Railroad Performance:

How good can it get? Quantifying the Opportunity

Larry Shughart, Global Lead Transportation

(352) 284 1250

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

For the last 10 years WorleyParsons analysts have

maintained a model that estimates U.S. railroads’

costs and prices by commodity and railroad.

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?

This model can be used to analyze prices, costs,

and traffic mix changes.

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

PRICE: Our work suggests railroads still have room

to raise prices on some commodities.

CSX NS BNSF UP KCS CN CPBase 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%

Revenue Performance Opportunity$Millions (Most recent 4 Quarters of QCS data)

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

Railroads should be able to price up to an

indifference level with truck, adjusting for service.

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”

We cap our estimate of maximum price at 200% of

long-term variable cost to reflect regulatory threats.

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

COSTS: Our work suggests railroads can lower

costs by matching historical best performance.

CSX NS BNSF UP KCS CN CPBase 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%

$Millions (Base adjusted for mostt recent volume)

Expense Performance Opportunity

Many are surprised to find that NS costs per KGTM

are higher than CSX in most categories.

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

These data are the railroads’ own numbers!

We fuse data from four publicly available data sets

with our expert knowledge of rail operations.

AAR Analysis of Class

I Railroads.xls

STB WaybillsSTB_yyyy.mdb

QCSQCS.mdb

Rail-TruckPricing

Opportunities

Truck-Rail Model.xls

Rev/RTM Analysis

Revenue Per RTM Analysis.xls

Length-of-Haul by RR and Commodity

Tons, Units, Rev by RR & Commodity

% LD Miles by RR by CarTypeHP/Loco & Loco Utilization by RR

LD Unit-Miles by RR by CarType

Sheet=Length of HaulRange=LOH

Sheet=AAR Data

Sheet=RTM CalculationsRange=LOH

Sheet=RTM CalculationsRange=LdCarMiles_AAR

Sheet=RTM CalculationsRange=PctRTM_STB

Sheet=STB DataRange=Inputs_STB

Sheet=QCS DataRange=Inputs_QCS

Sheet=QCS BaseRange=RevAllBase

Range=TonsAllBase

Range=UnitsAllBase

% Net Ton-Miles by RR & Commodity in

each CarType

Product density, tare & car capacity by East/West by Commodity

Tons, Units, Rev by RR & Commodity

UMLERReferenceTables

% of RR Car Fleet that is Privately Owned, by CarType

Sheet=Inputs - Commodity

Some key data lags several months

We use the model for strategic, trend, and sensitivity analyses rather than for tactical decision making

We update the model quarterly.

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

AA

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STB P

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aybill Sam

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We examine the underlying drivers of performance.

Cost $/GTM

Revenue $/RTM

RTM / GTM

> > >

Cost Efficiency

Price Efficiency

Network Efficiency

Cost $ / GTM

Rev $ / RTM

RTM

GTM X =

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

U.S. business of: NS, CSXT, UP, BNSF, KCS, CP, CN

Commodity Groupings in the Model

Our system details all 98 railroad-commodity combinations in an easy-

to-see format, linked to 20 other spreadsheets of back up detail and summary reports.

We have detailed assessments readily available

for seven railroads and fourteen commodities.

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

The model simulates an average train cycle for each

Railroad-Commodity combination.

NOTE: Data shown is an illustrative subset of the much larger model system

HP / TT

CSX BNSF

Chemicals Coal

Standard Train Formation

Average Freight Tons/Car or Intermodal Box 88 119

Average Car Tare Weight Tons/Car 35 23

% Loaded Mi les (rev. hi tch uti l . for intermodal) 51% 50%

Speed (mph) 18 16

Length of Haul 1-way (avg.) - mi les 536 1,036

Average Tons / Tra in (ld and mt) 4,220 9,180

HP / TT 1.3 1.0

Horsepower per Locomotive 3,545 3,839

Locomotives / Tra in 2.2 3.0

% of Cars Originated 83% 99%

Intermediate Handl ings / trip 1 0

% of Cars Terminated 85% 68%

Car Days per cycle

In-tra in Loaded Time (days) 1.3 2.6

Terminal Time per Cycle 5.6 1.9

In-tra in Empty Time (days) 1.2 2.6

The model attaches unit costs to each of the

physical work activities to estimate variable cost.

CSX BNSF

Chemicals Coal

Activity per cycle

Tra in Hours 59 127

Tra in Days 2.5 5.3

Ca lculated Locomotive Uti l i zation 45% 58%

Uti l i zed Locomotive Hours 130 380

Total Mainl ine Locomotive Days 12 27

Car Days 1,487 1,242

RTM / Cycle (loaded + empty) 2,525,326 13,716,401

GTM / Cycle (loaded + empty) 4,925,086 20,074,905

RTM/GTM 51% 68%

Unit Cost Assumptions

Main Line Tra in Crew and Management / Tra in Hours 223$ 221$

Track Maintenance / KGTM 1.39$ 0.67$

Track Depreciation & MOW Equipment / KGTM 2.16$ 1.49$

% of Cars Rai l road 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 / Tra in 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 Tra in Crew and Management 13,183$ 28,055$

Fuel 16,808$ 54,216$

Track Maintenance 6,844$ 13,521$

Car Costs 161$ 19,835$

Mainl ine Locomotive Maintenance 1,725$ 4,922$

Long Term Variable Cost / Cycle

Track Depreciation & MOW Equipment 10,626$ 29,922$

Mainl ine Locomotive Lease + Depreciation 3,350$ 10,298$

Operations Overhead 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 profi t / cycle 64,228$ 36,268$

Revenue to tota l cost ratio 1.73 1.18

Estimated Operating Ratio 58% 85%

If coal volumes go down 25% and chemicals volumes increase 25% what is the impact on income?

TRAFFIC MIX: Coal vs. Chemicals Analysis

• UP Operating Ratio Impact: +84 basis points • BNSF Operating Ratio Impact: (29) basis points

Current

Carloads

per year

Future

Carloads

25 % change

Revenue /

Carload

Cost /

Carload

Estimated

Current

Income

(000,000)

Estimated

Future

Income

(000,000)

Net

Change

UP Coal 2,001,669 1,501,252 2,019$ 1,559$ 921$ 691$

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)$

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

Summary

How can WorleyParsons help you ?