Factor Comparison Method: How It Works (and When to Use It)
Date Published
Factor Comparison Method
The factor comparison method is the job-evaluation approach almost nobody uses anymore, taught in almost every HR textbook anyway. It is elegant on paper: rank a small set of benchmark jobs on each compensable factor, assign a dollar value to each factor for each benchmark, then compare every other job factor-by-factor against those benchmarks. The output is a salary, not a point total. No mapping step required. If you have not encountered it in the field, that is because the maintenance cost has buried it for most of the last 30 years. This guide covers exactly how it works, why it largely disappeared, and the narrow set of conditions under which it might still earn its keep.
TL;DR — Key takeaways
- The factor comparison method is a quantitative job-evaluation technique that ranks benchmark jobs on each compensable factor and assigns a dollar value (not points) to every factor.
- It was developed in 1926 by Eugene Benge at Philadelphia Rapid Transit and dominated U.S. industrial job evaluation through the 1950s.
- Its key advantage: evaluation output is denominated in dollars, so the mapping to actual salary is built in.
- Its key weakness: when the labor market moves, every benchmark dollar value goes stale, and re-benchmarking is a months-long project.
- Most organizations that adopted it migrated to point-factor by the 1980s. In 2026, it is rarely the right choice — but the underlying logic still shows up in modern hybrid systems.
Table of contents
- How the factor comparison method works
- A worked example
- Strengths and weaknesses
- Factor comparison vs point-factor vs ranking vs classification
- When (if ever) to use it in 2026
- FAQ
How it works
The factor comparison method has five steps. The first two are the heavy investment; once they are done, evaluating a new job takes minutes.
Step 1 — Select compensable factors. Most implementations use the five factors Eugene Benge originally proposed: mental requirements, skill, physical requirements, responsibility, and working conditions. Modern adaptations drop "physical requirements" or fold it into "working conditions" for white-collar workforces.
Step 2 — Choose benchmark jobs. Pick 15 to 25 well-established jobs whose duties are stable, whose pay is broadly considered fair, and whose level varies across the organization (some entry-level, some mid, some senior). These are the anchors the whole system rests on.
Step 3 — Rank benchmarks on each factor. Take your 15-to-25 benchmarks and rank them on mental requirements alone — from highest to lowest. Then rank the same jobs on skill. Then responsibility. Then working conditions. You produce one ranking per factor.
Step 4 — Assign dollar values to each factor for each benchmark. For each benchmark job, split the current salary across the factors based on how much each factor "contributes" to that job's worth. A Senior Engineer making $120,000 might break down as: mental $48,000, skill $36,000, responsibility $30,000, working conditions $6,000. Do this for every benchmark.
Step 5 — Evaluate non-benchmark jobs. For any new job, compare it factor-by-factor against the benchmarks. If its "skill" sits between Benchmark A ($36,000) and Benchmark B ($28,000), assign a skill value in that range. Repeat for every factor, then sum. The total is the evaluated salary.
The clever bit is Step 4. By splitting each benchmark's salary across factors before you evaluate any new jobs, you create a built-in factor-to-dollar scale. New evaluations slide into the scale at the appropriate rate per factor.
A worked example
Say you run a 200-person engineering firm and you want to evaluate a new role — Senior Mechanical Engineer. You have already established the following benchmark scale on four factors (simplified):
Benchmark job | Current salary | Mental | Skill | Responsibility | Working conditions |
|---|---|---|---|---|---|
Office Administrator | $48,000 | $14,000 | $12,000 | $14,000 | $8,000 |
Project Coordinator | $72,000 | $22,000 | $20,000 | $24,000 | $6,000 |
Mechanical Engineer II | $95,000 | $32,000 | $28,000 | $29,000 | $6,000 |
Director of Engineering | $165,000 | $52,000 | $46,000 | $62,000 | $5,000 |
You evaluate Senior Mechanical Engineer. You judge it sits between Mechanical Engineer II and Director of Engineering on every factor, closer to the Engineer II end. You estimate:
- Mental: $40,000 (between $32K and $52K)
- Skill: $36,000 (between $28K and $46K)
- Responsibility: $42,000 (between $29K and $62K)
- Working conditions: $6,000 (similar to other engineer roles)
Total evaluated salary: $124,000. No point conversion, no band-mapping. The number you get is the number to pay.
