McKinsey Solve: Sea Wolf Game and Redrock Study Guide (2026)

McKinsey Solve is a game-based digital assessment taken by approximately 300,000 candidates per year, with only 20-30% advancing to first-round interviews. The most commonly reported format is a roughly 65-minute, two-module version (Redrock Study and Sea Wolf), but the exact timing and module mix are not fixed: candidate reports describe both this two-game version and a longer three-game variant of around 85 minutes, and McKinsey varies the assessment by role, level, and region. Most McKinsey Solve guides online are outdated: they still describe the Ecosystem Building game in isolation, which McKinsey phased out of the standard two-module rotation around 2023. If you're taking Solve in 2026, and especially if you're searching for "McKinsey Sea Wolf game" or "McKinsey Redrock," you should confirm your exact format in the invitation rather than assuming a single timing.

This guide covers the current formats, the dual scoring system most candidates don't know about, and a day-by-day prep plan built around the specific skills each module tests.

What are the McKinsey Solve games in 2026?

In 2026 the most common McKinsey Solve format is two games: Redrock Study, a roughly 35-minute data-interpretation module built on wildlife population data, and Sea Wolf, a roughly 30-minute ecosystem-optimization game. A longer three-game variant of around 85 minutes still appears for some roles and regions, typically combining Ecosystem Building, a Redrock-style data game (or Plant Defense), and the Sustainable Future Lab. The older standalone Ecosystem Building format that most outdated guides describe was phased out of the standard two-module rotation around 2023, so confirm your exact games from your invitation rather than assuming one fixed line-up.

What Is McKinsey Solve?

McKinsey Solve is an online, game-based assessment sent to candidates after resume screening and before live interviews, according to McKinsey's Solve page. It replaced the old Problem Solving Test (PST) starting around 2020, built on technology from Imbellus, a game-based assessment company McKinsey acquired, as described in McKinsey's game-based innovation lab announcement. McKinsey now administers Solve to approximately 300,000 early-career candidates per year globally.

Here's what you need to know upfront:

• Duration: typically around 65 minutes for the two-module version, with a longer three-game variant (about 85 minutes) reported in some markets. Treat the timer on your invite as the source of truth
• Format: game-based simulations, not traditional multiple-choice. The module count varies (most commonly two: Redrock Study and Sea Wolf; sometimes three)
• When: after resume screening, before first-round case interviews
• Retake policy: one attempt per application cycle, with a 12-24 month waiting period before you can retake
• Pass-through rate: roughly 20-30% of candidates, based on community reports on Wall Street Oasis, PrepLounge forums, and MConsultingPrep's pass-rate analysis
• Result usage: McKinsey evaluates Solve results alongside your resume to decide who gets interviews, not a standalone pass/fail gate

Once Solve prep is stable, move the same structured reasoning into live McKinsey practice cases so assessment practice does not crowd out the interview itself.

McKinsey Redrock and Sea Wolf: The Two Modules

Framework

1. 01

   Module 1: Redrock Study

   Data interpretation mini-cases (~35 minutes)

2. 02

   Module 2: Sea Wolf

   Ecosystem management simulation (~30 minutes)

Module 1: McKinsey Redrock Study (~35 minutes)

Redrock Study is the data-interpretation module. It places you in the role of a researcher analyzing wildlife population data and tests percentages, weighted averages, growth rates, and chart selection (roughly 60-70% of questions involve calculations). For the full module breakdown including the Investigation-Analysis-Report flow, worked math examples, and mini-case strategy, see our dedicated McKinsey Redrock Study guide.

Redrock presents you with a series of research scenarios. Each scenario contains a mix of data: charts, tables, written findings, and methodology descriptions. For each scenario, you answer questions about the data: identify patterns, assess evidence quality, and evaluate whether conclusions are supported.

Think of it as a scientific research evaluation exercise. You're not conducting the research. You're judging it. Typical question formats include:

• "Which conclusion is best supported by the data?"
• "What is the most significant limitation of this study?"
• "Which data point most contradicts the researcher's finding?"
• "Based on the evidence, which recommendation is strongest?"

You'll face 5-7 mini-cases during the module. Each one is self-contained with its own dataset and questions. The difficulty increases as you progress, and later scenarios involve more variables, messier data, and subtler distinctions between answer choices.

Module 2: McKinsey Sea Wolf Game (~30 minutes)

Sea Wolf is an ecosystem management simulation set in an ocean environment. You're given information about different ocean sites, each with specific conditions like water temperature, depth, current speed, and nutrient concentration. Your job: select the right combination of marine species for each site based on how species characteristics match site conditions.

