Transfer Pricing Benchmark: 2022 North American Construction Distribution

Transfer pricing has shifted toward a compliance-driven world. Multinational groups are required to issue transfer pricing documentation reports in more jurisdictions than ever before, leading to increased compliance costs. As compliance requirements have risen, consultancies have turned to automation and standardization of nearly all documentation work, decreasing their costs of performance.

One key aspect of nearly all transfer pricing documentation is a benchmarking analysis. For transactions driven by the comparable profits method, a search generally is required for identifying companies that are comparable to the tested party. However, most consulting firms have already standardized the process with dozens of off-the-shelf benchmarks that can be provided to clients on request. On the one hand, that benefits multinationals by significantly decreasing the turnaround time for benchmarking studies. On the other hand, taxpayers continue to pay for a service that has nearly become commoditized and yet still lacks publicly available secondary resources for practitioners.

Given the proliferation of publicly available data, free screening tools, and data-mining techniques, now is the time to provide clients with corroborative benchmarks and data. Enter this series of articles, meant to provide tax practitioners worldwide with suggestions for transfer pricing benchmarking and information for the most widely used CPM intercompany transactions. This series also attempts to take the complexity out of benchmarking analyses that use expensive tools, demonstrating that all practitioners could perform benchmarking analyses using information and tools that are likely already at their disposal.

This series could be used as a starting point for evaluating comparable companies. Certainly, the facts and circumstances of individual intercompany transactions should be scrutinized against the series content to make an informed decision on the intercompany transaction at hand. Practitioners should always examine each company before deciding whether it would be comparable to the tested party. This article uses data-mining techniques to pull data from companies’ Forms 10-K. Practitioners should always double-check data and validate company financials before using them in transfer pricing analyses and should not rely solely on the data in this article. Although all figures have been double-checked, I lack the manpower and expensive tools that consulting companies use in guaranteeing complete accuracy for their clients.

I. Construction Distribution Benchmark

I started by identifying the North American construction distributors that I wanted to benchmark. The goal is to have a set of companies that might be comparable to a tested party that performs distribution of building materials and ancillary items used in residential and commercial construction. The benchmark seeks to provide a range of companies distributing an array of construction distribution products, such as roofing; insulation; interior fixtures; and heating, ventilation, and air conditioning (HVAC) products. It also targets companies distributing maintenance, repair, and operating (MRO) products for construction use, such as fasteners, material handling equipment, and power tools. The goal is to focus on companies specializing in distribution, supply chain, and logistics functions, rather than vertically integrated providers that also develop and manufacture products.

Selecting the initial companies to include in the search is important. Many practitioners make those selections with standard industrial classification or North American Industry Classification System codes; however, in my experience, that leads to an excessive number of companies to screen that are not even closely comparable to the tested party. Given that, I chose instead to rely on the industry categorizations that investment analysts give to companies. After all, perhaps no one is better able to provide an initial industry categorization than those who are paid to study public companies in detail.

This study uses the 137 companies in TD Ameritrade’s “Industrials — Building products — Building products,” “Industrials — Trading companies & distributors — Trading companies & distributors,” and “Consumer discretionary — Distributors — Distributors” industries.

II. Quantitative Screen

Next, I performed a series of quantitative screens on the 137 companies. I excluded companies that lack any publicly available information, as well as those with less than two years of revenue or operating profit metrics reported during the past three years to ensure that companies are active and have not had a recent stoppage of activities. Also automatically omitted were companies with operating losses in the past three fiscal years. While that biases the results to some extent, I wanted to exclude companies that may be on the brink of financial collapse — a common practice in benchmarking studies. Next, I excluded companies with a three-year revenue average of less than $10 million to avoid wasting time on start-up or pink-sheet companies that may have much different expenses and challenges from those of the tested party. Last, I excluded companies with high annual research and development spending and a high ratio of intangible assets to total assets because those are likely not things a routine multinational’s distribution tested party would have. Table 1 summarizes my initial quantitative screens.

Table 1. Quantitative Screens and the Number of Companies Affected

Quantitative Screen	Companies Affected
Exclude companies lacking publicly available information	22
Exclude companies without at least two years of revenue or operating profit data	8
Exclude companies with operating losses in all of the last three years	19
Exclude companies with less than $10 million in average revenue in the last three years	20
Exclude companies with R&D spending as a percentage of revenue over 5 percent	6
Exclude companies with intangible assets as a percentage of total assets over 15 percent	16

After applying the quantitative screens, 84 companies were left.¹ Operating margin (OM) and return on assets (ROAs)² profit-level indicators (PLIs) for those 84 companies are listed in Table 2.³

Table 2. PLIs for Construction Distribution Companies After Applying Quantitative Screens

	OM	ROA
Maximum	50%	59.1%
Upper Quartile	13.8%	17.8%
Median	8.4%	9.1%
Average	10.3%	11.2%
Lower Quartile	5.3%	4.3%
Minimum	-33.9%	-53.5%

At this stage, I do not report the Berry ratio PLI because I have not performed an in-depth review of the Form 10-K statements. Reporting that ratio without an analysis would lead to meaningless results because companies in the distribution industry may report cost of goods sold and operating expenses differently, which would greatly affect the PLI.

