The Occupational Requirements Survey: Navigating Its Use in Vocational Expert Testimony

Vocational Testimony in Disability Adjudication

Vocational Experts (VE) providing testimony in a variety of forensic settings have traditionally relied on the Dictionary of Occupational Titles (DOT) and its companion resources (Selected Characteristics of Occupations, Classification of Jobs, etc.) to describe how occupations are generally performed in the national economy. The DOT, first introduced in 1939 and last significantly updated in 1991 (with minor updates in 1998) contains occupational information on 12,761 unique titles. Following the release of the 4^th edition in 1977, the Social Security Administration (SSA) took administrative notice of it as an authoritative reference for occupational information (20 CFR § 404.1566). It was also at this time the SSA first published the medical-vocational grids (Dubin, 2010) cited as critical to providing consistency to disability decisions (Heckler v. Campbell, 1983). Despite it being 35 years since its last significant update in 1991, the SSA continues to recognize the DOT as a reliable source of occupational information, reaffirming its status in a 2025 ruling (SSR 24-3p). This ruling however also invited use of other resources commonly utilized in formulating vocational opinions, specifically noting the Occupational Requirements Survey (ORS).

Prior to SSR 24-3p, a VE providing testimony in SSA disability hearings was permitted to provide testimony that conflicted with the DOT, provided they articulated a basis for this disagreement. Often this was in the form of referencing their own education, training and experience placing individuals into jobs, or pointing towards job analyses and labor market surveys they had conducted in the course of their clinical experience. Similarly, when relying on job numbers, VEs have typically relied on data from the Bureau of Labor Statistics (BLS) with the need to explain how specific functional limitations would reduce the availability of these jobs. But the DOT remained the overriding foundational and authoritative source in decision making, with the Administrative Law Judge (ALJ) typically requesting the VE provide examples of DOT Codes that would serve as occupational options for the claimant. While efforts have been made to replace the DOT, with the most notable effort being the introduction of the O*NET (Mariani, 1999), these have been found insufficient for disability determination due, in part, to lack of quantifiable data and the aggregation of occupations (Truthan & Karman, 2003). Smaller scale attempts have also been made, including in 2024 when the agency moved to strike or eliminate 114 titles deemed isolated and existing in limited numbers from VE testimony (EM-24026), and again in 2025 when it requested increased explanation during VE testimony regarding select occupations that had received widespread skepticism, such as document preparer, addresser, and microfilm processor (EM-24027 REV). With SSR 24-3p, the SSA signaled the beginning of a major shift from the DOT as its sole source of allowable occupational data.

Development of the Occupational Requirements Survey

With the recognition the DOT was rapidly becoming outdated (80% of its titles have not been updated since 1977), the SSA convened a panel of experts in 2009 to develop a replacement for the DOT (tentatively titled the Occupational Information System). The agency entered into an agreement in 2012 with the Department of Labor (DOL) to create a new database of occupational information, and began collecting data in 2015. Rebranded the Occupational Requirements Survey (ORS), the first wave of data became available in 2018, containing information designed to better understand the way work is performed in the modern labor market. The SSA noted in SSR 24-3p (2025) that while the VE was in the best position to determine which occupational resources to utilize, a viable alternative to the DOT for describing jobs is data contained in the ORS. Although ORS data collection had continued for 8 years, it was not until SSR 24-3p became effective January 6, 2025 that many VEs took notice of its value, leading to a newer and expanded understanding of how work activity is performed while also raising concerns regarding its reliability and application. For the ALJ, VE, claimant, and their representative, this marks a time of anxiousness and a marked departure from the traditional way of approaching assessments of employability.

The responsibility for collecting and disseminating data fell to the Bureau of Labor Statistics (BLS). Field economists were employed to contact businesses across the private sector and in state and local government via personal visits, mail, email, phone, and video calls (U.S. Bureau of Labor Statistics, n.d.-c) to obtain information on the physical, mental, and cognitive demands of work, as well as a host of other factors in how work is performed and the requirements for obtaining employment (education and training). Previously, the VE had utilized the DOT to understand most of these same variables, supplementing their understanding of how work was performed through their own in-person job analyses and labor market surveys (LMS). The ORS, in theory, serves as a more current and ongoing LMS. Through interviews with employer representatives, ORS gathers information on how an occupation is performed, allowing the VE to classify the skill and exertion level needed to perform work as it exists in today’s workplace, as opposed to how it was performed when the occupation was last updated in the DOT. Of interest to all parties involved in disability adjudication is that ORS recognizes that some jobs within the same occupational group are performed differently based on the industry setting in which the worker functions and the specific tasks assigned. That is, the exertion and skill level, as well as other key demands of an occupation, might vary among employers and industries. What it does not do however is disclose from which industries (North American Industry Classification Codes) the jobs came, at any level. Still, as each factor examined is reported in a percentage based on whether the respondent reports the variable being required or not and/or as a percentage of time, they can then be utilized by VEs as a basis for eroding job numbers from the larger base of employment as reported by the BLS.

