The Value of RFID in Transportation:
From Greater Operational Efficiency to
Collaborative Transportation Management
by
Antoine Guitton
M.S. in Mechanical Engineering, 1987
Universite de Technologie de Compiegne, France
Submitted to the Engineering Systems Division in Partial Fulfillment of the
Requirements for the Degree of
MASTER OF ENGINEERING IN LOGISTICS
at the
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
JUNE 2004
MASSACHUSETTS INSTITUTE
OF TECHNOLOGY
JUL 2 7 2004
0 Antoine Guitton. All rights reserved.
LIBRARIES
The author hereby grants to MIT permission to reproduce and to distribute publicly paper
and electronic copies of this thesis document in whole or in part.
Signature of Author .................................................
naineerinSyste nDivision
y 7 t,2004
C ertified by .....................................
7
Christopher Caplice
Program
Executive Director, Master of Engineering in Logis
upervisor
T/
L/
Accepted by.........................
MASSACHUSETTS INSTT1JTE
OF TECHNOLOGY
..
......
...... ......
...........
......
....
......
. ....
Yos si Sheffi
Professor, Engineering Systems Division
Environmental Engineering Department
and
Civil
Professor,
Director, MIT Center for Transportation and Logistics
JUL 2 7 2004
LIBRARIES
BARKER
The Value of RFID in Transportation:
From Greater Operational Efficiency to Collaborative Transportation Management
by
Antoine Guitton
Submitted to the Engineering Systems Division in Partial Fulfillment of the
Requirements for the Degree of Master of Engineering in Logistics
at the Massachusetts Institute of Technology
ABSTRACT
This paper assesses the value of Radio Frequency Identification (RFID) in the
transportation forecasting, planning, and execution processes for truckload (TL) and less
than truckload (LTL) services. The results show that the value of RFID in transportation
highly varies according to the sub-process and the player which are considered. The
value in forecasting and planning is high for consignees and TL carriers, but low for
shippers. For the execution process, the value is high for consignees, moderate for
shippers, low for TL carriers and potentially high for LTL carriers. Fundamentally, the
common value that RFID can bring to each player is labor cost reduction, obtained by
automation of dock and clerical activities, and better service in tracking and reconciling,
thanks to accurate and up-to-date information.
The potential for dramatic improvement in transportation through RFID exists.
Achieving such improvement will be possible only if information sharing rules, such as
those espoused by Collaborative Transportation Management (CTM), and well
formalized procedures are implemented. RFID can give to CTM invaluable "raw
material", while CTM can enable the transportation players to fully take advantage of this
material.
Thesis Supervisor: Christopher Caplice
Title: Executive Director, Master of Engineering in Logistics Program
2
ACKNOWLEDGEMENTS
It is a pleasure to thank those who helped me to achieve the research and writing of this
thesis. I am most grateful for the guidance, insight, and support of my thesis supervisor,
Dr. Chris Caplice, who provided valuable advice and analysis at every step along the
way. Jim Rice gave generously of his time and offered much needed assistance in
arranging meetings and providing advice. Prof. Brian Subirana was important in helping
me to frame this thesis.
My research is indebted to all the people who allowed me to visit their facilities and took
the time out of their busy schedules to review their procedures and answer my questions.
In particular, Jim S., Ray H., Chris N., Larry A. and Tim M, at anonymous companies.
I would also like to thank my colleagues and friends in the MLOG program for their
insights and solidarity, in particular Rose Mei, with whom I conducted most of the field
research. And finally, Judith Surkis, who fought off sleep to proofread my manuscript
and otherwise offered significant 'soutien moral'.
3
TABLE OF CONTENTS
I
GENERAL PRESENTATION AND OVERARCHING QUESTION OF RESEARCH............
SCOPE AND ASSUM PTIONS................................................................................
..
....
THESIS OUTLINE ..................................................................................
1.1
1.2
1.3
2
LITERATURE REVIEW .....................................................................................
RFID : OVERVIEW ...................................................................................
2.1
TRANSPORTATION: OVERVIEW AND CHALLENGES ..........................................
2.2
2.2.1
2.2.2
2.2.3
An overview of transportation:basic processes andplayers ................
Transportationmanagement .................................................................
Collaborative TransportationManagement........................................
RFID AND TRANSPORTATION ........................................................................
2.3
9
..9
17
17
21
23
27
27
Benefits of RFIDfor transportation.....................................................
Positive impacts of other RFID-enabledprocesses on transportation...31
Positive impacts of RFID-enabledtransportationon otherprocesses..... 32
2.3.1
2.3.2
2.3.3
ASSESSMENT OF CURRENT KNOWLEDGE..........................................................
2.4
2.4.1
2.4.2
What is covered, what is missing or poorly documented?....................
What is worthy offurther investment?.................................................
METHODOLOGY ...........................................................................................
3.1
3.2
3.3
3.4
3.4.1
3.4.2
3.4.3
4
6
7
8
How has RFID been covered in the literatureso far?............................ 9
10
EPC Network and RFID technology .....................................................
14
Capabilitiesand benefits ofRFID........................................................
16
Impediments to RFID implementation......................................................
2.1.1
2.1.2
2.1.3
2.1.4
3
6
INTRODUCTION ................................................................................................
INFORMATION COLLECTION...........................................................................
PROCESS A NA LY SIS.........................................................................................
EVALUATION OF NEW PROCESSES...................................................................
METHODS AND APPROACHES USED................................................................
32
32
34
37
37
37
38
38
Relationship between replenishmentlead time and safety stock level... 38
Relationship between lead time variability and safety stock level......... 39
40
Restrictions to the use of these approaches...........................................
RESEARCH: INVESTIGATIONS AND RESULTS......................................42
4.1
4.2
4.2.1
4.2.2
4.2.3
4.2.4
4.3
4.3.1
4.3.2
4.3.3
...... 42
.......
SCOPE AND APPROACH .................................................................
FROM "FORECAST" PROCESS TO "RECONCILIATION" PROCESS........................ 44
"Forecastand Plan Transportation"process.................................
"Execute Transportation"process - TL carriers..........................
"Execute Transportation"process - LTL carriers.......................
"Reconcile"process .......................................................................
44
52
66
90
RFID AND COLLABORATIVE TRANSPORTATION MANAGEMENT.....................
94
The
The
The
The
RFID - CTM: a mutual need .................................................................
CTM and RFID at work, afew illustrations.............................................
Difficulties and opportunities..............................................................
4
94
94
96
5
97
CONCLUSION ....................................................................................................
RESEARCH FINDINGS: ANALYSIS AND SIGNIFICANCE.......................................
5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.2
5.3
Forecastandplan transportation.........................................................
Execute transportation- TL carriers...................................................
Execute transportation- LTL carriers...................................................
Assessment offindings ...........................................................................
REMAINING GAPS, QUESTIONS, LIMITATIONS..............................................
