What Is the McKinsey Solve?
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.
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 20+ scenarios.
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.
McKinsey Solve Format Breakdown
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 |
60-70 min
Total assessment duration
2-3
Mini-games per assessment
No pause
Sections run continuously
1 attempt
Per recruiting cycle
Redrock Mini-Game Guide
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.
What Redrock Tests
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. Candidates describe three distinct phases in every Redrock scenario:
- Study Phase — You receive a research objective, background information, and multiple data exhibits (charts, tables, maps). You navigate between exhibits and save key data points to a Research Journal using a drag-to-save interface.
- Analysis Phase — Four quantitative questions test your interpretation of the data. You use a built-in calculator and can reference your Research Journal. Questions escalate in difficulty.
- Report Phase — Write a synthesis report and select a graph for your visual report. This tests executive communication under time pressure.
Strategy Tips from Candidate Reports
- Spend 40% of time on Study Phase. Candidates who rush through exhibits tend to struggle on the analysis questions.
- Use the Research Journal aggressively. Save 8-12 data points minimum. The journal is your only reference during analysis — anything not saved is effectively lost.
- Budget 5 minutes for the Report Phase. The written report is where most candidates lose points they did not expect to lose. A structured, concise report outperforms a detailed one that runs over time.
- Practice with the built-in calculator. Many candidates report the calculator feeling unfamiliar on test day. DrillCase simulations include the same on-screen calculator so you build muscle memory before the real assessment.
Ecosystem Simulation Guide
The ecosystem simulation tests systems thinking — your ability to understand how interconnected components affect each other. It is the second most commonly reported section.
What the Ecosystem Simulation Tests
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.
Strategy Tips
- Map relationships before placing species. Spend the first 3-5 minutes understanding the interaction diagram before you place anything.
- Start with foundational species. Build from producers (plants/algae) upward. Top-down construction is a common mistake.
- Monitor chain completeness. The validator shows broken links in real-time. Check it after every 2-3 placements rather than at the end.
- Do not over-optimize. A stable ecosystem with moderate diversity consistently scores better than an ambitious ecosystem that collapses. Prioritize stability over complexity.
McKinsey Solve Scoring
McKinsey does not publicly disclose its scoring methodology. The following reflects what candidates commonly report.
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. Candidate reports point to these primary scoring dimensions:
Accuracy
Correctness of quantitative answers and report conclusions. Candidates generally treat this as the most heavily weighted dimension.
Efficiency
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.
Process Quality
How you navigate exhibits, use tools, and approach problems. McKinsey appears to track interaction patterns, not just final answers.
Systems Thinking
Ability to identify second-order effects and optimize interconnected systems. Measured primarily through the ecosystem simulation section.
What candidates report: accuracy appears to matter more than speed, though both matter for borderline candidates. If you must choose, get the answer right.
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.
Pass Rates and What to Expect
McKinsey does not publish pass rates, and no reliable public figure exists. Here is what candidates consistently report.
20+
DrillCase Solve-style practice scenarios
10
Redrock-style data analysis scenarios
10
Sustainable Futures Lab scenarios
5-14 days
Typical completion window after receiving invite
Who Passes McKinsey Solve?
Candidates consistently say that practising in the specific format matters more than general case prep. The interface, the Research Journal and the timing are what catch people out, and those are learnable.
The Solve assessment does not know your school. It measures only your performance in the simulation environment.
Common Reasons Candidates Fail
- Running out of time. Time management is the most commonly reported failure reason. The 35-minute data analysis section feels short when encountering the format for the first time.
- Unfamiliar interface. Candidates who had never seen the Research Journal, built-in calculator, or multi-exhibit navigation lost critical minutes figuring out the tools.
- Weak report writing. Many candidates deprioritize the report phase, not realizing it carries significant scoring weight.
- Ecosystem section collapse. Building an unstable ecosystem that collapses is difficult to recover from within the time limit.
How to Prepare with DrillCase
Here is how to use DrillCase effectively.
Week 1
Learn the Format
Complete 2-3 data analysis scenarios without time pressure. Learn the interface, Research Journal, and calculator. Read this guide thoroughly.
Week 2
Practice Under Time Limits
Complete 3-4 scenarios with full 35-minute time limits. Focus on time allocation between Study, Analysis, and Report phases.
Week 3
Target Weaknesses
Use performance reviews to identify weak areas. If report writing is weak, focus there. If quantitative questions lag, drill calculations.
Test Day
Full Simulation Run
Complete 1-2 full scenarios the day before. Do not cram — the goal is confidence and familiarity, not learning new material.
20+ scenarios. Real time limits. Detailed scoring.
DrillCase VIP gives you lifetime access to every McKinsey Solve simulation scenario: 10 Redrock-style, 10 Sustainable Futures Lab, Sea Wolf and ecosystem challenges. One payment.
McKinsey Solve — Frequently Asked Questions
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