips & Best Practices

• Latest Updates and Changes in 2025

• McKinsey Recruitment Process

• The McKinsey Problem Solving Model

• FAQs

You are sitting in front of your computer, in the comfort of your home. A dynamic world appears on screen, waiting for you to interact with it. This isn't a casual gaming session; it is the McKinsey Solve Game, a test of your problem-solving skills, decision-making, and composure.

Along with your CV and application form, this problem-solving game can be the key to a career as a McKinsey consultant.

So, what is this digital assessment and what makes it so challenging?

The McKinsey Solve Game, sometimes called the McKinsey Problem Solving Game, McKinsey PSG, or McKinsey Digital Assessment, is a gamified cognitive ability test designed to evaluate candidates for consulting positions.

Despite its name, the assessment actually consists of two separate games, both measuring your ability to think like a consultant: strategise, build a work plan, and employ critical thinking.

Unlike Bain and BCG, who both use familiar pre-hire assessments (Sova and Pymetics, respectively), the McKinsey Solve Test is unique. After being launched in 2017, it quickly gained a reputation as the most flustering MMB exam, with complicated instructions and a tight time constraint.

Each of the games making up the solve assessment is 35 minutes long. On first inspection, they appear entirely disconnected from the world of consultancy, finances, business strategy, or market analysis. Instead, both the Ecosystem Building Game and Redrock Island Game are ecology-themed.

In fact, embedded in the McKinsey Solve Game are skills such as resource management, data interpretation, and logical reasoning. The Solve Game is built to reflect McKinsey's trademarked seven-step problem-solving method, which will be discussed further down this page.

Here is a quick overview of the two games:

Before taking the McKinsey Problem Solving Game, it is essential to know you will be evaluated not only by your final result. The game platform tracks your process and thinking style as you solve the games.

While stress-inducing, this is why McKinsey recruiters consider the McKinsey Game an appropriate recruitment tool for its consultants. It actively measures critical consultancy capabilities such as systems thinking, critical thinking skills, and the ability to filter out irrelevant data while prioritising crucial data.

JobTestPrep's McKinsey Problem Solving Game Course provides McKinsey PSG simulations for both the Ecosystem Game and the Redrock Game, complete with feedback reports to bolster improvement and growth. Equally as important, though, it also contains structured learning modules that delve deep into the strategy and rationale behind the games to minimise confusion.

Let's go over the gameplay of each part of the McKinsey Problem Solving Game:

The first section of the McKinsey Problem Solving Game teleports you into an uncharted wilderness. For some players, it is a rugged mountain ridge. For others, it is a lush subaquatic coral reef.

As you begin to explore by hovering your mouse across the terrain, you will soon discover the landscape is not uniform. Different locations differ in various aspects, such as elevation, depth, humidity, wind speed, and others. You can see these on your screen by pointing to a location you wish to inspect. To make things a little more frustrating, you can only view four of these statistics at one time.

Across the screen from your monitors, you will see a "species handbook"- an almanack of the region's flora and fauna. You can click on a plant or an animal to see information about it. Some of the information is related to the terrain monitors as it specifies where the animal can survive. Other stats, however, are related to the game's central puzzle: the eating rules.

The Ecosystem Building Game has one central goal: select one location and eight species and use them to create a stable and sustainable ecosystem with ensured food chain continuity. This means two things:

• All the animals can survive under the conditions in the chosen location.

• The food chain is balanced and at equilibrium—all animals have enough nourishment to survive, and no animal is eaten to extinction.

The first is a matter of choosing the correct location. The challenge lies in the second one. To achieve this balance, you must carefully adhere to the eating rules presented in the game.

Regardless of the ecosystem-building scenario you have been given, the game's rules are always the same. The main difference between the mountain ridge and the reef is the species in your guidebook.

The ecosystem-building mini-game measures several key skills, including situational awareness, systems thinking, inductive logical thinking, decision-making under pressure, planning, and strategizing.