SUGGESTIONS FOR FUTURE WORK ...................................................................
6
APPENDICES.........................................................................................
7
GLOSSARY ......................................................................................
8
REFERENCES ..................................................................................
5
97
97
98
100
102
103
104
... 106
.........-111
.... 112
1
INTRODUCTION
Radio Frequency Identification (RFID) is not a new technology: the fact that it was used
during World War II, as a way to recognize allied fighter planes, has been widely
mentioned. RFID technology is frequently used currently, at automatic tolls or to enter
secure areas. Thanks to new technical capabilities, such as chip miniaturization and the
Internet, new and promising applications are emerging. It has been extensively
announced that massive use of RFID throughout supply chain will revolutionize its
functioning and significantly improve its performance in the coming years. An abundant
literature has been produced on the subject recently.
1.1
General presentation and overarching question of research
Yet, in further investigating the broad scope of supply chain activities, we noticed that the
use of RFID in transportation does not raise as much enthusiasm as it does in other areas.
It is neither easy nor clear to find the reasons for this lack of interest. It may be due to the
usual disaffection from which transportation suffers compared to supposedly more
exciting logistics areas. Alternatively, it may have been already proven that benefits are
not tangible or investments too high. Between these extremes, it is most likely that
analysts do not have a clear view of possible RFID benefits in transportation, and face
difficulties in identifying and quantifying intrinsic and cross-functional gains.
The overarching question of our research is the following: "Can RFID technology bring
any value to the transportation process?" In order to address this question, we assign to
our research the two following objectives: first, to perform an in-depth review of what
has already been studied within the transportation area and its surrounding processes;
second, to carry out a thorough analysis of transportation sub-processes, in order to assess
if there may be opportunities to enhance their efficiency and performance using RFID.
To achieve this second objective, we break up the transportation process into its
elementary components, describe the role of different players involved and their mutual
6
exchanges, identify the main problems they confront as well as their possible causes, and
then assess if RFID may be of interest to improve the current situation.
A secondary purpose is to evaluate how the use of RFID should be beneficial for all
players involved in transportation (the carrier, the shipper and the consignee), and not
only to some of them, as well as to examine how RFID-enabled transportation may
positively impact other logistic processes, such as inventory management or control on
the whole supply chain. More than only involving the technical aspect of RFID, these
two latter objectives address organizational prerequisites to RFID implementation, in
particular in terms of collaboration between players.
1.2
Scope and assumptions
We specify below the general scope of the research and some of the important
assumptions we have made:
" We study transportation from shipping to receiving, through physical transportation
and consolidation in cross-docking terminals.
*
This research focuses only on the US Truckload (TL) and Less-than-Truckload (LTL)
industry.
*
We analyze the relationships between the three main players: the shipper, the carrier
and the consignee.
" RFID tags are applied at case/pallet level and not at item level.
" Tagging is performed at source by vendors, on all products; however, this assumption
may not be realistic in a short term horizon and could be relaxed in some cases.
*
Technical problems are addressed, meaning systems may allow 100% perfect reads,
and there will not be any interference or interoperability problems.
* Available RFID-generated data are shared between players.
7
1.3 Thesis outline
We first carry out a literature review, which presents an overview of the Electronic
Product Code (EPC) network and RFID technology, and "standard" RFID capabilities
and benefits. We then present an overview of processes and players in transportation,
transportation management basics, and identified RFID benefits for transportation. We
conclude the literature review by assessing what has been covered, what is missing, and
what is worthy of further investment. The next chapter presents the methodology used, in
terms of data collection, process analysis, evaluation of processes, and methods employed
to carry out these evaluations. The core research is then performed: we first describe the
scope and approach we have taken, then analyze all the processes we identified earlier,
following the pre-defined methodology, and lastly consider the organizational
implication. We conclude our research by first summarizing our findings and assessing
their significance, second listing the remaining gaps, questions and limitation of our
results, and finally suggesting some leads for future work on the subject.
8
LITERATURE REVIEW
2
RFID: overview
2.1
2.1.1 How has RFID been covered in the literature so far?
Year 2003 saw an exponential growth in the number of white papers, articles,
conferences and reports on RFID (Radio Frequency Identification). The Wal-Mart and
DoD (Department of Defense) mandates issued in 2003 have certainly been one of the
main causes for this increased attention, directed not only to industry players, but also to
the general public. As an introduction to this literature review, we propose to examine
the profile of this "offer" in resources about RFID.
Figure 1 shows the number of articles published on the subject in the last ten years
(Factiva, database of 8,000 news and business publications, by Dow Jones & Reuters).
6000
5000
-------
4000
1
-
3000
- -----
(D 2000 -
E
1000
Z 0
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2mths
Figure]
In the same period, we find 13 books or theses registered at the MIT libraries that
respond to the keyword "RFID". All of them were published in the past 5 years, 10 of
which as recently as 2002 and 2003. They essentially deal with the technical aspects of
RFID. Only one of them is related to the use of RFID in the supply chain.
To complete our view on the information sources, we launched a Google search. It
retrieved around 1.3 million results. In order to categorize the kind of information
discussed, we tried to find which words were the most often associated with RFID.
9
30
25
0
Google
-
20
15-
Factiva
-
0
0
Privacy
Security
Supply Chain
Inventory
Transportation
Warehouse
Figure2
The analysis of Figure2 highlights two factors. First, a great deal of articles are about
either the technical side of the subject or on the impacts of the technology on the general
public, in particular in the fields of privacy and security. Second, even if "supply chain"
or "logistics" are often cited, the number of hits decreases when it comes to more specific
areas such as inventory, and even more so for transportation and warehousing.
Our intent in this chapter is twofold. First, we aim to briefly explain the current state of
the knowledge in terms of technology, challenges, benefits and impediments of RFID,
referring to the sources that are accepted as authoritative. Second, we intend to point out
the work that we consider as an important contribution in the understanding of RFID use,
which have brought something new or original to the area of study.
Due to constraints of space, we will not explain RFID technology in detail nor address
implementation issues. Our goal is to remain focused on sources that describe both how
the logistics processes are impacted and how RFID can enable changes to or
improvements on these processes.
2.1.2 EPC Network and RFID technology
Functioning of a RFID system
RFID systems are a particular type of Automated Identification (Auto ID) systems, which
can be defined as involving "the automated extraction of the identity of an object" (Sheffi
& McFarlane, 2003).
10
Basically, a RFID system transmits to a reader a product's identity code embedded in a
tag, itself affixed to the product, through radio waves. Once the code has been read, a
data processing system enables access to the product information associated with the
code through networked databases. In order to make the whole system economically
viable, it is critical to lower the cost of the tag as much as possible. One way to achieve
this goal is to minimize the tag's functionality. The resulting cheap tag stores only a
unique identifier for the object, the Electronic Product Code (EPC) (Engels et al, 2002).
