Most common Tech Private Equity mistakes
Common mistakes in tech PE?
Modelling ARR/customer cubes/software and tech LBOs
What are some good ways people check efficiently as they go?
Common mistakes in tech PE?
Modelling ARR/customer cubes/software and tech LBOs
What are some good ways people check efficiently as they go?
| +72 | Does anyone believe their firm has a true competitive edge | 36 | 1d |
| +42 | Lateraling at senior associate / VP level | 11 | 3d |
| +33 | Do you regret doing PE? | 20 | 13h |
| +26 | Ares buying LGP...now what? | 8 | 18h |
| +26 | Imposter Syndrome: PE to Publics | 4 | 1d |
| +19 | Do PE VPs Always Have An Associate Under Them? | 12 | 15h |
| +17 | Francisco Partners Fundraise | 6 | 1d |
| +16 | GTCR vs BDT MSD vs MDP | 15 | 3m |
| +14 | Hours at MF Infra Funds in London | 1 | 1d |
| +14 | Setting the right LBO entry multiple without information | 3 | 4d |
Career Resources
Based on the most helpful WSO content, here are some insights on common mistakes in tech private equity and efficient ways to check your work:
Common Mistakes in Tech Private Equity:
Careless Errors:
Lack of Attention to Detail:
Inefficient Processes:
Efficient Ways to Check Work:
Use Checklists:
Print and Review:
Cross-Referencing:
Use Sums and Averages:
Stay Organized:
Visual and Spatial Intelligence:
By implementing these strategies, you can significantly reduce errors and improve the quality of your work in tech private equity.
Sources: Ways of Underperformance - and how to avoid them (Part 1), Practicing attention to detail, How to train attention to detail, https://www.wallstreetoasis.com/forum/investment-banking/advice-on-improving-terrible-attention-to-detail?customgpt=1, How to Escape Bottom Bucket
Bump
By having checks for all your analyses that tie back to the original cube... this should've been taught to you during training lol. Go and grab a sr. asso or someone if you're having trouble. These are fundamentals, always better to check with someone than to make a mistake. It's not banking anymore.
What kind of high level data is a must when tying back to the cube? Things you always triple check?
Bump
Over optimism resulting in self-justified growth targets that support paying a higher price. Even in this market a lot of folks do not seem to have fucking learned which is annoying for disciplined investors during bids but will come back to bite them come exit time. Don't try to rationalize the model backward from price.
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