Gamified assessment
The McKinsey Solve Game
McKinsey Solve is an immersive, non-traditional digital assessment designed to evaluate how you process information, manage complex data systems, and make critical decisions under pressure. Developed alongside Imbellus, this gamified test bypasses corporate case studies to evaluate your raw intellectual capacity. This definitive guide breaks down the underlying game logic, explores the core modules, and provides structured strategies to help you pass.
In short
McKinsey Solve is a 70-minute gamified assessment that uses ecological simulations to evaluate your cognitive abilities. Candidates typically complete two core modules: the Ecosystem creation game and the Redrock case study investigation. To pass, you must understand that the system tracks your entire behavioral process, not just your final answers. Success requires building a meticulous execution trail by verifying every single data constraint, executing rapid and precise mental calculations, and adapting your strategy cleanly when new information layers are introduced, rather than relying on rapid clicking or erratic trial-and-error methods.
The basics
What it is
McKinsey Solve, originally known as the Problem Solving Game or Imbellus assessment, is a mandatory digital gatekeeper that candidates encounter early in the recruitment pipeline. Whether you are submitting a CV or resume for an undergraduate graduate scheme in London or a summer associate role in New York, passing this test is required before securing an interview. The simulation completely strips away corporate jargon and financial spreadsheets, placing you instead in complex natural environments where you must manage delicate biological networks or investigate wildlife phenomena.
The assessment is administered globally and remains completely identical across all international offices. A candidate applying to a UK assessment centre faces the exact same digital interface, scoring engine, and cognitive challenges as an applicant attending a US superday. Because the game requires absolutely no prior business knowledge, economic training, or consulting framework familiarity, it levels the playing field for applicants from non-traditional backgrounds, ensuring raw analytical and problem-solving capability is measured uniformly worldwide.
What makes Solve distinctly challenging is its proprietary behavioral tracking engine. The platform does not simply grade your final output; it monitors your entire decision-making process. Every mouse click, data panel expansion, species selection, and calculation interval is logged to evaluate how you systematically gather information and handle trade-offs under tight time constraints. This dual scoring of product and process makes the assessment exceptionally difficult to game through memorisation, rendering expensive prep courses that cost upwards of 200 GBP / 250 USD entirely unnecessary if you understand the core mechanics.
Intervyo is an independent preparation platform dedicated to helping candidates navigate complex recruitment processes. We are not affiliated with, endorsed by, or partnered with McKinsey, Imbellus, or any test publisher. All preparation materials, practice frameworks, and strategy guides provided by Intervyo are completely original recreations designed to teach foundational cognitive skills, rather than direct copies or reproductions of live assessment software.
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What it measures
The dimensions under test
Critical reasoning
The game evaluates your ability to analyse dense, unfamiliar datasets and extract the underlying rules governing a system, allowing you to isolate relevant variables from distracting noise.
Decision-making under uncertainty
The assessment monitors whether you can calculate probabilities rationally, balance conflicting environmental trade-offs, and execute an optimal strategy when there is no single perfect answer available.
Comfort with data and numeracy
The modules require rapid interpretation of charts, tables, and mathematical equations, tracking your quantitative fluency as you calculate population dynamics and consumption ratios under tight countdown timers.
Systematic and metacognitive process
The algorithm tracks the order and logic of your actions, rewarding candidates who systematically test hypotheses while penalising chaotic, trial-and-error behaviours that suggest a lack of structural discipline.
Attention to rules and constraints
Success depends on your capacity to retain, cross-reference, and satisfy every individual operational rule simultaneously, as violating even a minor parameter will cause the simulated ecosystem to fail.
Situational awareness and adaptation
The simulation is dynamic and reacts to your inputs in real time, measuring how efficiently you identify when your initial assumptions are invalidated by new environmental changes.
The format
What to expect
See it in action
A worked example
To understand how the game evaluates your procedural discipline, let us examine an original, end-to-end recreation of a single critical choice within an Ecosystem scenario.
- 01
Parsing the species constraints
You open a predatory species card to read its strict operational parameters: a required depth band of 15 to 25 metres, a water temperature range of 12 to 18 degrees Celsius, and a mandatory dietary intake of at least 400 calories derived exclusively from herbivorous crustaceans.
- 02
Cross-referencing environmental data
You systematically open the current location metrics panel to cross-reference these criteria against your active zone, noting the local depth is 20 metres and the baseline temperature is 14 degrees Celsius, confirming the physical climate is perfect before auditing the available food supply.
- 03
Eliminating the near-miss candidate
You examine a highly attractive candidate species that perfectly matches the depth and temperature requirements and provides a massive caloric return, but close inspection reveals it consumes a specific micro-algae that is entirely absent from this zone, leading you to deliberately reject it.
- 04
Executing the justifiable placement
You locate an alternative species that yields fewer immediate calories but matches all environmental constraints and feeds reliably on the zone's actual inhabitants, then click to place it into the ecosystem slot cleanly, creating a logical, rule-compliant choice.
The takeaway
This methodical process demonstrates that the assessment actively punishes hasty, superficial selections while rewarding candidates who establish an explicit, verifiable rationale for every decision.
The scoring
How it is marked
McKinsey does not publish raw passing cut-offs or comparative percentiles for the Solve assessment. Instead, the scoring engine synthesises your final answers with your behavioral process data to categorise your performance into distinct operational tiers that feed into your broader application. Your final score profile is automatically transmitted to the recruiting team alongside your CV or resume, with overall application outcomes typically communicated within a couple of weeks.
