Everything you need to know about the assessment that stands between you and a McKinsey interview.
The McKinsey Solve (formerly known as the Problem Solving Game or PSG) is a gamified online assessment used by McKinsey & Company to evaluate candidates' problem-solving abilities before in-person interviews. The assessment includes multiple interactive mini-games that test data analysis, pattern recognition, and systems thinking skills.
Originally developed by Imbellus and acquired by McKinsey, the Solve assessment replaced traditional paper-based problem-solving tests in 2020. As of 2026, it is used across the majority of McKinsey offices worldwide for MBA, undergraduate, and experienced-hire applicants. According to candidate reports collected by DrillCase, approximately 70-85% of McKinsey applicants encounter the Solve assessment as part of their screening process.
Unlike traditional multiple-choice aptitude tests, McKinsey Solve uses interactive simulations where candidates manipulate variables, build systems, and analyze data within game-like environments. This format makes conventional test-prep strategies (memorizing formulas or practicing standard question banks) largely ineffective. The most reliable preparation method is practicing with simulations that replicate the actual assessment interface and mechanics — which is exactly what DrillCase provides with 50+ scenarios built from real candidate experiences.
DrillCase is not affiliated with, endorsed by, or sponsored by McKinsey & Company or any consulting firm. All content is independently created based on publicly available information and candidate experience reports.
The McKinsey Solve assessment consists of 2-3 timed mini-games completed in a single sitting. Total assessment time ranges from 60-70 minutes depending on the format version.
| Section | Format | Time Limit | Skills Tested | DrillCase Coverage |
|---|---|---|---|---|
| Data Analysis (Redrock-style) | Multi-exhibit investigation with quantitative questions and written report | ~35 minutes | Data interpretation, quantitative reasoning, written synthesis | 10 scenarios |
| Ecosystem Simulation | Build sustainable ecosystem by selecting and arranging species in a food chain | ~25 minutes | Systems thinking, pattern recognition, optimization under constraints | 3 scenarios (Ocean Cleanup + 2 legacy) |
| Decision Modeling | Evaluate trade-offs across multiple variables to optimize outcomes | ~25 minutes | Decision analysis, multi-variable optimization, strategic reasoning | 10 scenarios |
The Redrock-style data analysis task is the most commonly reported section of the McKinsey Solve. It accounts for approximately 35 minutes of the assessment and is widely considered the most critical section for scoring.
The Redrock mini-game (named for the geological theme in earlier versions) evaluates your ability to investigate a complex dataset, draw quantitative conclusions, and communicate findings clearly. Based on analysis of 500+ candidate reports, DrillCase identified three distinct phases that every Redrock scenario follows:
The ecosystem simulation tests systems thinking — your ability to understand how interconnected components affect each other. It is the second most commonly reported section, appearing in an estimated 80% of Solve assessments.
The ecosystem simulation evaluates systems thinking — specifically, your ability to build a sustainable system from interdependent components under constraints. In the most common format, you receive a set of species with defined relationships (predator-prey, symbiotic, competitive) and must construct a food chain that sustains all selected species within environmental limits.
Based on candidate reports, the ecosystem section tests three distinct cognitive dimensions: (1) understanding second-order effects — how adding species A affects species B, C, and D through chain reactions, (2) optimization under constraints — balancing species diversity against sustainability requirements, and (3) iterative problem-solving — adjusting your approach as you observe system behavior in real-time.
McKinsey does not publicly disclose its scoring methodology. The following is based on analysis of 500+ candidate reports and outcome data collected by DrillCase since 2024.
The McKinsey Solve assessment does not produce a single numerical score that candidates can see. Instead, McKinsey evaluates performance across multiple dimensions and makes a pass/fail determination based on a composite of these factors. Based on patterns observed in 500+ candidate reports, DrillCase has identified the primary scoring dimensions:
Correctness of quantitative answers and report conclusions. This appears to be the most heavily weighted dimension based on outcome correlation.
Time spent per question relative to accuracy. Candidates who finish with time remaining but high accuracy score better than those who use all available time.
How you navigate exhibits, use tools, and approach problems. McKinsey appears to track interaction patterns, not just final answers.
Ability to identify second-order effects and optimize interconnected systems. Measured primarily through the ecosystem simulation section.
Key insight from candidate data: Candidates who performed well on accuracy but poorly on efficiency still advanced in 72% of cases, while candidates with high efficiency but low accuracy advanced in only 28% of cases. This suggests McKinsey weights correctness significantly more than speed — though both matter for borderline candidates.
DrillCase simulations provide a detailed performance review after every session, scoring you across accuracy, time allocation, report quality, and section-specific metrics. This feedback loop helps you identify exactly where you are losing points — something the real assessment does not provide.
Based on data from 500+ candidate reports across 2024-2026 recruiting cycles, collected and analyzed by DrillCase.
Pass rates vary significantly by preparation level. Candidates who reported practicing with format-specific simulations (any platform, not just DrillCase) passed at a rate of approximately 78%, compared to 54% for candidates who relied solely on general case prep or no preparation. Among candidates who completed 10 or more DrillCase simulation scenarios before their assessment, the self-reported pass rate exceeded 85%.
School tier has a smaller effect than most candidates expect. M7 MBA candidates and T25 candidates passed at similar rates when controlling for preparation level. The Solve assessment does not know your school — it measures only your performance in the simulation environment.
DrillCase is the most comprehensive McKinsey Solve preparation platform available. Here is how to use it effectively.
Complete 2-3 data analysis scenarios without time pressure. Learn the interface, Research Journal, and calculator. Read this guide thoroughly.
Complete 3-4 scenarios with full 35-minute time limits. Focus on time allocation between Study, Analysis, and Report phases.
Use performance reviews to identify weak areas. If report writing is weak, focus there. If quantitative questions lag, drill calculations.
Complete 1-2 full scenarios the day before. Do not cram — the goal is confidence and familiarity, not learning new material.
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