Implementing OTM Fleet Management, By - Ted Gifford

ImplementingOTM Fleet Management

in a Large-ScaleIntegrated Environment:Successes and Challenges

Ted Gifford

OTM SIG ConferencePhiladelphia PAAugust 15 , 2012

pg.2

Outline

Schneider National Overview

Overall Project Scope

‘Go Live’ and ‘Rollout’

SNI ‘OTM Fleet’ Implementation

Conclusion

pg.3

Schneider is a transportation leader with a broad portfolio of services.

Schneider National, Inc. is a premier provider of transportation, logistics, and intermodal services

Operates more than 11,000 tractors, 15,000 drivers, and 55,000 trailers and containers with 22,000 associates.

Truckload• Long Haul• Dedicated• Regional• Bulk

Logistics• Supply Chain

Management• International

Logistics• Transportation

Management

Intermodal• TruckRail®

• TruckRail ®

Express

pg.4

Truckload Operations

10,000 orders tendered daily to multiple modes

Over-the-Road, Intermodal, Partner Carriers

Long Haul (LH), Regional, & Dedicated Fleets

LH Lead Time Distribution

2 hours to 14 days, Mean 60 hours

Length Of Haul Distribution

200 to 4000 mi, Mean 700 mi

LH Drivers/Tractors stay out 1-3 weeks

Intermodal Drivers haul 2-4 loads/day

Next load assigned 4-8 hours before Pickup

pg.5

Outline





Conclusion

pg.6

Project Scope

Order Capture & Quote (Revenue Management)

Asset Management & Maintenance

Fleeting Planning, Rating & Costing

Fleet Execution

Driver Management

Financials

OTM Siebel CRM

EBS HR EBS FIN

SOA Middleware

Oracle Fleet Management Components

pg.7

Schneider Developed Components

Customer Rating

Publication, Accessorial automation/billing, Rate Navigation

Revenue Management

Contract and Spot Pricing, Bid Evaluation

Load Acceptance

Capacity Availability, Service Reporting, Profitability Analysis

Network Management

Operational Forecasting / Demand & Supply Balance

Short-Haul (load matching) Optimization

Intermodal Dray & Regional Fleets

Mobile Communications

pg.8

Application Architecture Diagram

pg.9

Outline





Conclusion

pg.10

Go-Live and Roll-out

4404

2514

1371

3519

11,808

0

200

400

600

800

1000

1200

1400

VANS

VANR

RAIL

DEDC

REMAINING 1,507

Scheduled Driver Transitions by LOB

pg.11

Daily System Volumes

Driver Assignments

EOBR messages

Order Releases

Shipments

Shipment Hub

Tracking Events

Vouchers

Work Invoices

Agent Executions

DB SQL calls

9,000

60,000

11,000

6,000

238,000

3,000,000

3,000

37,000

11,978

235,040

8,842

14,613

646,000

702,825

2,820

23,223

9.5 million

2.5 billion

Estimated Actual

pg.12

Outline





Conclusion

pg.13


Development of non-Oracle components

Code Extensions to OTM

Automation Agents

Integration & Component Interfaces

Data Model ‘extensions’

Functional Testing

Performance Testing and System Scalability

pg.14

Extensions to OTM

Events Pre-processing & Handling

Mobile communications

External data inputs

External Workflow

Management of non-OTM-native data – statuses, references, remarks, special services.

‘Closely-coupled’ companion Components

Short Haul (Intermodal) Optimizer

Trailer/Container Management

Shipment & Driver ‘HUB’

pg.15

Automation Agents

ShipmentTracking EventOrder ReleaseDriverLocationWork InvoiceInvoiceShipment StopShipment Special ServiceEquipmentOther

1961692117766544

11

Number of Agents

Lines of Code 18,400

446

OTM Implementation

pg.16

Automation Agents

Lesson Learned – Agent Framework is not a ‘programming’ environment and should be used principally to ‘automate’ OTM processes and NOT to extend product functionality.

OTM Implementation

In particular, the framework lacks …

Robust constructs for conditional logic or loopingProvision to define functionsDebugging capabilityControl of synchronicityAbility to monitor ‘error’ conditions Auto Retry ‘failed’ actionsTracking individual agent actions

pg.17

Seibel (customer & order)Mobile CommunicationsDray OptimizationRelay OptimizationTrailer ManagementData HubDriver ComplianceMappingDist/Geog ServiceAsset MaintenanceODS – AnalyticsEBS –HR & FinCustomsB2BOther

65455321251

1439

74


To/From OTM

pg.18


Implemented CDC (change data capture) via Data Hubs (shipment and driver) to provide timely OTM data to other subsystems.

Initially planned to leverage ORACLE AIA PIPs – now using only EBS-OTM driver PIP (driver data and work invoices) but plan to replace.

