i
Before the
FEDERAL COMMUNICATIONS COMMISSION
Washington, DC 20554
In the Matter of
Connect America Fund
A National Broadband Plan for Our Future
Establishing Just and Reasonable Rates for Local
Exchange Carriers
High-Cost Universal Service Support
Developing an Unified Intercarrier
Compensation Regime
Federal-State Joint Board on Universal Service
Lifeline and Link-Up
Universal Service Reform – Mobility Fund
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)
)
)
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)
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)
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WC Docket No. 10-90
GN Docket No. 09-51
WC Docket No. 07-135
WC Docket No. 05-337
CC Docket No. 01-92
CC Docket No. 96-45
WC Docket No. 03-109
WT Docket No. 10-208
COMMENTS
of
SCIO MUTUAL TELEPHONE ASSOCIATION
ii
TABLE OF CONTENTS
INTRODUCTION AND SUMMARY ..................................................................................... iii
I. ANALYSIS PERFORMED BY SCIO ..........................................................................1
II. THE FCC’S REGRESSION ANALYSIS UTILIZES INCORRECT DATA ...........2
III. THE MODEL DOES NOT YIELD CONSISTENT RESULTS FOR
SIMILARLY SITUATED COMPANIES.....................................................................2
IV. THE LIMITATIONS ARE APPLIED INCORRECTLY TO THE HIGH
COST LOOP SUPPORT ALGORITHM .....................................................................4
V. THE LIMITATIONS ARE MISSING CRITICAL COMPONENTS .......................7
VI. THE FCC’S REGRESSION ANALYSIS DOES NOT APPROPRIATELY
CALCULATE LIMITATIONS ON DEPRECIATION EXPENSE ..........................8
VII. CONCLUSIONS .............................................................................................................9
iii
Introduction and Summary
The Federal Communications Commission’s (Commission or FCC) Report and Order
and FNPRM1 in the above captioned proceeding requests comment on proposed changes to the
existing Universal Service Fund (USF) and Intercarrier Compensation (ICC) mechanisms for
rural rate-of-return carriers, among other issues. Specifically, the FCC requests comments on
Sections XVII.A-K of the FNPRM, which address a wide variety of USF related issues.
Scio Mutual Telephone Association2 (Scio) submits these comments for the FCC’s
consideration. Scio is a rural telecommunications provider serving 1,585 voice access lines and
930 broadband customers in the State of Oregon. The following characteristics are true of Scio:
Scio is the Carrier of Last Resort designated by the Oregon Public Utilities Commission,
which legally obligates the company to provide telecommunications service to all
requesting customers within its service territory.
Scio is the Eligible Telecommunications Carrier (ETC) determined by the Oregon Public
Utilities Commission to provide universal service within the company’s designated
service territory.
1 In the Matter of Connect America Fund, WC Docket No. 10-90, A National Broadband Plan for Our Future, GN
Docket No. 09-51, Establishing Just and Reasonable Rates for Local Exchange Carriers, WC Docket No. 07-135,
High-Cost Universal Service Support, WC Docket No. 05-337, Developing an Unified Intercarrier Compensation
Regime, CC Docket No. 01-92, Federal-State Joint Board on Universal Service, CC Docket No. 96-45, Lifeline and
Link-Up, WC Docket No. 03-109, Universal Service Reform – Mobility Fund, WT Docket No. 10-208, Report and
Order and Further Notice of Proposed Rulemaking and Further Notice of Proposed Rulemaking, FCC 11-161 (rel.
November 18, 2011) (Report and Order and FNPRM).
2 Scio, incorporated in 1932, is located in the northwest region of Oregon and serves an area of 103 square miles
within Linn County, 25 miles southeast of Salem and 69 miles southeast of Portland. As of 2010 census, the
population within the city limits of Scio is 838 and an estimated 3,000 people in the service territory. The service
territory is located in a mountainous region with solid rock subsoil with clay and rock topsoil surrounding plains
areas with loam topsoil and cemented round rock subsoil.