Clearly strong
Candidates in this tier achieve highly optimised, fully accurate outcomes across all modules while maintaining an exceptionally clean execution trail characterized by low redundant clicking, logical data sequencing, and perfect adherence to constraints.
Solid
This tier represents candidates who successfully solve the core problems and submit viable final answers, even if their background process was slightly less efficient, showing minor navigation errors but maintaining structurally sound outputs.
Borderline
Candidates here often reach the correct final answers but do so through an erratic process that looks like luck or brute-force trial and error, or they demonstrate excellent process data that is undone by simple calculation mistakes.
Below the bar
This category occurs when a candidate fails to submit completed answers within the time limit or violates fundamental structural rules, with background data showing a combination of disorganised exploration and panic-driven clicking.
The variants
Versions you might be sent
The Ecosystem simulation
The primary anchor module requires you to select a natural location, such as a mountain lake or a coral reef, and populate it with a stable, self-sustaining food web by balancing caloric inputs.
The Redrock case study
This module presents a series of research dossiers, data tables, and field journals tracking a specific wildlife population crisis, requiring you to perform deep quantitative analysis to find the root cause.
Plant Defense module
A fast-paced, tactical scenario reminiscent of classic tower-defence games where you must protect a native plant species from waves of invasive pests by placing defensive barriers on a grid map.
Disaster and migration scenarios
Regional variations occasionally introduce localized modules focusing on managing natural disasters or guiding animal migration routes through fragmented landscapes to test your dynamic resource allocation skills.
Legacy problem-solving tests
Prior to the rollout of the gamified Solve platform, McKinsey utilised the paper-based Problem Solving Test (PST), which focused purely on manual business maths and document reading rather than real-time behavioral simulation.
Who uses it
Firms that screen with this test
Each links to a dedicated firm guide: the application process, the interview stages, and what they look for.
The prep
How to prepare
Master the fundamental interface mechanics
Spend time understanding how gamified simulation grids, data overlays, and drop-down menus operate so you do not waste precious seconds fighting the user interface during the live test, keeping your mechanical execution entirely automatic.
Sharpen your data interpretation and numeracy
Dedicate preparation time to practicing rapid data extraction from complex charts, multi-axis graphs, and dense matrices, alongside fast mental arithmetic, to prevent the Redrock case study clock from becoming an insurmountable obstacle.
Audit every single constraint systematically
Train yourself to read species cards and scenario rules with absolute precision, treating every listed parameter as an unbreakable law, and create a mental checklist for every choice before committing to an action.
Maintain a deliberate and structured process
Avoid the temptation to click randomly or experiment rapidly within the active simulation window, ensuring that every action serves as a purposeful, logical entry in your background data trail to demonstrate structured analytical thinking.
How not to fail
Common failure modes
The specific ways candidates lose marks on this test. None of these need talent to avoid, only awareness.
- 01Overlooking a minor ecosystem parameter. Failing to double-check a single constraint, such as a narrow pH tolerance, which instantly triggers a hidden chain reaction that collapses your entire food web design.
- 02Erratic clicking and random experimentation. Attempting to solve the simulation via rapid trial and error, which floods the backend tracking software with chaotic data points and signals a lack of methodology.
- 03Slow mental arithmetic on Redrock. Spending too many valuable minutes manually calculating basic math operations across large data tables, causing you to fall badly behind the module's strict progression timeline.
- 04Freezing when the scenario shifts. Panicking and losing execution momentum when the game introduces unexpected environmental data layers or updates constraints mid-way through the assessment, destroying your established pacing.
- 05Skimming the un-timed tutorial window. Rushing through the introductory walk-through without fully understanding the navigation tools, leaving you to waste precious timed minutes figuring out how to interact with the game board.
- 06Running out of time on final inputs. Mismanaging your internal clock during the final stages of a module, leaving several critical final decisions entirely blank or unsubmitted as the countdown reaches zero.
On the day
What strong candidates do
The habits that separate high scorers, most of them decided before the timer even starts.
Rehearsing mechanical layout interactions
Navigating menus fluidly, expanding data panels with precise intent, and closing windows cleanly to maintain a highly efficient, professional digital process footprint.
Executing rapid and clean numeracy
Performing calculations on a notepad with fast, accurate precision, allowing them to interpret complex wildlife datasets without experiencing cognitive fatigue or time stress.
Using a strict one-constraint checking routine
Evaluating candidate options against a rigid, sequential rule list, ensuring no species is ever placed into the simulation without passing every single environmental filter first.
Making deliberate and highly justifiable moves
Pausing to think before executing an action, resulting in a sparse, purposeful click history that demonstrates absolute certainty and analytical control to the scoring algorithm.
Maintaining steady pacing per module timer
Allocating their time perfectly across the reading, calculation, and execution phases, ensuring they finish the final submissions comfortably with minutes left to spare.
Adapting calmly to mid-game disruptions
Treating new data points as logical updates to their existing equations, pivoting their strategy smoothly without breaking their methodical execution rhythm.
Practise on the real format
Reading about the test is not practising it.
Intervyo recreates McKinsey Solve in its real format, timed and scored, with instant feedback so the structure is familiar before it counts. Start free, no card required.
FAQ
Common questions
The total active testing time is typically around 70 minutes. Each individual game within the assessment operates on its own dedicated timer, which runs continuously once that specific module begins. You are provided with un-timed tutorials before each section, so you should budget approximately 90 minutes of total uninterrupted time to account for setup and reading instructions.
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