Tamer Ovutmen

Bart MacCarthy

The Effect of Introducing a Vehicle Holding Compound In an Automotive Order Fulfilment System.

A case study using simulation models for a specific national market

2

Passenger vehicle – a multi-featured product

Interior Trim

Body style

Exterior colour

Engine types

Wheel type

TransmissionEngine size

Buildable combinations - potentially hundreds of thousands of buildable combinations

Series

User specified options++++

Order Fulfilment in the volume automotive sector

High levels of potential variety and customization

Mass Customization - challenging Diverse, heterogeneous customer base Trend has been to develop flexible order

fulfilment systems - opening the pipeline and Virtual-Build-to-Order (VBTO)

Alford et al. 2000; MacCarthy et al. 2003; Holweg and Pils, 2004; Meyr, 2004; Fredriksson and Gadde 2005;

4

Open pipeline approach

Build to forecast CustomerPipeline

fulfilment Stock fulfilment

Switch ‘to-order’ (Floating decoupling point)

Fulfil from anywhere in the system (multi-mode fulfilment) Combines Build-to-Forecast with allocation from the pipeline, stock and BTO Add reconfiguration and trading for more flexibility How beneficial is opening the pipeline? Limited research on this type of system – Brabazon and MacCarthy (2004; 2006) and forthcoming in JORS and POM

BTO fulfilmen

t

Case study of a specific national market

Based on substantial theoretical work and earlier models

Goals Capture a specific market in a

model Evaluate impact of different

operating policies Answer specific business

questions and issues related to opening the pipeline

Approach Develop a simulation

model to study and evaluate alternative operating policies

More faithful to a specific real system Scale and detail Operating

characteristics

Order Fulfilment system

Customer

Customer

Virtual pipeline

Gate

Planning Process

Status FeedbackOrder Process

Vehicle movement

Selling ProcessDealer Influence

Module

Delivery Logistics

Other Dealers stocks

Customer

Dealer Lot

Dealer stock

Search + Promise process

Dealer

Pipeline scheduler

Wholesale planning

NSC policies and targets

Unscheduled order bank

Operating policies / system configurations

Pipeline control Open/closed Order amendment Pipeline trading (unconsented)

System stock levels (forward coverage) Dealer behaviour

Wholesale volume commitment Physical stock trading (consented) Reservation of unsold pipeline orders

Customer behaviour Willingness to compromise

Validation

Data validity Sufficiency Appropriateness Accuracy

Conceptual model validation Consultation with system experts

Assumptions Model input Model structure

Operational validation Is the model sufficiently accurate to use for

experimental purposes Consider key system metrics

Experimental plan

Approach Define two base case

scenarios Base case 1 - Absolute Base case 2 - Relative

Vary input parameters to simulate different system configurations

Two levels of variety Entity - 370 Entity + Colour - 3724

Base case 1

Base case 2

Pipeline status

open open

Initial stock volume

0 7 days coverage

Dealer wholesale commitment

100% 80%

Pipeline trading

no no

Stock trading

no 5%

Pipeline amendment

no full

Pipeline compromise

0 0 (entity variety)

Stock compromise

0 20% (entity variety)

Experiment specification

Factor Number of trials

Base case 2

Amendment 10

Pipe trading 20

Stock trading 20

Wholesale volume 10

Initial stock level 32

Customer compromise 30

Total 124

Variety levels 2

Total experiments 248

Observe relative changes in system performance based on key metrics Fulfilment mechanisms

Stock Pipe BTO

Stock Volume/level Coverage Age

Customer waiting time

Q. What is the effect of pipeline trading on retail fulfilment?

-1

-0.5

0

0.5

1

0.1 0.3 0.5 0.7 0.9

chan

ge in

fu

lfilm

ent

pipe trade availability

BTO pipeline stockBase case 77% 12% 11%

Reduced availability of pipeline orders for trading due to dealer reservation of unsold pipeline orders