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Scio receives High Cost Support from the Federal Universal Service Fund. This support
totaled 2,010,867in 20103 and comprised over 58% of Scio’s revenues in 2010. Support
came from the following sources:
o High Cost Loop Support (HCLS) $1,.325,067
o Safety Net Additive (SNA) $27,024
o Interstate Common Line Support (ICLS) $576,624
o Local Switching Support (LSS) $82,152
Scio generates substantial revenues from providing intrastate switched access and
reciprocal compensation services. In 2010 intrastate switched access and net reciprocal
compensation revenues totaled $410,389.
Scio provides voice and broadband services to schools, libraries, rural health care
facilities, governmental agencies, and/or other anchor institutions within its service
territory.
Scio is one of the largest employers in the company’s rural service territory, providing
jobs and financial stability in rural areas of Northwest Oregon. In 2011, Scio employed
11 people on a full and/or part time base and provided combined payroll and benefits of
$952,997.
Scio has deployed substantial financial and human resources to provide voice and
broadband services under the existing rate of return rules prescribed by the FCC and by
3 2010 revenues are used throughout these comments because final 2011 numbers are not yet known. We believe
that 2010 revenues are reasonably representative of 2011.
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the Oregon Public Utilities Commission. In 2010, Scio had regulated capital investment
of $18,714,043 and now has 1,060 subscribers on fiber to the home.
Scio would not have had the financial resources to deploy and maintain either voice or
broadband services without rate of return regulation and the support of the Universal
Service Fund under the existing rules.
Scio is very concerned with the potential financial implications of the Report and Order
and FNPRM and the impact they will have on Scio’s ability to continue to provide high
quality voice and broadband services at the public interest standards established by the
Commission.
In these comments, Scio outlines the impacts that adoption of the limitations on capital
and operating expenses, as proposed in the Report and Order and FNPRM, would have on its
financial results.
1
Before the
FEDERAL COMMUNICATIONS COMMISSION
Washington, DC 20554
In the Matter of
Connect America Fund
A National Broadband Plan for Our
Future
Establishing Just and Reasonable Rates
for Local Exchange Carriers
High-Cost Universal Service Support
Developing an Unified Intercarrier
Compensation Regime
Federal-State Joint Board on Universal
Service
Lifeline and Link-Up
Universal Service Reform – Mobility
Fund
)
)
)
)
)
)
)
)
)
)
)
)
)
)
)
)
)
)
)
WC Docket No. 10-90
GN Docket No. 09-51
WC Docket No. 07-135
WC Docket No. 05-337
CC Docket No. 01-92
CC Docket No. 96-45
WC Docket No. 03-109
WT Docket No. 10-208
COMMENTS
of
SCIO MUTUAL TELEPHONE COMPANY
I. Analysis Performed by SCIO
In order to provide relevant financial context to the FCC in these comments, Scio
engaged Moss Adams LLP4 to perform a detailed financial analysis of the potential impacts of
the limitations on capital and operating expenses proposed in the Report and Order and FNPRM.
This analysis primarily focused on the impacts of the proposed regression analysis identified in
4 Moss Adams LLP (Moss Adams) is the 11th largest accounting and consulting firm in the United States, with more
than 225 partners and 1,800 staff. Moss Adams’ Telecom Group has served the telecommunications industry since
1957. Today, they provide audit, tax, and consulting services to more than 80 small and mid-sized
telecommunications carriers throughout the United States and its territories.
2
Appendix H to the Report and Order and FNPRM. This analysis was performed using Scio data
used by, and provided by, the FCC in the development of its regression analysis. In doing so,
Moss Adams recreated the regression analysis performed by the FCC and reproduced the same
results. In addition, Moss Adams also utilized other information generally available from Scio in
the analysis. The following comments include our overall assessment of the FCC’s regression
analysis and provide a summary overview of the financial impacts on Scio, including the impacts
of changes in the analysis proposed by Scio.
II. The FCC’s Regression Analysis Utilizes Incorrect Data
The census data that the Commission uses as inputs to its model in the Report and Order
and FNPRM are subject to a substantial degree of error. In any model, where there are errors or
inaccuracies in the inputs, those data flaws will also create errors or inaccuracies in the outputs
of the model. The Report and Order and FNPRM relies on significantly flawed data, and
therefore produces similarly flawed results.