This short introduction has presented the basic components of an RFID system:
" The identity code of a product is given by the Electronic Product Code
" Tags host the code and readers get the code emitted by the tag and transmit it
downstream; different types of tags and readers may be used, depending on utilization
and needs
" Software then links the captured code to the global Internet and permits access to a
large amount of information about the product
The network is schematically represented in Figure 3, and we will briefly describe these
various elements in the next sections.
ONS Server
EPC
IPAddress
IP Address
RFID
Tag
EPC
EPC
(avant
Local
ServerPMSrv)
Information
Figure 3
11
Sre
The Electronic Product Code
Brock (2001) defined the EPC as a "naming scheme to enumerate and uniquely identify
physical objects". He added that the EPC must have the following critical characteristics:
be sufficiently large to enumerate all objects, be, as much as possible, universally and
globally accepted, and be extensible to allow future expansion in size and design.
As represented in Figure 4, the EPC scheme consists of four distinct, hierarchical
partitions: version number, domain manager number, class code, and serial number. The
version number partition contains information on the length and structure of the code
being used. The three remaining partitions contain the actual unique identifier for the
object.
ELECTRONIC PRODUCT CODE
- 96 bits
O1
0000A40
01963F
00250570A
n
Domain Manager Number
Class Code
Serial Number
28 bits
24 bits
36 bits
8 bits
Figure 4
In the 96-bit EPC, the version number spans 8 bits, allowing 256 possible versions, the
second partition spans 28 bits, encoding a maximum of 268 million manufacturers, the
object class partitions, with 24 bits, permits each manufacturer to manage 16 million
SKUs, and finally, the 36 bits of the serial number partition authorize to encode 68 billion
unique object identification number (Engels et al, 2002).
RFID Tags and readers
EPCs are embedded in special tags and transmitted through radio waves to a reader.
RFID tags have a small radio antenna that transmits information over a short range to an
RFID tag reader. Basically, a tag contains a microchip and an antenna. Tags come in a
variety of sizes and design, and may be categorized according three main criteria: power
source, frequency, and encoding method.
12
Tags may or may not use a battery to transmit data. Tags that use batteries are called
"active tags" and can transmit data to a more distant reader than tags without batteries,
called "passive tags". Passive tags draw power from the reader (which sends out
electromagnetic waves that induce a current in the tag antenna) to transmit data. "Semipassive" tags use a battery to run the chip's circuitry, but draw the power from the reader
to broadcast data.
Frequencies employed are low (LF), high (HF), and ultra-high (UHF). The frequency
used has a great impact on the tag's range and on the data transfer rate.
Tags may be "read-write", "write once-read many" (encoded on demand) or "read-only"
(encoded during tag's manufacturing process).
It is important to point out again that the constant objective of the Auto ID Center has
been to design tags at the lowest possible cost. For this reason they only considered the
passive tags, and focused on read-only tags. For complete information on the
components of a tag, for explanations on how to reduce its cost, and for cost model
benchmarks and simulations, see Sarma (2001) and Swamy and Sarma (2003).
Readers have two basics roles: to transmit a signal that empowered the tag; and to receive
the signal that the tag sends back. Contrary to a bar code scanner, a reader can read
multiple tags within its transmission field, but must use an anti-collision scheme to avoid
signal interferences. Readers can be fixed, at portals or at storage area, or they can be
mobile, on handheld devices or on vehicles.
The software: Savant, ONS and PML - Linking the EPC network
All information transmitted by readers must be processed before being routed to
application systems. First, a software technology called "Savant" controls, filters and
transmits data. Second, the Object Name Service (ONS) locates where information is
stored for a specific EPC. Third, the Physical Markup Language (PML) is used to
convey information through the Internet all over the EPC network and stores files in
dedicated servers (Singer, 2003).
13
The Savant manages the flow of information: it performs data capture, data monitoring
and filtering and data transmission. Networked Savants react to the EPC values
communicated to the tag readers, and act as gateways to local networks, devices, data
storage and inference engines. The savant systems are deployed in a hierarchical,
distributed framework, well suited for business application. It may, for example, provide
accurate real-time information to corporate ERP systems (Engels et al, 2002).
ONS indicates where to locate information on the Internet about ay object carrying an
EPC, meaning that it gives a web address or Uniform Resource Locator (URL) for every
EPC. All information about this EPC resides at this address, in an EPC-IS server
(formerly called PML server).
The PML language provides the means for the requesting application to retrieve the
information. Using the XML principles, PML includes a set of schema describing
common aspects of physical objects, like matter, physical properties (mass, volume,...),
measurable states (temperature, pressure,...).
To get more information, the reader can refer to "Savant Guide" (Goyal, 2003) and "The
Physical Markup Language. Core Components: Time and Place", (Brock et al, 2001).
2.1.3 Capabilities and benefits of RFID
The capabilities of RFID
Before describing the potential benefits of RFID, let us review briefly what RFID
systems can perform that other systems (like bar coding) cannot. Sheffi & Mc Farlane
(2003) provide an exhaustive summary of the basic capabilities that RFID has compared
to barcodes. RFID systems:
" Have a continuous and automatic (non-human) capture of data,
" Get simultaneous reads of multiple tags,
14
*
Do not require line-of-sight, meaning that manual scanning is not required,
" Provide a less fragile data support: weather-proof, scratch-proof, dirt-proof,
" Can provide the location of an object,
" When coupled with EPC system, allow to have a unique identification for any single
object.
The generic benefits of RFID
These basic capabilities can benefit many processes within a company or an extended
network of companies. In this section, we describe the common benefits that RFID can
provide, without detailing them process by process, which will be addressed later in the
chapter. The most frequently cited benefits can be categorized as follows:
*
Higher visibility
" Better accuracy
*
Labor costs reduction
" Increased speed
" Shrinkage reduction
Higher Visibility - By being provided with a continuous flow of data, stakeholders
have real-time and up-to-date information at their disposal and have a subsequent
visibility all along the supply chain. This means more effective tracking and improved
traceability. This also should indirectly lead to a better accountability of the data
transmitted from one entity to another.
The availability of information does not necessarily mean sharing it. However,
information sharing, by facilitating communication between entities, inside or outside a
company, is viewed as one of the most promising uses of RFID. "Using RFID to
collaborate across enterprise boundaries is an area that holds great opportunity"
(Fontanella & Bilodeau, 2003).
Better accuracy - Accuracy in data acquisition is a key benefit of RFID. By
eliminating human errors in reading an identification (whatever the technology is), RFID
improves greatly the quality of data acquired (Singer, 2003). The major impact on
15
operations is the reduction of unexpected events such as misreads or miscounting. It
should also lead to a claims reduction, making the whole reconciliation process easier and
leaving fewer grounds to dispute.
