Andrew Case v. KILOLO KIJAKAZI, Acting Commissioner of Social Security

United States Court of Appeals
For the Seventh Circuit
Chicago, Illinois 60604
Argued April 25, 2023
Decided August 1, 2023
Before
KENNETH F. RIPPLE, Circuit Judge
AMY J. ST. EVE, Circuit Judge
DORIS L. PRYOR, Circuit Judge
No. 22-2379
ANDREW CASE,
Plaintiff-Appellant,
v.
KILOLO KIJAKAZI,
Acting Commissioner of Social Security,
Defendant-Appellee.
Appeal from the United States District
Court for the Northern District of
Indiana, Fort Wayne Division.
No. 1:21-cv-00051-SLC
Susan Collins,
Magistrate Judge.
O R D E R
Andrew Case, a former construction worker, has physical impairments that
affect his back, left knee, and left shoulder. An administrative law judge (ALJ) denied
his application for Social Security disability benefits after concluding that, despite
Case’s limitations and inability to return to construction work, he could perform other
jobs that exist in significant numbers in the national economy, and thus was not
disabled. This conclusion was based on the testimony of a vocational expert who
provided job-number estimates. Adopting the vocational expert’s estimates over Case’s
NONPRECEDENTIAL DISPOSITION
To be cited only in accordance with F ED. R. APP . P. 32.1

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objection, the ALJ determined that the expert’s testimony was reliable and consistent
with jobs found in the Dictionary of Occupational Titles (DOT). The district court,
proceeding through a magistrate judge with the parties’ consent under 28 U.S.C.
§ 636(c), upheld the ALJ’s decision, and Case appealed. Because substantial evidence
supports the ALJ’s decision that a significant number of jobs exist in the national
economy that someone with Case’s limitations could perform, we affirm.
Background
Case applied for disability insurance benefits and supplemental security income
in 2018. After the agency denied his claim initially and upon reconsideration, Case
received a hearing before an ALJ in 2020.
At the hearing, Case testified that he had previously worked in construction,
welding, and housing manufacturing, but that he could not return to those jobs because
of numerous impairments. He presented evidence of his physical limitations, stemming
largely from degenerative disc disease. He testified that he experienced problems with
his back, left shoulder, and left knee, along with other conditions such as asthma and
hypoglycemia.
Following Case’s testimony, a vocational expert testified about jobs which are
prevalent in the national economy that a hypothetical claimant could perform in light of
various restrictions. The expert testified about the work available to someone with
Case’s age, experience, and physical limitations. The ALJ posed hypothetical examples
of a worker’s limitations. The vocational expert testified that some combinations of
these limitations were work-preclusive, while others would allow the person to perform
jobs that exist in the national economy in significant quantities. The vocational expert
explained that this hypothetical individual could perform such jobs as retail marker,
sales attendant, and bakery conveyor worker. He further testified that, in the national
economy, there were 271,000 retail marker jobs, 210,000 sales attendant jobs, and 18,000
bakery conveyor worker jobs.
On cross examination, Case’s counsel probed the vocational expert’s estimates
and asked the witness to explain his methodology. The vocational expert responded
that he used the “SkillTRAN numbers.” Counsel then questioned whether the expert
agreed that the SkillTRAN software operated by starting with a Standard Occupational

