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| Type | Master's Thesis |
| Scope | Discipline-based scholarship |
| Title | A Quantitative Framework for Analyzing the North American Freight Railroad Industry's Value Chain |
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| Language |
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| Institution | University of Zurich |
| Faculty | Faculty of Economics, Business Administration and Information Technology |
| Number of Pages | 71 |
| Date | 2015 |
| Abstract Text | This thesis presents a quantitative profitability framework tailored to the North American Class I freight railroads covering the industry’s most important KPIs and allowing an objective benchmarking among companies. The structure of the thesis follows the logic of the framework and concludes with the summary of chances and risks on company as well as industry level. In addition, the appendix provides a brief discussion of profitability in context of the equity market. Profitability is expressed in Return on Invested Capital (“ROIC”), which according to Koller, Goedhart and Wessels (2010) is a better KPI to measure operational performance than return on equity (“ROE”) or return on asset (“ROA”): While ROE mixes operational performance with capital structure making benchmarking among peers less meaningful, ROA includes non-operating assets and ignores the financing capability of operating liabilities. Additionally, in order to guarantee a more accurate benchmarking of operational performance, ROIC is calculated on a pre-tax basis excluding goodwill. In contrast to the commonly used KPI average revenue per carload (“ARC”), the framework is denominated in revenue ton-miles (“RTM”). This allows a clear segregation between volume and price. Moreover, ARC itself depends ultimately on ton-miles which is driven by length of haul and weight per carload. Additionally, the American Association of Railroads (2014c) is recommending using ton-miles as KPI. Opex items are denominated in gross ton-miles (“GTM”) also taking into account empty shipments. For a more detailed benchmarking and a better identification of potential bottlenecks, the opex items are further segregated, where appropriate. Endorsed by the Rail Staggers Act of 1980, railroads are fortified to apply a differential pricing strategy meaning to discriminate shippers based on their willingness and capability to pay. However, from the 39 Class I railroads existing back in 1980, merely seven remained implying a high concentration of market share. By 2014, the four largest companies accounted for nearly three quarters of market share in terms of handled carloads. When considering freight specific submarkets, frequently, only one railroad’s market share is accounting for more than a quarter of volume. In addition, more than 78% of freight rail stations and more than a third of shippers are estimated to be served by merely a single railroad (Escalation Consultants (2012) and Kimes (2011)). The combination of market concentration and a differential pricing strategy is a powerful mix. It is no surprise that shippers face surging freight tariffs: For example OxyChem, a subsidiary of Occidental Petroleum, claims its rates to have risen by 150% within just five years (Kimes (2011)). In addition, Dairyland Power, a utility, asserts having faced a 93% increase in a single year (Kimes (2011)). But also Fortune 500 companies North American Freight Railroad Industry such as DuPont were confronted with rates climbing 100% on average (Kimes (2011)). Escalation Consultants estimate more than half of all rates are exceeding the revenue to variable cost (“RVC”) ratio of 180%, which is the threshold were the Surface Transportation Board considers market dominance to be present. However, despite of the concept of revenue adequacy which guarantees a certain revenue level but should also limit excessive rates, the rate relief process is considered to be notoriously complex, costing a shipper frequently up to USD 3.5m and is spanning over several years (Fishman (2006)). This might also be the reason why since the STB’s inception in 1996, merely 50 inquiries related to excessive rates were brought to the board’s attention. Despite the high degree of unionization of employees, railroads are not expected to be confronted with labor related issues. In contrast, the highly institutionalized bargaining process protects railroads from employees resorting to extreme measures: Over the past 35 years, merely six days were lost related to nationally-handled freight railroad negotiations (American Association of Railroads (2015d)). Increasing average labor expenses per employee was largely offset by increased labor productivity. Both effects are likely to be attributable to employees working overtime. However, due to recent changes in the Railroad Retirement Act, nearly one quarter of the workforce is expected to be eligible for retirement by 2015 (Federal Railroad Administration (2015)). Consequently, avoiding loss of industry knowledge by retaining talents and at the same time recruiting young talents is a major task railroads need to face. Over the past years, the freight railroad industry has managed to increase fuel efficiency by implementing several fuel conservation initiatives including incentive programs for railroad engineers. However, some railroads such as the Canadian National Railway benefit from favorable terrain of its route network, while KSU and especially NSC operate tracks in more mountainous terrain and consequently face higher fuel consumption per GTM. Over the past years, KSU was able to procure fuel most efficiently. This is likely to be attributable to both its way of procuring fuel via online auctions (Pricelock (2015)) and its beneficial position along the Gulf of Mexico where refineries are abundant which facilitates logistics. In contrast, Canadian railroads face the highest fuel procurement price, which is likely to be attributable to increased logistic costs given their rather remote position from major refinery centers. In order to mitigate commodity price risk exposure, railroads have successfully implemented fuel surcharge mechanisms and are able to recover approximately two thirds of the costs in such manner. Despite cost of equipment ownership per GTMs having decreased for most railroads since 2009, net book values (“NBV”) of equipment have overall been inclining. Particularly North American Freight Railroad Industry pronounced is the surge of NBVs for railcars amounting to a CAGR of approximately 15% for the industry. This increase was likely to be driven by increasing demand for covered hoppers and tank cars as a consequence of an overall recovery of the economy in combination with the North American shale boom. Between 2011 and 2014, lease rates for freight cars indicated by GATX’s lease rate index representing primarily covered hoppers and tank cars have more than doubled. In addition, the NBV of one track-mile, the industry’s largest property, plant & equipment (“PPE”) item, was also increasing showing annual growth rates between 3.5% and almost 5%. While a direct impact on depreciation charges was not observable, it certainly affected asset utilization. Due to the industry’s capital intensive nature, asset utilization represents a major performance driver. In 2004, Union Pacific “estimated that each decrease of one mile an hour required 250 extra locomotives, 5,000 extra freight cars and 180 extra employees to make up for the decrease in efficiency” (Phillips (2004)). This statement implies train velocity being a major driver of asset utilization, however, while this was appropriate in the past, recent surges in volume led to congestion issues on certain routes and terminals causing higher traffic density despite slower velocity. Consequently, velocity is rather considered to measure service quality while a more appropriate KPI to measure asset utilization is ton-miles per dollar of invested capital. With the exception of both Canadian railroads the majority of Class Is failed to improve asset utilization although traffic density expressed in RTM per operated track miles has increased. As indicated in the previous sub-section this is largely attributable to increased net book values per equipment unit. Since longer shipments are more efficient than shorter ones from a railroad’s perspective, Class Is recording higher average length of haul benefit from better capital productivity. It is therefore no surprise that BNSF and UP record the highest asset utilization. Overall, the Class I companies managed to improve profitability on average by approximately 580bps over the past years. Having in mind that most companies did not manage to considerably improve asset utilization, it is no surprise that ROIC improvement was driven by higher profit margins. Although the Class I’s operating costs per GTM have increased continuously, the industry managed to improve revenue even faster. In the course of this thesis a profitability framework has been developed. The framework includes the industry’s most important KPIs and allows an objective analysis scrutinizing the industry’s profitability particularly identifying the chances and risk inherent to the North American Class I railroad industry. Despite this particular framework being tailored to railroads, the underlying |
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