Existing benchmark studies are based on past data that do not capture new COVID-19 market conditions

Our colleagues, Frank Janssen and Yoran Noij, are currently analysing our 2020 benchmarking strategies for determining the arm’s length compensation for service providers, contract manufacturers and limited-risk distributors by applying the TNMM method. These limited-risk companies are commonplace in supply chains and do not usually assume significant economic risks. Generally, benchmark studies indicate that such companies are expected to earn guaranteed profits under arm’s length conditions. However, benchmarking studies based on past data do not reflect the impact of COVID-19.

The assumption that limited-risk companies should earn guaranteed returns might be questioned as a result of the COVID-19 outbreak. It is uncertain whether independent companies performing similar functions, assets and risks to limited-risk companies will report operating losses. Independent comparable companies may be compensated with different margins or even losses in 2020. Therefore, by relying on pre-COVID-19 data, companies risk over-compensating affiliated limited risk companies. Hence, it is prudent to re-evaluate the levels of guaranteed/minimum profits previously ensured to affiliated limited risk companies and, to check whether an adjustment is possible, taking into consideration existing contracts, the position of the countries involved, the OECD TP Guidelines, the interplay with domestic COVID-19 relief measures (that may call for a freeze of the existing TP policy), customs duty and the TP policy of the group.

We are currently analysing subsets of US listed companies (as they are obliged to file quarterly figures) in terms of sensitivity to an economic downturn as well as other functional characteristics (a.o. whether the subsets are impacted by the pandemic in the same way). Analysing the Q1 financials of comparable companies, the preliminary conclusion is that a large number of the listed comparable companies report large decreases in operating income. For example, subsets active in the heavy machinery industry report an average decrease of operating income of 51,4% and subsets active in the logistics industry report an average decrease of operating income of 28,2% (as compared to Q1 2019). This may trigger a re-evaluation of the search strategies applied, for example focussing on a single year (as the impact of COVID-19 pandemic may be reflected in a limited period of time) and assessing the comparable data. The decrease as depicted in the Q1 figures will be even more significant in the Q2 figures.

Following the filing of the Q2 figures, we will draw our final conclusions and report in a more elaborate blog.

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