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?