The ORS is viewed as an attractive source of information because it can serve as a ready-to-use, up-to-date LMS. When working with individuals in job placement or engaging in forensic work in tort litigation, the VE may choose to conduct their own LMS geared to a specific client and typically in a specific geographic area. The VE interviews the client, obtains information regarding past work activity, reviews medical files to determine the residual functional capacities, identifies feasible occupations for the client to perform, and then verifies this by doing labor market research, which may include the LMS (Weed & Field, 2001). It has been estimated however that a LMS alone may take 6 hours to complete (Barros, 2012), a length of time not reasonable given the manner in which vocational opinions are rendered in the SSA disability determination process.

In SSA disability appeals, the VE might not have a full picture of the claimant’s vocational history until the hearing itself. Further, it is not until called on to testify when the VE is presented with the functional limitations in the form of a hypothetical. Yet the VE is expected to be able to respond quickly in offering occupational alternatives and associated job numbers. To help expedite this testimony, the VE generally has a spreadsheet prepared ahead of time containing a list of select occupations and its corresponding labor market data. Web and software-based occupational data systems allow the VE to access the DOT, the ORS and job numbers, and the VE may have their own LMS to use for guidance when specific restrictions are given in the judges’ hypothetical. But as the LMS is performed ahead of time, it is unlikely that the VE could anticipate every permutation of hypothetical that might apply to the multiple cases each day in which the VE testifies. ORS data may therefore be a solution, as it covers a wider range of job traits and likely across a more national region than the VE can hope to achieve. This would then allow the VE to rapidly calculate the degree of job erosion based on the specific limitations outlined in the hypothetical. Traditionally, absent a highly detailed LMS, the VE had to generalize their findings or rely on their “professional experience, education, and training” as a basis for their knowledge of how jobs are performed, a rather sweeping statement that, while deemed acceptable by the courts, did little to clarify methodology. Naturally, this is a common focus of cross-examination and subsequent appeal.

The ORS aims to address this gap. The VE can prepare a list of occupations to cite in testimony, and have a starting point for job numbers taken from the BLS. But as additional limitations are added to the hypothetical, the VE can reduce the number of jobs based on actual data from the United States government, which is stated in terms of percentages, duration, weight, education, and skill level. The idea of ORS then is that through up-to-date data, the VE can erode job numbers based on specific functional limitations, and the consistency among the larger population of experts testifying in hearings should increase. Potential flaws in data, or failure of the expert to apply correct data accurately however will have significant consequences for any VE relying solely on the ORS when providing vocational opinions. This is of present concern.

Comparing the use of DOT, ORS, and BLS data

In SSA disability hearings, the VE has traditionally used the DOT to provide information on the demands of jobs, and to match occupations to a hypothetical list of restrictions. The strength of the DOT lies in its data, established through on-site job analysis conducted by trained job analysts (Heitzman et al., 2009). Recognizing that the DOT has not been updated in more than 35 years (with some occupations going even longer without revision), the SSA signified in a 2000 ruling that the VE could offer testimony in conflict with that resource, provided they can explain the basis for this conflict (SSR 00-4p). This ruling was subsequently rescinded in favor of SSR 24-3p, with the later ruling maintaining that the VE can provide information different from occupational resources, again with explanation. In response, the claimant’s representative may question the VE on their methods and sources of data, particularly in regards to how job numbers are calculated and when resources other than the DOT are used as the basis for vocational opinion. Despite no official ruling requiring it, the ALJ has traditionally asked the VE to cite three DOT Codes per hypothetical to support the existence of work that can be performed. The VE may need to prepare data for only a handful of unskilled, sedentary, light, and medium occupations prior to the hearing, since disability determination typically hinges on the ability to perform work at these skill and exertion levels. As additional restrictions are added (e.g. no kneeling, occasional public contact, need for close supervision) determining which occupations remain available to the claimant, and the overall impact on job numbers, becomes increasingly challenging. The ORS may partially solve this problem by allowing the VE to quantify the influence of each restriction. And yet, when considering the following hypotheticals, its use may also be problematic.

