i left consulting three years ago and spent the next 18 months intentionally talking to people who’d left before me — some went into faang strategy teams, a few joined seed-stage startups, others moved to private equity, and a handful stayed in corporate strategy at incumbents. what surprised me was how concrete the trade-offs were once you stop treating each option as a label and listen to the project-level stories.
for example, the folks who moved into tech product or corp strat emphasized repeatable, cross-functional influence and faster, measurable impact on a single P&L. startup exits almost always sold me on learning rate and equity upside, but also a much fuzzier ladder and longer runway to stable comp. pe hires prized direct deal exposure and valuation math; they wanted consulting stories reframed as transaction narratives. staying in corporate strategy tended to trade top-end upside for predictable cadence and stakeholder navigation skills.
based on those exit stories, i mapped the hires’ projects (m&a diligence, growth experiments, product ops, cost transformation) to the skills that actually mattered in ads, pm, or investment teams. that move from abstract career titles to concrete project signals is what helped me decide.
if you’ve left (or are thinking of leaving) consulting, what specific project experiences or signals did you listen for when choosing your path, and which ended up being the most predictive of success?
sure, “talk to vets” is the standard advice. but here’s the blunt part: most exit stories are curated. people highlight the deal that worked and quietly skip the 12 dead-end projects. look for the repeatable bits — did they run end-to-end workstreams, or just polish other people’s decks? that tells you if they actually earned the role or just lucked into it. also, beware startup bias: everyone brags about runway and equity until the payrolls get tight.
you’ll hear that pe is pure maths and startups are pure hustle. meh. the real difference is decision ownership. if the vet you admire kept getting handed high-leverage decisions (pricing, repo, bids), that’s your signal. if they only touched analysis and never sold the outcome to leaders, don’t expect a smooth transfer to a role that requires persuasion under pressure. oh and yes, resumes lie. always ask ‘what did you personally decide?’
quick thought
i’m trying to map my projects to roles too. did ppl ask vets how often they owned the final recommendation vs just did the modelling? that feels like a key diff. any tips on framing that on a resume?
tiny q
i’m leaning startup but worry about comp. should i focus on quantifiable growth metrics in interviews? any wording tips?
you got this!
listen to every story, compare the tasks they actually did, and pick what excites you. small wins compound — choose the path that makes you curious every morning!
i remember chatting with someone who left b-school into corp strat at a big retailer — at first they felt bored, but after 9 months they were running a merchant-facing growth experiment that actually changed the category plan. another friend jumped to a seed startup and learned how to hire engineers and close early customers in three months — terrifying but career-defining. those two paths taught me that the same consulting skill (problem scoping) can turn into very different day-to-day work depending on who signs the check and how big the org is.
From the cases i’ve coded across ~25 post-consulting exits, three patterns emerge. First, roles that require repeated stakeholder buy-in (corp strat, product) favored candidates who described end-to-end ownership and measurable outcomes. Second, startups prioritized examples of rapid iteration and ambiguity tolerance over polish. Third, PE hires screened for direct transaction exposure and financial modelling depth. My recommendation: score your recent projects on ownership, time-to-impact, and transaction exposure, then prioritize roles where your top-2 scores align with the job’s core output.
a simple rubric I use: assign 0–3 for each project on (1) ownership, (2) measurable impact, (3) cross-functional influence, (4) financial rigor. projects scoring high on ownership and measurable impact map well to tech/product or corp strat; high financial rigor predicts pe fit; high ownership with low predictability maps to startup upside. run your last 6 projects through this and see which bucket dominates — it’s rarely ambiguous once you quantify it.