The Mckinsey & Company Problem Solving Game

The Mckinsey Problem Solving Game (PSG) is a simulation-based assessment tool designed to test a candidate’s ability to think critically and approach complex business problems. The game is used by Mckinsey & Company during their recruitment process to identify candidates who possess the necessary analytical and problem-solving skills to succeed in the industry.

HOW DOES THE PROBLEM SOLVING GAME WORK?

The 2026 iteration of the Mckinsey Problem Solving Game consists of 3 possible scenarios: Redrock Study Task, Sea Wolf Game , and the Sustainable Future Lab. Candidates invited to a 65-minute assessment will be given the Redrock Study Task (35 minutes), and the Sea Wolf Game (30 minutes) to solve. Candidates invited to a 65-minute assessment will be given the Redrock Study Task, Sea Wolf Game and Sustainable Future Lab.

Pre-February 2023, the PSG had 5 scenario games that candidates have reported as part of the PSG. Each candidate is given 2 out of 4 games to solve in a 70-minute time slot. The vast majority of candidates are given the Ecosystem Builder and then the Plant Defense scenarios to solve. There have been a small number of cases with candidates being given the Disease Diagnosis or Disaster Identification instead of the Plant Defense scenario.

McKinsey 2026 Problem Solving Game

Redrock Study Task

Redrock Study Task, often referred to as Redrock, has assumed the role of the second scenario within the McKinsey PSG, replacing Plant Defense. Although the precise scoring mechanism for the game is not explicitly detailed, we can infer, given its math-like format akin to the former McKinsey PST, that the final score is computed based on the number of correct answers. The Redrock study task involves comprehending a written report and solving mathematical problems using the information embedded in the report. It’s essential to acknowledge that due to Redrock’s similarity to the previous PST, there exists the potential for candidates to incur deductions for incorrect responses. Therefore, it’s imperative to ensure that every response you provide carries significance, as it might affect your score. Practice is key!

Sea Wolf (Ocean Cleanup)

The Sea Wolf is a new game introduced by McKinsey in spring 2024 as part of its official assessment, played after the Solve and Redrock tests, and contributing to the final score. In the game, players design microbial treatments for 3 ocean sites, aiming to match each site’s ideal characteristics with a combination of three selected microbes. The gameplay, repeated 3 times with different parameters, emphasizes strategic selection and alignment of traits, following a distinct logic from the Solve game despite some superficial similarities.

Sustainable Future Lab

The Sustainable Futures Lab is the newest addition to the McKinsey Solve assessment, introduced in March 2026 as the third module in the 85-minute version of the test. Unlike Red Rock and Sea Wolf — which evaluate analytical reasoning and optimisation — the SFL is a behavioral assessment that places you inside an environmental research team and asks you to make a series of connected decisions as a project unfolds under time pressure. McKinsey evaluates five core dimensions across 13 sequential questions: how you prioritise, how you make decisions when evidence is incomplete, how you interpret conflicting information, how you balance competing trade-offs, and how effectively you operate within a team. There are no calculations and no data models — only judgment, consistency, and the ability to think clearly under pressure. As of April 2026, the module is live for candidates receiving 85-minute Solve invitations across the US, UK, Germany, the Middle East, Southeast Asia, and Canada, with the global rollout continuing.

Ecosystem Scenario

The objective of the Ecosystem Builder game is to simulate the process of building and maintaining a sustainable ecosystem. The candidate must balance various factors, such as environmental conditions and predator-prey relationships, to ensure the long-term viability of the ecosystem. The game tests a candidate’s ability to process large volumes of data, think systemically, and make informed decisions based on incomplete or ambiguous information.

Legacy Games

Plant Defense:

The objective of the Plant Defense game is to simulate the process of defending a plant from pests and diseases. The candidate must identify the appropriate treatments and implement a strategy to protect the plant while minimizing the impact on the surrounding ecosystem. The game tests a candidate’s ability to think critically, analyze complex information, and make informed decisions under pressure.

Disease Diagnosis:

You are tasked with identifying and diagnosing an unknown disease that is affecting members of an animal population. Using a vast amount of data, you must determine the root cause of the issue and propose a treatment plan. Your diagnosis and treatment plan should be based on a comprehensive analysis of the available information.

Disaster Identification:

Your task is to identify the type of natural disaster that is causing the death of members of an animal population. Like the disease diagnosis scenario, you need to determine the specific nature of the disaster based on available information. Once you have diagnosed the problem, you must select a suitable relocation site where the animals can thrive. This decision must be based on a comprehensive analysis of a significant amount of data, much like in the initial stages of the Ecosystem Building scenario.