Labor cost reduction - By eliminating manual tasks, such as scanning or counting, as
well as by reducing clerical activities, such as data entry or data reconciliation, RFID will
eliminate or greatly reduce labor expenses. It should also significantly improve
efficiency, leading to a less expensive acquisition of data. "RFID basically eliminates
waste and inefficiencies created from process non-compliance" (Fontanella & Bilodeau,
2003).
Increased speed - Manual processes cause friction and slow down the flow of goods.
Speed may be increased by automating them through RFID. Goods flow faster, thus
reducing the order cycle time and allowing faster inventory turns (Dinning & Schuster,
2003). Moreover, RFID may enable earlier detection of discrepancies, which result in
saving the precious time that would have been necessary to solve a problem.
Shrinkage reduction - Finally, by applying tags on products (at "item level"),
visibility, traceability and accuracy in information gathering should reduce shrinkage and
theft at every stage of the supply chain.
2.1.4 Impediments to RFID implementation
Some technical issues still remain to be addressed and fixed before RFID can be widely
adopted. Read problems, due to a wrong tag's antenna orientation or presence of metal or
liquid, and interferences with a proliferation of wireless devices are still frequently
reported (Sheffi & Mc Farlane, 2003). Interoperability between readers and tags of
different vendors and read ranges, which appear to be much shorter than announced by
vendors are also not matching user's expectations (Fontanella & Bilodeau, 2003)
16
The impact of the enormous amount of data that will have to be stored, processed and
accessed has not been fully addressed by software vendors and future users.
RFID should facilitate collaboration between players, notably through information
sharing. But a key issue that may arise is the determination of ownership of the data
(Sheffi & Mc Farlane, 2003).
Finally, one of the most important and visible issue is privacy. Privacy advocates such as
CASPIAN (Consumers Against Supermarket Privacy Invasion and Numbering) have
issued a position statement on the use of RFID on consumer products (CASPIAN,
ACLU, EFF, EPIC, 2003). They respect businesses' interests in tracking products in the
supply chain, but emphasize individuals' rights not to be tracked within stores and after
products are purchased. Acceptable uses of RFID include the tracking of
pharmaceuticals and the tracking of manufactured goods if tags are confined to the
outside of product packaging and permanently destroyed before consumers interact with
them. Their main concerns are hidden placement of tags (embedded into objects) without
knowledge of the buyer, link of unique object's identifier to a purchaser performed at
POS, hidden readers (incorporated invisibly in tiles, carpeting, doorways,...), and
individual tracking and profiling (e.g., through a tag embedded in a shoe).
2.2 Transportation: overview and challenges
2.2.1 An overview of transportation: basic processes and players
The place of transportation in logistics
Total logistics cost as a percentage of US GDP (Figure5) has been decreasing for the
two last decades, and each of the components of this cost (i.e. inventory related costs,
transportation costs and administrative costs) has decreased as well.
17
Cost of Business Logistics in Relation to GDP
18.00%
16.00%
-
14.00%
12.00%
10 .00%
8.00%
-U-Inventory carrying costs
Transportation costs
-+- Administrative costs
f-I
6.00%
4.00%
2.00%
0.00%
-oo
C)
00)
M)
00
Figure 5
00
C)
M)
-
00)
)
Source:
m
C)
14
M
M)
M
O
M)
M
M
Total logistics costs
C)
M
C
>
" Annual State of Logistics Report - Delaney & Wilson (2003)
However, as shown in Figure 6, the relative weight of transportation costs in the total
logistics cost has constantly increased during the last twenty years. Transportation costs
grew more than other costs during this period, mainly due to JIT trends that tend to
drastically reduce inventory, resulting in a decrease in carrying costs as well as an
increase in transportation costs due to more frequent replenishment (Frazelle, 2002).
1982
1992
2002
3.85%
3.77%
3.80%
-.
37.26%
449.37%
58
46.84%
96
63.412
* Inventory carrying costs
*Transportation costs
U Inventory carrying costs
U Inventory carrying costs
UTransportation costs
E Transportation costs
O Administrative costs
OAdministrative
D Administrative costs
Figure 6
- Source:
1 4 th
costs
Annual State of Logistics Report - Delaney & Wilson (2003)
In the literature, it is extensively claimed that RFID should help to reduce even more
inventory costs, thanks to better visibility and to streamlined operations in warehouses.
The impact of RFID on transportation costs is not expected to be as high as it is in
inventory, but some savings should be attained through a reduction of expedited
shipments and a better utilization of assets. Administrative costs should also decrease,
but the gross reduction should be very small with respect to the total logistics cost. We
will more extensively address the impacts of RFID and the related benefits and savings
later in the chapter.
18
The players
In a basic and typical transportation transaction, a shipper pays a carrierto transport
cargo from an origin to a destination, where the consignee receives the cargo. The
document describing and contracting the movement of the goods is called a Bill Of
Lading (BOL). In the trucking industry, the carrier could be a parcelcarrier (UPS,
Fedex), a less-than-truckload(LTL) trucking company (Yellow, Overnite, Roadway), a
full-truckload (TL) trucking company (JB Hunt, Werner). Carriers may also be ocean
liners, railroad companies and air carriers. Finally, shippers and consignees may operate
their own privatefleet (Frazelle, 2002).
We will focus here only on for-hire TL and LTL carriers processes.
As shown in Figure 7 and 8, TL carriers manage relatively simple operations, with very
few break loads. A full truckload may be constituted by shipments from several shippers
and/or for several consignees, but generally, their number does not exceed three entities.
One of the main challenges for TL carriers is to find backhauls, especially when they
operate spot contracts.
Line haul
P osge
TL Carrier - Point-to-Point
Figure 7
Consgee 2
Shipper 2
haul
Pc-pLine
0osge
C3~
Shipper3
TL Carrier
-
Deliery
Cnin
e
~ ~
Multi Stop
Figure8
LTL carriers have to manage much more complex operations to carry smaller shipments
from one shipper to one consignee, as illustrated in Figure 9. Transportation is
segmented in several parts, each having its own resources and constraints. The multiple
break loads make the routing and tracking of the goods more subject to errors than for TL
carriers. However, these carriers follow regular routes, and the planning of capacity and
19
backhaul may be simpler than for TL carriers. As LTL operations are likely to present
more opportunities for using RFID than TL operations , we describe in the section below
some of their key specificities.
4
3
Em
L
Shuttle
Line haul
Shuttle
De er
LTL Carrier
Figure 9
Specificities and challenges faced by the LTL Carriers
LTL carriers can be divided into regional carriers and long-haul carriers. The regional
LTL carriers cover up to 1000 miles and offer an overnight or a two-day service. They
focus primarily on service and are required to be highly reliable. The biggest challenge
they face is that they have so little time to move a shipment that they have to make
decisions very quickly. The long-haul LTL carriers cover 1000 to 3000 miles and can
deliver in from two to five days. They focus on cost, with an acceptable level of service.
They can take advantage of day-to-day variation to fill the trailers to different destination
as opportunities arise (Powell, 2002).