Once you've added eight species from your guidebook to the ecosystem, you can submit your result. In the most recent iteration of the McKinsey Problem Solving Game, you are not given any information on how well you did after submitting. Instead, you are taken directly to the next section of the McKinsey Problem Solving Test - the Redrock Island Case Study.

Following the ecosystem game is the second section of the McKinsey Solve Game, largely described by candidates as the more challenging section. The game's objective is to complete a series of quantitative research questions.

As the game begins, you must accept a phone call. After answering, you are greeted by the Chief Researcher at Redrock Labs, an ecological research centre located on the isolated Redrock Island.

She welcomes you into your new position as a research assistant at the lab. Your job, she explains, is to transform raw data points collected across the island into a comprehensible report.

To do this, you must follow four steps:

On your screen, you will see an extensive collection of verbal and numerical data points regarding the wild populations on the island. Some are highlighted to indicate that they are movable. A movable data point can be dragged and dropped into a section of your screen labelled "Research Journal."

After reading the research questions the lab is trying to answer, your job is simply to collect only the most relevant data points out of all the data available. Once in the research journal, data points can be labelled, rearranged, and given additional text for context.

A relatively small portion of the data, about one in ten points, is relevant data and belongs in your on-screen research journal. However, you must choose well because data that you do not choose to save will not be available to you past this stage.

Now that you have narrowed down your data, your research questions will now be presented to you. You must perform calculations using the data you have saved to reach an answer.

There will be an on-screen calculator within the game format at this stage. You can drag your significant data points from the on-screen research journal to the calculator's input screen to use it. While it is true that the same calculations can be performed on a pen and paper or even mentally, we recommend using the embedded calculator to allow the game software to track your process.

The mathematical concepts you must be familiar with are basic operations, averages (mean, median, mode), percentages, ratios, and sometimes compound growth. Make sure you brush up on these before starting the McKinsey Problem Solving Game.

Once the results are in, all that's left is to report them. First, you will need to fill in the blanks in a textual report of your results. Next, you will have to select the right form of data visualisation to represent your results, such as a pie chart, bar chart, or line chart.

After selecting your chosen graphic display, use the game interface to create the graphs to accurately convey the data. After making a textual and graphical report, you will have completed the study.

The first three phases have all surrounded a singular research subject and with three research questions.

Once you enter the cases section, the format changes to something more akin to a "rapid fire" round. Each "case" is a research question unrelated to the broader study, and there are typically six of them.

Candidates hoping to become McKinsey Consultants often report this as the most stressful part of the game. Just as you are in the final stretch and have just completed a big research task, you are suddenly bombarded with six more questions.

It is recommended that test takers split the 35 minutes allotted to the Redrock part of the McKinsey Game into two - because the cases part can be as long and taxing as the main study.

At its core, this section of the McKinsey Solve Game assesses your critical thinking and numerical reasoning. This includes an understanding of data visualisation methods and following basic calculation instructions.

It also evaluates your ability to prioritise information and focus on important data points while filtering out nonrelevant ones. Keep in mind that saving unimportant data to your journal "just in case" may negatively affect your score. The game wants you to understand which relevant data you will require.

The game also assesses verbal reasoning and reading comprehension. This is reflected in the fact that choosing which data to save is based on your understanding of the research questions.

Finally, this part of the McKinsey Problem Solving Game also measures your organisational skills. As stated earlier, data points in your journal can be arranged and labelled as you like. This provides you with an opportunity to showcase your capacity to be methodic and organised in the way you save your data for later use.

On our McKinsey Problem Solving Game Prep Course, we introduce a five-step system to optimise and expedite the Ecosystem Building Mini-Game.

For the purpose of this article, let's focus on several simpler tips that can help you achieve success in the McKinsey Solve Game.

According to McKinsey, one of the five key cognitive abilities measured by the Ecosystem Building Mini-Game is situational awareness. This refers to the ability to predict results using educated intuition. In the case of the ecosystem-building game, instead of analysing all 39 species, it is helpful to first divide them into "clusters" based on the environmental conditions in which they can survive.

After creating your clusters, you can now make an educated guess as to which cluster has the best chance of containing a sustainable food chain based on the sum total of the species' calorie input. You can also look at the diversity of food sources in each cluster to ensure no species is over-eaten.