Hypothetical 1: The claimant is a younger individual with a high school education and no past work. The ALJ instructs the VE to consider an individual with that profile who is limited to unskilled and light work. A VE might, prior to the introduction of ORS, offer the occupation of “Cashier II (DOT Code 211.462-1010)” as it is defined in the DOT. Turning to the BLS, the VE finds there to be approximately 1,007,370 full-time cashiers utilizing May 2024 data from the Occupational Employment and Wage Survey (U.S. Bureau of Labor Statistics, n.d.-a). Some software and/or web-based programs allow the VE to filter for full-time jobs and estimate numbers by specific DOT Code. The VE would then testify that there are 399,000 full-time cashiers specific to the DOT Code 211.462-010, and assumes that are all unskilled, just as defined in the DOT. The SSA acknowledges that these are estimations only.

If the VE instead uses ORS data, the numbers change significantly. This is because ORS does not consider specific DOT Codes, but rather the larger grouping of occupations under the Standard Classification of Occupations (SOC). The occupation of Cashier falls into the SOC Group “41-2111 Cashiers”, which contains a total of 18 DOT Codes. These include other titles such as auction clerk, ticket seller, toll collector, cashier-checker (as found in a grocery or department store), and a cluster of six very infrequent DOT occupations that are only found in race tracks or off-track betting facilities. Because the entire group is used by the ORS, the VE cannot provide DOT specific job numbers but must provide SOC Group numbers. In this case, the VE would cite the larger group and identify the approximately 1,007,370 full-time (35 or more hours/week) positions. The VE then would apply the ORS data and find that 63% of these positions are performed at the light level, with the rest falling into other exertional categories. This in turn would reduce the job numbers down to 634,643 cashiers. Factoring in the 96% of the jobs in this SOC Code that are identified as being unskilled, and utilizing the statistical method of probability, the final number becomes 609,257. Because this number is based on the aggregate of all DOT Codes in the SOC group, the VE can only testify that there are 609,257 unskilled jobs within the SOC group “41-2111 Cashiers”. The VE cannot definitively identify any particular DOT Code, but instead may cite a “representative” DOT Code. That would most naturally be Cashier (DOT Code 211.462-1010), as this Code matches the hypothetical or it could be any of the other 17 DOT Codes, including those that are more than unskilled or some other exertion level. This opens the door to confusion and almost certainly cross-examination from the claimant (if not the judge themselves). Therefore, it is incumbent upon the VE to explain why the “representative” DOT Code they provide may not match the hypothetical in exertion and skill level.

Hypothetical 2: Again, the claimant is a younger individual with a high school education and no past work. The ALJ now directs the VE to consider an individual who is limited to unskilled and sedentary work. Prior to the ORS, any VE strictly adhering to the DOT could no longer consider Cashier (DOT Code 211.462-1010) as a viable option. But any VE willing to offer an opinion deviating from the DOT, as they are permitted to do, might still offer this occupation, perhaps arguing that some Cashiers work where they could remain seated and lift a negligible amount of weight (e.g. in a parking garage or a cafeteria where they could remain seated and not handle anything beyond a credit card or receipt. In this instance, the VE could still utilize the DOT Code 211.462-010, and explain that based on their clinical experience placing individuals into jobs, or conducting their own LMS, that some percentage of positions are performed in a sedentary manner. Given the likelihood that different VEs would have arrived at different data (based on individual LMS methods), this number would likely vary. Upon cross-examination, the VE would likely need to explain their methodology that led them to deviate from the DOT, an explanation that would surely draw scrutiny, but one that is permissible.

With ORS, there is support for the existence of sedentary cashiers. Again, there are 1,007,370 full-time cashiers under the SOC Group 41-2111. ORS data indicates that just 0.8%, or 8,059, of all jobs in this SOC Group are performed at the sedentary level. This would mean that even if all the sedentary positions were from the occupation of Cashier (DOT Code 211.462-1010), the VE accepting the data would likely testify that there are 8,059 sedentary, unskilled cashier positions. They would have data from a government resource to support their opinion, and all VEs would arrive at the exact same numbers leading to consistency in opinions influencing disability determination. This does assume however, that ORS data is indeed reliable.

Other challenges arise when employing ORS data into testimony.

Potential challenges for the VE when using the ORS

Challenges in explaining data collection methods

Sampling error is the difference between the sample (respondents providing data) and the larger population. A sample may not be truly representative of its population. As sample size increases however, the expectation is that sampling error will decrease, as the more participants in the survey, the more likely they are to approximate the characteristics of the general population.