Speed is critical for LTL carriers. They must develop abilities to respond quickly to
changing requirements (Bradley, 2004). For this reason, and also because of the extreme
variability of shipment size, planning LTL activities is not an easy exercise. Contrary to
TL carriers, which handle full loads, and to parcel carriers, which handle almost
exclusively very small shipments, LTL carriers must deal with considerably more
variability in the day-to-day flows. They also have to build separate planning for pickup
and delivery operations and for line haul operations (Powell, 2002).
Tracking is essential for LTL carriers because of its shipments' tortuous path, punctuated
with many break loads. Reducing the number of blind spots reduces the inventory; it is
achieved by getting real-time information (Frazelle, 2002). A "waybill" is created at the
20
first terminal for each shipment and follows the shipment up, from this point to the last
terminal, where a delivery receipt is generated for the last section to the final customer.
This waybill, generally materialized by a bar code, is critical to track the shipment.
Systematic bar code scanning at terminals is a must, as it allows carriers to know exactly
when a shipment was pulled from one trailer and loaded to another one. On the other
hand, as they follow fixed routes between their terminals, on-board vehicle tracking is
less necessary for them than for TL carriers (Powell, 2002).
2.2.2 Transportation management
Transportation management covers a wide range of activities, from strategic decisions to
execution tasks.
We will not here describe the strategic questions such as network design, nor the tactical
transportation modeling tasks like mode choice and routing options, nor transportation
procurement. We rather focus on activities going from medium and short-term
transportation planning to execution and monitoring to reconciliation. Our main sources
are Frazelle (2002) and the model developed by the VICS CTM sub-committee (2004).
As seen earlier, the three players are the shipper (vendor), the consignee (customer) and
the carrier. The relationship with the carrier may be led by either the vendor or the
consignee, depending on the freight term ("prepaid" if led by the vendor, "collect" if led
by the customer). We use the term proposed in the VICS CTM white paper (2004):
"owner of carrier relationship" (In this thesis, we assume that the owner of carrier
relationship is the shipper, as it is more frequently the case).
Product order fulfillment "end-to-end process" is schematically represented in Figure 10,
from forecast to delivery, through planning, transportation and reconciliation. The
diagram presents the respective roles of the three players and their exchanges, in
chronological order. Note that a distinction has been made between the corporate and the
operational level functions for the vendor and the customer.
21
END-TO-END PROCESS
Schedule
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Concerns all
tasks involved
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Figure 10
From product order forecast to shipment forecast
The first task is to convert a product order forecast into a shipment forecast. Having a
product order forecast, the owner of the carrier relationship aggregates the product orders
on different horizons (day, week, month,...) and builds planned shipments. Depending
on the relationships with its carriers, it may assign shipments and send them the shipment
forecasts. Carriers have then the possibility to compare shipment forecast with their
planned capacity and to identify discrepancies, and may update their capacity planning.
The two players then resolve the shipment forecast exceptions.
Shipment consolidation and carrier selection: building the transportation plan
When the owner of the carrier relationship gets the firm orders, it creates shipments from
these orders and assigns them to containers trying to maximize their utilization.
Shipments are then tendered, and carriers are chosen. Appointments are scheduled with
shipper and consignee, allowing resources to be allocated for shipping and receiving.
22
Transportation execution, tracking and reconciliation
Products are shipped, and shipment documentation and Advanced Shipment Notice
(ASN) are generated by the shipper. The carrier must be able to track the shipment and
to provide some visibility to the owner of carrier relationship, for him to monitor the
status of shipment. The carrier invoices the owner of carrier relationship. Freight
invoices are audited and paid.
2.2.3 Collaborative Transportation Management
Introduction to CPFR
Collaborative Planning, Forecasting and Replenishment (CPFR) is one form of
collaboration between trading partners' supply chains.
The main objective of CPFR is to better align supply and demand through trading
partners' data interchange, exception-based management, and structured collaboration to
eliminate issues and constraints in fulfilling customer expectations. The benefits of
CPFR are clear. CPFR not only helps to realize cost savings, but more importantly, by
developing new efficiencies, it helps companies to maintain or gain a competitive
advantage. The goal of CPFR is to change the relationship paradigm and create
significantly more accurate information that can drive the value chain to greater sales and
profits (VICS, 2002).
An extension of CPFR: Collaborative Transportation Management
In 2000, the Voluntary Inter-industry Commerce Standards Association (VICS)
committee - a non-profit organization that takes a global leadership role in the
improvement of the flow of product and information throughout the entire supply chain recognized transportation as the "the missing link" of CPFR. Collaborative
Transportation Management (CTM) is thus a new extension of CPFR (Russell, 2002;
Sutherland, 2003a).
23
CPFR results in a more accurate forecast, and is a win-win relationship between suppliers
and retailers. By including carriers in the collaboration process and by converting the
order forecast developed via CPFR into a shipment forecast, CTM extends CPFR to a
win-win-win relationship between suppliers, carriers and retailers (Esper, 2003).
Actually, the concurrent use of these two collaboration practices should ease the
convergence of companies' planning and execution processes (Browning, 2000).
In short, we can say that "CTM reduces transit time and inventory carrying cost for
retailers and its suppliers, while increasing asset utilization for carriers" (Cooke, 2000).
One of the main reasons for keeping a high level of inventory is to protect against
uncertainties. Better visibility and more information sharing contributes to lower
uncertainties, and will help to reduce inventory. It also helps to get more accurate
inventory and in-transit information, which will ultimately lead to a reduction of the
variance between order forecast and final order generation, resulting in a better planning
of capacities for carriers (Browning, 2000).
Cross-functional benefits of CTM
One of the most promising benefits of CTM is to provide a better visibility that would
allow a more efficient tracking of freight in the supply chain, and consequently improve
service level (less stock-outs) and on-time performance (Karolefski, 2002). A better
tracking should also permit an easier and faster processing of claims, leading to a
reduction of related administrative costs (Esper, 2003).
Another benefit of CTM is the cycle time reduction. By reducing the loading and
unloading time, by implementing more efficient cross-docking operations, by loading
trailers directly, bypassing the staging phase, the replenishment lead time will diminish,
leading to a decrease in safety stocks (Esper, 2003).
It should be mentioned that, if CTM enables more efficient cross-docking, loading and
unloading operations, the coordination of the flow of inbound and outbound shipments
24
requires a pinpoint planning of a number of variables. CTM is also an opportunity to
secure comprehensive and useful documentation (Urbanski, 2002).
Benefits for retailers
For retailers, CTM improves end-customer satisfaction through more perfect orders from
the vendor. It thus may also increase its revenue, thanks to a better on-shelf availability
(Karolefski, 2002). For example, the Wal-Mart - P&G - JB Hunt 2000 pilot test
demonstrated that the early obtaining of forecasted shipping information helps to secure
the right amount of capacity for a specific location, and therefore helps to meet retailers'
service needs. Finally, lead time variability is also expected to decrease, which should
improve reliability of delivery (VICS, 2001; Russell, 2002).
