Fair Offer, Part IV: Beyond Borders
How to think about location-based salary adjustments
Apr 24, 2025
After covering role, level, and non-cash compensation, we now turn to the final variable: location.
Refresher: an algorithmic approach to comp
All too often, companies design their compensation bands by only using survey data — to “snipe” compensation for every role in every job family, one by one.
Take someone designing compensation — it could be Total Rewards / People Ops, or a Finance / Biz Ops person, or even a VP figuring out how to compensate their team. They start with extremely messy “survey data,” which has been ostensibly parsed and cleaned by the survey data provider; but is usually
- full of gaps and inconsistencies (e.g., a Director getting paid more than a Sr. Director!)
- has a low sample size for most roles
- and has a very wide range with overlapping bands (especially outside of major metros)
- requires dozens of hours of work to triangulate compensation bands for each title, from these scattered and contradictory data points
- and of course, data on non-base salary (bonus, commission, or equity) is virtually non-existent
Some data sets are better than others — e.g., Pave has more data than most, and Carta tends to do equity quite well. But all “comp surveys” fundamentally suffer from this issue due to methodological constraints.
So when you want to set Staff Engineer comp at a Series B company in Memphis, you get a “🤷 Not Enough Sample Size”… or worse, misleading data points.
This is backwards. Your philosophy and framework should generate your compensation bands; benchmarks should inform and validate your bands.
What we do think is useful, is a data science approach, which accounts for each factor. E.g., let’s say
- L6 vs. L5 is a progression of 117% in base salary
- zone 1 vs. zone 4 results in a 20% adjustment
- and a L5 Sr. Software Engineer at Series B in NYC is $165,000
Then:
→ an L6 Staff Engineer at Series B in NYC is $193,000
→ an L6 Staff Engineer at Series B in Memphis is $154,000
This approach is essential to ensure internal consistency, fairness, and equitability. This is what Fair Offer does.
In Part I we discussed why an alternative to just using benchmarks is worth exploring.
In Part II we discussed…
- Determining the “entry-level” salary tied to minimum exempt compensation
- How to plot levels for each Job Family
- The idea of a fixed progression or multiplier across levels for total comp
- A single, simple formula to estimate total compensation
In Part III, we discussed…
- how to take the same “progression” approach to setting base salary
- norms for bonus across levels
- calculating equity / profit share / other “skin in the game”
- translating between equity “target value” in dollars ←→ equity in shares
In Part IV, we’ll discuss…
- the case for cost-of-labor adjustments (COLA)
- converting cost–of-living differences in the US into cost-of-labor adjustments
- taking a more nuanced approach to international COLA
The case for cost-of-labor adjustments (COLA)
The last — and possibly least agreed-upon — element of setting your compensation philosophy and framework is location adjustments.
This is a contentious topic. We’ve heard both employees and people in compensation argue “equal pay for equal work,” which seems very reasonable at first blush. However, we believe that COLA (to some degree) is an essential component of a mature compensation framework. We’ll make three arguments for this.
Argument one: first principles
Let’s say you’re making an offer to two people: one in the US, one abroad (say, Mexico or India). The US base salary is $100,000.
- Should the foreign offers be 100,000 pesos or 100,000 rupees? That's obviously silly, because they’re different currencies.
- Should the foreign offers be $100,000, converted into pesos or rupees? That’s less silly but obviously wildly above market norms.
So… most companies end up with COLA in some format outside the US. OK, so… why not within the US? “Well that’s the same currency!”
But is it? We would pose the question: is a dollar in New York City the same as a dollar in Denver? In Iowa City?
Technically, yes. Practically, not at all.
The challenge, then, is: currencies have ForEx conversion rates. What’s the “conversion rate” for the USD between cities? As we’ll cover below, we do have such a rate: CPI and cost-of-living.
Argument two: based on pragmatism
If you are paying someone the same amount in NYC and Denver, it is guaranteed that you’ll lose out on much of the best talent.
This is because:
- a company can’t afford to pay everyone NYC salaries because it will be structurally cost-disadvantaged vs. competitors in the market
- so, this company might select an “average” level (e.g., “Zone 2 compensation”) and pay that rate across the country
- however, job markets are quite localized — even for knowledge work; so this company is paying well above-market in zone 3 cities (e.g., Des Moines), at-market in zone 2 (e.g., Denver or Chicago), and well below-market in zone 1 cities (e.g., NYC, San Francisco)
- unfortunately — much (not all) of the best talent resides in NYC or SF; which means that this company is systematically opting out of some of the most important labor markets
Argument three: based on empirical observations
This one is simple: almost every company at scale (i.e., >1,000 people) ends up with some sort of location adjustments.
Say what you will about the free market: it finds the optimal solution, through trial-and-error if nothing else. If virtually every successful company ended up with the same policy, it’s probably not the wrong one.
So, if you’re a 100-person company that’s avoiding COLA (but you plan to scale over time to, say, 500+), you’ll face a painful migration for hundreds of employees to a COLA-based system later on. It’s much more painless to take this approach sooner than later, if you can do so simply.
How to set COLA within the US
Because the labor market shifts rapidly, it’s very laggy to only use compensation data to determine COLA.
Instead: given that cost of living eventually flows to cost of labor over time (when a city gets more expenses, salaries have to rise over time to enable people to continue to live there), it’s faster and easier to track CPI to predict how the labor market for that city will move, and hence determine what COLA should be! As a forward-thinking company, this means you can skate to where the puck’s going, not where it is.
First, let’s find a solid (ideally public) source for CPI data. We like Numbeo, and specifically the “Cost of Living + Rent Index.” Of course, there are other good ones so feel free to pick one that works for you.