The BLS acknowledges this issue. Further, ORS data includes information on standard error of measurement, which allows the user to provide an extrapolation of its data to the larger population by identifying a range in the job numbers. To date however, ORS has only described its sampling method at a high level of observations for the entire current panel. No data is released that describes the sample size at each 6-digit SOC level. Nor is there any disclosure about the size of sampling by various industry classifications (i.e. North American Industry Classification Codes) nor any evidence provided based on the ORS sampling that it truly is collecting and reporting data at similar proportions to the OEWS survey.

Further, data collection is done not by observation of the work, and not by the individual performing the work, but rather by some representative of the company who may not actually be familiar with the job. It would appear likely that the estimation on the job requirements may be less reliable than a traditional LMS, which often incorporates not just responses to an interview, but vocational counselor knowledge of how the job is traditionally performed via experience in job placement and job analysis, as well as interviews with the worker and the worker’s immediate supervisor.

Greater confidence emerges when data collection actually corresponds to the similar distribution pattern by NAICS industry reported in the OEWS data collection. ORS data is collected by field economists and typically obtained via interviews and surveys completed by human resources personnel, who are individuals other than the ones actually performing or supervising the occupation being surveyed. Performance of an occupation does vary by the industry context in which the work is performed. This is not being disclosed in reported ORS data. Further, HR personnel typically also process worker compensation claims and uphold OSHA regulations, responsibilities that may alter what data is reported in such areas as Strength. There is evidence in the existing ORS data sets that there are no production occupations (SOC Group 51-xxxx ) that require lifting more than 50 lbs (i.e Medium Strength). This would appear more in line with OSHA regulations than reality.

Challenges with identifying specific occupations

Any testimony using data obtained from a larger SOC group, instead of from a singular, specific DOT title, results in a broader generalization of how jobs are performed. Whereas the DOT has 12,761 unique job titles and descriptions, the SOC has combined and condensed these into 848 detailed civilian occupations (U.S. Bureau of Labor Statistics, n.d.-e). The ORS does not differentiate what occupations were surveyed other than at the SOC level, leading to the potential for the VE to provide testimony on how one specific DOT Code was performed when data was actually gathered from another DOT Code (though this should not happen if the VE is mindful that ORS data applies not to the DOT Code but to the larger SOC group).

In a SOC group with just one DOT, it can be safely concluded that all data obtained by the ORS is specific to that single occupation. There are 216 SOC groups with just one DOT Code. The VE can offer testimony on telephone solicitors, identified in the DOT as sedentary and semiskilled (with a specific vocational preparation of 3). There are an estimated 41,851 full-time telephone solicitor jobs in the national economy. ORS data reports that 50% of workers require up to 1 month to achieve proficiency, meeting the definition for unskilled work. Therefore, the VE could conclude that 21,500 telephone solicitors are unskilled, and 21,500 are more than unskilled (oddly, ORS doesn’t report the skill level of this other 50% of jobs, it is simply left to the VE to deduce). But there is no question that the field economists were surveying telephone solicitors, and that ORS data is specific to telephone solicitors because again, it is the sole DOT Code in the SOC Group.

Conversely, the SOC group for production workers (51-9199) contains 1,530 DOT. These DOT Codes range from SVP 1 (short demonstration) to SVP 8 (4-10 years of training and/or work experience), and from sedentary to very heavy in physical demand. That is to say, likely every combination of skill and exertion level is represented, and within the 1,530 titles are certain to be variations in other physical, mental, cognitive, environmental, and aptitude requirements. Which occupations were specifically surveyed to obtain ORS data, and how many total occupations were queried is information not provided by the ORS data collectors.

ALJs have traditionally requested the VE provide 3 examples of occupations that could be performed under each hypothetical. For a hypothetical limiting the claimant to unskilled and light work, the VE could utilize the DOT to cite the occupations of cashier, ticket seller, and toll collector and turn to the BLS (May 2024 data) to provide job number estimates for each occupation (399,322; 10,590; 5,337 respectively). As each of these occupations are defined in the DOT as unskilled and light, no further reduction in job numbers is required. Utilizing the ORS however would preclude the VE from citing two of these, as all three occupations fall within the same SOC group, and thus become one indistinguishable occupation. There are 823,140 full-time jobs total for this group, and per ORS 63% are light and 96% are unskilled. Using the probability method of calculation, there are 497,835 jobs in this SOC group that are light and unskilled. This equates to approximately 82,586 more jobs than cited using the DOT, but with less specificity on exactly which occupations generate these job numbers.

