Advice for McKinsey SOLVE

Question

Hallo everyone,

I’m currently preparing for the McKinsey Solve and I’ve been trying to learn from different resources online, but I noticed there are quite a few conflicting opinions, so I wanted to ask for some clarification.

In the part of Redrock Study:

1. For the investigation phase, some people say we should capture almost everything in the research journal to play it safe, while others suggest being selective. What kind of information is actually worth prioritizing and noting down?

2. For the analysis and case part, are there any practice resources or platforms that felt genuinely close to the real Solve experience? Not necessarily exact replication, but similar in terms of thinking process and difficulty.

In the part of Sea Wolf:

1. During the site setup part (first part), how do you usually think about setting the characteristics or ranges for each attribute? I’m still trying to understand the logic behind choosing the numerical ranges.

And lastly, I’ve heard some candidates receive the Sustainable Future Lab version instead. What kind of thinking or skills does that assessment tend to evaluate?

Thank you

Answer 1

Hi,

Coming to your questions:

For the investigation phase in Redrock, I would definitely not recommend capturing everything in the research journal. If you try to save all the information “just in case,” it will actually hurt your performance because that is not really what the exercise is testing. The goal is to identify and prioritize only the information that is relevant to answering the question or testing the hypothesis. So focus on selective information gathering rather than exhaustive note-taking.

For the analysis/case part, there are several simulation platforms online that are directionally useful. The real Solve is not extremely difficult from a pure math perspective; the calculations are usually relatively straightforward, and the charts are not overly complex either. The key is more about:

prioritization;
speed;
logical thinking;
extracting insights efficiently.

So I would focus less on finding a “perfect replica” and more on getting comfortable with fast business reasoning under time pressure.

For Sea Wolf, in the site setup section, the general logic is usually to:

prioritize the attributes that are explicitly required;
and choose values that are the most extreme relative to the average.

And yes, nowadays almost all the candidates receive the Sustainable Future Lab simulation as well (if your email says that the test will be 85 minutes long, it means you will have to do the Sustainable Future Lab simulation). This part is less about technical problem solving and more about evaluating:

leadership style;
prioritization;
collaboration;
decision-making under ambiguity;
stakeholder management.

So the assessment becomes more behavioral/judgment-oriented compared to the classic Solve modules.

Let me know if you need more details on any specific section.

Franco

Answer 2

hi! For Redrock, write down only info that actually helps you solve the mystery, key facts, numbers, contradictions. Don’t copy everything; selective notes score better. For the analysis part, nothing perfectly replicates SOLVE, but CaseCoach drills, MConsultingPrep charts, and GMAT IR‑style logic train the same thinking. For Sea Wolf, choose ranges that feel realistic, create trade‑offs, and match the mission, think like an engineer making sensible choices, not guessing random numbers. The Sustainable Future Lab version tests systems thinking, trade‑offs, long‑ vs. short‑term impact, and prioritization.

Alessa

Answer 3

Quick takes on all four.

Redrock journal. Be selective, not exhaustive. Capture variable relationships, key quant data, and exceptions. Skip the flavour text. Use a structured format from the start.
Practice resources. Nothing perfectly replicates Solve. McKinsey's official practice problem, GMAT integrated reasoning, and exhibit reading drills come closest in spirit.
Seawolf ranges. Match the species survival window, think about interaction effects, and build in buffer for variability. Don't pick the exact theoretical optimum.
Sustainable Future Lab tests sustainability trade-offs, data interpretation, and judgment under uncertainty. Read climate and energy transition reports for context.

Good luck.