III. Qualitative Screen

For the remaining 84 companies, I reviewed all business descriptions, company websites, and Form 10-K filings to determine whether the company could be comparable for inclusion in the broad construction distribution benchmark. I rejected companies for some common reasons, including because they:

• distribute products focused on a different sector (for example, oil and gas or mining);

• primarily provide leasing and financing services to the aviation industry;

• distribute dissimilar products (for example, automotive or food products);

• operate as subsidiaries; or

• operate as vertically integrated designers and manufacturers of products.

That list includes the most critical rejection reasons in my benchmark. I rejected companies based on their general functionality for several other reasons — for example, because they distribute metals or chemical products. I omitted a company if it distributes home products that are not specifically used in construction or repair projects, such as companies that distribute pool products. I also rejected companies that distribute primarily electronic home devices, such as connected temperature or security systems.

As stated, the goal is to try to isolate as best possible the distribution function in the commercial and residential construction, repair, and maintenance sectors. Thus, vertically integrated manufacturers were rejected if most of their business is the distribution of self-manufactured products.

I also wanted to provide a range of potentially comparable companies that operate in the construction distribution sector. For example, I wanted to include companies that distribute roofing, siding, insulation, lumber, cabinets, bathroom and kitchen fixtures, HVAC, fasteners, tools, safety equipment, and other similar products. After reviewing the companies, I noticed that there are two general categories: companies that distribute actual construction components, such as roofing, lumber, fixtures, HVAC, and insulation, and those that distribute MRO products, such as fasteners, tools, and other ancillary products that would be used primarily in repair, remodeling, and maintenance.

Further, after reviewing the companies’ profitability indicators, there was a clear difference between companies distributing construction components and those distributing MRO products. I accepted both for the benchmark, so practitioners will want to examine this step closely should they choose to use this analysis as a starting point for their benchmarking purposes.

After the qualitative screen, I accepted 11 companies for the general North American construction distribution benchmark. (See Table 3.)

Table 3. Companies Accepted as Potential Construction Distribution Comparables

Beacon Roofing Supply Inc.	Hardwoods Distribution Inc.
BlueLinx Holdings Inc.	Huttig Building Products Inc.
CCOM Group Inc.	MSC Industrial Direct Co. Inc.
Fastenal Co.	WW Grainger Inc.
Ferguson PLC	Watsco Inc.
GMS Inc.

The resulting PLIs for those 11 companies are shown in Table 4.

Table 4. PLIs for Construction Distribution Companies

	OM	Berry Ratio	ROA
Maximum	20.3%	2.21	36%
Upper Quartile	10.2%	1.62	22.9%
Median	9.2%	1.41	18.6%
Average	9.1%	1.49	18%
Lower Quartile	6.3%	1.34	11%
Minimum	1.6%	1.07	4.4%

After reviewing the Forms 10-K of the 11 remaining companies, I found there may be differences in the way companies classify various expenses — that is, COGS versus operating expenses. Although that would not affect the OM and ROA results, it means a practitioner wanting to use a Berry ratio for benchmarking a construction distribution intercompany transaction should scrutinize the financial accounts of potentially comparable companies to ensure there are no differences between the tested party and comparable companies’ classifications of salary expenses.

One interesting takeaway from the PLIs of the accepted companies is the very large increase in profitability year-over-year in the interquartile range, which is clearly linked to pandemic-driven demand for home improvement and construction inputs. That trend in increased profitability may continue in the short term, given supply chain challenges and pent-up demand for home improvement and construction products, particularly in companies distributing lumber products. For the 11 companies accepted, Table 5 shows the three-year trend in OM.

Table 5. Three-Year Trend in OM for Construction Distribution Companies

	OM	OM-1	OM-2
Maximum	20.3%	20.2%	19.8%
Upper Quartile	10.2%	8.2%	10.1%
Median	9.2%	5%	5.8%
Average	9.1%	6.8%	6.7%
Lower Quartile	6.3%	3.2%	2.2%
Minimum	1.6%	0.6%	-0.4%

IV. Conclusion

As transfer pricing benchmarking turns toward compliance and automation, tax practitioners should have readily available resources to assist them in reviewing and challenging their intercompany pricing and benchmarking analyses. The goal of this series is to provide multinationals with an additional resource using publicly available data and resources.

I simplified the benchmark by including broad industry categories and allowing for a range of construction distributors in the accepted comparable companies. I then reported the PLIs resulting from the benchmarking analyses. In performing any analysis, practitioners should be cautious about companies that are vertically integrated and manufacture their own products. Further, deciding whether to include MRO product distributors is important because their profitability can be different from companies distributing only construction components, such as lumber, siding, roofing, and fixtures. Lastly, practitioners should pay attention to the upward trend in profitability stemming from demand for construction inputs during the coronavirus pandemic.

I welcome any feedback on data points or figures that practitioners would like to see in future articles in this series.