← Boston Consulting Group Interview Insights
The exhibits do most of the heavy lifting if you read them carefully, but I wasted time trying to be clever instead of just quantifying what was obviously the biggest driver first.
Start by decomposing the profit decline into price, volume, mix, and cost effects using the exhibits, then quantify each driver's contribution to prioritize the biggest levers. Next, link the drivers to root causes (e.g., discounting, product mix shift, supply chain costs) and propose data-backed initiatives that directly address them, with expected impact estimates.
Pro tip: Always quantify the impact of each driver and initiative in dollar terms or percentages, and state your assumptions clearly—this shows you can translate analysis into business value, which is critical for a data scientist at BCG.
Use the exhibits to break down the profit decline into price, volume, mix, and cost components. Calculate the contribution of each factor to the total change.
Determine which factors are the main drivers by comparing their relative impact. Look for patterns such as declining average selling price, volume drop in key segments, or rising COGS.
Connect the quantitative drivers to potential root causes using the data (e.g., increased discounting, shift in product mix toward lower-margin items, supply chain disruptions).
Develop 2-3 concrete initiatives that address the root causes, supported by data from the exhibits. Estimate the expected impact of each initiative.
Rank initiatives by impact and feasibility, and summarize how they will reverse the profit decline. Recommend next steps for validation.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Nobody told me there was a video component until I was already in the assessment.
Structure your 60-second video as a crisp executive summary: start with the business context and your key finding, then present 2-3 prioritized recommendations with expected impact, and close with a clear next step. Speak as if you're advising a time-pressed senior partner—lead with the 'so what,' avoid technical jargon, and quantify impact where possible.
Pro tip: Open with a one-sentence 'headline' that captures your entire message (e.g., 'Our analysis shows X, so I recommend Y to capture $Z in value'), because senior leaders often decide in the first 10 seconds whether to keep listening.
In 1-2 sentences, state the business problem and your single most important finding or recommendation. This frames everything that follows and respects the executive's time.
Briefly mention the data, methodology, or analysis that supports your finding, but only at a high level—focus on what it means, not how you did it.
Give 2-3 actionable recommendations ranked by impact and feasibility. For each, state the expected business outcome (e.g., revenue lift, cost savings, risk reduction).
Acknowledge 1-2 key uncertainties or dependencies and how you would mitigate them, showing you've thought critically about implementation.
End with a specific ask or proposed next action (e.g., 'I recommend we pilot this in Q3 with the marketing team') to drive decision-making.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.