Even when the correct study area boundary is used to collect the census data used for the
FCC model inputs, the process still produces substantial input errors. Census block boundaries
and study area boundaries are not always coterminous. Applying the FCC’s methodology, where
a study area boundary contains the centriod of a particular census block, that census block data is
counted for the carrier as if the entire block was served. For carriers like Scio which serve low
density areas adjacent to high-density areas, this introduces significant errors in inputs.
III. The Model Does Not Yield Consistent Results for Similarly Situated
Companies
Scio notes that the FCC’s model used to perform the regression analysis does not take
into account the length of loops – a major factor leading to high loop costs. In Scio’s case, its
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approximate average loop length is 5 miles, meaning that it has to build 5 miles of cable plant to
serve an individual customer. The model also does not take into account unusual terrain
conditions such as rock that must be cut or bored to bury loops. Scio estimates that the rocky
conditions throughout much of the exchange area adds an additional $17 per foot or $89,000 per
mile in boring costs of burying fiber and that it sometimes takes a full day to cut through a few
hundered feet of rock to bury a loop. Scio points out that when comparing Scio to similarly
situated companies like those listed in the table below, companies with higher concentrations of
loops had significantly higher cable and wire facility (CWF) caps than Scio. Noted elsewhere in
these comments, the limitation on Scio’s CWF plant yields devastating impacts to the company.
Scio’s service area has 15.56 loops per square mile. Scio has a ceiling or cap on its cable
and wire loop facilities of $92,514 per mile. The table provided compares loops, land area
served and the resulting caps under the proposed regression model. The table supports Scio’s
position that areas with few subscribers, or loops, per mile necessitate higher values under the
regression caps and that caps should be comparable for similarly situated companies. However,
the table shows contrary results. The table demonstrates that of the six companies listed, four
have more loops per mile, (i.e., have a higher population density than Scio) however all four
have significantly higher caps per mile. Specifically, Example E Telephone with 38.91 loops per
mile, which is very similar to the total loops of Scio (1,574 for Example E versus 1,608 for Scio
yields a significantly higher cap. The regression model yields a cap of $217,934 per mile for
Example E Telephone, $125,420 more per mile than Scio even though Example E has a more
densely populated area. Scio points out that utilizing the same $217,934 per mile cap for its area
would yield a loop cable and wire facility investment cap of $22,526,674, $12,964,002 or 136%,
higher than its current cap and much more consistent with Scio’s actual investment in cable and
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wire facilities. Scio also points out that Example A which has a density less than Scio’s density
(2.96 loops per mile for Example A), has a cap that is up to 16 times lower than the companies
depicted in the table provided with more loops per mile. This is yet another example of the
regression analysis not producing consistent results for similarly situated companies.
There are several ways to improve the FCC’s regression model. Scio and other carriers
can provide the FCC with average loop lengths and other relevant data similar to what the
industry does for the United States Department of Agriculture Rural Development Utilities
Program Form 479. Because loop lengths are a major component of loop cost, is a critical
component that must be included in order for the model to work accurately. Terrain data is also
not included in the model, other than percentage of water in the study area, which is not a
significant driver of loop costs.
Loops Land Area
AL1 ‐ FCC Cap
(Est.) Cap/Mile Loops/Mile
Example A
1,110
374.39
9,953,892
26,587
2.96
Scio
1,608
103.36
9,562,672
92,514
15.56
Example B
1,479
35.60
6,852,993
192,481
41.54
Example C
9,675
81.71
36,256,650
443,716
118.40
Example D
2,424
49.06
10,773,032
219,600
49.41
Example E
1,574
40.45
8,816,398
217,934
38.91
Example E Cap/Mile for Scio =
22,526,674
IV. The Limitations Are Applied Incorrectly to the High Cost Loop Support
Algorithm
Scio believes there are three accounting issues that must be addressed in the calculation
and application of the proposed regression-based limitations. First, the High Cost Loop Support
5
(“HCLS”) data inputs (“data lines” or “DL”) should be limited, not the outputs (“algorithm
lines” or “AL”). Second, the limitations must take into account the impact of accumulated
depreciation and other Part 32 accounts on the calculation of support. Third, the methodology
used to calculate the limitations on depreciation expense must be modified.