Benefits for vendors
A better forecast and more information allowed P&G to avoid premium freight costs
(VICS, 2001). In another CTM pilot, Best Buy asserted that better communication with
carriers led to a 20% reduction in administrative costs, that on-time performance rates
rose by 35%, and that it lowered its freight costs due to new opportunities to consolidate
LTL into TL freight (Field, 2004).
Benefits for carriers
By better communicating on shipment forecast and shipper's and receiver's docks'
availability, empty backhauls and dwell time can be significantly reduced, allowing
transportation costs to decrease (Karolefski, 2002). According to a 2003 VICS/CPFR
presentation, waiting time per driver to load and unload shipments reaches 33.5 hours
each week! The same source cites a 15% improvement in percentage of deadhead miles
and a 15% reduction in dwell time (Sutherland, 2003a). We find these results (too)
exceptionally good; the way they were obtained have not been detailed
Longer windows of visibility would also permit carriers to plan further ahead and reduce
empty miles, leading to an increase of asset utilization (Karolefski, 2002). Moreover, if
advance notices are longer, carriers may have more time to find other loads to
25
consolidate, resulting also in a better utilization of assets (Field, 2004). This has been
confirmed by the pilot test in 2000, when JB Hunt saw some opportunities to better plan
and maximize its assets (VICS, 2001; Russell, 2002).
Various other tests have brought encouraging results. Autozone, the largest US auto
parts retailer, reported a 33% improvement of truck-fill rate. In another pilot, Best Buy
took the responsibility of transportation to its facilities (passing from "prepaid" term to
"collect" term) and decided to share key information about forecasts with its carriers and
suppliers. Best Buy then saw over-the-road driver turnover improved by 15%, "days onhand" inventory passed from 12.3 to 6.5 days, on-time performance from 32% to 65% of
deliveries, and average lead time from 19 to 17 days (Field, 2004).
The role of technology
What makes CTM technically possible is technology, which permits instant and cheap
communication, and devices that gather information such as on-board computers, cell
phones and all other devices that get real-time status (Field, 2004). The merging of
common technologies such as Global Positioning System (GPS) and bar code (and soon
RFID tags) make deft management of freight possible, with the help of some softwarebased decision aids, feeding with real time information. The need for such digital aids
are clear to retailers (Urbanski, 2002).
The future of CTM
Some important questions remain to be more thoroughly addressed: how can companies
leverage the investments? how can the value created by the different players actually be
shared? Some resistance may have been perceived against CTM, but events such as the
new rules governing truckers' hours of service are an opportunity to turn the tide against
this resistance.
The fact is that CTM is still a work in progress (Sutherland, 2003b). But one may
reasonably be optimistic, as more and more major companies use CPFR and should see
CTM as a continuation of that process (Karolefski, 2002).
26
We can conclude this overview of CTM with this citation, which is of particular interest
in our study: "The collaborative piece is all information. Getting the right information its accuracy and timeliness - and integrating it correctly has been the Achilles' heel of
CTM" (Karolefski, 2002).
2.3
RFID and Transportation
RFID, enabler of process changes
As is the case with many new technologies, it is important to point out that RFID will not
be the magic bullet that will solve all problems related with long lead times, lack of
visibility or inaccurate information. RFID will not cure a bad business process, and will
deliver value only when applied to well defined and controlled business processes
(Fontanella & Bilodeau, 2003). Every player should be prepared to make process
changes to accommodate the technology and take advantage of its key benefits (Kinsella,
2003). A major CPG retailer has recently said that in order to maximize the benefit of
RFID, extensive rework has to be done with internal operational processes. It considers
this one of its biggest challenges, but also one of the most rewarding (Fontanella, 2003).
2.3.1 Benefits of RFID for transportation
In the sections below, we describe the major benefits of RFID within the transportation
process that have been identified so far. The processes we examine are:
" Pick-up at shipper's
" Movement of goods: line haul and shuttle operations, pick-up and delivery cycles
*
Delivery at consignee's
*
Consolidation / cross-docking at end-of-line and break-bulk terminals
27
LnhalConsignee
Shipper
TL Carrier - Point-to-Point
Consignee 2
Shipper 2
Pck-up
Shipper 3
Line haul
Consign e 1
Delivery
Con signee 3
Shipper 1
TL Carrier - Pick-up and/or Delivery cycles
4e
Pk-p EOL
cycle
tr
Shuttle
Line haul
Shuttle
EOL
a
natr
Dlvr
cycle
LTL Carrier
Figure 11
In Figure 11, we have highlighted, with dots and bold frames and arrows, the different
components of the transportation process. We should note that the number of tasks
impacted in a single transportation operation is particularly high for a LTL carrier.
Pick-up process
The main benefit identified in the pick-up operation is the suppression of systematic
verification, and all that this entails: less labor, better accuracy, higher speed, both for the
carrier and the shipper. As Dinning points out, manual counting and verification is
purely an error reduction process that adds no value. With RFID technology, products
can be instantly checked to ensure that shipment has the right products at the right
quantities (Dinning & Schuster, 2003).
An immediate effect is a significant verification cost reduction for the shipper, as it may
eliminate the need for the shipper's auditors and loaders (as loading can be made directly
by the order picker, suppressing the need for staging) and precious time saving for the
driver. The sending of Advanced Shipment Notices (ASNs) is much simplified, and
28
documents are created with fewer errors, which may critically help shipping the "perfect
order" and increase the order fill rate (Alexander et aL., 2002).
Some more subtle improvements are made possible by using RFID technology. Having
at one's disposal real-time information on loaded trailers, shippers may exchange the
content of these trailers when waiting for carriers if priorities change (Sheffi & Mc
Farlane, 2003). Late orders and emergency shipments may also be handled more
efficiently (McFarlane & Sheffi, 2003).
Delivery process
Benefits at delivery are not very different from those listed for pick-up, as they involve
almost the same players and the same tasks performed in reversed. Manual verification is
eliminated, the consignee automatically checking the data captured and transmitted at
shipping. Moreover, a electronic Proof-of-Delivery can be obtained by reading a
shipment's tags through a portal when unloading it (Sheffi & Mc Farlane, 2003).
Delivery / receiving is often cited as the operation that can benefit the most from RFID.
In particular, case receiving would benefit much more than pallet receiving as all cases
can be simultaneously read, even if they are "hidden" in the interior of a pallet (Singer,
2003).
More advanced benefits include automatic detection of item shortage, wrong item, wrong
quantity or wrong location, which may be valuable inputs for the Supply Chain Event
Management (SCEM) process aimed at reacting and making decisions when specific
events and variations are detected (McFarlane & Sheffi, 2003).
Transportation process
Through increased visibility, RFID may first enable a better operational efficiency.
