Root Cause Analysis and Exploration of Unplanned Costs in Truckload TransportationCapstone Advisor : Dr. Chris CapliceCapstone Partner: C.H.RobinsonTeam members: Nishitha Aemireddy, Xiyang Yuan

Background

Motivation

Methodology

Model Results

Business Insights

Further Research

2

Agenda

TMC is a division of C.H. Robinson that offers Managed TMS®, a unique combination of global transportation management system (TMS) software, logistics process management, and consulting services.

3

Operated as an independent division of C.H.Robinson since 1999

Offers managed TMS®

Operates from 5 different locations across globe

10.4 Million shipments $3.1b in Freight under management

Background – TMC

Tender to Primary Carrier

Tender to Backup

Carriers in Routing guide

Auction in Spot Market

Primary tender

Backup tender

Spot tender

AcceptAccept Accept

Reject Reject

Reject

Background – Load Tendering Process

TMC uses routing guides for their load tendering. Loads are tendered in sequential order where the sequence of carriers is determined based on prices, performance levels and capacities.

Tender rejections by primary carrier increased from 19% in 2015-16 to 37% in 2017-18.

2015-16 is a soft market, 2016-17 is a transitional market and 2017-18 is a tight market

5

Motivation

80.60%73.11%

63.12%

15.87%20.77%

27.49%

3.53% 6.12% 9.39%0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

2015-16 2016-17 2017-18

Percentage distribution of loads accepted primary, backup and spot

Primary Backup Spot

Primary acceptance rate decreased by 22%

Backup acceptance rate increased by 73%

Spot acceptance rate nearly tripled

Backup premium : Average of percentage difference in backup carrier rates in routing guide and primary carrier rate over all lanes

6

Increase in premiums with Routing guide depth

Premiums paid increased from 2015 to 2018

Premiums increased at a decreasing rate with

sequence number

0%

2%

4%

6%

8%

10%

12%

14%

16%

1 2 3 4 5

% in

crea

se o

ver P

rimar

y Ca

rrie

r Rat

e

SeqNum

Percentage increase in backup premiums with sequence number

2015 - 2016 2016 - 2017 2017 - 2018

! = −0.0015() + 0.0304( + 0.0146.) = 0.9967

! = −0.0021() + 0.0368( + 0.0099.) = 0.9916

! = −0.0043() + 0.0504( + 0.0074.) = 0.9999

Spot premium : Average of percentage difference in spot rate and primary carrier rate over all lanes

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Routing guide and Spot pricing premiums

9%12% 12%

23%

32%35%

0%5%

10%15%20%25%30%35%40%

2015 - 2016 2016 - 2017 2017 - 2018Perc

enta

ge In

crea

se o

ver P

rimar

y Ca

rrie

r Rat

eRouting Guide & Spot Percentage Premium

Routing Guide Spot

Spot premium increased significantly in 2016-17

Backup premiums did not increase as much

Not a significant increase from 2016-17

to 2017-18

The project uses 3 years of load and tender data from October 2015 to September 2018. The dataset contains only full truckload (TL) dry van shipments with a minimum length of haul of 250 miles

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Methodology

Data collection

Data Cleansing

Data Profiling

Hypothesis generation

OLS & Logistic

Regression modeling

Business Insights

• Longer the distance, higher the cost.

• Distance has no clear impact on tender acceptance rates.

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Data Modeling Results - Distance

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

1500

1600

1700

1800

1900

2000

2100

2200

2300

2400

2500

0

500

1000

1500

2000

2500

3000

3500Avg.CostPerLoad(Dollars)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

AcceptanceRate

ImpactofDistance

MeasuresAvg.CPL

AcceptanceRatebyCarrierCategoryPrimaryCarrier BackupCarrier Spot

Distance(Miles)

2015-2016 2016-2017 2017-2018

Low

Volume

Medium

Volume

High

Volume

Low

Volume

Medium

Volume

High

Volume

Low

Volume

Medium

Volume

High

Volume

0

200

400

600

800

1000

1200

1400

1600

Avg.CostPerLoad(Dollars)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

PrimaryAcceptanceRate

1,356

1,161

1,048

1,360

1,134

984

1,573

1,276

1,086

ImpactofCorridorVolume

PrimaryAcceptanceRate Avg.CPL

• Corridor volume: Monthly average volume for each 3-digit to 3-digit zip code combination.

