How the Job Calculator Works

A Structured Comparison, Not a Prediction

Job-Calculator.com compares a current job and a potential new job across five scored categories: Money, Free Time, Quality of Life, Career Growth, and Benefits. You provide both job characteristics and your priorities. The tool makes the resulting trade-offs visible.

It does not predict happiness, prove which job is objectively better, or know whether an offer will match its promises. Work Setup—remote, hybrid, or on-site—is useful context but receives no automatic score.

1. Money

Money uses expected annual compensation. Enter the bonus you realistically expect, not a theoretical maximum.

currentComp = currentSalary + currentExpectedBonus
newComp = newSalary + newExpectedBonus
compChangePct = (newComp - currentComp) / currentComp
moneyScore = clamp(compChangePct / 0.50, -1, 1)

A 10% increase scores about +0.20, 25% scores +0.50, and 50% or more reaches +1.00. A 25% decrease scores about -0.50. These are transparent design choices, not statistically calibrated coefficients.

If current compensation is zero, the implementation returns 0 when both jobs are zero and uses a capped +100% change when the new job has positive compensation. This avoids an undefined percentage.

2. Free Time

Free Time combines scheduled work, round-trip commuting, and PTO on one time scale. Commute is never assigned a monetary value.

weeklyCommute = oneWayMinutes × 2 × officeDays / 60
annualPtoHours = PTOdays × 8
weeklyPtoEquivalent = annualPtoHours / 52
weeklyEffectiveTimeLoad = workHours + weeklyCommute - weeklyPtoEquivalent
weeklyHoursDelta = currentLoad - newLoad
timeScore = clamp(weeklyHoursDelta / 10, -1, 1)

A positive delta favors the new job. PTO is not literally deducted from every working week; annual leave is averaged across 52 weeks only to compare it consistently with weekly work and commute. Five additional PTO days equal 40 annual hours, about 0.77 hours per week, and about +0.077 Time if everything else is equal. A 10-hour effective weekly difference reaches the ±1 cap.

For costs and practical questions outside this formula, see How Commute Enters Free Time.

3. Quality of Life

stressImprovement = clamp((currentStress - newStress) / 5, -1, 1)
happinessImprovement = clamp((newHappiness - currentHappiness) / 5, -1, 1)
qualityScore = clamp(0.50 × stressImprovement + 0.50 × happinessImprovement, -1, 1)

Lower expected stress is favorable; higher expected happiness is favorable. Stress moving from 8/10 to 5/10 and happiness from 4/10 to 7/10 produce +0.60 each, so Quality is +0.60. These ratings are estimates, not objective measurements.

4. Career Growth

Career Growth asks three distinct questions:

• Learning & skill growth: Will the role build valuable capability?
• Advancement potential: Is there a credible path to promotion or responsibility?
• Future career opportunities: Will the role improve later options and marketability?

eachImprovement = clamp((newRating - currentRating) / 5, -1, 1)
growthScore = (learning + advancement + futureOpportunity) / 3

All three receive equal weight. Use evidence such as likely projects, promotion criteria, mentorship, alumni outcomes, and skills you will practice. Avoid assigning all three high values from the same vague impression.

5. Benefits

benefitsScore = clamp((newBenefits - currentBenefits) / 5, -1, 1)

Benefits might include health insurance, retirement contributions or matching, parental benefits, disability coverage, education support, and other meaningful employer support. A three-point improvement produces +0.60. Work Setup is not part of Benefits. PTO is already included in Free Time, so do not raise Benefits solely for the same PTO difference.

Why Work Setup Is Not Scored

Remote, hybrid, and on-site work receive no automatic positive or negative value because preferences and job requirements differ. The calculator instead scores explicit consequences through commute, office days, stress, and happiness.

Changing only Remote to On-site produces no score change. Adding a 45-minute commute, five office days, and higher expected stress changes the result because those consequences changed—not because On-site is assumed to be bad. See the work-style guide for factors worth considering.

Your Priorities Are Relative

normalizedWeight = rawPriority / sumOfAllRawPriorities

Values 5/5/5/5/5 become 20% each. Values 10/5/5/5/5 make Money about 33.3% and each other category about 16.7%. Thus 1/1/1/1/1 and 10/10/10/10/10 are equivalent. All-zero priorities are rejected.

Contributions and the Final Score

categoryContribution = categoryScore × normalizedWeight
finalScore = sum of all five contributions

The final score ranges from -1 to +1. Positive favors the new job under your assumptions and priorities; negative favors the current job; near zero means the modeled trade-offs offset. It is not a probability: +0.24 does not mean a 24% chance that switching is correct.

These are interpretation bands, not empirical probabilities. +0.299 and +0.300 represent essentially similar trade-offs even though their labels differ. A tiny implementation tolerance prevents floating-point noise at an exact boundary from contradicting the displayed result.

Complete Worked Example

The calculator opens with this reproducible comparison:

Compensation rises from 65,000 to 81,000: +24.615%, producing Money +0.492. Weekly commute is 3.000 versus 0.667 hours. PTO averages 2.308 versus 3.077 hours per week. Effective time load is 40.692 versus 42.590 hours, so the new job costs 1.897 effective hours per week and Time is -0.190.

Stress worsens by two points (-0.40) while happiness improves by one (+0.20), making Quality -0.100. Each Growth factor improves three points, making Growth +0.600. Benefits improve two points, making Benefits +0.400.

Priorities are Money 7, Time 5, Quality 8, Growth 6, Benefits 6:

Career Growth and Money are the largest positive contributors, with Benefits adding support. Free Time works against switching because five extra work hours outweigh the shorter commute and extra PTO. Quality slightly favors the current job.

What Could Change the Result?

Sensitivity analysis changes one input at a time, holding all other inputs and priorities constant. It searches practical increments for an adjacent band and groups findings into Compensation, Time, and subjective assumptions.

For the default example, Strong case for switching can be reached with salary around 81,000 (bonus unchanged), work hours around 41 per week, or expected Benefits closer to 10/10 rather than 8/10. Salary and bonus alternatives are deduplicated, and subjective changes of four or more points are suppressed from ordinary findings.

Sensitivity does not optimize your answers or prove an assumption is right. Some useful changes do not cross a band, and correlated changes are not modeled.

Avoid Accidental Double Counting

A commute is represented by minutes and office days. It may also genuinely affect stress or happiness because time and emotional experience are different consequences. Do not mechanically penalize the same concern across several ratings unless each consequence is genuinely distinct.

PTO is already included in Free Time; do not increase Benefits solely for the same PTO difference. Likewise, make sure the three Growth ratings reflect distinct evidence rather than one repeated impression.

Limitations and Assumptions

• Subjective inputs depend on user estimates, and future conditions may differ.
• Expected bonuses are uncertain and are not guaranteed compensation.
• Compensation is not adjusted for taxes, inflation, or purchasing power.
• PTO assumes eight hours per day; availability does not guarantee actual use.
• The model omits some personal, family, health, manager, stability, and market factors.
• Normalizations are design choices, not scientifically estimated coefficients.
• Scores are capped at ±1.
• Sensitivity changes one variable at a time and does not model correlations.
• The tool is decision support, not professional career, financial, or legal advice.

If an estimate is uncertain, compare realistic, optimistic, and cautious cases. The FAQ provides additional guidance, while About explains the project’s purpose.