6%

90%

4%

Fully

op

en

pip

elin

e

Q. What is the effect of dealer wholesale behaviour on retail fulfilment

Pipeline Initial Stock Dealer Wholesale

Pipe Trading

Stock Trading

Amendment Pipe Compromise

Stock Compromise

Open None 50% - 100% No No No No No

-0.08

-0.04

0

0.04

0.08

0.12

0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1

cha

nge

in f

ulfi

lmen

t

wholesale proportion

BTO Stock Pipe

Base case 77% 12% 11%

Reduction in dealer wholesale commitment

5%

7%

88%

2.5 % increase (approx)

2 % decrease (approx)

VHC Study

What is VHC (Vehicle Holding Compound)? The objective of the VHC is to facilitate free

trade of unsold physical vehicles throughout the dealer network by: Delivering the unsold dealer stock to a central

compound. All dealers are able to search for and call off any

vehicle in the compound . It essentially replicates free trading of physical

vehicles throughout the dealer network by over-coming the physical logistics barriers .

VHC Study Objectives

1. How does the implementation of a VHC affect the overall system performance?

2. What is the optimal setup for operating the VHC in terms of:

i. VHC/Local stock split

ii. Auto-shipment duration

iii. Selection of vehicles for Local Stock (in progress)

iv. Logistics (in progress)

Experiments for VHC

Factor Number of configurations

VHC – Local Stock Split

8

Auto – Shipment Duration

14

Pipe Trading 3

Stock Trading 3

VHC Stock Selection 3

Logistic Distributions 4

Total 90

Observe relative changes in system performance based on key metrics Fulfilment mechanisms

VHC Stock Pipe BTO

Stock Volume/level Age

Customer lead time

3.3%

41.4%

1.5%

53.8%

26.2%

42.3%

31.5%

0%

10%

20%

30%

40%

50%

60%

BTO - Retail Pipe - Retail Stock - Retail VHC - Retail

VHC

No-VHC

Q.1.i. What is the effect of VHC on retail demand fulfilment?

Retail Demand

10.70

16.77

0

2

4

6

8

10

12

14

16

18

VHC No-VHC

Lead Time

VHC

No-VHC

Q.1.ii. What is the effect of VHC on Lead time?

40% decrease in Lead time

Q.2. What is the effect of Stock Split on Retail Fulfilment?

0%

10%

20%

30%

40%

50%

60%

10% 20% 30% 40% 50% 60% 70% 80%

Fulfi

lmen

t Per

cent

age

VHC Stock Proportion

bto(ret)

pipe(ret)

stock(ret)

vhc(ret)

Retail Demand

Increasing VHC stock

Q.3 What is the effect of Auto Shipment duration on VHC performance?

0%

5%

10%

15%

20%

25%

30%

35%

40%

15 30 45 60 75 90 105 120 135 150 165 180 195 210

Fulfi

lmen

t Per

cent

age

Auto-Shipment Duration (Days)

bto(all)

pipe(all)

stock(all)

vhc(all)

Current Practice

All Demand

Key Observations

Introducing a VHC reduces the BTO requirements from 26% to 3% in retail demand

Introducing a VHC reduces lead time by 60% When more than 60% of stock is kept in VHC,

no customer compromise required Auto-shipment duration can be reduced by

1/3 (30days) without changing performance and may reduce stock.

Future Work

How to select vehicles, which are going to local stock? Options – random, maintain local FDC,

most demanded, least demanded? Controlling the logistics time from VHC

to Dealers?

Achievements

Model realism - scale, functionality and

configurability

Managerial implications

showing the magnitude of effects and when they occur

showing the relative benefits obtainable from different

operating policies and flexibilities + the impact of variety

Enabling managers to support arguments and

consider opportunities

Limitations and challenges

Dynamic behaviour in the system Customer and dealer behaviour Data accuracy/integrity/interpretation Scale and level of detail Understanding and interpreting simulation outputs Validation

large scale business systems where does knowledge of the system reside? parameter setting composite ‘closeness’ measures

Any questions?