Job Offer Scorecard

Each offer’s inputs are transformed into sub-scores from 0 to 100: total pay uses base salary + annualized bonus/equity, commute is inverted (shorter commute scores higher), and work-from-home uses the selected policy category. Growth, stability, and benefits come from your 0–10 ratings scaled to 0–100. Risk is treated consistently either as an inverse of stability (or a separate risk rating if you choose to override), then all sub-scores are combined using your weights (which total 100%).

Because pay and commute are normalized relative to the other offers you enter (or your benchmark when applicable), the “best” offer can shift when you add/remove a competing package. Equity/bonus are annualized into a simplified cash-equivalent, so vesting schedules and probability of earning equity aren’t modeled. Also, commute is assumed to be one-way and consistent, and WFH is simplified into a few policy buckets—so partial-week arrangements should be represented using the closest category you select.

If two offers end up within about 5 points, the tool flags a “close call” and focuses on the biggest differentiators (for example, stability vs. higher pay). If all offers have the same commute time or the same total compensation, those normalized sub-scores will be tied and the ranking will rely more heavily on the remaining factors. If you enter extreme weights (e.g., almost all weight on stability), small changes in that category can outweigh large pay gaps—this is expected behavior.

Be sure all inputs are comparable: use the same commute measurement (minutes one-way) and treat bonus/equity as annualized in the same way for every offer. Don’t enter negative values for salary, bonus/equity, or commute time—those are invalid. Finally, remember this is a decision aid, not a financial forecast: it excludes taxes, inflation, cost of living, promotion timing, and vesting schedules.