Due to OTM and Oracle limitations, we developed structures to support

– Synchronous messaging protocol

– Unit of order for multi-threaded processes

– Locking and flexible queueing schemes

– Error handling and retry on failure

pg.19

Data Model ‘extensions’Additional data elements

OTM Implementation

Order Release ShipmentSpecial Services 5 3References 30 50Remarks 15 4Status Indicators 43 90Stop Special Services (per) 3 8Stop Remarks (per) 3 1Ship Unit References (per) 13 14

Inefficient to query on these elements as they are stored in secondary tables as type-value pairs

pg.20

Testing

Process Integration FinalClaims 44 9Generate Business 229Acquire Customer Order 4162 1AO-EDI 1110 411Revenue Management 2231 46Execute Order (OTM) 4941 47STM 125PP-Procure to Pay 522 38Manage Receivables 543 97General Ledger 328 82Loss Prevention 237 22Driver Pay 1120 196HR-Hire to Retire 454 78HR-OLM 301 7QTC-Quote to Cash 77Total 16347 1111

Number of Business Scenarios Tested

pg.21

Testing

0

50

100

150

200

250

300

350

400

1/1

7

1/2

1

1/2

7

2/2

2/8

2/1

4

2/1

8

2/2

4

3/2

3/8

3/1

4

3/1

8

3/2

4

3/3

0

4/5

4/1

1

4/1

5

4/2

1

4/2

7

5/3

5/9

5/1

3

5/1

9

5/2

5

5/3

1

6/6

6/1

0

6/1

6

6/2

2

6/2

8

7/4

7/8

7/1

4

7/2

0

7/2

6

8/1

8/5

8/1

1

8/1

7

8/2

3

8/2

9

9/2

9/8

OTM C/H Open Defects by Severity

# Open High

# Open Critical

Retest Factor ~ 1.5, Automated Regression Testing

Staffing – 130 FTE Business, 30 TCE, 5 Automation

Data – 26K orders, realistic network configurations, etc.

Defects – order execution related – 4,987

OTM SRs opened – 847, fixed – 447, ER – 87

pg.22

OTM Physical Application Architecture

UxPrd433

UxPrd435 UxPrd436

UxPrd431 UxPrd432 UxPrd433

App Tier

Web Tier Web Tier Web Tier Web Tier

App TierApp TierRead Only App TierApp Tier

Read Only App Tier

OTM DB1

OTM DB2

OTM DB3

OTM DB4

OTM DB5

OTM DB6

pg.23

System Performance and Scalability

After

Changes – July 7Node AffinityCache AdjustmentsTable Reorganization

0

20

40

60

80

100

120

Buffer Gets (10^8) Disk Reads (10^6) SQL Execs(10^6) Cluster Waits

(10^6)

Total Wait Time

(10^3 s)

%DB time

Node 1 (RW)

Node 2 (RW)

Node 3 (RW)

Node 4 (RW)

Node 5 (RW)

Node 6 (RW)

0

20

40

60

80

100

120

140

Buffer Gets (10^8) Disk Reads (10^6) SQL Execs(10^6) Cluster Waits

(10^6)

Total Wait Time

(10^3 s)

%DB time

Node 1 (RW)

Node 2 (RW)

Node 3 (RW)

Node 4 (RW)

Node 5 (RO)

Node 6 (RO)

pg.24

0

10

20

30

40

50

60

70

80

90

100

110

2/13

2/20

2/27

3/5

3/12

3/19

3/26

4/2

4/9

4/16

4/23

4/30

5/7

5/14

5/21

6/4

6/11

6/18

6/25

7/2

7/9

7/16

7/23

Res

po

nse

Tim

e (s

ecs)

Saved Query Weekly Average Response Time

DED

IM

TL"Re-used " Shipment Table Fields

Added DB CPUs

New Hardware -solid state disk

Converted 2 DB nodes to read-only

System Performance and Scalability

pg.25

Outline





Conclusion

pg.26

Conclusion OTM ‘Fleet’ can adequately support smaller fleets and limited

integrations but … needs additional development in key areas to support a ‘large scale’ integrated environment ...

Improve ‘robustness’ for rework, change, and ‘imperfect’ data.

Improve ‘usability’ of ‘Decision Control Center’.

Expand ‘fleet’ data model & improve ‘database’ efficiency (sql call ratio).

Add ‘fleet’-related ‘configuration screens and associated metadata.

Improve technical and functional integration.

Improve ‘agent framework’ or provide alternative ‘logic extension’ scripting capability.

Thank you

Ted Gifford

[email protected]

Implementing OTM Fleet Management, By - Ted Gifford

Technology

Transcript of Implementing OTM Fleet Management, By - Ted Gifford