This is fundamentally a pattern-matching and optimization problem. Each species has defined traits: preferred temperature range, depth tolerance, nutrient requirements, predator/prey relationships. Each site has a set of environmental parameters. Your task is to match species to sites so the ecosystem functions.

The module runs across multiple rounds with increasing complexity:

• Early rounds: Fewer species, fewer sites, clear matches between traits and conditions
• Middle rounds: More species options, overlapping trait profiles, and sites with mixed conditions
• Late rounds: Species interactions matter, and some species compete for resources, others have symbiotic relationships. Placing two competing species in the same site will hurt your score

Does McKinsey Solve always use the same two games?

No. The two-module version (Redrock Study plus Sea Wolf) is the most commonly reported format, but it is not the only one. Candidate reports on Wall Street Oasis and PrepLounge describe a longer three-game variant that runs closer to 85 minutes, and the specific games, total time, and even whether you see a video or audio check vary by role, seniority, and region. The safest move is to read your invitation email carefully: it usually states the time limit, and the in-test instructions screen confirms the modules before you start.

The 85-minute three-game variant

Some candidates, especially in certain offices and for some roles, report a longer assessment built from three games rather than two. The combination people describe most often is Ecosystem Building, a Redrock-style data game (or, in older sittings, Plant Defense), and the Sustainable Future Lab. Because McKinsey rotates and localizes the assessment, do not assume you will get any specific combination. Use the list below to recognize each game if it appears, not as a guaranteed line-up.

• Ecosystem Building. You place a set of species into a location so the food chain stays stable. Each species has rules about what it eats, where it lives, and which conditions (depth, temperature, terrain) it tolerates. The core skill is building a self-sustaining chain where every species has a viable food source and no condition is violated. McKinsey itself has described this "build a reef, save a species" design. Treat it as a constraint-satisfaction problem: satisfy every species' requirements at once rather than optimizing any single trait.
• Redrock or Plant Defense. The middle game is most often the Redrock data-interpretation flow covered above. In older or alternate sittings, candidates instead report Plant Defense, where you defend a plant against waves of invaders by placing defenses with limited resources and reacting as conditions change. If you get Redrock, lean on clean exhibit math and evidence checks. If you get Plant Defense, think in terms of resource allocation under pressure and adapting your placements each round.
• The Sustainable Future Lab. This is a newer scenario several candidates describe as a sustainability or city-planning style optimization: you balance competing objectives (for example growth, cost, and environmental impact) under constraints and tradeoffs, with no single "perfect" answer. The skill it rewards is structured tradeoff thinking, choosing the option that best balances the stated goals rather than maximizing one metric at the expense of the others.

Per-game benchmarks and pacing

McKinsey does not publish scoring thresholds for any game, so treat the figures below as time-budgeting guidance drawn from candidate reports, not official cutoffs. Based on practice on Road to Offer, the candidates who pace well tend to read fully before acting and reserve time to review the final round rather than rushing it.

• Redrock Study (~35 min): budget 5-7 minutes per mini-case across the 5-7 scenarios, and flag a hard stop near 8 minutes so a single case cannot eat the time you need for the last two or three.
• Sea Wolf (~30 min): the difficulty climbs each round, so spend a little less time on the early, clear-cut placements and bank that time for the later rounds where species interactions and resource competition decide your score.
• Ecosystem Building: there is no fixed species count to memorize, so check every species' food source and condition rules before placing anything. An unsustainable chain (a species with no viable food, or one placed in a condition it cannot tolerate) is the common failure, not slow play.
• Plant Defense: treat your resources as a budget. Place defenses where the pattern of incoming waves is densest, and adjust each round rather than committing everything early.
• Sustainable Future Lab: there is no single correct answer, so do not chase a perfect score on one objective. Pick the configuration that best balances the stated goals within the constraints, then move on.

The Dual Scoring System

This is the piece most candidates miss, and it changes how you should approach every minute of the assessment.

Product score measures whether you selected correct answers. Did you identify the right patterns? Did you place the right species? This is straightforward accuracy.

Process score measures your approach. McKinsey's platform tracks behavioral signals throughout both modules:

• Reading time: Do you spend time reading scenarios before answering, or do you jump straight to questions?
• Navigation patterns: Do you review all available information, or do you skip panels?
• Revision behavior: Do you change answers after reviewing additional data, or do you commit without checking?
• Decision consistency: Does your clicking pattern suggest systematic analysis or random guessing?
• Pacing: Do you spend proportional time across questions, or do you rush through some and stall on others?