Challenges With Eroding Job Numbers

Consider another hypothetical situation with a completely made-up occupation and equally conjured (by the authors) ORS data. In testimony, the VE identifies the sedentary occupation of “Plinko Chip Maker” and using BLS data notes that there are 10,000 jobs for this occupation in the national economy. Turning to ORS data, they find that 50% of “Plinko Chip Makers” are sedentary with the other 50% classified as medium. The VE could then testify that there are 5,000 sedentary “Plinko Chip Makers”. But further suppose the ALJ adds to the hypothetical that there are additional limitations of no low postures, no climbing, and no proximity to moving mechanical parts, and that for each of these variables the ORS finds that exactly 50% are present and 50% are not present. It has been proposed that the VE calculate these numbers using the statistical concept of simple probability (Aliff et al., 2024). That is, that it would be expected that 50% of the sedentary “Plinko Chip Maker” jobs would require low postures while 50% would not, and 50% of those sedentary/low posture jobs would require climbing while 50% would not, and so on. The formula would be as follows: 10,000 x 0.5(sedentary) x 0.5 (low postures) x 0.5 (climbing) x 0.5 (moving parts).

Calculating in this manner would result in the VE testifying that there were just 625 “Plinko Chip Makers” that satisfied the totality of the restrictions, a number that would likely be found by the ALJ as insufficient (not existing in significant numbers) to demonstrate the claimant could perform work. The authors take issue with this methodology. Probability assumes that we know nothing about the way an occupation is performed. It is just as possible that the 50% of sedentary “Plinko Chip Makers” are the same ones that do not require low postures, or climbing, or exposure to moving mechanical parts, and that it is the 50% of medium jobs that require all these additional physical demands and that therefore even with these additional restrictions, the 5,000 sedentary “Plinko Chip Makers” remain.

Common sense, along with a review of how jobs are typically performed, suggests that sedentary jobs do not require low postures (made up of crawling, crouching, stooping, and kneeling). Indeed, running an occupational analysis of the DOT finds that there are 1,407 sedentary titles across all levels of SVP. When climbing, stooping, balancing, kneeling, crouching, and crawling are reduced to not present, the total number of sedentary occupational titles is reduced by just 38, for a total of 1,369 titles. When no exposure to moving mechanical parts is added in, only 2 additional titles are removed. The VEs job placement experience would likely be enough to inform them that a sedentary job would not be expected to require the individual to climb or operate machinery.

Conversely, medium jobs commonly require these physical demands. The DOT contains 3,773 medium occupations. Eliminating climbing alone reduces this number to 3,031, while adding in the restriction of no low postures (stoop, kneel, crouch, and crawl) takes the number to 1,543. Even without restrictions to these physical demands, if just medium titles that contain exposure to moving mechanical parts alone were completely eliminated, only 1,430 occupations would remain.

It is clear that sedentary occupations are not impacted by physical limitations in the same way as medium occupations, yet the probability method of calculation assumes they are. The result is that by calculating job erosion using the probability method, instead of 5,000 “Plinko Chip Makers” that meet the outlined restrictions, a dramatically different number of 625 would be offered, a number that would likely result in an ALJ finding that sufficient jobs do not exist for the claimant and the potential for an incorrect disability determination. The ORS recommends multiple approaches to calculating job numbers based on job requirements, one of which is the probability method, which assumes “job requirements exist similarly in different subsets of the population” (U.S. Bureau of Labor Statistics, n.d.-b). While this hypothetical is wholly invented by the authors, applying the same process to real occupational titles has similar impacts.

Relevant Case Law

Because the use of ORS data in SSA disability determination is relatively new, there is little yet in the way of appellate court decisions (or published research for that matter) that might help guide the VE in understanding standards of best practice. A review of established case law may provide some guidance on what occupational resources the VE may employ, the ability of the expert to continue to use their own clinical experiences to formulate opinions that differ from these resources, and what possible objections might be made to the way ORS data is utilized.

Continued use of the DOT

Hall v. Commissioner of Social Security (Hall v. Commissioner of Social Security, No. 3:2023cv01141 - Document 31, 2024). The VE testified that the occupations of marker, ticketer, and routing clerk met the restriction of light work. Indeed, these occupations are identified in the DOT as falling in the light category of exertion. The Plaintiff appealed, pointing to ORS data showing these occupations require lifting 50 pounds or more. The District Court affirmed the decision, finding both the ALJ and VE had correctly relied on DOT descriptions for these jobs.

