Create intermediate Works with: Any AI

Job Offer Comparison Matrix

Table output Has example

Compare offers on more than salary.

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Help me compare job offers and decide with a clear head. My offers: [OFFER_DETAILS_FOR_EACH]. My priorities in order: [MY_PRIORITIES]. Constraints: [CONSTRAINTS].

Build a weighted decision matrix:
1. Propose 8 to 10 criteria (for example base pay, bonus, benefits value, growth, manager quality, flexibility, commute, stability, mission fit, learning). Let me adjust the weights; start with weights that reflect my priorities and add up to 100.
2. Score each offer 1 to 5 per criterion with a short reason, and mark scores that are guesses as "guess".
3. Compute weighted totals in a table and show the arithmetic.
4. Convert each offer to a comparable yearly total compensation, listing assumptions.
5. Run a sensitivity check: how much would the weights have to change to flip the winner?
6. List unknowns to find out before deciding, with questions to ask each employer.

Remind me that the matrix informs my choice rather than making it, and finish by asking what my gut says and why.

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See an example result (fictional data)
Criteria and weights (100): base pay 25, growth 20, manager quality 15, flexibility 15, benefits 10, stability 10, commute 5.
Offer | Pay | Growth | Manager | Flexibility | Benefits | Stability | Commute | Weighted
A | 4 | 3 | 4 | 5 | 3 | 3 | 4 | 3.75
B | 5 | 4 | 3 | 2 | 4 | 4 | 2 | 3.70
Arithmetic A: 0.25x4 + 0.20x3 + 0.15x4 + 0.15x5 + 0.10x3 + 0.10x3 + 0.05x4 = 1.0+0.6+0.6+0.75+0.3+0.3+0.2 = 3.75.
Sensitivity: B overtakes A if the base pay weight rises from 25 to about 35, since B scores higher on pay.
Total compensation: A 62,000 + 3,000 bonus; B 70,000 with no bonus (assumptions listed).
Unknowns: manager style at B; equity terms at A. Matrix informs, you decide.

Illustrative only, made-up data. Your results will differ and must be reviewed.

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