Scio believes that the limitations should be applied to the HCLS data lines instead of the
algorithm lines, which would allow the 26 step algorithm to work as designed. The current
limitation of the algorithm lines does not account for the interrelationship between many of the
data lines used in the calculation of support. It should be noted that all of the algorithm lines are
calculations based on various data lines, so any proposed limitations can also be accomplished
by adjusting the data lines. As currently proposed, the FCC’s regression model limits outputs,
rather than limiting inputs and allowing the inputs to be run through the model. An excellent
example of this is AL 3, also referred to as the “A” Factor, which is calculated as Cable and Wire
Facilities (CWF) divided by Total CWF. The “A” Factor is used in the allocation of expenses
associated with CWF. AL 3 is one of several algorithm steps that uses both AL and DL inputs to
produce the result; in this case AL1, DL 255 (Account 2400 - Total CWF) and DL 815 (Account
2680 – Amortizable Tangible Assets – CWF). The FCC’s proposed treatment only limits the
AL1 amount, however, neither DL 255 (which includes AL1) nor DL 815 are adjusted. As a
result, the algorithm is not allowed to calculate support as it was intended and produces an
incorrect result.
This is extremely significant to Scio. Prior to regression caps, 2010 Scio data at a
national average cost per loop of $509.06, yielded estimated HCLS of $1,403,889. The proposed
regression caps, taking only AL1 – CWF assigned to Cat 1.0 into consideration which is a
proposed reduction of $5,920,322, reduced HCLS to $742,578, a reduction of $661,311 or
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47.11%. A significant driver in this reduction was the fact that AL3 was erroneously adjusted.
AL3, prior to the regression caps, was 97.38%, which dropped to 60.14% after the caps. AL3,
referred to as the “A” factor, represents the CWF loop percentage of the carrier. The higher this
amount, the more plant and expenses are allocated to a carrier’s study area cost per loop,
increasing their support. The FCC’s approach incorrectly impacts this factor and significantly
impacts Scio. Again, AL3 is just one example of this inappropriate result and Scio firmly
believes that applying caps to the DL lines will resolve this error.
While further comments will show that other HCLS inputs, such as accumulated
depreciation, need to be taken into consideration while applying the proposed FCC regression
caps, the following example shows the specific impact of removing the capped investment for all
of the appropriate data lines and allowing the HCLS algorithm to work as intended. Instead of
removing $5,920,322 from AL1- CWF assigned to Cat 1.0, AL1 should not be adjusted and the
following Data Lines should be reduced instead by this same $5,920,322:
DL 160 – Account 2001 – Total Plant in Service
DL 255 – Account 2410 – Total CWF
DL 700 – Cost Study Average CWF – Total Account 2410
DL 710 – Cost Study Average CWF Cat 1 – Total Subscriber Line Plant
Doing so results in adjusted HCLS of $841,510, $98,932 higher than the FCC’s capped
amount. AL3 is a significant driver of this reduction. This inappropriate limitation of AL1
reduces AL3 to 60.14%. If the data lines were capped, AL3 would be a much more appropriate
95.82%.
7
V. The Limitations Are Missing Critical Components
As mentioned above, accumulated depreciation and other Part 32 accounts must be taken
into consideration if the FCC is going to limit the 11 proposed algorithm lines, or follow the
approach to limiting the data lines described above. The FCC’s proposed regression analysis
does not limit the accumulated depreciation related to Scio CWF assets removed via AL1, nor
does it remove amounts from other associated accounts. If the FCC is going to limit AL1, the
following data lines should also be limited:
DL 160 – Account 2001 – Total Plant in Service
DL 190 – Account 3100 – Accumulated Depreciation
DL 255 – Account 2410 – Total CWF
DL 280 – Account 3124 – CWF Accumulated Depreciation
DL 700 – Cost Study Average CWF – Total Account 2410
DL 710 – Cost Study Average CWF Cat 1 – Total Subscriber Line Plant
By not limiting these data lines, the FCC’s regression analysis yields flawed and punitive
results on Scio. In addition, as discussed above, limiting the algorithm lines and not the data
lines does not allow the HCLS algorithm to work as designed. There could be some question as
to how to appropriately limit the accumulated depreciation reported on DL 190 and DL 280, but
this could be handled one of two ways. First, a ratio of the limited investment in the associated
plant account to the total plant account could be developed and applied to the accumulated
depreciation. Alternatively, the limited plant could be handled as a retirement, in which case
Part 32 for retirement accounting would treat the investment as fully depreciated. Whichever
method is selected would be more appropriate than the current approach of ignoring depreciation
reserve and other associated accounts in the algorithm. The limitation of algorithm lines rather
8
than data lines yields inappropriate results and ignores the net book value of the assets being
removed.
