Decision-Making

Type-1 (fast/automatic) decisions: < 5 mins, reversible, high-frequency (daily priorities, meeting agendas). Type-2 (deliberate) decisions: reversible calls get 1–2 days + framework; irreversible calls (hire, launch, pivot) get weeks + diverse input + pre-mortem. The trap: slow people treat reversible calls like irreversible ones (analysis paralysis), fast people skip frames on irreversible ones (regret). Signal you're balancing well: 70% of your decisions you'd make the same way if you could redo them.

A framework cuts analysis short: RAPID = 3 days max for a hire decision (not 2 weeks of interviews). OODA = reorient every 24–48 hours, not every hour. Pre-mortem = 45 mins of 'what could kill this?' not endless risk brainstorms. Paralysis = no stopping rule; frameworks = the stopping rule is built in. You know you're good when people say 'you decided fast' not 'you decided recklessly.'

AI as tool (helpful): reframe options ('what if we flipped the revenue model?'), surface second-order consequences ('if we hire this way, what culture emerges?'), stress-test assumptions. AI as oracle (harmful): 'tell me the answer.' Use AI to broaden the frame, not to replace your decision authority. Ask it 'what's the worst case I'm not seeing?' not 'what should I do?'

Use DACI: Pick one Driver (owns the call), get explicit input from Contributors and Approvers (parallel, async), then Driver decides. Set a deadline (e.g., 'decision Friday 3pm'). Silent brainstorm first (5 mins written), then 10 mins discussion, then Driver calls it. Groups fall apart when there's no role clarity or no deadline — DACI fixes both.

Reverse if: (1) new info invalidates your assumption (not 'sentiment shifted'), (2) cost of reversal < cost of staying course, (3) you can do it fast (else you're being flaky). Don't reverse if: people just don't like it yet (they need 2 weeks to adjust), or reversing wastes 3 months of work for a 5% better outcome. Good decision-makers reverse ~5–10% of calls. Zero reversals = either you're ultra-conservative or the stakes are too low.

Write your decision reasoning down BEFORE you act: 'We're hiring Sarah because X, assuming Y, and we'll know by Z.' Six months later, review that doc, not the current narrative. Did Y stay true? Did Z happen? This decouples 'was the decision good?' (frame + reasoning were sound) from 'did the outcome work?' (outcome depends on luck too). Expect ~60–70% hit rate on big decisions; if you're higher, your standards are too low.

'Thinking in Bets' (Duke) teaches probabilistic reasoning + decision journals. 'Decisive' (Heath) covers bias + how to widen frame. 'Algorithms to Live By' (Christian/Griffiths) explains exploration/exploitation tradeoff and why 'good enough' beats perfection. 'Superforecasting' (Tetlock) shows how expert forecasters avoid overconfidence and update on evidence.