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HCL’s ADW initiative aims to create a powerful decision support system that provides a single, integrated view of automotive business data in order to enable insightful analysis for making meaningful, reliable and accurate business decisions.
Our solution bridges data silos and maximizes the automotive information, providing:
?Visibility of automotive operation from manufacturer to dealer delivery at the VIN level
?Actionable information supporting proactive decision making
?Shorter response time-to-market changes thereby enhancing competitive advantage
?Data and insight to detect revenue leakage
Automotive Data Warehouse (ADW) - Solution Overview
In North America, motor vehicles and automotive parts comprise approximately 5-8% of the total commodities being shipped by rail and are accountable for close to 5% of the annual rail revenues, growing at a rate of 40% since 2009. Though shipping vehicles by rail has its own benefits compared to trucking (more freight by gross tons, reduced emissions), the following challenges faced in automotive freight movement reduce the profit potential that can be accrued by the industry:
?No visibility of shipments at the VIN (Vehicle Identification Number) level
?Increased transit time due to dwell times at classification yards
?Improper utilization of equipment/ ramp/ railcar?Low customer satisfaction (due to lack of visibility in
tracking and tracing shipments)?Insufficient information relating to damages and delays in
claim settlement?Empty movement of railcars on back-haul movements to
origin
Industry Scenario
Hello, I’m from HCL. superhuman capabilities. We make sure that the rate of progress far exceeds the price. And right now, 85,000 of us bright sparks are busy developing solutions for 500 customers in 31 countries across the world.
We work behind the scenes, helping our customers to shift paradigms and start revolutions. We use digital engineering to build
How can I help you?
www.hcltech.com
?Minimize revenue leakage in freight operations?Improved utilization/ optimization of asset/ resources by
20%?Improved transit time by 15%?Visibility and real-time information availability?Better customer satisfaction
Potential Benefits:
?Pre-built logical model?Pre-built dimensions and attributes?Subject area-wise KPIs
Key Differentiators:
New cars manufactured in auto plant
?Long-term contract performance verification
?New car shipment only
Revenue/ Opportunity Loss
?Utilization of freight cars based on occupancy levels
?Potential multiple manufacturer co-loading within railcars
?Visibility into individual movement of shipped automobiles
?Customer commitments on shipments
?Optimal auto ramp location planning
?Demurrage charges for delayed railcar shipments
Cars loaded into empty freight cars
Freight cars sent to train head for
transport
Trains scheduled from destination
and loads
Trains switch tracks, moving
across tracks of Class 1 Railroads
Trains reach destination and
cars unloaded on ramps
Each car has a unique VIN
number
Way Bills created and mapped to VIN
numbers
Freight railcars tracked/ no automobile
level visibility
RFID-based data generated at auto-
car level
Classification yard switching creates
train blocks
No data sharing between Class 1s in
real-time
Auto ramps store the cars till the
dealers pick it up
Automotive Freight Management
A set of KPIs, dimensions and data modeling specifically applicable to the automotive business of the railroads of North America
For more information please contact – [email protected]
DimensionsVIN
?Code?Number?Type?Color?OEM
FacilityLocation
?Type?Size?SPLC?State?City
Date/Time
?Year?Qtr?Mth?Day?Hour
Claim/Damage
?Type?Code?Type?Reason
Customer
?Name?Type?Plant
Location
Dealer
?Name?Location?Zone?OEM
TruckCarrier
?Name?Type?OEM?Dealer
Railcar
?Number?Type?Capacity?Owned
Flag
Segment(Lane)(OD Pair)?Origin?Type?Dstn?Type
RailCarrier
?Code?Name
Train
?Number?Symbol
Hold Type
?Code?Reason
KPIs