Automatic generation of Bill Of Lading (BOL) will provide a carrier with shipment
content and let him know exactly what he has picked up. Notifying downstream
locations of these inbound shipments will allow a consignee to access quickly the actual
29
shipment, verify it against purchase orders and send an alert in case of mismatches missing goods, excess goods - allowing the problem to be addressed earlier, and
potentially suppressing extra trips (Boushka et al., 2002). RFID should also enable
management of events and variations in transportation, by anticipating delays (when
detected at shipping), identifying misrouted packages, diverting a trailer at the last minute
(McFarlane & Sheffi, 2003).
Claim processing should greatly benefit from RFID technology and the accuracy it
provides. Automatic BOL, invoice and Proof Of Delivery, directly generated by physical
movement of goods, will minimize human error and interpretation. Less time and effort
will be spent in reconciliation, leading to a reduction of both charge-backs and claim
processing costs (AT Kearney, 2003).
Carriers will be able to track and trace the assets and the detention and demurrage. The
reduction of the "invisibility" of their assets should allow them to better plan their
capacity and enhance asset utilization and productivity (Chappell et al., 2002).
Finally, financial management may also be facilitated, a coherence between
documentation and physical movements being ensured thanks to automatic generation of
invoice for freight in accordance with the BOL. The compliance of pricing to contract
will be easier to verify as invoices, based on shipping information, will be very accurate
(Boushka et al., 2002).
Consolidation process
As Fontanella points out, process steps that create an interrupted flow because of manual
scanning and data entry at each step are the prime targets for RFID technology
(Fontanella &Bilodeau, 2003a). As seen in Figure 10, LTL carriers constantly transfer
goods from one point to another to go from the shipper to the consignee. Almost each
point involves counting and documentation tasks, which cause "friction", slowing down
the flow of goods (Dinning & Schuster, 2003). Speeding these tasks will reduce cost,
30
benefit vehicles waiting to be processed, reduce driver wait time and lead to a better
utilization of vehicles (Boushka et al., 2002).
Moreover, goods are staged with other parties' items before being reloaded on a truck.
This constitutes one of the major sources of error, with the constant risk of goods left
behind or loaded onto the wrong truck, leading to lost inventory and late and incorrect
deliveries. By continuously providing visibility on goods that sit on a dock, RFID
technology will reduce these errors. For those that could not be avoided, the data
captured and stored at each point of the supply chain should significantly ease the
reconciliation of disputes (Dinning & Schuster, 2003).
The real-time availability of data about all merchandise present in a terminal will allow
the operator to alert consignees of the status of each case in the hub (Singer, 2003), and
further, it will increase visibility of drop shipments.
2.3.2 Positive impacts of other RFID-enabled processes on transportation
Our discussion so far has concerned the benefits that could be attained within the
extended transportation process, i.e. including pick-up, delivery and consolidation
operations. In what follows, we present the benefits that RFID can bring to upstream
processes and that may indirectly benefit transportation.
Demand planning can greatly benefit from RFID. On the supply side, having a precise
knowledge of what is on hand gives a more accurate base for replenishment. On the
demand side, sales (POS) and shrinkage can be captured, making the projection of
demand more accurate, and leading to better in-stock position, less out-of-stocks and less
average inventory, increasing sales while decreasing inventory cost. (Kambil & Brooks,
2002).
31
The use of RFID in the warehouse will have some beneficial effect on transportation as it
will improve the accuracy of its inputs. For example, RFID will enable continuous
inventory count, which, in addition to suppressing time cycle-counting or wall-to-wall
inventories, will give an exact picture of inventory at every stage. RFID will also provide
the ability to verify putaways, replenishments, picks, counts. These capabilities will
reduce erroneous putaways and mis-picks and allow for error correction before the final
step of shipping (Alexander et aL., 2002; Singer, 2003).
2.3.3 Positive impacts of RFID-enabled transportation on other processes
RFID used in transportation can also profit downstream processes.
If, by speeding several intermediary tasks within the transportation process, RFID can
decrease the total transportation lead-time and then contribute to a decrease in the order
lead time between the vendor and the customer, safety stocks should also decrease at
every echelon, as it is directly related to lead time. (Chappell et aL., 2002)
By knowing perfectly what has been sent, a vendor or a intermediary terminal can notify
a downstream location of the exact content they will receive, allowing them to better
manage their personnel and their equipment to handle fluctuations (Boushka et aL., 2002).
2.4 Assessment of current knowledge
2.4.1 What is covered, what is missing or poorly documented?
As mentioned at the very beginning of this chapter, articles, white papers and reports
have been abundant, particularly in the last two years, dealing with many aspects:
technical, business, financial, sociological, etc...
32
The most covered area is the technical one. We must cite the clear and thorough papers
published by the Auto ID Center, which address numerous questions and have constituted
a valuable source of information. This field has also been treated by many IT vendors or
consulting firms, and by the specialized press. By contrast, the financial side is certainly
least well documented, due to the fact that costs (tags, equipment) are far from being
stabilized, and that gains are very difficult to assess.
The impacts of RFID on business has been quite well documented too on most areas of
the supply chain, mainly by consulting firms. Academics' production on the subject is
not very developed yet. The business press has well covered RFID, but could not go very
far due to a lack of tangible examples. All in all, capabilities and benefits are extensively
described, and every reader interested in the subject can have a clear view of the potential
the technology presents. As most papers have not gone much further than a list of
expected benefits, the impact that RFID will have on current business processes have
been rarely addressed, nor have the concrete ways to integrate the technology into these
processes in order to achieve the promised benefits been well described.
While we may assume that many pilots are currently being led, very few results have
been disclosed and presented yet.
RFID and transportation
Some functions, like warehousing and demand planning, are well covered. Store
operations and manufacturing have also been described, but with fewer details.
Transportation is often briefly cited, mainly because its strategic situation between the
two ends of the supply chain, the shipper and the receiver. As a result, the shipping and
receiving parts of the process are quite well described. Many papers assert that functions
that should be the best impacted by RFID in transportation are asset management and
yard management. However, these functions are, in a certain sense, disconnected from
the other components of the supply chain, first because they concern only one player, the
carrier, and second, because these functions use active tags whereas most other logistics
33
processes use passive tags: there is only a distant link between them from a "RFID point
of view"
Yet, if we remain in the "passive tag world", the potential value that RFID can generate
within the transportation process itself, as well as in upstream and downstream processes,
deserves a deeper analysis in many respects. We list some possible further investigations
in the next section.
2.4.2 What is worthy offurther investment?
Again, theoretical capabilities of RFID in transportation have been well described, from
visibility, to accuracy, to speed, to automation and so on. The expected benefits - better
service to customer, less labor, fewer claims, more flexibility, better financial
management,... - have similarly received considerable treatment. However, we find that
a few aspects and subjects have been overlooked, or at least, have not been given
sufficient attention. We list below some that we will try to address in the core part of this
thesis.
1.
