Most organisations β especially nonprofits β lack the resources for professional salary benchmarking. This tool takes your salary anchors and builds a principled, transparent salary grid you can defend to your board, your donors, and your team.
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Your numbers, not ours
No cost-of-living data, no positioning assumptions. You set the floor and senior anchor; the formula fills everything in between.
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Deterministic arithmetic
All salary figures are calculated in-app before AI is involved. Same inputs always produce the same grid.
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Fully transparent
The exact formula and AI prompt are published on the methodology page β nothing is hidden.
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Takes 2 minutes
Two salary figures plus a few structure choices. No benchmarking data required.
β When to use this version
This tool is for organisations that have already done the hard work: you've consulted a salary survey, looked at the market, talked to your board, and you know what your entry-level and most senior roles should pay. What you need now is a consistent grid that connects those two points β one that you can defend internally and apply fairly across all roles.
If you don't yet know what your floor and ceiling should be, try our PPP-calibrated version or our UN PAI version, which derive starting points from cost-of-living data.
This tool does not tell you what to pay. It assumes you already know. It just builds the structure consistently from your inputs.
Used to shape grade titles and typical role examples. The salary figures come entirely from your inputs below β not from any data about your organisation type.
Organisation name optional
Used only in the report header.
Describe your organisation optional β helps with titles
A sentence or two. Used only to help the AI generate appropriate grade titles and role examples β e.g. "An international humanitarian NGO working in food security across East Africa" or "A social enterprise running vocational training programmes in West Africa."
Currency
All salary figures will be shown in this currency. Enter your salary anchors below in the same currency.
Step 2 of 2 β Your salary anchors & grid shape
Set your floor and senior anchor
These two numbers define the outer bounds of your grid. Everything in between is calculated automatically using a geometric formula. Enter annual gross salaries in the currency you selected above.
Lowest salary β Grade 1, Step 1
The absolute minimum in your organisation. The starting salary for your most junior role, at the lowest step.
$
Senior anchor β Top grade, Step 1
The entry point of your most senior grade. Not the very top of the grid β the starting step of the highest grade.
$
Number of grade levels
How many rungs between your floor and senior anchor? Intermediate grades are spaced geometrically.
5grades
2 β 12
2 flat5812 large
Steps within each grade
Pay points within a single grade, reflecting progression through experience or performance. Three to five steps is most common.
4steps per grade
2 β 15
2 minimal581215 detailed
Step increment
Percentage increase from one step to the next within a grade. 5β7% is most common.
6% per step
3% β 12%
3% tight5%8%12% steep
Grade spread shape
Should the pay range within each grade be the same width at all levels, or wider for senior grades?
Flat
Same spread at every grade level. Simpler and more transparent.
Widening
Junior grades tight; senior grades wider. Most common β reflects negotiation latitude at senior levels.
Narrowing
Wider band at entry; tighter at top. Less common β signals senior roles have less negotiation room.
Employer cost load optional
Add a percentage on top of each salary to show true employment cost β pension, health cover, social security, etc. Set to 0 for base salary only.
0% employer cost load
0% β 40%
0% base only10%20%40%
Other cities where you have staff optional
If you have staff in other locations, add them here. Salaries are scaled using World Bank PPP data relative to your primary location. Cities in the same country share the same value.
Primary location required for multi-city
Building your salary gridβ¦
Applying World Bank PPP data for your locations
Reading cost-of-living data for your cities
Applying sector positioning and PPP calibration
Calculating grade anchors and compression ratio
Spacing steps within each grade geometrically
Generating titles and typical role examples
Finalising and formatting your grid
β Important β please read before using this grid
This is a principled estimate based on country-level purchasing power data and nonprofit sector norms β not a market salary survey. When we say "market", we mean the nonprofit and social sector market, not a blended average across private sector, government, and NGOs. The grid is a starting point for internal discussion, not a substitute for professional benchmarking or HR advice. It does not account for local labour market dynamics, skills scarcity in specific roles, individual performance differentials, benefits package values, tax structures, or collective bargaining agreements. Salary decisions affect real people's lives β please use this tool responsibly, and supplement it with local expertise and, where possible, a sector-specific salary survey.
A salary grid is not a decision β it's a starting point. Here's how to move from this output to something you can actually use.
1
Sense-check the floor and ceiling
Look at Grade 1, Step 1 β the absolute entry salary. Does it feel right for your city and sector? If it's too low, consider moving up one positioning level or adjusting the compression ratio. If it's too high for your budget, the living wage anchor may be more appropriate for now. Then look at the top of the grid: could you realistically pay your most senior leader that amount?
2
Map your current team onto the grid
Before sharing externally, plot every current staff member onto it. Note who falls below the grade minimum, who is above the grade maximum, and who is at an unusual step. People below the range floor need a pay rise to bring them into band. People above the ceiling ("red-circled") are a more sensitive conversation β typically their pay is frozen until the grid catches up.
3
Check it against one or two real data points
Search one or two roles on a local job board or sector salary resource (Devex, BOND, ReliefWeb, Glassdoor for your sector). Do the step values for those roles feel in the right neighbourhood? You're not looking for an exact match β you're checking for a major mismatch that would suggest the positioning or PPP calibration is off for your specific context.
4
Decide on grade assignment criteria
The grid shows ranges β it doesn't tell you which grade a role belongs in. You need a simple job grading approach: typically based on scope of responsibility, level of supervision, decision-making authority, and required qualifications. Even a one-page grading rubric makes this consistent and defensible. Without it, grade assignment becomes arbitrary and breeds resentment.
