Railroad Performance: How good can it get?

Railroad Performance: How good can it get? Quantifying the Opportunity Larry Shughart, Global Lead Transportation (352) 284 1250

For the last 10 years WorleyParsons analysts have maintained a model that estimates U.S. railroads costs and prices by commodity and railroad. Examines cost drivers (fuel, labor, cars, etc.) Analyzes price per revenue ton-mile Allocates all expenses across traffic using activity based costing methods Uses economic theory to estimate a production function, costs and operating ratio by commodity by railroad

This model can be used to analyze prices, costs, and traffic mix changes. Example Price Analyses: Where are prices too low or too high, and by how much? What prices are constrained by trucks, regulators, or other railroads? What is the top line growth potential if optimal prices were achieved? Example Cost Analyses: Where can each railroad lower costs as compared to their competitors? How do current costs and productivity compare to historic best? What is the income growth potential if optimal costs were achieved? Example Traffic Mix Analyses: What income is expected from a 25% shift from single to double stack? If coal volumes go down 25% and chemical volumes increase 25% what is the impact on revenue, costs, income, and operating ratio? Sensitivity of Operating Ratio different volume growth scenarios?

PRICE: Our work suggests railroads still have room to raise prices on some commodities. Railroads have done a great job raising prices on most commodities to meet customers willingness-to-pay Pockets of opportunity to raise prices remain for some commodities We constrain prospective price estimates by regulatory threats and trucking competition Revenue Performance Opportunity $Millions (Most recent 4 Quarters of QCS data) CSX NS BNSF UP KCS CN CP Base Revenue $ 10,310 $ 11,123 $ 20,445 $ 20,093 $ 1,253 $ 2,670 $ 1,519 Incremental Potential Opportunity $ 2,392 $ 1,720 $ 5,870 $ 4,767 $ 452 $ 723 $ 612 Prospective Revenue $ 12,702 $ 12,844 $ 26,315 $ 24,861 $ 1,704 $ 3,393 $ 2,131 Opportunity % of Base 23% 15% 29% 24% 36% 27% 40%

Railroads should be able to price up to an indifference level with truck, adjusting for service. We constructed a truck cost model for each commodity and geography, including: Product density (cube out or weight out) Speed (adjust for length of haul) Equipment cycle time and maintenance costs Driver costs (wages and benefits) Fuel efficiency and price (including highway taxes) We assume truck price = truck cost We reduce truck price by a logistics penalty to find rail indifference price 10% modal penalty for ease of doing business applied to non-bulk commodities Inventory carrying cost reflects the value of the commodity being shipped and the added in-transit inventory time on rail vs. truck

We cap our estimate of maximum price at 200% of long-term variable cost to reflect regulatory threats. We constructed a railroad cost model for each commodity and company, including: Productivity and unit costs unique to each railroad company as reported to the STB in the R-1 Applied standard operating practices for time factors, intermediate handlings, and train lengths We include depreciation and an allocation of SG&A in our definition of long term variable costs We assume 200% of LTVC is a good surrogate for regulatory threshold of pain

COSTS: Our work suggests railroads can lower costs by matching historical best performance. We benchmark costs within East and West to adjust for geography Rebuilding traffic density is one element of regaining cost efficiency, but management focus remains the principle driver of cost control These numbers should be viewed as conservative, as we do not account for new technology or any expectation of new productivity gains Expense Performance Opportunity $Millions (Base adjusted for mostt recent volume) CSX NS BNSF UP KCS CN CP Base Operating Expense $ 8,397 $ 8,505 $ 14,589 $ 14,241 $ 877 $ 2,035 $ 1,191 Total Opportunity $ 1,307 $ 1,472 $ 1,430 $ 1,347 $ 161 $ 438 $ 237 Prospective Operating Expense $ 7,090 $ 7,034 $ 13,159 $ 12,894 $ 716 $ 1,596 $ 954 Opportunity % of Base 16% 17% 10% 9% 18% 22% 20%

Many are surprised to find that NS costs per KGTM are higher than CSX in most categories.

