Evidence Building
How to Document Compensation Above the 90th BLS Percentile for O-1A When Your Role Is in a New Market
When your O-1A role is in a market with thin BLS coverage or where you have recently relocated, documenting compensation above the 90th percentile requires more than a standard wage table comparison. This guide covers the geographic recalibration methodology, acceptable supplementary sources, and common errors that generate RFEs.
New markets and the high salary criterion
The O-1A high salary criterion under 8 C.F.R. § 214.2(o)(3)(ii)(B)(8) requires demonstrating that the petitioner commands high remuneration relative to others in the same field. USCIS adjudicators apply this standard geographically — compensation is high or not high relative to what others in the same occupation earn in the same labor market, not relative to a national figure. This geographic specificity is generally favorable for petitioners in established metropolitan markets, where the BLS OEWS data provides a 90th percentile benchmark for the metropolitan statistical area. But for petitioners entering a new market — either because they have recently relocated or because they are taking a position in a city or region without robust BLS occupational wage coverage — documenting the geographic benchmark requires additional analysis.
A "new market" for purposes of the high salary criterion means either a market where the petitioner has not previously worked and for which the wage comparison must be established from scratch, or a market where BLS OEWS data is not collected at the metropolitan statistical area level — typically because the MSA is too small or the occupational sample in that area is below the Bureau of Labor Statistics reporting threshold. Both situations require the petitioner's counsel to supplement the standard BLS exhibit with additional geographic analysis, either to establish the correct benchmark for the new location or to construct a proxy benchmark for a thin-data market.
The stakes of getting the geographic benchmark right are higher than many petitioners appreciate. An exhibit that uses national-level wage data when the petitioner works in a lower-cost regional market may appear to show compensation above the 90th percentile nationally while the compensation is not high relative to local peers. Conversely, an exhibit that defaults to national data for a petitioner in a major metro market may understate the relevant 90th percentile threshold and make compensation appear less exceptional than it actually is relative to local peers. The geographic precision of the benchmark has real consequences for whether the criterion is satisfied.
How the regulatory standard maps to geographic data
BLS OEWS data is organized by Standard Occupational Classification code, and for each SOC code the Bureau reports wage percentiles at the national level, the state level, and the metropolitan statistical area level. The MSA-level data is the most specific and most directly applicable to a petitioner working in a defined geographic market. When MSA-level data is available and the sample is sufficient for the Bureau to publish percentile estimates, that data should be the primary benchmark. The MSA that covers the petitioner's work location — not the MSA where the petitioner lives, if different — is the appropriate geographic unit.
When MSA-level data is not available for a specific occupational code in a specific area, there is a hierarchy of fallback options. State-level data is the next most specific; it may not precisely reflect the labor market conditions in a major metro within the state, but it covers the correct jurisdiction. National data is the least specific and should be used only when neither MSA nor state data is available for the relevant SOC code. The petition should explain why each level of data was selected and why more granular data was not available, so that the adjudicator understands the evidence is not being cherry-picked from a more favorable but less applicable benchmark.
One complication in new market situations is that BLS OEWS data has a publication lag. The most recently published survey is typically about 18 months behind the filing date. For a petitioner who relocated to a new market recently, the relevant MSA wage data reflects conditions at the time of the survey, not at the time of filing. In rapidly growing markets — technology corridors, energy hubs, major metro areas with significant recent labor market development — the published data may understate current market wages, and supplementary evidence from more current sources is useful to establish that the petitioner's compensation is high relative to what the market currently pays.
Evidence that establishes the benchmark in thin markets
For markets where BLS OEWS does not publish MSA-level wage data for the relevant occupation, alternative sources establish the geographic benchmark. Professional association salary surveys that include regional breakdowns are a primary resource. The Society for Human Resource Management compensation surveys, the Radford Global Compensation Database (for technology and life sciences roles), and occupation-specific surveys from professional bodies often provide regional wage data at a finer level of geographic detail than BLS, or at minimum provide data broken out by state and company size tier that can be used to construct a benchmark for the relevant market.
Online compensation databases — such as employer-reported wage data submitted to the Department of Labor under H-1B and PERM prevailing wage determinations — provide a contemporaneous market-based benchmark for specific occupations in specific geographic areas. The Foreign Labor Certification Data Center publishes all prevailing wage determinations, and these can be queried by SOC code and geographic area to identify what employers have paid for comparable roles in the same market. This data is particularly useful for thin markets where BLS has not published percentile-level estimates, because the prevailing wage database reflects actual employer wage commitments in the market during the period immediately before filing.
Expert declarations from compensation consultants with regional expertise provide another form of benchmark evidence for thin markets. A compensation consultant who has conducted salary surveys or compensation benchmarking in the relevant market can testify to the wage distribution for the relevant occupational category based on their proprietary data, explaining the methodology and the resulting percentile rankings. This approach requires that the expert's data be more current and geographically specific than BLS data, not simply an assertion that the expert agrees the compensation is high. Declarations that tie the expert's conclusion to specific survey data they have personally reviewed and that state the petitioner's compensation percentile relative to that data are the most persuasive form of expert compensation testimony.
