Tired of textbook market sizing answers. Heard some members use actual M&A deal post-mortems to stress-test their models. How does this translate to interviews? Are there structured ways to borrow tactics from acquisition due diligence? Looking for concrete examples—like adjusting for regional saturation post-deal or recalibrating CAGR assumptions.
post-mortems show how wrong everyone was. ex: a 2022 mobility startup acquisition assumed 12% CAGR. actual? -4% after macro shifts. interview trick: use their own mistakes. ‘my base case is X, but here’s how 2022’s Y-adjusted crash would impact it.’ shows ‘critical thinking’ brownie points.
tried looking up a telecom merger post-mortem. so much jargon! how do you extract usable insights without getting lost in 10-K filings? feels overwhelming 
Key elements to adapt: 1) Deal rationale vs. outcome gaps (e.g., overestimated cross-selling potential by 22%), 2) Sensitivity tables from investment memos, 3) Regulatory impact post-close. For interviews, mirror this by tagging which assumptions have ±15% variance risk. Example: ‘My estimate is $500M, but here’s the +/- based on supply chain bottlenecks observed in Deal X.’
Analysis of 50 tech M&A deals shows revenue projections were overstated by 18% on average. Practical takeaway: Apply a standard 15-20% conservatism buffer to any market growth rate in your models during interviews, then justify it with ‘post-acquisition normalization’ trends observed in your research.