Merit Increase Matrix: How to Build One That Fits Your Budget

Merit Increase Matrix: How to Build One That Fits Your Budget

Every fall, the same thing happens. Finance hands you a salary increase budget. You hand managers a spreadsheet. Managers hand back recommendations that total 4.4% against a 3.5% budget, with the biggest raises going to the people who already earn the most. Then you spend three weeks clawing it back one conversation at a time.

A merit increase matrix stops that cycle. It is a grid that converts two inputs — a performance rating and a position-in-range measure — into a recommended increase percentage. Managers stop guessing. You stop negotiating. And because the grid is published in advance, you can defend every number in it if a regulator, an auditor, or an employee asks how the raise was decided.

This guide walks through building one from scratch: choosing the axes, sizing the grid, filling the cells with real numbers, and — the step most teams skip — cost-modeling the matrix against your actual population before you release it to managers.

TL;DR

• A merit matrix maps performance rating (columns) against compa-ratio band (rows) and outputs a recommended increase percentage for each combination.
• Build it against your real budget. U.S. employers reported 3.6% mean actual salary increase budgets for 2026 and project 3.6% for 2027, with merit running around 3.2% of that.
• The compa-ratio axis is what makes the grid work. It pushes dollars toward underpaid strong performers and slows increases for people already above midpoint.
• Always cost-model the grid before publishing. A matrix that looks reasonable cell by cell routinely lands 0.1–0.3 points over budget once you apply your actual headcount distribution.
• The matrix is only as good as your midpoints. If your salary structure is built on stale or inconsistent grades, compa-ratio is measuring against the wrong denominator.

What a merit increase matrix actually does

The matrix solves an allocation problem, not a motivation problem. Your total merit pool is fixed. The question is how to distribute it so that two things stay true at once: strong performers get meaningfully more than average performers, and people who are underpaid relative to their range move faster than people who are overpaid.

Those two goals pull against each other constantly. A top performer at the top of her range and a top performer at the bottom of his range both "deserve" a large increase on performance grounds. Give both of them 6% and you have widened an internal pay gap between two people doing equally valued work — the exact pattern that shows up later as pay compression or a pay equity finding.

The matrix resolves the tension mechanically. Performance sets the ballpark. Position in range adjusts within it.

Step 1: Confirm the budget you are actually funding

Start with the number, not the grid. Two figures matter and they are not the same:

• Total salary increase budget — everything: merit, promotions, cost-of-living, market adjustments, equity fixes.
• Merit budget — only the portion the matrix distributes.

WorldatWork's 2026–2027 Salary Budget Survey, covering 1,799 organizations, put U.S. mean total salary increase budgets at 3.6% actual for 2026 and 3.6% projected for 2027 — the fourth straight year without an increase in the projection. Mercer's survey of more than 1,000 U.S. organizations breaks the total apart: 3.2% for base merit increases and 3.5% for total increases including promotions, cost-of-living, and other adjustments.

That gap between 3.2% and 3.5% is your promotion and adjustment reserve. Mercer found employers planned to promote about 9% of the workforce at an average promotional increase of 8.7%. If you fund promotions out of the merit pool, your matrix has to be built at roughly 3.0%, not 3.5%. Decide this before you draw a single cell.

For this walkthrough, assume a 3.5% merit budget, promotions funded separately, on a population of 400 employees and a $38M base payroll.

Step 2: Choose your two axes

Columns: performance rating. Use whatever rating scale you already run. Four levels is the practical sweet spot — three collapses too much of your population into the middle, five creates distinctions managers cannot defend.

Rows: position in range. You have two reasonable options:

• Compa-ratio — salary divided by range midpoint. Simple, portable, and the standard choice.
• Range penetration — where the salary sits between range minimum and maximum, as a percentage. Better if your ranges have widely different spreads by grade.

Use compa-ratio unless your range widths vary a lot across the structure. It is easier for managers to interpret and easier to explain to employees.

Do not add a third axis. Tenure, retention risk, and flight risk all feel relevant, and all of them will blow up the grid's size and its defensibility. Handle those as documented exceptions instead.

Step 3: Size the grid

Four performance levels by four compa-ratio bands gives you sixteen cells. That is enough resolution to be meaningful and few enough that a manager can hold it in their head.

Standard compa-ratio bands:

• Under 0.90 — below the market rate for the job
• 0.90 to 0.99 — approaching midpoint
• 1.00 to 1.10 — at or just above midpoint
• Over 1.10 — well above midpoint

If you are unsure your midpoints are right, fix that first. How to set salary range midpoints covers the mechanics.

Step 4: Fill the cells

Here is a worked 4x4 matrix built for a 3.5% merit budget:

Three design rules are doing the work here.

Increases fall as you move down. An Exceptional performer under 0.90 gets 8.00%; the same rating over 1.10 gets 3.50%. Both are rewarded. One moves toward market, the other is already past it.

Increases rise as you move right, and the spread widens at the bottom. In the "Over 1.10" row, the gap between Meets and Exceptional is 2.0 points. In the "Under 0.90" row it is 3.5 points. Differentiation matters most where there is room to move.

