The FCC contracts with CostQuest Associates to create and maintain the cost estimation models. The cost models have been used in the past in establishing FCC subsidies, such as Universal Service Fund payments made to small telephone companies under the ACAM program. For a peek into how the cost models work, this link is from an FCC docket in 2013 when the small telcos challenged some aspects of the cost models. The docket explains some of the basics about of the cost model functions.
This blog is not meant to criticize CostQuest, because no generic nationwide cost model can capture the local nuances that impact the cost of building fiber in a given community. It’s an impossible task. Consider the kinds of unexpected things that engineers encounter all of the time when designing fiber networks:
- We worked in one county where the rural utility poles were in relatively good shape, but the local electric company hadn’t trimmed trees in decades. We found the pole lines were now 15 feet inside heavy woods in much of the fiber construction area.
- We worked in another county where 95% of the county was farmland with deep soil where it was inexpensive to bury fiber. However, a large percentage of homes were along a river in the center of the county that consisted of steep, rocky hills with old crumbling poles.
- We worked in another county where many of the rural roads were packed dirt roads with wide water drainage ditches on both sides. However, the county wouldn’t allow any construction in the ditches and insisted that fiber be placed in the public right-of-way which was almost entirely in the woods.
Every fiber construction company can make a long list of similar situations where fiber construction costs came in higher than expected. But there are also cases where fiber construction costs are lower than expected. We’ve worked in farm counties where road shoulders are wide, the soil is soft, and there are long stretches between driveways. We see electric cooperatives that are putting ADSS fiber in the power space for some spectacular savings.
Generic cost models can’t keep up with the fluctuations in the marketplace. For example, I saw a few projects where the costs went higher than expected because Verizon fiber construction had lured away all local work crews for several years running.
Cost models can’t possibly account for cases where fiber construction costs are higher or lower than what might be expected in a nearby county with seemingly similar conditions. No cost model can keep up with the ebb and flow of the availability of construction crews or the impact on costs from backlogs in the supply chain.
Unfortunately, the FCC determines the amount to be awarded for some grants using these cost models, such as the recently completed RDOF grants. The starting bid for each Census block in the RDOF auction was determined using the results of the cost models – and the results make little sense to people that understand the cost of building fiber.
One might expect fiber construction costs to easily be three or four times higher per mile in parts of Appalachia compared to the open farmland plains in the Midwest. However, the opening bids for RDOF were not as proportionately higher for Appalachia than what you might expect. The net results are that grants offered a higher percentage of expected construction cost is the open plains compared to the mountains of Appalachia.
There is an alternative to using the cost models – a method that is used by many state grants. Professional engineers estimate construction costs and many state grants then fund some percentage of the grant cost based upon factors like the technology to be constructed. This kind of grant would offer the same percentage of grant assistance in all different geographies of a state. Generic cost models end up advantaging or disadvantaging grant areas, without those accepting the grants even realizing it. The RDOF grants offered drastically different proportions of the cost of construction – which is unfair and impossible to defend. This is another reason to not use reverse auctions where the government goofs up the fairness of the grants before they are even open for bidding.