decision-maker

Decision Maker

Overview

This skill applies proven decision-making frameworks—pros/cons analysis, weighted scoring matrices, RICE prioritization, the Eisenhower urgency-importance matrix, and pre-mortem analysis—to help you cut through ambiguity and make defensible, well-reasoned choices. By externalizing the decision into a structured format you reduce cognitive bias, surface hidden trade-offs, and create a record of your reasoning that can be revisited or shared with stakeholders.

When to Use

• You have two or more meaningful options and are unsure which to choose
• The decision has significant, lasting consequences (career, finances, product roadmap, hiring)
• Multiple stakeholders need to align around a shared rationale
• You feel emotionally stuck and want an objective framework to cut through the noise
• You need to prioritize a backlog of features, tasks, or projects
• You want to stress-test a decision you've already leaned toward

When NOT to Use

• The decision is low-stakes and reversible (where any choice is fine)
• You need licensed advice (legal, medical, financial) — frameworks support, not replace, professionals
• The situation requires immediate crisis action with no time for structured analysis
• Data needed to score criteria is completely unavailable or unknowable
• You simply want validation for a decision already firmly made

Quick Reference

Framework	Best For	Output
Pros / Cons	Simple binary choices, fast gut-check	Two-column list
Weighted Scoring Matrix	Multi-option, multi-criteria trade-offs	Ranked score table
RICE	Feature or project prioritization	Priority-ranked backlog
Eisenhower Matrix	Task triage and time management	4-quadrant urgency/importance grid
Pre-Mortem	Risk identification before committing	List of failure modes and mitigations

Instructions

1. Clarify the decision — State the decision in one clear sentence. Define what "success" looks like and the deadline by which you must decide.

2. Enumerate options — List every realistic option, including "do nothing" or "defer." Aim for at least two, no more than six manageable choices.

3. Choose a framework — Match the framework to the decision type: use Pros/Cons for simple binary choices; Weighted Scoring for multi-criteria comparisons; RICE for backlog prioritization; Eisenhower for task triage; Pre-Mortem for risk stress-testing.

4. Define criteria (Weighted Scoring) — Identify 3–7 criteria that matter most (e.g., cost, time-to-value, strategic fit, risk). Assign each a weight from 1–5 reflecting its relative importance.

5. Score each option — Rate every option against each criterion on a 1–10 scale. Multiply by weight. Sum the totals. Higher scores indicate better overall fit.

6. Apply RICE (if prioritizing work) — For each item calculate: Reach × Impact × Confidence ÷ Effort. Reach = users affected; Impact = 1–3 scale; Confidence = percentage (0–100); Effort = person-weeks.

7. Map urgency vs. importance (Eisenhower) — Plot tasks on a 2×2 grid: Do Now (urgent + important), Schedule (important, not urgent), Delegate (urgent, not important), Eliminate (neither).

8. Run a pre-mortem — Imagine it is 12 months from now and the chosen option has failed spectacularly. Brainstorm every plausible cause. Use this list to add mitigations or re-weight criteria.

9. Check for bias — Review the analysis for sunk-cost fallacy, status-quo bias, and confirmation bias. Ask: "Would I choose this if I were starting fresh?"

10. Document and decide — Write a one-paragraph decision summary: chosen option, top three reasons, top two risks and their mitigations, and a review date.

Examples

Example 1: Career Choice — Stay at Current Job vs. Accept Startup Offer

Input: "I have a stable senior engineer role at a Fortune 500 paying $160k. A Series B startup offered me a staff engineer role at $140k base + 0.4% equity. I have a mortgage and two kids. Help me decide."

Output:

Weighted Scoring Matrix

Criteria	Weight	Fortune 500 (score)	Fortune 500 (weighted)	Startup (score)	Startup (weighted)
Financial security	5	9	45	5	25
Career growth	4	5	20	9	36
Compensation upside	3	4	12	8	24
Work-life balance	4	7	28	5	20
Mission alignment	2	4	8	8	16
Total			113		121

Pre-Mortem (Startup): Startup runs out of runway (mitigate: verify 18+ months runway, ask for accelerated vesting cliff), role scope shrinks post-hire (mitigate: get title and scope in writing).

Recommendation: The startup scores marginally higher, but the margin is within noise given your dependence on financial stability. Negotiate: request a $150k base, 12-month cliff vesting, and written role definition before accepting. If negotiation fails, the stability of the Fortune 500 warrants staying.

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Example 2: Product Prioritization — RICE Scoring a Feature Backlog

Input: "We have 5 features to prioritize for Q3: (A) SSO login, (B) CSV export, (C) Mobile app, (D) Audit logs, (E) Bulk delete. We serve 2,000 enterprise users."

Output:

RICE Scores

Feature	Reach	Impact	Confidence	Effort (wks)	RICE Score
A – SSO Login	1,800	3	90%	3	1,620
D – Audit Logs	1,500	2	80%	2	1,200
B – CSV Export	1,200	2	95%	1	2,280
E – Bulk Delete	800	1	90%	0.5	1,440
C – Mobile App	600	3	60%	12	90

Recommended Priority: B → A → E → D → C. CSV Export delivers the highest RICE score at low effort. Mobile App scores last due to high effort and low confidence — defer to Q4 or a dedicated mobile initiative.

Best Practices

• Always score options blind (fill in scores before revealing which option you prefer) to reduce anchoring bias
• Involve at least one dissenting voice in the criteria-weighting step to stress-test your priorities
• Revisit your decision at a predetermined date — decisions are hypotheses, not facts
• Use the Eisenhower matrix daily/weekly; reserve weighted scoring for quarterly or life decisions
• When stakes are very high, run both a weighted scoring matrix AND a pre-mortem before committing
• Document your reasoning even if you ultimately go with intuition — you'll learn from the outcome

Common Mistakes

• Weighting criteria after scoring options (this introduces confirmation bias into the weights)
• Using too many criteria (>7) which dilutes meaningful differentiation between options
• Treating RICE scores as precise — they are directional estimates, not exact measurements
• Skipping the pre-mortem step when you're excited about a preferred option — that's exactly when it's most needed
• Equating a higher score with a guaranteed good outcome — the framework improves odds, not certainty
• Forgetting to include "do nothing" as an explicit option with its own score

Tips & Tricks

• If two options score within 5% of each other, flip a coin — the framework has told you they're essentially equal, so other factors (gut feel, optionality) should break the tie
• Timebox the analysis: 30 minutes for a pros/cons, 2 hours for a full weighted matrix — decisions don't improve linearly with analysis time
• Use a "regret minimization" sanity check (Bezos): imagine yourself at 80 looking back — which option would you regret NOT trying?
• For team decisions, have each person score independently before sharing results to avoid groupthink
• Export your scoring matrix to a shared doc so stakeholders can see and challenge the inputs, not just the conclusion

Related Skills

• task-planner
• note-taker