Implication for the VE: While the DOT has been criticized as being outdated, SSR 24-3p makes it clear that it is still an acceptable source of occupational information (see Chavez v. Berryhill, 2018). In this case, there is a conflict between the DOT and ORS. It is commonplace for the claimant’s attorney to inquire of the VE regarding any conflicts between the DOT and expert testimony. The introduction of ORS data adds another layer to potential conflicts, where the VE may need to respond to questions regarding why they chose one source over another. The VE will be challenged to explain the basis for this choice, and to explain why, regardless of the resource(s) chosen, they may still deviate from any published resource in describing how work is performed. The ability to continue to use the DOT, as well as the ability to instead use the more recent ORS data, does not insulate the VE from questions regarding their basis for concluding how work is performed. Regardless of the occupational resource chosen, the expert can expect questions regarding the validity of the data cited. Conducting their own independent evaluation of the respective occupation will help justify their agreement or differences with the DOT and any alternative resource the claimant’s representative may mention.

Ability of the VE to differentiate from the ORS

Carey v. Apfel (Carey v. Apfel, 2000). The claimant appealed a denial of disability benefits, in part, based on testimony from the VE which conflicted with information found in the DOT. The claimant had a past work history best described as construction labor. The VE testified that he could perform other work with only one arm, including usher, cashier, and ticket seller, and that these jobs existed in significant numbers. Carey appealed based on DOT information which identifies frequent handling and fingering, average finger dexterity, and below average manual dexterity. The court found this non persuasive, reasoning that “social security regulations do not require the ALJ or the vocational expert to rely upon the classifications in the DOT, or that the categorical DOT job descriptions are neither comprehensive nor exclusively probative of a claimant’s ability to perform a particular job.”

Implication for the VE: Rulings like Carey clearly allow for the VE to deviate from the DOT. This is reinforced by SSR 24-3p, where it is specifically noted that the VE can utilize data sources that define exertion, education, and skill level different from agency regulations, but that the VE is expected to explain the basis for the differences. Further, regardless of the source used (DOT, ORS, or some other source), the VE can testify that the occupation is performed in some other way, provided they again explain the basis for this difference. This position is further supported by Haddock v. Apfel, (Haddock v. Apfel, 1999) where it was ruled that any conflict in testimony from the DOT does not preclude the ALJ from relying on VE testimony, provided that the record reflects substantial reason for deviating from this authoritative resource. By record, it is meant that the VE (under SSR 24-3p) is responsible for providing some form of evidence for that difference. The DOT could not possibly be expected to have evaluated every permutation of an occupation. The same is true for the ORS. If it claimed to have done so, it would not be a survey but rather a census, and this is not the case. Unfortunately, the ORS data does not provide information on how many respondents there were for any SOC group, and thus the reliability of the data for generalization purposes comes into question. The VE, by virtue of their training and expertise on occupational resources, job analyses, labor market surveys, and labor market conditions remains best positioned to provide testimony on how a job is performed. ORS data, like the DOT, can provide valuable information, but cannot be relied upon as a definitive resource outweighing VE testimony. The very purpose of VE testimony is to provide more specific information about an occupation than the aging DOT or emerging ORS.

Concerns with ORS source information

Kuleszo v. Barnhart (2002). The ALJ posed a hypothetical of sedentary work with no fine manipulation. The VE testified the claimant could perform work as a cashier (as found in toll booths, parking garages, off-track betting, theaters, and sports arenas) and surveillance system monitor. The VE further opined that there were 100,000 cashiers, and while acknowledging the positions required the manipulation of coins to make change argued that this was “more a gross manipulative type movement”. On cross the VE acknowledged that working with small objects would be fine manipulation, but did not agree that coins were small objects. The VE further opined that while the DOT lists the occupation of cashier as requiring a light physical exertion level, the VE testified that the select positions did not require lifting. The court found that the VEs definition of fingering was at odds with the DOTs definition and that the VE failed to address the standing requirements when identifying this occupation. Finally, the VE testified that he based his job numbers on a conversation he had with an unidentified member of the BLS. The Court found that this testimony could not be considered substantial evidence. “Substantial evidence is more than a scintilla and is such relevant evidence as a reasonable person would accept as adequate to support a conclusion” (Crawford v. Commissioner of Social Security, 2004). In regards to the surveillance monitor position, the VE testified that the position required less than 6 weeks of training. This was considered ambiguous given that unskilled is less than 30 days. Further, while the occupation, as defined in the DOT, requires only below average finger dexterity, this still indicates some level of finger dexterity is required, thus exceeding the limitation of no fine manipulation.