Second, the best practice is to set Zones for compensation, because a) the delta between an index of 83.7 and 81.1 is not very material, and b) the approach needs to be manageable. Typically, 3-4 Zones is enough for the US; Fair Offer uses:
- Zone 1: index >90 (New York, San Francisco Bay Area)
- Zone 2: index 70 - 90 (secondary cities, e.g., Seattle, Los Angeles)
- Zone 3: index <70 (effectively, anywhere outside of the metro areas in zone 1/2)
But: what should the adjustments be? It doesn’t seem right that some people could make 40% less despite living in a major city (e.g., Atlanta has an index of ~60). And the data also doesn’t bear it out; Atlanta salaries for comparable roles are lower, but not that much lower.
It turns out that COLA is unsurprisingly affected by the principles of economic surplus:
Economic surplus, also known as social surplus, represents the total benefits enjoyed by consumers and producers in a market.
The employee is the producer of labor, and the employer is the consumer of that labor. All the benefit does not accrue to one side; in an efficient market, it gets divided to some reasonable extent.
(This is the final reason for why salaries shouldn’t be flat; the benefits shouldn’t accrue 100% to the producer, either.)
From our experience reviewing compensation at dozens of companies, it’s a good-enough heuristic that this surplus is split roughly down the middle.
To reiterate the earlier point on predicting COLA with CPI adjustments: this also helps with retention. We’ve seen firsthand that many employees in Zone 2+ get frustrated when their city gets more expensive quickly… this means that their cost of living has risen, but the labor markets are still catching up.
Taking a “split the difference” approach to CPI makes it incredibly simple and easy for a company to get ahead of this issue, and proactively update COLA for these cities: compare the CPI index now, compared to the prior period when you set COLA. If a city has moved enough to shift zones, reassign its zone. Otherwise, no change is needed.
Note 1: Generally, if the employee is choosing to move locations, that should come with a change in cash compensation (barring certain exceptions where they’re moving at the request of the company or due to circumstances out of their control).
Note 2: All of the above changes are referring to base salary; bonus, typically expressed as a percent of base salary will end up matching COLA as a result. If you express bonus as a dollar figure, it’s worth adjusting that to match COLA, as well.
Note 3: We generally do not see (and don’t recommend) equity compensation being adjusted for COLA, at least for US residents; the reason is because no one knows where the employee will be living when they “spend” the equity, and vesting schedules make it infeasible to adjust equity over time based on location.
A nuanced approach to international COLA
Indexing to CPI / cost of living differences goes quite far in explaining the differences in pay rates between countries, with two additional, major adjustments.
Much more of “economic surplus” accrues to the employer
In the US, employees capture most of the surplus. Outside the US, employers do.
For example in the US, if a city has a CPI of 70-75, then it might see a 10% adjustment in cost of labor. This is likely due to ease of mobility between regions within the US, leading to a “national” talent market.
Outside the US — with the possible exception of Canada — we see this inverted, and in fact the vast majority accrues to the employer. E.g., Google and Meta (which have sufficient presence that we can run an apples-to-apples comparison) would probably pay 40% less when there’s a 50% COL difference, or 70% less when there’s a 90% COL delta. For all the discussion of a “global” talent market, borders have a material effect on the cost of labor.
“Cost of employment” affects countries with strict employment laws
First, we see that salaries in countries with extensive social safety nets (funded by very expensive payroll taxes) and restrictive worker regulations add a significant “cost of employment.” This makes the same sense as other demand / supply contexts; if a similar product is available from Amazon with free shipping and Etsy with a $10 shipping fee, the Etsy product gets pushed down in price until it reaches some sort of pricing equilibrium.
Similarly: the incremental “total cost” of a salary
- in the US, with added payroll taxes, state & local taxes, typical health benefits, paid time off, etc. is 25-30% for a median exempt employee
- in France, the high payroll taxes (40%+!!), 5 weeks mandated PTO, and months of notice period / severance works out to ~60%
So at first glance, Paris is comparable to Philadelphia or Phoenix based purely on cost of living (indexed at ~60 compared to NYC’s 100), which might justify Zone 4 and a ~30% adjustment. However, the additional ~30% “cost of employment” knocks it down to a Zone 5 (~50% adjustment). This is indeed what we see; e.g., Google and Facebook pay ~50% less in Paris than they do in the SF Bay Area.
Equity norms vary widely across countries and cultures
Most other countries take a very different approach to equity; most simply don’t do it. There are a handful of emerging startup hubs (UK, Israel, Australia / New Zealand, Singapore, China, India) which have seen large exits where it’s slowly starting to become normal to offer and receive equity — especially illiquid equity. But even there, the relative unfamiliarity leads to a bias towards cash compensation.
Combining this with the compliance complexity of issuing equity to international residents, we would tentatively recommend:
- issuing equity in only select regions where there is a critical mass of employees (e.g., if the company has a hub or office there); then it makes sense to structurally issue equity in a compliant way
- err on the side of applying COLA to equity as well as cash compensation for international employees
The totality of cost-of-labor adjustments for the cash in the US, cash abroad, and and equity adjustments are briefly summarized below:
Conclusion: Fair Offer in a nutshell
The insights and writings underlying Fair Offer have been a labor of love for the last ~7 years. Throughout this period, through multiple iterations, it has only become more clear that there are undoubtedly compelling patterns underlying compensation. These patterns enable and unlock an algorithmic approach to paying people which is intrinsically more transparent, consistent, and fair.
This enabled us to take a few thousand data points across public and proprietary data to design a predictive model that can produces millions of combinations: across 250+ titles, 500+ locations, and 30+ company stages (from seed-stage to 90th percentile public companies).
“All models are wrong, but some are useful.” — George Box
We hope you find our model useful.
Share article
Write your description body here.
