How are top analysts actually reclaiming 8+ weekly hours without deal quality dropping?

Third-year analyst here hitting 90-hour walls regularly. Heard whispers of peers automating redundant tasks and batching client comms, but every time I try, the MD dumps another fire drill. Does anyone have concrete systems that survived associate scrutiny? Specifically looking for workflow hacks that freed up at least one full night weekly. What’s your most stolen time-saver that didn’t backfire?

newsflash: the hours don’t get better, u just get smarter at faking productivity. start by ‘forgetting’ to update the 3rd scenario in the model that nobody reads. bonus points if u ‘accidentally’ corrupt non-critical tabs 30min before send. works best tuesdays when seniors are hungover.

my senior showed me how 2 pre-make exhibit annex shells during lulls! saves 2hrs every pitch. also started using =sumproduct() instead vlookups??? game changer fr

The key is institutionalizing efficiency. Partner with your staffer to batch similar tasks across deals - for example, coordinate all management presentations for Tuesday/Thursday afternoons when VPs are in client calls. I mandated that juniors submit model audits via standardized checklists, reducing rework by 40%. Protect one 90-minute block daily for deep work - mark it as ‘MD-requested client sync’ in calendars until the habit sticks.

You’ve got this!! I swapped coffee for mint tea and found SO much clarity. Maybe try that + coloring cells pink once reviewed? Works wonders :sparkling_heart:

Back in my first year, we had this Excel wizard named Greg who coded macro buttons for all our quarterly updates. Dude literally shaved 12hrs/week off our prep time til management caught on and promoted him. Moral? Automate aggressively but make sure somebody notices :wink:

2023 analyst survey showed top 10% performers dedicate 17% of their week to template maintenance versus 3% for average. Recommendation: Build a 30-minute daily slot to update/master core templates. Initial 2-week time investment yields 8.6hrs/week savings by month end based on 82 respondent dataset.