These data are the railroads own numbers! WorleyParsons provides a framework to analyze the railroads own publically reported numbers We work with clients to use our model to answer specific questions with detailed facts We constructed the model to facilitate what-if analyses The model totals cross-foot to actual reported numbers

We fuse data from four publicly available data sets with our expert knowledge of rail operations. UMLER ReferenceTables AAR Analysis of Class I Railroads.xls LD Unit-Miles by RR by CarType % of RR Car Fleet that is Privately Owned, by CarType % LD Miles by RR by CarType HP/Loco & Loco Utilization by RR Sheet=Inputs - Commodity Product density, tare & car capacity by East/West by Commodity Sheet=AAR Data Sheet=STB Data Range=Inputs_STB Sheet=QCS Data Range=Inputs_QCS Rail-Truck Pricing Opportunities Truck-Rail Model.xls Sheet=Length of Haul Range=LOH Tons, Units, Rev by RR & Commodity Length-of-Haul by RR and Commodity STB Waybills STB_yyyy.mdb % Net Ton-Miles by RR & Commodity in each CarType Sheet=RTM Calculations Range=LdCarMiles_AAR Sheet=RTM Calculations Range=LOH QCS QCS.mdb Tons, Units, Rev by RR & Commodity Sheet=RTM Calculations Range=PctRTM_STB Sheet=QCS Base Range=RevAllBase Range=TonsAllBase Range=UnitsAllBase Rev/RTM Analysis Revenue Per RTM Analysis.xls

We update the model quarterly. Some key data lags several months We use the model for strategic, trend, and sensitivity analyses rather than for tactical decision making Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Quarterly Commodity Statistics (Previous Quarter) STB Public Use Waybill Sample (Previous Year) Quarterly Commodity Statistics (Previous Quarter) AAR Analysis of Class I Railroads (Previous Year) Quarterly Commodity Statistics (Previous Quarter) Quarterly Commodity Statistics (Previous Quarter)

We examine the underlying drivers of performance. Cost $/GTM Revenue $/RTM RTM / GTM > > > Cost Efficiency Price Efficiency Network Efficiency Cost $ / GTM Rev $ / RTM RTM X = GTM Operating Ratio

Some key drivers impact all three performance metrics; we examine facts at the commodity level. Fuel Cost, Fuel Efficiency Labor Cost, Labor Prod Track Maint. & Track Capital Train and Car Velocity Tons per Carload Length of Haul Traffic Mix Truck Pricing STB Regulators Cost $ / GTM P P P P P P P Rev $ / RTM P P P P P P RTM / GTM P P

We have detailed assessments readily available for seven railroads and fourteen commodities. U.S. business of: NS, CSXT, UP, BNSF, KCS, CP, CN Commodity Groupings in the Model Agriculture Automotive Chemicals Coal Coke Food Products Forest and Lumber Intermodal- Conventional Intermodal- Double Stack Iron Ore Metals Phosphate Pulp and Paper Stone and Gravel Our system details all 98 railroad-commodity combinations in an easyto-see format, linked to 20 other spreadsheets of back up detail and summary reports.

The model simulates an average train cycle for each Railroad-Commodity combination. CSX BNSF Chemicals Coal Standard Train Formation Avera ge Frei ght Tons/Ca r or Intermoda l Box 88 119 Average Car Tare Weight Tons/Car 35 23 % Loaded Miles (rev. hitch util. for intermodal) 51% 50% Speed (mph) 18 16 Length of Haul 1-way (avg.) - miles 536 1,036 Average Tons / Train (ld and mt) 4,220 9,180 HP / TT HP / TT 1.3 1.0 Horsepower per Locomotive 3,545 3,839 Locomotives / Tra i n 2.2 3.0 % of Cars Originated 83% 99% Intermediate Handlings / trip 1 0 % of Cars Terminated 85% 68% Car Days per cycle In-train Loaded Time (days) 1.3 2.6 Terminal Time per Cycle 5.6 1.9 In-train Empty Time (days) 1.2 2.6 NOTE: Data shown is an illustrative subset of the much larger model system