Mental math, as well as pen and paper, are both effective ways to make calculations in the mini-games.

However, the McKinsey Solve Assessment intentionally floods you with information, and it might not be a good idea to rely solely on yourself. Using tools like Microsoft Excel can come in very handy for organising and manipulating the data. Our McKinsey Solve Prep Course will teach you how to do this effectively for the ecosystem-building mini-game, as well as the Redrock case study.

The exception to this is the Redrock game's analysis phase, where you will want to show your work using the in-game calculator.

One of the biggest criticisms faced by the McKinsey Solve is its hardware-intensive nature. You will want to make sure your system is up to scratch to avoid uncomfortable situations like the "blue screen of death."

You will also want to make sure you have a stable internet connection. If you get disconnected in the middle of the game, you might have to start over or reschedule.

• Consider the game's structure - the Solve Game is unlike other exams in that you are not only expected to produce results but also demonstrate how you approach problem-solving. Your results will comprise a product score and a process score. Make sure you stop to think about strategy before you start playing with the interface and doing things that may cost you points.

• Do not be overwhelmed - the McKinsey Solve Game actively tries to throw you off by giving you a tremendous amount of information. Remember, you do not need to handle all of it. If you did, you would not be able to finish the game under the time limit. One of the skills being measured is focusing on relevant data.

• Take action to prepare - while not everyone might have to prepare, and some candidates might feel that they are experienced enough with problem-solving that they can take the test as they are, it should not be fair for you to lose your chance at McKinsey for lack of readiness. Make sure you are familiar with the game interface and useful strategies before you begin. Our McKinsey Prep Course is a great way to get yourself ready!

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.

The recruitment process at McKinsey begins with applying. Virtually all those who fill in an application form (which includes sending in a CV) will receive an invitation to take the McKinsey Solve Test.

If you plan to prepare for the assessment, we recommend doing so before sending in your application. This is because McKinsey has asked you to take the test within a specific time since you received your invitation. This is typically one or two weeks, but can also be several days.

Approximately 70 per cent of applicants finish their journey with McKinsey after this stage. Those who move on do so based on their McKinsey Game score and CV.

If you are a part of the remaining 30 per cent, your next challenge will be 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 with your interviewer.

The decision to use the McKinsey Problem Solving Game as a key recruitment stage reflects McKinsey's organisational culture, which places a strong emphasis on structured problem-solving as a core competency.

While problem-solving can be defined in many ways, McKinsey has its own structured approach, which the Solve Game is designed to assess and reinforce. They call it the Seven-Step Problem Solving Model.

You can explore McKinsey’s perspective on problem-solving and critical thinking here.

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

• Define the Problem – Clearly identify what stands in the way of your desired outcome. In the McKinsey Solve Game, this is reflected in the Investigation Phase of the RedRock task and the data collection stage of the Ecosystem Building mini-game.

• Disaggregate the Problem – Break the issue down into manageable components. This approach helps uncover root causes and viable solutions.

• Prioritize Issues – Identify the most impactful actions with the least cost or effort. In the digital assessment, prioritization is tested when selecting which species bundle to examine or which cases to analyze first.

• Develop a Work Plan – Consider available time and resources to create a structured plan.

• Analyze Data – Use analytical tools to transform raw data into actionable insights. This step is reflected in the Analysis Phase of the RedRock scenario in the Solve Game.

• Synthesize Findings – Integrate insights from various analyses to develop a coherent understanding of the issue and potential solutions.

• Develop Recommendations – Formulate a clear, well-supported recommendation based on the synthesized findings. This step mirrors the structured, data-driven approach McKinsey uses in real-world consulting engagements.

By embedding these principles into the McKinsey Problem Solving Game, McKinsey ensures candidates align with its structured and analytical approach to tackling challenges.

Recruiters evaluate both your McKinsey Digital Assessment performance and your CV as part of the selection process. If you are aiming for a consulting role at McKinsey, it’s essential to ensure that both your resume and Solve Game score are strong—one cannot compensate for the other.

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