That elegance is what gave factor comparison its run from the 1930s through the 1970s. Then the labor market changed underneath it.
Strengths and weaknesses
What it gets right.
- Output is a dollar value. Every other method (ranking, classification, point-factor) requires a separate step to translate the evaluation into actual pay. Factor comparison skips that step.
- It forces a clear theory of pay. When you assign dollar values to factors at Step 4, you are stating publicly: "we pay X for skill, Y for responsibility." That clarity is rare in compensation.
- It is granular per-factor. Unlike ranking (which produces an undifferentiated order), factor comparison gives you a separate evaluation on each factor — useful for pay-equity analysis on subsets of the workforce.
Where it breaks down.
- Market drift. When salaries move 5 to 8 percent year over year, every benchmark dollar value drifts. Re-doing them across all factors is a multi-month project. Point-factor systems can map updated market data onto bands without re-running the evaluation.
- Benchmark contamination. If your "current salary" on a benchmark is itself inequitable (because of historical pay gaps, market over-paying for one role, or a one-off retention bonus), that distortion propagates into every evaluation that compares against it.
- Communication burden. Try explaining "your skill is worth $36,000 of your job's value" to a frontline manager. Point-factor's "your job scored 480 points, which puts it in Band 7" lands more cleanly.
- No clean pay-band structure. The method produces a salary per job, not a band a job belongs to. That makes range-and-promotion logic harder to build on top.
The Equal Pay Act compatibility note. The four factors at the heart of the U.S. Equal Pay Act of 1963 — skill, effort, responsibility, working conditions — map cleanly onto factor comparison's structure. In principle, factor comparison can produce a defensible audit trail. In practice, the dollar-value step has been hard to defend in pay-equity litigation because the "current salary" inputs at Step 4 can carry forward historical inequities.
vs. other methods
Here is where factor comparison sits relative to the other three classical job-evaluation methods.
Method | Output | Setup cost | Maintenance cost | Best for |
|---|---|---|---|---|
Ranking | Ordered list | Hours | Low | <25 jobs, single decision-maker |
Classification | Grade assignment | 4–8 weeks (grade definitions) | Low | Stable, well-defined job families (government) |
Point-factor | Numerical score → band | 3–6 months (manual) / 4–6 weeks (AI-augmented) | Medium | Most modern private-sector organizations |
Factor comparison | Dollar value | 2–4 months | High (re-benchmark on market drift) | Rare in 2026 |
The defining trade-off: factor comparison front-loads less than point-factor, but back-loads more. Once you have built a factor framework with documented anchor definitions, point-factor's evaluations age gracefully — you re-validate the framework every 3 to 5 years. Factor comparison's dollar values age every quarter the market moves.
For a side-by-side walkthrough of all four methods, see our complete comparison of job evaluation methods.
Want to see how point-factor compares on real jobs? Download our free Point-Factor Job Evaluation Scorecard (Excel) — it ships with the recommended factor framework, anchor definitions, and weights. Start scoring jobs in the next 20 minutes.
When (if ever) to use it in 2026
Three narrow situations where factor comparison still earns serious consideration:
1. You operate in a single-market labor pool with stable wages. If your entire workforce is in one geography, one industry, and the wage data is reliable and slow-moving, the maintenance penalty drops. Some specialty-trades organizations and a handful of unionized environments fit this pattern.
