fleet of intermodal containers carrying domestic freight on rail network in the u.s., mexico and...

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Fleet of Intermodal Containers carrying Domestic freight on rail network in the U.S., Mexico and Eastern Canada.

Business Model is rail ramp to rail ramp Wholesale loaded moves (does not include the pickup and delivery components of the moves). Customers are IMC’s.

Objective is to maximize the ultimate return on the container assets. How to identify and capture more of the most beneficial freight in the network to drive the best total profit contribution from the fleet.

Variable contribution to fixed costs◦ Revenue (ramp to ramp paid by

IMC)◦ - Rail Linehaul (ramp to ramp paid to Rail)◦ Contribution

Other Network Costs◦ Container cost◦ Chassis costs◦ Maintenance & Repair of Assets◦ Repositioning costs (empty containers to next

load point)

City A City B ($300)

City A City C ($250)

City A City B ($300) 15days = $20/day

City A City C ($250) 10 days = $25/day

Introducing the concept of “velocity”

Trip days include empty awaiting dispatch, pickup, rail transit, delivery, return of container.

Contribution/day more of a surrogate for return on investment

City A City B ($300) 15days = $20/day

City A City C ($250) 10 days = $25/day

City B is a balanced/deficit equipment market (all inbound loads become subsequent outbound loads).

City C is a surplus equipment market (50% of inbound loads are repositioned out empty to another market at cost of $200).

Introducing the concept of “market balance”

City A City B ($300) 15days = $20/dayCity B outbound loads avg. $250 contrib.

City A City C ($250) 10 days = $25/dayCity C outbound loads avg. $200 contrib.Surplus equipment is repositioned out at $200 cost to another market. Subsequent loads from that market avg. $500 contrib.

And so on………………

Each Market evaluated for Outbound CTB/day adjusted for empty repositioning costs out net of the subsequent load CTB at repo destination

100 Outbound Loads:

◦ 80 at $350 CTB; avg. $25/day (multiple destinations and customers)

◦ 20 repos at $200; subsequent load at $300; net=$100 CTB; avg. $5/day (including repo + load days)

◦ Load Center weighted avg. = $21/day

Drive more business into profitable Load Centers

Drive less business into less desirable Load Centers

“High Grade” business into surplus markets by choosing the best inbound business and handling less low end business (more important if total fleet is fully utilized)

Accommodate seasonality by viewing Load Center on Quarterly basis.

Sales Focus◦ Seek business into attractive Load Centers◦ Deemphasize growth into underperforming markets

Pricing◦ Establish pricing floors on new business in/out markets

to improve network profitability Repositioning

◦ Direct repo flows to most optimal market opportunities Equipment Dispatch

◦ Influence volume flows in support of network optimization. “Street turns” defeat next load discretion.

Total Contribution Per Period $5,400,000

Number of Containers

10,000

Contribution per Container/Period

$540

Loads per Container/Period

1.68

Contribution Per Load

$320

Empty Repo Cost/Load

$30

Empty to Load Ratio

10%

Unit Empty Repo Cost

$300

Contribution b4 Equip per Load

$350

Loads per Active Box

1.9

Active Inventory

89%

Total Inventory

10,000

Out of Service

Inventory 300/ 3.0%

Surplus Container Inventory

800/ 8.0%

Fleet Capacity Planning Empty Repositioning Network Balance (Including Spot Pricing) Network Directed Sales Network Pricing Guidance (Floors, Targets)

◦ At Capacity: High Grading, Velocity◦ Underutilized: Incremental Opportunities

Load Center Management (Cross-Functional Teams to Implement)

Using equipment dispatch to influence the network

Constraining dispatch to undesirable markets “Wait List” management (constrained

environment)◦ Customer priority◦ Destination priority◦ Dispatch Limits (allow “overdispatch” based on

historical gate turn data and customer behavior)◦ Equipment Specifications (limited to selected

customers or destinations)

Simulation to identify optimum flows/mix

Challenge in setting proper boundaries and constraints in the model (demand, limits, etc)

Work began but not seen through with change in the network business model

Provided some insights into opportunities that we had not fully considered previously.

Complexity of any modeling will be greatly increased by incorporating the “street” economics of the load pickup, delivery and empty miles.