Both scores contribute to your overall evaluation. A candidate who gets 80% of answers correct through careful analysis may outscore a candidate who gets 85% correct through rapid guessing, because the process score penalizes erratic behavior.

What Happened to the Old Games?

If you've been researching Solve, you may have encountered advice about "building an ecosystem with 8 species" or "protecting a plant from predators." That information is outdated. Here's the timeline:

• 2020: McKinsey replaces the Problem Solving Test (PST) with Solve, initially featuring Ecosystem Building and Plant Defense modules (per McKinsey's recruiting blog)
• 2021-2023: Format evolves, with Redrock Study and Sea Wolf gradually replacing older modules
• 2023-2024: Ecosystem Building (the food chain game) and Plant Defense dropped out of the standard two-module rotation across most offices
• 2025-2026: Redrock Study and Sea Wolf are the most common modules globally, while a longer three-game variant (which can revive Ecosystem Building or Plant Defense alongside the Sustainable Future Lab) still appears for some roles and regions

If a guide describes Ecosystem Building or Plant Defense as the only games you will see, it is outdated, because the default two-module format does not include them. That said, those games are not extinct: they resurface in the three-game variant. The practical takeaway is to confirm your own format from the invitation, then study the games you will actually face. The underlying cognitive skills overlap across all of them (pattern recognition, systems thinking, tradeoff analysis), but the specific strategies, interfaces, and time-management approaches differ game to game.

10-Day Preparation Plan

Generic advice like "practice logic puzzles" wastes your limited prep time. Each day below targets the specific skills Redrock Study and Sea Wolf actually test.

Days 1-2: Understand the Format

• Read this guide thoroughly and take notes on the question types in each module
• Watch 2-3 YouTube walkthroughs of the current Solve format (search "McKinsey Solve 2025 2026 walkthrough", filter for videos showing Redrock Study and Sea Wolf, not the old Ecosystem Building)
• Read 5-10 candidate experience posts on Wall Street Oasis and PrepLounge to understand what the real test interface looks like
• Write down the specific skills each module targets: data interpretation for Redrock, pattern-matching and optimization for Sea Wolf

Days 3-5: Build Data Interpretation Skills (for Redrock Study)

Redrock Study tests your ability to evaluate research evidence. The fastest way to build this skill:

• Practice reading scientific study summaries and identifying flaws. Khan Academy's statistics and probability unit is free and directly relevant, covering percentages, mean/median/mode, and probability, the exact math Redrock requires
• Do 15-20 GMAT-style data sufficiency problems per day. Focus on: identifying sample size issues, distinguishing correlation from causation, and reading charts with precision
• Practice evaluating conclusions against evidence: given a chart and a written claim, determine whether the chart supports, contradicts, or is irrelevant to that claim
• Read two research abstracts per day (from any field) and write one sentence on the strongest limitation of each study

Days 6-8: Build Systems Thinking Skills (for Sea Wolf)

Sea Wolf tests whether you can match multiple variables simultaneously under constraints. Train this:

• Practice constraint satisfaction problems: "If species X needs warm water and high nutrients, and species Y needs cold water and low nutrients, which site accommodates both?"
• Play optimization games that involve multi-variable matching. Sudoku variants, logic grid puzzles, and resource allocation exercises build the right mental patterns
• Practice if-then reasoning chains: "If I place species A here, it competes with species B. If I move species B to site 3, it conflicts with the temperature range. So species A must go to site 2."
• Focus on systematic approaches: practice completing one site fully before moving to the next, checking your work, then proceeding

Days 9-10: Simulate Test Conditions

• Find a quiet space with no distractions. Close all other browser tabs and applications. Set a timer matching your invite (around 65 minutes for the two-module version, or about 85 minutes if you have the three-game variant)
• Run through a practice session focusing on process: read before answering, work systematically, don't rush
• After your simulation, review: Where did you spend too much time? Where did you rush? Did you read all available information before answering?
• Adjust your pacing strategy based on what you learned. A second timed simulation on Day 10 should feel noticeably smoother

Pre-Assessment Checklist

Complete this checklist before starting your Solve session. Once you begin, you cannot pause or restart.