Implication for the VE: The ORS has the potential to provide the detailed information that could have informed the VE’s opinion that there are no cashier jobs that are sedentary and do not require fine manipulation. As previously stated, ORS finds that 0.8%, or 8,440 cashiers, are reported as sedentary. ORS also finds that more than 99.5% require fine manipulation, effectively eliminating all cashier jobs from consideration. The surveillance system monitoring occupations encounters similar issues. With more than 95% requiring fine manipulation, this occupation would similarly be eliminated utilizing ORS data. Kuleszo would appear to be a great example of how detailed information provides for an improved analysis. Certainly it would be anticipated that everyone involved in the hearing process would appreciate its level of detail. Close inspection however highlights a significant issue. Given the VEs testimony was based on a mere conversation with an unidentified individual at the BLS, it is understandable the court found this unpersuasive. Yet the current method of gathering ORS data via a field economist interviewing an individual who may never have seen the position in question performed (U.S. Bureau of Labor Statistics, n.d.-d) hardly seems to exceed the VEs method in Kuleszo.

Combining Resources to Establish Job Numbers

Chavez v. Berryhill (Chavez v. Berryhill, 2018). In this matter, the VE offered two widely varying estimates of the number of jobs available to the claimant, opining that for one particular occupation, bench assembler, there were either 800 or 108,000 jobs. The VE found the lower number based on a DOT-specific estimate implausible, and instead opted for the higher number based on Occupational Employment and Wage Statistics (OEWS), the more likely true estimate of light unskilled bench assemblers. The ALJ accepted this opinion. The appellate court found that this opinion was not based on substantial evidence, as the ALJ had failed to determine if the expert’s numbers were reliable. “The use of one system to supply the job titles and another to provide the number of jobs creates a matching problem: a one-to-one correlation does not exist. When a VE identifies an SOC Code and the number of jobs in that Code, that number approximates (at best) the number of positions within a DOT job group—not the specific DOT job title that the VE identified as suitable for a particular claimant.”

Implication for the VE: SSR 24-3p was introduced 7 years after Chavez, seemingly negating that decision. This newer policy does “not dictate any specific approach to estimating job numbers, and the numbers provided are only general estimates”. That is, the VE can come up with their own method provided they are able to explain the source of their information and basis for their conclusions. “In addition, the VE may cite multiple acceptable sources of occupational data that do not precisely correspond to each other. In some instances, it may be necessary for the VE to explain how they accounted for the differences in classification.”

While this policy would seem to negate the Chavez decision, it does not absolve the VE from having to explain why any chosen methodology, including combining resources, would be reliable. It is possible, for example, that the VE could first use the DOT, then apply the BLS and any software based occupational information program to generate DOT-specific job number estimates, and then reduce the numbers for that DOT utilizing ORS data. The VE could even then reduce or add numbers based on their professional experience. To illustrate, the VE could cite the occupation of fast food cook (DOT Code 313.374-010) defined as skilled (SVP 5) and medium. Using BLS data and filtering for full-time numbers only, the expert may identify 120,603 positions in the national economy. Using ORS data, the expert finds that 43.2% are actually identified as light exertion, while 93% of all jobs are unskilled (SVP 2). Employing the equal distribution method (calculating by probability), the number of light and unskilled jobs would be 48,000 in the national economy. Subsequent questions, such as time off task, may lead the VE to utilize their professional judgment to further reduce these numbers.

While the current policy allows the VE to employ this methodology, Chavez still has implications for the need to explain the method used and its reliability. Simply assuming one can use a calculator to crunch numbers falls well short of this bar and will certainly lead to appeal and potentially to remand.

Discussion

The SSA ruled in SSR 24-3p that “VEs are in the best position to determine the most appropriate sources of data to support the evidence they offer. We expect (VEs) to identify the source of the data they use and, where applicable, to explain their general approach to estimating job numbers”. The interpretation is clear: there is no single method mandated.

What approach ultimately is chosen and how it is accepted by the courts is left to be determined. It may be that only through testing out a method in actual hearings, and waiting to find if any subsequent appeal is successful, will the VE discover what method holds muster. This is a rather frightening proposition. What is clear is the VE must be able to explain their methodology. Recent surveys of VEs (Johnston, 2026) found that only 56% of respondents either agreed or strongly agreed they understood the methods used in obtaining ORS data, only 31% responded affirmatively (agree or strongly agree) they could articulate the reliability and validity of the data, and 45% responded affirmatively that they believed employers provided accurate information (conversely, 51% responded negatively to this question, while 45% responded that they could not explain the reliability and validity of the data). These numbers indicate that in general, the field is not prepared to face cross-examination on data from the ORS. Immersive training on the subject should be the focus of professional organizations concerned with VE testimony, with introductory training supplied in Masters’ level Rehabilitation Counseling programs. The focus of these education should be on methods of data collection, statistical concepts of the dataset, its use in eroding job numbers and potential flaws with simple probability to erode job numbers, and the reinforcing of the value of clinical judgment derived from in-person job analysis and labor market surveys conducted by trained rehabilitation counselors.