• Higher the corridor volume, lower the cost per load.

• Increasing corridor volume increases primary carrier acceptance rate and reduces the chance of going to spot market.

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Data Modeling Results – Corridor Volume

Soft MarketDifference: 23%

Tight MarketDifference: 45%

ConsistencyFactor

0.0-0.2 0.2-0.4 0.4-0.6 >0.6

HighConsistency

MediumConsistency

LowConsistency

0

500

1000

1500

Avg.CPL(Dollars)

0

500

1000

1500

Avg.CPL(Dollars)

0

500

1000

1500

Avg.CPL(Dollars)

0.6

0.7

0.8

0.9

PrimaryAcceptanceRate

0.6

0.7

0.8

0.9

PrimaryAcceptanceRate

0.6

0.7

0.8

0.9

PrimaryAcceptanceRate

0.850.81

0.96

0.78

0.74

0.79

0.69

0.81

0.64

0.63

0.66

0.62

ImpactofLaneConsistencyandVolatility

PrimaryAcceptanceRate Avg.CPL

CV

• Lane Consistency: Number of weeks that a lane has at least one load in a year

• Lane Volatility: Coefficient of Variation (CV) of the weekly volume on a lane when volume is present

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Data Modeling Results – Lane Consistency & Volatility

↑ Consistency↓ Cost Per Load

↑ Primary Acceptance Rate

↑ Volatility↑ Cost Per Load

↓ Primary Acceptance Rate

The impact of volatility is more profound in high consistency lanes.

• Weekend: Friday, Saturday, Sunday• Quarter Ends: Last 5 days of each quarter

12

Data Modeling Results – Weekends & Quarter Ends

Cost Per Load

Weekday $1195

Weekend$1302

Acceptance Rate

Weekday0.75

Weekend 0.73

↑ 9%

↓ 3%

Cost Per Load

None Quarter Ends $1222

Quarter Ends$1237

Acceptance Rate

None Quarter Ends 0.75

Quarter Ends0.72

↑ 1%

↓ 4%

• Lead time: the time between tendered date and pickup date• Shorter the lead time, higher the cost per load.

• Increasing lead time decreases acceptance rates and increases the likelihood of going to spot market.

Data Modeling Results – Lead Time

2015-2016 2016-2017 2017-2018

0-48hrs 48-120hrs

>120hrs 0-48hrs 48-120hrs

>120hrs 0-48hrs 48-120hrs

>120hrs

0

200

400

600

800

1000

1200

1400

Avg.CostPerLoad(Dollars)

0.0

0.2

0.4

0.6

0.8

1.0

AcceptanceRate

ImpactofLeadTime

Measure

Avg.CPL

CarrierCategory

PrimaryCarrier BackupCarrier Spot

LeadTime

Soft MarketDifference: 13%

Tight MarketDifference: 15%

• 135 distinct key market areas• If a key market area is a cheaper origin, it is likely to be an expensive destination and vice-versa.

14

Data Modeling Results – Origin & Destination

Miami, FLOrigin Value: -$439Destination Value: $270

Chicago, ILOrigin Value: $338Destination Value: -$511

y = -0.8016x - 45.004R² = 0.3894

-800

-600

-400

-200

0

200

400

600

800

-600 -400 -200 0 200 400 600 800

Dest

inat

ion

Origin

Origin & Destination Market Value

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Data Modeling Summary

Variables Cost Per Load Primary Acceptance Routing Guide Failure

Distance ↑ - -

Corridor Volume ↓ ↑ ↓

Lane Consistency ↓ ↑ ↓

Lane Volatility ↑ ↓ ↑

Weekends ↑ ↓ ↑

Quarter Ends ↑ ↓ ↑

Lead Time ↓ ↓ ↓

Regions Various

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Managerial Implications

Focus attention on low volume corridors

Improve lane consistency and control volatility

Avoid weekends and quarter ends shipments

Consider regional values when constructing new networks

Increase lead time

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Further Research

• Lead time: carriers’ capability of managing short lead time loads• Market index: impact on tender acceptance rates• Seasonality in demand• Network design with regional sensitivity

Suggestions

• The impact of lead time on primary tender acceptance rate• The combined effects of different factors• Regression models capture the correlation but not the causation

Limitations

Thank YouCapstone Advisor: Dr. Chris CapliceCapstone Partner: C.H.RobinsonTeam members: Nishitha Aemireddy, Xiyang Yuan