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No. 22-2379 Page 3
Code (SOC) and then allocating job estimates to a DOT title.1 The vocational expert
affirmed. When pressed for more detail, however, regarding how the software
functioned, the vocational expert was unable to describe either the allocation factors or
mathematical formulas that SkillTRAN used to arrive at the DOT numbers. In response
to further questioning by the ALJ, the expert testified that he identified three job
classifications appropriate for the hypothetical claimant the ALJ inquired about and
relied on SkillTRAN software to estimate the availability of the jobs in the national
economy based on government survey data. The expert described SkillTRAN’s role in
his analysis in very broad strokes, explaining why the results were reliable more than
how the software generated those results.
The expert further explained that he relied on his four decades of research and
job counseling experience, as well as his personal observations. He testified that the
estimates the software produced seemed reasonable in light of his four decades’
experience observing these job categories.
The ALJ issued her opinion in August 2020. Following the five-step process
explained in 20 C.F.R. § 404.1520(a)(4), the ALJ concluded that Case is not disabled. At
step one, the ALJ found that Case had not engaged in substantial gainful activity since
his alleged onset date of May 1, 2015. At steps two, the ALJ acknowledged Case’s
physical impairments and chronic fatigue syndrome. At step three, the ALJ determined
that Case’s severe impairments did not meet or equal the severity of the presumptively
disabling impairments listed at 20 C.F.R. Pt. 404, Subpart. P, Appendix 1.
Moving to step four, the ALJ had to first establish Case’s residual functional
capacity, which is the most that he could do given his limitations, and then to evaluate
1 Vocational experts frequently rely on the U.S. Department of Labor’s DOT job classification
system because the Social Security Administration regulations authorize the agency to take
administrative notice of reliable job information from the DOT. See 20 C.F.R. § 404.1566(d)(1). The DOT
divides jobs into groups and describes particular job titles within each group. The DOT, however, does
not provide estimates of the number of positions that exist in the national economy for each job title.
Accordingly, vocational experts will rely on the United States Bureau of Labor Statistics’ Occupational
Employment Statistics (OES), which contains annual employment estimates for 800 occupations. Fetting v.
Kijakazi, 62 F.4th 332, 337 (7th Cir. 2023). OES, however, uses a different classification system from DOT
called Standard Occupational Codes (SOC). See Chavez v. Berryhill, 895 F.3d 962, 965–66 (7th Cir. 2018).
SOC codes sort jobs into broad occupational categories which encompass multiple DOT job titles. Ruenger
v. Kijakazi, 23 F.4th 760, 762 (7th Cir. 2022). Because of this matching problem, vocational experts, when
calculating job number estimates, must convert the information in the OES from the SOC system to the
DOT system. Fetting, 62 F.4th at 337.

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whether Case could perform any relevant past work. The ALJ found Case had the
residual functional capacity to perform light work with various restrictions concluding
that “the claimant can occasionally climb ramps and stairs, he can never climb ladders,
ropes, or scaffolds, he can occasionally balance, stoop and crouch, he can never kneel or
crawl, he can never reach overhead with the bilateral upper extremities, and he should
avoid concentrated exposure to extreme heat, extreme cold, wetness, humidity,
vibration, fumes, odors, dusts, gases, poorly ventilated areas, and hazards such as
unprotected heights and unguarded moving machinery.”
Concluding Case could not perform his past work, the ALJ proceeded to step
five, at which the Commissioner bears the burden of showing that there is work that
exists in significant numbers in the national economy. Relying on the vocational
expert’s testimony at the final step, the ALJ concluded that, in spite of his limitations,
Case could perform certain jobs in the economy—including retail marker, sales
attendant, and bakery conveyor worker—meaning that Case was not disabled.
After the Appeals Council declined review, Case appealed to the district court.
He challenged the residual functional capacity determination on the ground that it did
not account for his need for frequent breaks and time off, and he argued that the
vocational expert’s testimony was insufficient to support the ALJ’s step five conclusion.
The district court concluded that substantial evidence supported both the residual
functional capacity and the step five determination concerning jobs in the national
economy Case could perform.
Discussion
On appeal, Case solely argues that the vocational expert did not establish that his
estimates of job prevalence were the product of a reliable methodology. Because of this
deficit, Case contends, the Acting Commissioner did not meet her burden at step five of
showing that sufficient jobs exist in the national economy that Case can perform with
his residual functional capacity. See 42 U.S.C. § 423(d)(2); 20 CFR § 404.1560(c)(1); Brace
v. Saul, 970 F.3d 818, 820 (7th Cir. 2020). The agency defends the methodology, arguing
that the vocational expert’s testimony provided a sufficiently reliable foundation for the
ALJ’s decision.
This court reviews the ALJ’s decision under the substantial evidence standard,
which is not a high threshold. 42 U.S.C. § 405(g); Biestek v. Berryhill, 139 S. Ct. 1148, 1154
(2019). It requires only enough “relevant evidence as a reasonable mind might accept as