The model attaches unit costs to each of the physical work activities to estimate variable cost. CSX BNSF Chemicals Coal Activity per cycle Train Hours 59 127 Train Days 2.5 5.3 Calculated Locomotive Utilization 45% 58% Util i zed Locomotive Hours 130 380 Total Mainline Locomotive Days 12 27 Ca r Da ys 1,487 1,242 RTM / Cycl e (l oa ded + empty) 2,525,326 13,716,401 GTM / Cycl e (l oa ded + empty) 4,925,086 20,074,905 RTM/GTM 51% 68% Unit Cost Assumptions Main Line Train Crew and Management / Train Hours $ 223 $ 221 Track Maintenance / KGTM $ 1.39 $ 0.67 Track Depreciation & MOW Equipment / KGTM $ 2.16 $ 1.49 % of Cars Railroad Owned or Leased 0% 39% Adjusted Cost - Ownership + Maintenance / Car Day $ 0.11 $ 15.97 Locomotive Maintenance / Locomotive Day $ 144 $ 180 Intermediate Terminal costs / Car or Box handled $ 78 $ 78 Locomotive Lease + Depreciation / Locomotive Day $ 280 $ 377 Operations Overhead / Train Hour $ 65 $ 121 SG&A / Car Load $ 356 $ 178

We view Fixed costs as Long-term Variable and allocate them to appropriate work activities to get a total cost of the movement. CSX BNSF Chemicals Coal Short Term Variable Cost / Cycle Main Line Train Crew and Management $ 13,183 $ 28,055 Fuel $ 16,808 $ 54,216 Track Maintenance $ 6,844 $ 13,521 Ca r Cos ts $ 161 $ 19,835 Mainline Locomotive Maintenance $ 1,725 $ 4,922 Long Term Variable Cost / Cycle Tra ck Depreci a tion & MOW Equi pment $ 10,626 $ 29,922 Mainline Locomotive Lease + Depreciation $ 3,350 $ 10,298 Opera tions Overhea d $ 3,854 $ 15,380 SG&A $ 19,129 $ 19,741 Total Cost / Cycle $ 88,000 $ 205,919

We combine our cost model output with reported revenue per car to estimate operating ratio by commodity for each railroad company. CSX BNSF Chemicals Coal Total Cost / Cycle $ 88,000 $ 205,919 Revenue Yield - Revenue/kRTM $ 60 $ 18 Revenue / Carload $ 2,834 $ 2,178 Revenue / Cycle - on a Carload basis $ 152,228 $ 242,187 Operating profit Operating profit / cycle $ 64,228 $ 36,268 Revenue to total cost ratio 1.73 1.18 Estimated Operating Ratio 58% 85%

TRAFFIC MIX: Coal vs. Chemicals Analysis If coal volumes go down 25% and chemicals volumes increase 25% what is the impact on income? Current Carloads per year Future Carloads 25 % change Revenue / Carload Cost / Carload Estimated Current Income (000,000) Estimated Future Income (000,000) UP Coal 2,001,669 1,501,252 $ 2,019 $ 1,559 $ 921 $ 691 Net Change UP Chemicals 1,149,990 1,437,488 $ 3,242 $ 1,605 $ 1,882 $ 2,353 $ 240 BNSF Coal 2,237,877 1,678,408 $ 2,178 $ 1,852 $ 730 $ 547 BNSF Chemicals 705,137 881,421 $ 3,631 $ 3,062 $ 402 $ 502 $ (82) UP Operating Ratio Impact: +84 basis points BNSF Operating Ratio Impact: (29) basis points

Summary Railroads can still raise prices 15% - 25% Railroads can still lower costs 10% - 20% Changes in traffic mix may impact bottom line performance in non-intuitive ways Our model is a useful tool for examining these issues in detail

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