5
Get board sign-off before sharing with staff
If this grid will be used to make actual pay decisions, your board needs to approve it β particularly the top of the range, which constrains executive pay. Boards often have strong views on compression ratios and on whether leadership salaries are appropriate given donor expectations. Get alignment before staff see numbers.
6
Most common adjustments people make
After seeing a first grid, organisations most often: (a) increase the compression ratio β the initial ceiling felt too low for senior roles; (b) adjust the step count β either more steps for longer progression paths, or fewer for simplicity; (c) shift the positioning up one level β the P25 floor felt embarrassingly low once they saw real numbers; (d) add a separate scale for a specific role family (e.g. finance or tech) that competes in a different market.
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Questions to bring to an HR advisor or compensation specialist
If you're commissioning professional advice, come prepared with: your current pay distribution, any existing grade structure or job titles, the roles that are hardest to hire and retain, your budget envelope for total salary cost, and whether you operate under any donor restrictions on pay levels. A specialist can validate the structure, advise on grade overlap, and help you design a transition plan for existing staff.
Benefits & employment conditions
Statutory minimums and sector norms for each of your locations, researched from live sources by Perplexity AI. Verify locally before making HR decisions β legislation changes frequently. Confidence level noted on each card.
Sources used by Perplexity
About this tool
Salary Grid Generator (manual entry) is a free tool built for the social sector. It takes user-provided salary anchors and fills in a complete grade structure using a geometric formula. Salary figures are calculated entirely in JavaScript β AI is used only for grade titles, role descriptions, and notes. This tool is provided free of charge with no warranty. The authors accept no liability for decisions made on the basis of this output. It does not replace professional compensation consultancy.
Data: No external benchmarking data is used. Salary figures derive entirely from the floor and senior anchor you provide. Other-city columns (if used) are scaled using World Bank PPP data (PA.NUS.PPPC.RF, 2024). AI model: claude-sonnet-4-6 (Anthropic).
Transparency
About the method
This version uses no external benchmarking data. Your salary figures come entirely from the two anchors you provide. This page explains how they are used to build the full grid.
What this tool does
You provide two numbers: the floor salary (Grade 1, Step 1) and a senior anchor (Top grade, Step 1 β the entry point of your most senior grade). The tool uses a geometric formula to fill in every grade and step between them. No cost-of-living data, no positioning assumptions, no external benchmarks. This is the same method professional compensation specialists use to build pay scales from known endpoints.
Step 1 β Your anchors set the outer bounds
Your floor salary becomes Grade 1, Step 1. Your senior anchor becomes Step 1 of the top grade. The ratio between them β senior Γ· floor β is the implied compression. A floor of $24,000 and a senior anchor of $120,000 gives a 5Γ implied ratio. The actual top-to-bottom compression is slightly higher due to within-grade step progression, and is shown in the results header.
Step 2 β Grade midpoints progress geometrically
From your two anchors, midpoints for intermediate grades are spaced geometrically β each grade's midpoint is a fixed multiple of the previous one. This means the percentage increase between consecutive grades is consistent, producing a structure that feels fair and explainable at every level.
Step 3 β Steps fill each grade geometrically
Within each grade, steps are spaced geometrically from range minimum to maximum. The step increment (e.g. 6%) sets the approximate percentage increase per step. The spread shape (flat, widening, or narrowing) controls how wide each grade's band is relative to its midpoint β widening gives senior grades more negotiation room and is most common in the sector.
Step 4 β AI for qualitative content only
Once all figures are calculated in JavaScript, Claude (Anthropic) is called with the finished grid and told explicitly not to change any numbers. Its only job: assign grade titles, write typical role examples based on your organisation description, and draft the notes paragraph. Salary figures are identical for identical inputs β AI variability only affects labels.
Does not: calculate, change, or validate any salary figure. All numbers are pre-calculated before Claude is involved.
Other-city columns
If you add other locations, salaries are scaled using World Bank PPP ratios relative to your primary city. This is country-level data β all cities in the same country share the same value. The scaling is shown in each column header. For manual anchors per additional city, run the tool separately.
Data sources
Your salary anchors
All HQ salary figures derive entirely from the floor and senior anchor you provide. No external data is used to set or adjust these figures.
World Bank WDI β PA.NUS.PPPC.RF
Used only for other-city scaling. Country-level PPP index, 2024 data, 130+ countries. data.worldbank.org
Claude (Anthropic)
Used for grade titles, role examples, and notes only. All salary figures pre-calculated. Model: claude-sonnet-4-6.
Perplexity AI (sonar model)
Used for the benefits and employment conditions section. Searches live web sources. Source URLs cited on each card.
Known limitations
The tool is only as good as your anchors
If your floor or senior anchor is wrong, the entire grid inherits that error. This tool assumes you've established appropriate anchors through consultation, surveys, or expert advice.
Actual compression exceeds implied ratio
The achieved top-to-bottom compression is typically higher than senior Γ· floor because of within-grade step progression. It's always shown in the results header.
Other-city scaling is approximate
World Bank PPP is country-level and measures purchasing power parity, not labour market rates. Use other-city columns as indicative only.
Tax and benefits not included by default
The grid shows gross base salaries. Use the employer cost load setting to add a benefits uplift if needed.
AI can be wrong on qualitative content
Salary figures are deterministic β same inputs, same numbers. But Claude generates titles and notes based on your description and can make mistakes. Always review before sharing.
Share your feedback
Help us improve the Salary Grid Generator. What worked? What didn't? What's missing?
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