2. You inherited a factor comparison system you cannot replace yet. If your organization already runs factor comparison and migration would disrupt active union contracts or trigger collective-bargaining renegotiation, the right move is often to maintain the existing system and shore up its weak points (re-benchmark on a fixed cadence, audit Step 4 dollar values for equity) until a future window opens.
3. You want a hybrid: point-factor for breadth, factor comparison for executive roles. A few organizations use factor comparison just for the executive layer where the population is small and the salaries are highly market-sensitive. Point-factor handles everything below. The risk is consistency — and explaining why one part of your structure uses a different methodology.
Outside those cases, the right move in 2026 is point-factor. It gives you the defensibility of a documented factor framework, scales as new roles get added, and adapts gracefully to market and skills-based shifts.
If you want the full case for point-factor, see our point-factor method pillar. If you want the broader workflow that any method fits into, read our complete job evaluation guide.
A note on Eugene Benge
Most modern HR references mention factor comparison briefly without crediting its origin. The method was developed by Eugene J. Benge at Philadelphia Rapid Transit Company in 1926 and codified in his 1941 book Manual of Job Evaluation. Benge was responding to the same problem we still face today: how to set internally fair pay across a workforce of dozens of distinct roles without resorting to "what feels right." The Hay Group's point-factor system, published in 1951, built directly on Benge's structure but replaced dollar values with points to solve the maintenance problem.
If you read modern Korn Ferry or Mercer methodology documentation, you can still see Benge's fingerprints — the four umbrella factors, the benchmark-anchored evaluation flow, the focus on internal equity across functions. The factor comparison method's idea is alive even where its mechanics are not.
FAQ
What is the factor comparison method of job evaluation? It is a quantitative job-evaluation technique that ranks a set of benchmark jobs on each compensable factor (skill, effort, responsibility, working conditions, sometimes mental requirements), assigns dollar values to each factor for each benchmark, then evaluates other jobs by comparing them factor-by-factor against the benchmarks. The output is a salary.
Who invented it? Eugene Benge developed it at Philadelphia Rapid Transit Company in 1926. He formalized the method in his 1941 book Manual of Job Evaluation.
How is it different from point-factor? Point-factor scores jobs in abstract points and requires a separate mapping step to translate points into pay. Factor comparison expresses scores in dollars directly. The trade-off: factor comparison's dollar values go stale as the labor market shifts, while point-factor's points stay valid until you decide the underlying factor framework needs updating.
Is it still used today? Rarely. Most organizations that adopted factor comparison in its mid-20th-century heyday migrated to point-factor by the 1980s. Some unionized environments and a handful of specialty-trades organizations still run it, and the underlying logic shows up in hybrid systems for executive-level evaluations.
What are the main weaknesses? Market drift (benchmark dollar values age constantly), benchmark contamination (if your benchmark salaries carry historical inequities, every new evaluation inherits them), and communication difficulty (explaining "your skill is worth $36,000" to a manager is harder than explaining a band assignment).
How long does setup take? Two to four months for a 200-job organization, plus ongoing re-benchmarking work every six to twelve months. Point-factor is faster to set up for the same workforce when you use AI-augmented tooling, and the maintenance cost stays lower over the life of the system.
Is factor comparison defensible in a pay-equity audit? In principle, yes — the method's factor structure maps cleanly onto Equal Pay Act criteria. In practice, the dollar-value step at Step 4 can carry forward historical pay inequities from the benchmark salaries, which has been a vulnerability in litigation. Point-factor's separation of evaluation (points) from pay decisions (band mapping) gives you a cleaner audit trail.
Ready to move past factor comparison?
If your organization is running factor comparison and the re-benchmarking cycle is consuming a quarter of your comp team's time, book a 20-minute demo. PointFactors evaluates every job in your organization using a documented point-factor framework — defensible, low-maintenance, and audited by your team — in days rather than months.
About the author: Justin Hampton is the founder and CEO of PointFactors. He has spent 18 years designing job-evaluation systems and pay structures for organizations ranging from Series B startups to Fortune 500 enterprises.