Checklist

Execution checklist

• Stable internet connection and quiet environment

  Technical issues or interruptions can invalidate your attempt

• Laptop or desktop computer (not phone or tablet)

  The interface is designed for a full screen with mouse navigation

• All other browser tabs and applications closed

  Behavioral tracking can detect multitasking and tab-switching

• 90+ uninterrupted minutes blocked off

  Around 65 minutes for the two-module version (about 85 for the three-game variant) plus buffer for loading, instructions, and transitions

• No external tools: calculator, notes, or reference materials

  Use only what the Solve platform provides

• Completed at least one full practice run under timed conditions

  Familiarity with format and pacing reduces test-day anxiety

• Webcam and microphone permissions ready if prompted

  Some sessions require identity verification or proctoring

• Read the full instructions page before clicking 'Start'

  The instructions screen contains module-specific guidance you won't see again

Five Mistakes That Tank Solve Scores

These aren't hypothetical. They come from candidate reports on Wall Street Oasis and PrepLounge forums, patterns from candidates who felt confident during the assessment but received rejections afterward.

1. Clicking answers before reading the full scenario. In Redrock Study, the first answer option often looks plausible in isolation. But the correct answer depends on the full data context. Candidates who jump to questions before reading the scenario consistently pick the "obvious" wrong answer. The process score also penalizes this. The platform tracks how long you spend on the information panels before selecting an answer.

2. Matching species on a single trait in Sea Wolf. A species that prefers cold water seems like a fit for a cold-water site. But if that species also needs shallow depth and high nutrients, and the site is deep with low nutrients, it's a bad placement. Always check every trait against every site parameter. One-variable matching is the most common Sea Wolf error.

3. Using external tools. Opening a calculator app, taking a screenshot to study offline, or switching to a browser tab to look something up, all of these are detectable. Management Consulted reports that McKinsey's platform tracks focus state and application switching. Don't risk it.

4. Treating process score as secondary. Many candidates focus entirely on getting right answers and ignore how they arrive at them. But the process score captures whether you're engaging with information systematically. Skipping data panels, clicking rapidly between questions, and never revisiting answers all generate negative behavioral signals, even if your accuracy is high.

5. Running out of time on the last 2-3 scenarios. Poor pacing in Redrock Study means the final mini-cases get rushed or skipped entirely. Unanswered questions are worse than imperfect answers. Track your time: if you've spent more than 7 minutes on a single scenario and still aren't sure, pick your best option and move forward.

Bridge from Solve to Case Interviews

Passing Solve gets you to the interview round. It doesn't get you the offer. Once you clear the digital assessment, you'll face McKinsey's interviewer-led case interviews and Personal Experience Interview (PEI).

The good news: the analytical skills you build for Solve, data interpretation, structured reasoning, pattern recognition, transfer directly to case performance. The transition is about applying those skills in a live conversation rather than a digital interface.

Start your case prep in parallel with Solve prep, not after it:

• How to practice case interviews, build the live format skill set
• Free McKinsey interview prep tools, collect Solve, PEI, case, and math resources in one path
• McKinsey PEI guide, prepare the behavioral interview that accompanies every McKinsey case round
• Mental math for case interviews, the quantitative fluency Solve doesn't directly test, but McKinsey cases demand
• Consulting interview prep timeline, map out your full preparation schedule across Solve, case, and fit prep

Interactive Solve Prep Drills

Sources and Further Reading (checked June 17, 2026)

• McKinsey interviewing resources: https://www.mckinsey.com/careers/interviewing
• McKinsey Imbellus acquisition announcement: https://www.mckinsey.com/about-us/new-at-mckinsey-blog/from-apprenticeship-in-space-to-selecting-microbes-meet-mckinseys-game-based-innovation-lab
• Wall Street Oasis McKinsey Solve discussion threads: https://www.wallstreetoasis.com/forum/consulting/mckinsey-solve-game-2024
• PrepLounge McKinsey Solve forum: https://www.preplounge.com/en/consulting-forum/mckinsey-problem-solving-game-15229
• Management Consulted McKinsey digital assessment guide: https://managementconsulted.com/mckinsey-digital-assessment/
• Khan Academy statistics and probability: https://www.khanacademy.org/math/statistics-probability
• CaseInterview.com McKinsey prep resources: https://www.caseinterview.com/
• McKinsey careers students page: https://www.mckinsey.com/careers/students

Related Guides

• McKinsey Redrock Study Guide
• McKinsey Sea Wolf Guide
• McKinsey case interview guide
• McKinsey PEI Guide
• BCG Online Case (Casey) Guide: BCG's equivalent online assessment screen
• Consulting aptitude test overview: how Solve compares to BCG, Bain, and Big 4 assessments