Approaches USCIS consistently rejects
Mixing geographic levels without explanation is the most common error in new market salary exhibits. An exhibit that compares the petitioner's compensation to the national 90th percentile in a region where wages are substantially lower than the national average presents a misleading comparison that adjudicators and USCIS counsel will recognize. If the correct geographic benchmark shows the petitioner's compensation below the 90th percentile but the national benchmark shows it above, using the national benchmark without disclosing that more specific geographic data exists — and explains why the national benchmark is more appropriate — is likely to be viewed as misleading, which undermines the overall credibility of the exhibit.
Using a broad SOC code to inflate the apparent percentile rank of the petitioner's compensation is another consistently rejected approach. If a software engineering manager's compensation is compared against all computer and information systems managers nationally, the comparison group includes roles with substantially different compensation profiles — CISOs at major corporations, IT directors at small businesses — and the resulting percentile ranking does not accurately reflect the petitioner's standing relative to true peers. The most specific applicable SOC code, even if it produces a less favorable percentile, is the correct benchmark. Adjudicators who notice that a broad SOC code was used when a more specific one was available may discount the entire salary exhibit.
Relying on unverifiable salary data from anonymous crowdsourced platforms — salary information from user-submitted databases without employer verification — is regularly discounted. These platforms provide useful background context, but USCIS treats them as anecdotal rather than authoritative compensation data. The BLS, employer prevailing wage submissions, and credentialed compensation surveys are the appropriate sources. If a petitioner's counsel cites data from an online salary aggregator as the primary benchmark, the exhibit does not carry the evidentiary weight that the criterion requires, and the adjudicator is likely to request additional documentation in an RFE.
Building a geographic argument for borderline compensation
When a petitioner's compensation in a new market falls near but not clearly above the 90th percentile for the most specific available geographic benchmark, there are several legitimate techniques for strengthening the exhibit. The first is to document total compensation comprehensively — base, bonus, equity at fair market value, signing bonus amortized over the initial contract period, and employer-paid benefits that are quantifiable and included in comparable compensation surveys. If the comparable survey data includes total cash compensation rather than base salary alone, the comparison should use total cash to match the methodology.
The second technique is to establish that the new market has a wage distribution that is higher than the published BLS benchmark due to recent market developments. If the petitioner relocated to a rapidly growing technology market or energy corridor in the 18 months before filing, the BLS data may reflect an earlier, lower wage distribution. Documentation of wage growth in the market — through Department of Labor prevailing wage determination trends over the period, through industry association surveys that show year-over-year compensation increases in the market, or through expert testimony about market conditions — can support an argument that the petitioner's compensation exceeds the current effective 90th percentile even if it appears close to the published benchmark.
A third technique is to narrow the peer group definition. If the petitioner is in a senior leadership role within a specific industry segment in the new market, the relevant comparison group may be more narrow than the full SOC code population — senior technology executives in a specific sector, senior energy engineers in a specific technical sub-specialty. Establishing a more defined peer group through industry-specific compensation data and expert testimony allows the petition to show that the petitioner's compensation is exceptional relative to the most relevant comparators, even when the broader SOC-level benchmark is less clear-cut.
Preparing a defensible new-market salary exhibit
A well-constructed new market salary exhibit has a clear logical structure: it identifies the SOC code, the geographic market, and explains why that geographic market is the appropriate benchmark; it presents all available geographic levels of BLS data — MSA if available, state if MSA is unavailable, national as context; it supplements BLS data with industry survey data and prevailing wage determination records where relevant; it presents total compensation components with specific dollar amounts and documentation; and it concludes with a calculation showing the petitioner's total compensation as a percentage of the benchmark at the applicable geographic level. The adjudicator should be able to follow the analysis from benchmark selection through compensation calculation without inference gaps.
Where supplementary sources are used, the exhibit should include a brief explanation of each source's methodology and geographic coverage, so the adjudicator can assess the source's relevance and reliability without independent research. A one-paragraph explanation of how a professional association survey collects data, what its geographic coverage is, and how it has been used in similar wage benchmarking contexts is sufficient. The goal is to close the inference gaps that lead to RFEs — if the adjudicator can see exactly where the data comes from and why it applies to the petitioner's situation, the exhibit needs no elaboration in an RFE response.
For petitioners who have recently relocated and whose prior compensation in a different market was substantially above the 90th percentile, it may be worth documenting the prior market compensation as context, showing that the petitioner's earning history establishes a pattern of high compensation. This is not a substitute for demonstrating that current compensation is high relative to current peers in the new market, but it provides useful context for an adjudicator who is trying to assess whether the petitioner's overall compensation trajectory is consistent with extraordinary ability. The prior market evidence should be clearly labeled as historical context and should not be presented as the primary benchmark.
What we typically gather for this kind of case
| Document | Where to source | Why it matters |
|---|---|---|
| Peer-reviewed publications | Web of Science / Scopus exports | Anchors original-contributions and authorship criteria |
| Citation analysis | Google Scholar profile + ESI top-1% data | Quantifies major significance in the field |
| Salary benchmark | BLS OEWS for SOC code + locality | Documents high-salary criterion at 90th-percentile or above |
| Critical-role letters | Direct supervisor + program director | Establishes role's importance, not just title |
What we see go wrong, again and again
- 01Treating extraordinary ability as a credentials checklist rather than a story of field-wide impact.
- 02Submitting bibliometric data (h-index, citation counts) without explaining what makes those numbers high relative to peers in the same sub-field.
- 03Relying on letters from collaborators or co-authors rather than independent experts who can speak to influence.
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