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corresp

June 25, 2009

John Cash

Division of Corporation Finance

United States Securities and Exchange Commission

100 F Street, N.E.

Washington, DC 20549-7010

Mail Stop 3561

    RE:

    Quanta Services, Inc.

    Form 10-K for the year ended December 31, 2007

    Definitive Proxy Statement, April 18, 2008

    Form 10-Q for the quarter ended September 30, 2008

    File No. 1-13831

Dear Mr. Cash:

          We are providing the following response to the comment letter dated May 26, 2009 from the
staff (the “Staff”) of the Securities and Exchange Commission (the “Commission”) regarding the Form
10-K for the year ended December 31, 2007, the Definitive Proxy Statement dated April 18, 2008 and
the Form 10-Q for the quarter ended September 30, 2008 filed by Quanta Services, Inc. (“Quanta” or
the “Company”). The following response is keyed to the Staff’s comment, and unless otherwise
stated, all page numbers in our response refer to the respective page numbers in the relevant
filing. For purposes of this letter, references to Quanta’s operating units are intended to mean
those 25 operating segments that comprise Quanta’s Infrastructure Services segment. This response
has been prepared with the expectation that the Company will have the opportunity to discuss with
the Staff information submitted in this response if, following a review of the information, the
Staff has further questions or comments.

Form 10-Q for the period ended September 30, 2008

Notes to the Condensed Consolidated Financial Statements

Note 9. Segment Information, page 25

    1.

    We have reviewed your response to our previous comment in our letter dated February
2, 2009 and appreciate the additional information you have provided. However, it continues
to appear to us that you have not fully demonstrated how you determined it was appropriate
to aggregate the 25 operating units that comprise your Infrastructure Services reportable
segment. Therefore, please address the following items:

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    •

    Please clarify for us what measures or group of measures is used by your CODM
to evaluate the economic performance of your operating segments. In addition,
please provide us with an analysis of these measures for each quarter in the past
two fiscal years as well as the most recent interim period with an explanation of
how you have considered the similarities and differences in these measures when
determining it was appropriate to aggregate your operating segments.

Response:

The primary measures that are used by Quanta’s CODM to evaluate the performance of Quanta’s
operating units are monthly, quarterly and year-to-date revenues, gross profit and operating income
by operating unit and detailed analyses of revenue and gross profit by project at each operating
unit for the applicable reporting period. Each operating unit performs and provides to Quanta a
project-by-project analysis describing the various items impacting project performance for the
period and their effect on billed and unbilled revenue, project costs incurred and estimated to be
incurred and overall project profitability compared to previous expectations. As reflected in our
January 9, 2009 response letter to the Staff, we have previously provided to the Staff, under a
confidential treatment request, various reports provided to Quanta’s CODM labeled Category A,
including a July 2008 example of the monthly CODM package, which evidences that a significant
amount of the information included within Quanta’s CODM package is this type of project level data.
This information provides management’s basis for understanding the overall performance of each
operating unit and its variations from expectations for the applicable reporting period. We note
for the Staff that the monthly CODM package does not include aggregated information by type of work
or geographic location, and also does not include any measures of operating income by project, or
of EBITDA either by operating unit, by geographic location, by project or by type of work, or any
other data that might indicate that a different methodology currently exists for managing Quanta’s
operations other than that currently used for analysis of results by operating unit.

The project-by-project performance measures of revenues and gross profit are key to management’s
analysis of each operating unit’s performance in any given reporting period and we note that
examples of this information are included in the examples of Quanta’s CODM packages that were
previously provided to the Staff on a confidential basis in our January 9, 2009 response to the
Staff. However, for purposes of responding to the Staff’s request for additional information
regarding management’s analysis of performance measures, we believe that such project level
information for each quarter in the past two fiscal years and the most recent interim period would
be too voluminous (e.g., it would present information covering thousands of projects) to provide to
the Staff. In response to the Staff’s request, we have prepared a summary schedule of each of the
measures of revenue, gross profit and operating income by operating unit for each quarter in the
past two fiscal years and the most recent interim period, which we have

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provided as Attachment A to the Staff supplementally by hand delivery and under separate cover,
pursuant to a confidential treatment request under the Freedom of Information Act and applicable
regulations of the Commission (the “Confidential Treatment Request”). Further, we have also
provided to the Staff an analysis of these performance measures in the detailed discussion in
Attachment B to this letter.