This situation is critical to Scio and we continue our example from above to show the
impacts on the company. As before, instead of removing Scio’s $5,920,322 from AL1- CWF
assigned to Cat 1.0, AL1 should not be adjusted and the following Data Lines reduced instead by
this same $5,920,322:
160 – Account 2001 – Total Plant in Service
255 – Account 2410 – Total CWF
700 – Cost Study Average CWF – Total Accounts 2410
710 – Cost Study Average CWF Cat 1 – Total Subscriber Line Plant
The next step is to reduce CWF accumulated depreciation reported on DL 280 and total
company accumulated depreciation reported on DL 190 to reflect the net book value of the assets
removed. For purposes of this example, this was done via a ratio. Scio reported $7,644,000 of
CWF accumulated depreciation on DL 280 and $15,900,451 of total CWF on DL 255,
consequently, Scio’s CWF plant is 48.07% depreciated. Multiplying this 48.07% ratio by the
$5,920,322 of CWF limited results in an accumulated depreciation figure of $2,845,899, which is
the figure used to reduce DL 190 and DL 280.
Doing so results in adjusted HCLS of $1,070,882 for Scio, $447,322 higher than the
FCC’s cap on Scio and an overall $333,007 adjustment to the company.
VI. The FCC’s Regression Analysis Does Not Appropriately Calculate
Limitations on Depreciation Expense
Depreciation expenses have not been properly accounted for in the FCC’s regression
model. Specifically, depreciation expenses should not be analyzed independently via regression,
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as they are a byproduct of the associated plant investment. Instead, depreciation expenses should
be reflected as a function of the asset values removed. The FCC’s current, regression-based
approach results in limitations on depreciation expenses on AL 17 that are excessive and
inconsistent with Part 32 accounting principles. Scio’s depreciation rates are approved by the
state commission and are therefore not subject to unilateral adjustment by the company. Finally,
we are audited annually by an independent CPA firm that verifies the proper use of the approved
depreciation rates, thus there is minimal risk of improper application. Therefore, we recommend
that regression not be used to limit depreciation expense. Instead, we believe that depreciation
expense limitations should be computed as the percentage of limitation of the associated plant
investment multiplied by depreciation expense. .
VII. Conclusions
Scio Mutual Telephone Company appreciates the opportunity to provide these comments
to the FCC. There are simply too few cost-cutting measures available that would enable Scio
Mutual Telephone to withstand the reductions in cost recovery that would stem from the
Commission’s USF and ICC reform measures. Scio has not engaged in practices that result in
the recovery of excessive capital and operating expenses. The company identified in the mid-
2000’s they had to keep up with the current and future bandwidth demand of their members and
began the process of upgrading its facilities to ensure the ability to provision advanced services.
The loss of support outlined above would seriously impact those efforts going forward and put
the quality of service for those in rural northwest Oregon at risk. The company invested in its
network hoping to promote the advancement of the rural communities with the promise of cost
recovery from a variety of sources, including the universal service fund, and a reduction in
support would negatively impact those efforts. Scio Mutual Telephone urges the Commission to
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consider the analyses provided in these comments and reconsider its approach to reform of high
cost support.
January 18, 2012
Respectfully Submitted,
/s/ Tom Barth
SCIO MUTUAL TELEPHONE ASSOCIATION
By:
Tom Barth, General Manager
38982 SE 2nd Avenue
Scio, OR 97374-1100
503.394.3363