Below expectations pays zero everywhere. If a below-standard rating still earns money, your managers will learn that ratings do not carry consequences, and they will stop giving honest ones.

Step 5: Cost-model the grid before you publish it

This is the step that separates a matrix that works from one you have to retract in November. Apply your actual population distribution to the grid and see what it costs.

Assume this organization's distribution:

Weight each band by its performance mix, then weight the bands together:

The grid costs 3.60% against a 3.5% budget. On $38M of payroll, that is roughly $37,000 over. Every cell looked defensible, and the matrix is still overspent — because most of your population sits in the middle two bands where you were generous.

The fix is small. Drop the entire Meets column by 0.25 points — 4.50% becomes 4.25%, 3.75% becomes 3.50%, 3.00% becomes 2.75%, 1.50% becomes 1.25%. Rerun the math and the grid costs 3.45%, comfortably inside budget with room for in-cycle corrections.

That is the lesson worth keeping: because 60% of your people sit in one column, a quarter-point change there moves total cost by about 0.15 points. Changes to the corners barely register. Model it, do not eyeball it.

Leave yourself 5–10% of the pool unallocated. You will need it for equity corrections that surface during manager review.

Step 6: Handle exceptions on purpose

Every cycle produces cases the grid cannot resolve: a genuine market gap on a hot skill, a new hire who arrived below range, an employee whose scope grew mid-year without a formal promotion.

Do not widen the matrix for these. Create a separate exception process with a documented reason code, a second-level approver, and a hard cap — 5% of the pool is a workable ceiling. Exceptions with reason codes are auditable. Exceptions buried inside a manager's merit recommendation are not.

If the same exception appears three years running, it is not an exception. It is a signal that the job is graded wrong.

Building your grid on ranges you are not confident in? See how PointFactors scores jobs against weighted compensable factors to produce grades and midpoints your compa-ratios can actually stand on.

Where merit matrices fail

Almost every failure traces back to the same root cause: the denominator is wrong.

Compa-ratio only means something if the midpoint reflects a defensible judgment about the job's internal value and its market rate. When grades were assigned by negotiation, inherited from an acquisition, or last reviewed four years ago, the matrix distributes money with precision against a number that is simply incorrect. A person the grid says is at 1.15 may actually be at 0.95 in a correctly graded job — and you have just given them the smallest increase in the matrix.

That is why the sequence matters. Evaluate jobs, build the salary structure, then build the matrix. Job evaluation scores the work against weighted compensable factors — skill, effort, responsibility, and working conditions — and produces point totals that map to grades. That is a different exercise from performance evaluation, and the distinction is the whole point: the matrix rewards the person, the structure prices the job.

The other common failure is a matrix that contradicts the compensation philosophy it is supposed to express. If your philosophy says you pay at the 60th percentile for engineering talent but your grid caps everyone over 1.10 at 3.50%, you will drift below your own stated target within three cycles. Check the grid against the philosophy document, in writing, every year.

FAQ

What is a merit increase matrix?

A two-dimensional grid that maps a performance rating against a position-in-range measure — usually compa-ratio — and outputs a recommended base pay increase percentage for each combination. It gives managers a defensible starting point and keeps total spend inside the budget.

What is a typical merit increase in 2026 and 2027?

Mercer reported U.S. employers planning 3.2% for base merit increases in 2026, with 3.5% total including promotions and other adjustments. WorldatWork's survey put 2026 actual mean total salary increase budgets at 3.6% and 2027 projections at the same 3.6%. Your own budget may differ by industry — healthcare and retail have run below average, while financial services, energy, and high-tech have run above.

Should I use compa-ratio or range penetration?

Compa-ratio for most organizations — it is simpler to explain and compares cleanly across grades. Use range penetration if your range spreads vary widely by grade, since compa-ratio treats a 30% spread and a 60% spread as if they were the same.

How many performance levels should the matrix have?

Four. Three flattens too much of your population into a single middle cell; five asks managers to defend distinctions that are hard to evidence. Match whatever your performance system already produces — do not invent a new scale for comp.

Should below-standard performers receive an increase?

No. A zero in that column is what makes the rest of the grid credible. If a below-expectations rating still earns 1%, managers will conclude the rating carries no consequence and will stop assigning it.

Do I have to publish the matrix to employees?

You do not have to, but pay transparency rules are steadily raising the expectation. At minimum, publish the logic: that increases are based on performance and position in range, and that people below midpoint move faster. Employees who understand the mechanism argue with it far less than employees who suspect there isn't one.

How often should I rebuild the matrix?

Rebuild the numbers annually against the new budget. Revisit the structure — bands, thresholds, number of levels — every two to three years, or whenever you re-evaluate jobs and your midpoints move.

Get the structure right first

A merit matrix is a distribution tool. It cannot fix grades that were never defensible, and it will quietly amplify whatever inconsistency already exists in your salary structure.

PointFactors evaluates jobs with AI-assisted point-factor scoring — every job scored against the same weighted compensable factors, with a documented audit trail behind every point. You get grades and midpoints your compa-ratios can stand on, and a record you can produce when someone asks how a pay decision was made.

Book a demo to see how it works on your jobs, or review pricing to plan your next cycle.

Justin Hampton is founder and CEO of PointFactors.