The information provided supplementally as Attachment A and the discussion included in Attachment B
illustrates the substantial variability in gross margins and operating income margins that
routinely occurs at the operating unit level. In addition, it illustrates that the variability
occurs between reporting periods for the same operating unit, among operating units that have
similar mixes of services and between operating units with different mixes of services. These
variations also exist whether analyzing margins over sequential periods or on a year-over-year
basis. This variability is a function of the project-by-project nature of the services that each
of Quanta’s operating units provide.

The analyses described in Attachment B are not exhaustive, and their relevance is not limited to
the discussion presented. However, we do believe they provide representative examples of the
variability that exists among all operating units, by type of work and in period-to-period
comparisons. These examples also support the conclusions reached in considering the similarities
and differences in these measures when determining it was appropriate to aggregate Quanta’s
operating segments and why we believe that Quanta’s current enterprise-wide disclosure of revenues
by type of work enhance the financial statement user’s understanding. We believe that the analyses
in Attachment B illustrate that the fundamental similarities underlying Quanta’s operating units
cannot be measured in a simplistic comparison of operating margins. Such an approach would not
lend itself to consideration of the more relevant economic characteristic that is similar across
all operating units, which is the project-by-project performance risk at each of Quanta’s operating
units. Inherent to each project within the specialty contracting industry is a unique set of
performance risks which are associated with, among other things, the complexity of the individual
project requirements, the location and physical conditions of the project site, the need to
coordinate with other contractors, the labor pool involved, the risks of customer outages, the use
of subcontractors, right-of-way requirements, permitting and licensing requirements, the level of
customer change orders, production time frames and completion deadlines as well as the capabilities
of the individual project management teams. These types of project-specific performance risks
represent the similar economic characteristics associated with Quanta’s specialty contracting
services that management considers in evaluating Quanta’s operating units for aggregation.

    •

    Please further explain the statement contained in your response letter dated
December 11, 2008 that, in determining that it was appropriate to aggregate the 25
operating segments into your Infrastructure Services reportable segment, you
concluded that the economic characteristics will be similar over the long-term in
the sense that they are expected to vary.

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Response:

We note the full statement made in our previous letter was as follows: “Accordingly, Quanta
anticipates that its operating units’ economic characteristics will be similar over the long-term
in the sense that they are expected to vary among the operating units and between periods due to
the nature of the work performed.”

The context of this statement was closure to a point discussing that the similarity in long-term
average gross margins is an important factor for aggregation. In this discussion, we noted that
“similarity of gross margins has frequently been discussed as being within 5% or 10%.” The
statement the Staff refers to was included to illustrate that pricing and production risk are
inherent to Quanta’s industry due to the project-by-project nature of Quanta’s work and that the
narrow definition of this economic characteristic was not meaningful in Quanta’s case due to the
significant fluctuations in margins that frequently result from these risks. The intention of this
statement in our previous response was to succinctly convey the same conclusion that is discussed
under the response included in this letter to the first bullet point of the Staff’s comment: that
the project-level risk among all operating units is what creates the similar economic
characteristic associated with margins, which is also what is expected to be similar in both the
near-term and long-term for Quanta’s operating units.

    •

    Tell us how the geographic location of the operating units impacts the results
of the operating unit by addressing the location of each unit, the impact that the
difference in local labor costs may have on your units and the impact of the
region on your revenue stream.

