The McKinsey Ecosystem game: complete strategy guide

Overview & objective

In the Ecosystem module you're given a pool of species — producers (plants / algae) and animals — and environmental data for each. Your job is to (1) pick a starting location and a set of producers, (2) build a matrix of species and predator–prey relationships, and (3) derive the longest viable food chain (up to 8 species) that maximizes total calories flowing through the chain.

Each species has:

• Calories provided — energy available to predators.
• Calories required — energy the species itself needs to survive (0 for producers).
• Depth/elevation range and temperature range — environmental constraints (producers only).

A predator can only eat a prey if it's listed as able to do so. The calories a prey provides minus the calories the predator requires gives the "net" energy available to the next level up.

Step 1 — Pick the optimal producers

Producers are grouped by their environmental range (depth/elevation + temperature). The optimal starting location is the environmental cell shared by the most producers that maximizes total calories provided. In practice: group producers with identical ranges, sum the calories in each group, and pick the group with the highest total.

Step 2 — Build the species matrix

With producers locked in, you add the remaining animal species. Each animal has calories provided and calories required. You then mark which species eat which in a predator–prey matrix. A "×" in cell (row, column) means the row species eats the column species.

Constraints:

• No species eats itself.
• A predator must be able to get enough net calories from its prey to survive.

Step 3 — Derive the optimum food chain

The optimum food chain is up to 8 species long, with producers at the base. The algorithm sorts species by calories provided (descending), greedily places producers, then for each predator selects the highest-calorie available prey whose remaining calories (after subtracting the predator's requirement) are still non-negative. If the best prey can't sustain the predator, it falls back to the next-best available prey.

How you're scored

• Chain length — longer is better (max 8).
• Total calories in the chain — higher is better.
• Producer set quality — did you pick the highest-calorie group?
• Move efficiency — how quickly you completed the steps.

Optimal strategy

1. Always group producers by identical environment. Don't mix depth/temperature ranges — it dilutes your calorie total.
2. Pick the group with the highest calorie sum, not the single highest-calorie producer.
3. In the matrix, be comprehensive. Mark every true predator–prey relationship you can find — the algorithm can't use a relationship you didn't enter.
4. Work fast. The selection algorithm itself is deterministic; the score-killer is time spent second-guessing.
5. Balance accuracy and speed across modules. Ecosystem rewards calculation discipline; Sea Wolf rewards fast repeated decisions, which you can practise in the Sea Wolf Simulation Redrock Simulation Sustainable Futures Lab.