As there is some concern about the reliability and validity of information gathered (Johnston, 2025, 2026), independent verification should be obtained by vocational professionals uniquely trained and experienced in performing on-site job analysis. The BLS did conduct a job observation pilot test, again done by field economists, finding that what they saw in person was consistent with employer self-reports (Chang et al., 2016). Yet it is unknown whether the individuals observing the work were trained to perform this work. Rehabilitation counselors are educated to perform this work as part of their Master’s level education, and it has been argued by Gibson (2001) through review of the literature as well as Weed and Field (2001) that subject matter (rehabilitation counselor) experts are best positioned to conduct job analysis. This task is a critical component in vocational rehabilitation (Commission on Rehabilitation Counselor Certification, January 2024) and is covered extensively in the national certification exam (Leahy et al., 2018). Confidence in the data among the very professionals it was designed to be used by may increase via independent study. As the data is ongoing, it is not too late for the BLS to release a request for proposals (RFP) to engage in this study. Short of that, the expert community may need to take the initiative on its own.

Finally, a concern articulated in this paper is the application of the data to an entire SOC Group, as opposed to a specific DOT title. The use of ORS data was triggered by the Social Security Administration for use in its disability determination hearings. As the benchmark for adjudication typically is an individual’s ability to engage in unskilled work at the sedentary, light, and medium levels, any future data collection should disaggregate the data for those select DOT often cited by VEs in supporting their opinions. While no formal study identifying these titles could be found, through informal discussions at conferences, on-line message boards, ALJ feedback, and other sources providing anecdotal information, there are titles generally used across VEs. Examples include cashier, hand packager, parts assembler, ticket taker, housekeeper, order picker, fast foods worker, and dishwasher, among others. As ORS data is incomplete, with many SOC Groups having no data obtained to date, it is clear that data can be accumulated for those occupations most commonly cited in support of testimony. Again, this task should fall to trained job analysts, who by virtue of their clinical experience and formal education, are best positioned to understand how to assess traits required to perform these occupations.

Ultimately certain truisms appear to exist: First, the DOT still has a place in SSA disability adjudication (and in other types of litigation where vocational testimony is sought). The ORS has missing data, aggregates data from large SOC Groups, and completely omits key factors used to identify transferable skills (worker functions, Work Fields, and MPSMS Codes). The DOT fills that gap. It is not denied that the DOT is dated. Yet while the ORS aims to provide an updated and expanded understanding of how work is performed in today’s economy, it lacks elements offered by the DOT. It is therefore left to the VE to decide how multiple sources, including the DOT and ORS, can be effectively commingled to best understand the types of occupations that an individual can perform in light of functional limitations. To do this, a second tenet appears to be true: nothing replaces clinical experience in understanding the world of work. The VE is trained and experienced in placing individuals into jobs, performing on-site job analyses, conducting labor market surveys, and interviewing workers and their supervisors directly. Under SSR 24-3p the VE is deemed to be “in the best position to determine the most appropriate sources of data to support the evidence they offer.” That determination can only be made if the VE, from their clinical experience, is able to substantiate the way in which these resources report how occupations are performed in today’s labor market. The VE would be derelict to simply employ the statistical method of simple probability. This is almost certain to provide imprecise job numbers and negate the very basis for their presence in court - namely, their ability to educate the courts on matters related to employability of individuals with disabilities.

Finally, it appears that whatever the criticisms, the ORS is in play. While the BLS anticipates that Third Wave data will be “complete” by 2031, it is difficult to see how this will happen, at least in terms of reporting all variables traditionally seen as crucial to the VEs testimony. The VE will need to find a way to address a dataset that has not yet been fully completed, a problem not unlike that facing the DOT (where outdated may be seen as equating to incomplete data). Absent a willingness by the Department of Labor to change course in its approach to collecting data, the VE community will need to take it upon themselves to pursue research on its validity and reliability and establish best practices of integrating ORS data into vocational testimony. It is almost certain the appellate courts will be busy until the VE becomes well versed in explaining their chosen methodology and a generally acceptable methodology is established.