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adequate to support a conclusion.” Biestek, 139 S. Ct. at 1154. With respect to a
vocational expert’s testimony about job prevalence, “the substantial evidence standard
requires the ALJ to ensure that the approximation is the product of a reliable method.”
Chavez v. Berryhill, 895 F.3d 962, 968 (7th Cir. 2018). Thus, the expert’s explanation of the
methodology that he used to produce his estimate must be “reasoned and principled”
enough to instill some confidence that the estimate was not “conjured out of whole
cloth.” Ruenger, 23 F.4th at 763 (quoting Donahue v. Barnhart, 279 F.3d 441, 446 (7th Cir.
2002)).
Case primarily takes issue with the vocational expert’s explanation of
SkillTRAN. As we have explained, there is a mismatch between the DOT codes and
Occupational Employment Survey (OES) data because they use different classification
schemes. See Chavez, 895 F.3d at 965–66. Accordingly, vocational experts must employ
some analytical method to match DOT job categories with OES data on job prevalence.
But Case contends that the reliability of the expert’s method is unknown because he did
not testify clearly about how the SkillTRAN software operates to reconcile the two
classification systems.
The inability of the vocational expert to precisely explain the software’s
algorithms does not render his explanation unreliable. See Fetting, 62 F.4th at 339
(vocational expert not required to a use a market study, computer program, or
publication to make his calculations); Bruno v. Saul, 817 F. App’x 238, 243 (7th Cir. 2020)
(vocational expert’s testimony sufficient, though description of SkillTRAN “did not
reveal the precise mechanics and statistical model involved”); Purdy v. Berryhill,
887 F.3d 7, 16–17 (1st Cir. 2018) (vocational expert not required to “duplicat[e] the
software analysis of the basic material”). At minimum, the vocational expert made clear
that he uses the SkillTRAN approach, and that the software can sometimes directly
estimate how many jobs exist for a DOT code. Other times, the software calculates DOT
estimates by predicting whether certain DOT codes are more likely to be found in some
industries than others. In other words, some of SkillTRAN’s estimates for DOT codes
are straightforward because the software derives its estimates from SOC categories, and
certain SOC categories contain only one DOT code. In other situations, the software
begins with an SOC category whose estimate has been adjusted to reflect the number of
jobs available for that category in a given industry. The software then determines how
that industry-adjusted estimate distributes to its relevant DOT codes by predicting how
likely each DOT job title is to arise in that industry.

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Case insists, however, that the expert must be more specific about the factors and
formulas underlying his analysis, and we agree that the expert could have explained the
SkillTRAN methodology more clearly. See Brace, 970 F.3d at 822 (“Testimony that
incants unelaborated words and phrases such as ‘weighting’ and ‘allocation’ and ‘my
information that I have’ cannot possibly satisfy the substantial-evidence standard.”).
Here, however, the ALJ conducted a deeper inquiry into the vocational expert’s
methodology before relying on it. When questioned, the vocational expert explained
that his estimates were not only the product of the software, but also of his experience
providing job counseling, his prior research, and his observations of the jobs in
question. The vocational expert here explained that SkillTRAN produces consistent data
year over year and that he has personally observed and researched these job categories
through four decades of placing workers in jobs. The ALJ was entitled to conclude that
both the expert’s use of the software and his prior research and professional experience
produced sufficiently reliable estimates.
This supports the ALJ’s finding that the vocational expert’s methodology was
“sufficient” and that his job estimates were not “conjured out of whole cloth.” Ruenger,
23 F.4th at 763; cf. Brace, 970 F.3d at 822 (expert explanation of methodology “entirely
unilluminating”). A vocational expert can buttress estimates from survey data with his
own observations and experience placing people in jobs to provide a “reasoned and
principled explanation.” Chavez, 895 F.3d at 970; see also Fetting, 62 F.4th at 339
(vocational expert’s methodology explanation sufficiently reliable when combined with
testimony of his professional experience).
Finally, Case argues that the ALJ failed to probe the expert’s methodology
enough during the hearing, which had the result of shifting the burden of proof to Case.
See Chavez, 895 F.3d at 970. But the record suggests the ALJ did question the expert’s
methodology at some length, see Ruenger 23 F.4th at 764, and though we would prefer to
see the ALJ push for more specific, responsive answers, the ALJ did not shift the burden
of proof to Case to disprove the existence of sufficient jobs in the national economy.
AFFIRMED

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