Response:

The geographic location of the operating unit itself does not impact the revenue stream or the
results of the operating unit. As discussed in the above responses, an operating unit’s results
are impacted by the performance and associated risk on each of its individual projects. The aspect
of the geographic location that impacts the projects is not the geographic region within the United
States where each unit is located, but rather the geographic characteristics associated with the
physical location where the work is being performed. Such characteristics include urban versus
rural settings, mountainous versus open terrain, rock versus dirt, or even a location’s
susceptibility to inclement weather. These types of geographic factors are evaluated as a part of
the overall risk that may impact project productivity, which are then considered when pricing the
work to be performed. However, their impacts on productivity vary from project to project, and
therefore the margins on projects can vary significantly due to the inherent risks of performance,
including risks associated with specific locations.

Additionally, in response to the Staff’s request, we have provided to the Staff a listing of the
location of each of Quanta’s operating units in Attachment C. This listing indicates the
location of each of the corporate offices of the operating units, which has minimal correlation
with where the contracted work is actually performed by that operating unit.

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In addition, we have indicated each of the operating unit’s operating locations, some of which may
be used for project-specific purposes. As noted in the listing, most of Quanta’s operating units
have multiple offices and many of them have a presence in numerous states. Many of these offices
overlap the geographic areas of operation for other operating units. To further illustrate how the
geographic location of each operating unit does not impact the results of an operating unit, we
note that all but one of Quanta’s operating units performed work in multiple states during 2008.
Of the total number of operating units, seven performed work in over twenty states and fifteen
performed work in over ten states. Many of those operating units that performed services in less
than ten states performed a significant amount of work across a broad geographic area. For
example, one operating unit whose corporate office is located in Colorado performed work in five
states: Colorado, California, Nevada, Massachusetts and Rhode Island. Another operating unit whose
corporate office is located in California performed work in six states: California, Florida,
Maryland, New Mexico, Nevada and Texas.

Regarding the Staff’s inquiry about the impact that the difference in local labor costs may have on
operating units, Quanta does have variable labor costs that may be impacted by the geographic
location of the work. However, factors other than the geographic location of the work also impact
labor costs such as the mix of skill levels required for a particular project. None of these
factors directly impact the margins for the work that Quanta performs. Numerous factors are
considered when deriving the pricing for a particular project such as equipment, subcontractors,
and materials, with labor costs being just one of the many factors considered when deriving the
costs and risks associated with performing a particular type of project. Local operating unit
management considers all such factors, along with customer expectations, to determine the pricing
for each project.

We note for the Staff that financial information is not aggregated by geographic region on a
regular basis by Quanta, and it is not provided to the CODM or any other level of management for
the purpose of allocating resources or managing Quanta’s operations. We believe that the above
analysis supports Quanta’s aggregation considerations in that it indicates how the management of
Quanta’s organization by some defined geographic region is not supportable as each operating unit
functions independently and throughout numerous geographic areas.

    •

    Provide us with a quantified discussion regarding the degree to which your
operating units earn revenue across industry lines. It appears that each of your
operating units is concentrated in one predominant industry.

Response:

As discussed in detail in our response letter to the Staff dated April 20, 2009, Quanta considers
that all of its operating units operate in one industry, which is the specialty contracting service
industry. However, given the Staff’s comment, we presume that the Staff’s reference to “industry”
means a specific type of work or the industry in which

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Quanta’s customers operate. Under that assumption, we respectfully disagree that “each of
[Quanta’s] operating units is concentrated in one predominant industry.” Nineteen of Quanta’s 25
operating units aggregated within the Infrastructure Services segment routinely report revenues
from multiple types of work. However, to address the Staff’s comment under the expressed
assumption, the following discussion focuses on the types of work or contracting services that
Quanta provides to its customers in different industries. Quanta agrees that certain operating
units earn a majority of their revenues from one type of work; however, numerous operating units
exist that have large amounts of revenues from multiple types of work other than the predominant
type of work, which precludes the meaningful segregation of the operating units on the basis of
their predominant type of