More attention has been given to physical operations than to planning or to
reconciliation
2. Transportation has been considered as a homogeneous field, rather than an area
composed of different type of carriers (TL, LTL), or players of different sizes
3. Benefits have been described from a "holistic point of view" rather than player by
player, making it difficult to assess the value of RFID for each player
4. The organizational implications have been rarely analyzed, or, if they have been, it
has not been very thoroughly performed
5. Finally, some areas have not been very well studied; we may cite impacts of lead time
reduction, asset utilization, driver's productivity, etc...
34
We briefly describe below what we intend to do to address these points.
1. Analysis of all transportation operations
Our first task will be to make an "extended" transportation process mapping. It will go
from forecasting transportation, to planning, to execution of physical and administrative
operations, to reconciliation. We have a sense that the main part will be dedicated to
execution, but we are willing to see how RFID could directly or indirectly benefit the
other processes.
2. Distinction between TL and L TL operations
We do not assert even before having made any analysis that the results should be very
different for TL and LTL carriers in their use of RFID technology. However, as it is
clear that their operations are quite different, in terms of organizations, materials,
constraints, customers, etc..., it should not be surprising that RFID could apply in
different ways, have different prerequisites and bring different benefits to these two
different types of carriers.
3. Analysis of the value of RFID for the various players involved in transportation
The players we cite here are those which "use" transportation, from the point of origin to
the point of destination: the shippers (we will also often call them "vendors"), the
carriers, and the consignees (often called "customers"). Actually, we will try to separate,
for each RFID application we will identify, who invests in RFID and who benefits from
the investment, in order to assess the value of RFID for each player. We will not do it in
a rigorous quantitative way as we did not have the resources nor the time to do so, but we
will try to give a general evaluation of these RFID values.
35
4. Organizational implications of RFID implementation on the players
This theme has been mentioned several times in our literature review, in particular
through Collaborative Transportation Management (CTM). However, it is not clear to us
to what extent RFID will be an enabler for the development of CTM, or whether, on the
contrary, the full benefits of using RFID will not be highly dependant of a better
collaboration between players. In other words, will it be possible to implement RFID in
the transportation world only if we can achieve a better collaboration between shippers,
carriers and consignees.
5. Other issues
We will try to address here various subjects. It has often been mentioned, for example,
that lead times and lead time variability reduction should have many impacts, from safety
stock reduction to better use of assets to enhanced driver's productivity. We will try to go
further than what we may have found on these subjects to assess to what extent these
assumptions are justified.
36
3
METHODOLOGY
3.1 Information collection
Information has been mainly collected through literature (see previous chapter). We have
also taken advantage of our past professional experience in logistics and transportation.
Finally, we have also worked closely with a few companies that gave us some very
valuable information. For confidentiality reasons, we will not cite their names. However,
we may specify which kind of company it was:
" A major CPG manufacturer (3 interviews, 1 field visit)
" A major and a mid-size retailer (3 interviews, 3 field visits)
" A major LTL carrier (2 interviews, 1 field visit)
3.2
Process analysis
We will present in the first section of chapter 4 the scope of the research and how we
have divided it up; each process will be analyzed following this "analysis road map":
1.
Mapping of the current process ("As-Is")
2. Main issues we have to cope with
3. Identification of problems' causes
4. RFID capabilities that can address the problems
5. Mapping the RFID-enabled process ("To-Be")
6. Main changes or improvements
The following methodologies were used to perform these analyses:
" Process mapping: current process ("As-Is") and RFID-enabled process ("To-Be")
*
[.
Cause and effect diagram (also called: Ishikawa diagram and fishbone analysis).
[1] Precious information and guidance have been provided by the following resources: "Process
innovation", by Davenport (1993) and "Business process change", by Grover and Kettinger (1995).
37
3.3
Evaluation of new processes
Each process is then assessed, following these steps:
1.
Expected benefits of RFID implementation
2. Assumptions and prerequisites (technical; financial; organizational)
3. Estimation of the value of proposed changes
4. Evaluation of the changes
3.4
Methods and approaches used
We further measure the impact of lead time and lead time variability reduction on safety
stocks. We present below the method we will use:
" Relationship between replenishment lead time and safety stock level
*
Relationship between lead time variability and safety stock level
*
Limitations of these approaches
3.4.1 Relationship between replenishment lead time and safety stock level
The safety stock is the amount of inventory that is kept to protect against the deviations
from average demand during the replenishment lead time (Simchi-Levi et aL., 2003). The
quantity is calculated as follows:
- Safety stock = z *
*Y -
(1)
Where:
" z = "safety factor"; it is chosen from statistical tables, and corresponds to the service
level (i.e. the probability of not stocking out during the replenishment lead time) that
we wish to reach
*
T = standard deviation of the demand, that characterizes demand variability
*
L = replenishment lead time
38
We may infer from (1) that for a given demand variability and a given service level, the
safety stock depends only on the lead time, and most precisely is proportional to the
square root of the replenishment lead time.
For example, if we want to have a 96% service level, which corresponds to z= 1.75
assuming a normal distribution, and if the demand is 100/day, with a variability 7 = 20,
then the safety stock will be proportional to 35* JT. Consequently, if the lead time is one
day, the safety stock is 35, whereas it is 50 with a lead time of two days.
3.4.2 Relationship between lead time variability and safety stock level
Most of the time, it appears that the lead time itself may be subject to great variations.
The classical example is in ocean transportation, where bad weather conditions may have
a strong effect on total transit time. In road transportation, events like delays at loading or
unloading, road works, traffic jams or truck breakdown have the same effect.
If we assume that demand at any time is normally distributed, with average demand
during lead time g and standard deviation of the demand (, and that lead time also
follows a normal distribution, with average replenishment lead time L and standard
deviation of the lead time SL, then it has been shown that the standard deviation of
demand during lead time is (L*2 + p2 *S 2 ) (Nahmias, 2001).
Strictly following the assumptions above, and considering the safety factor z, we can
express the safety stock as follows (Simchi-Levi et al., 2003):
- Safety stock = z * 1(L*&2 + g2*L
2
)
(2)
When using this model later in the research, we will not go into such details (that is, we
will not consider all these parameters at the same time). In particular, we will not
calculate the safety stock considering different average demands and demand variability.
39
However, in order to take these two variables into account, we use the coefficient of
variation, which is the ratio between the demand standard deviation and the average
demand (cv = a/g). Using the coefficient of variation, we can quantify the safety stock as
follows:
-
Safety stock
z*
*
(L + (SL2 / cv 2 ))
(3)
We can infer from this formula that decreasing lead time will mechanically decrease
safety stock. If we reduce the lead time variability, the effect will also be a reduction of
the safety stock. Finally, if we can reduce both lead time and lead time variability, the
safety stock reduction should be even more significant.
3.4.3 Restrictions to the use of these approaches
Chopra et aL. (2004) reminds us that the validity of this approach depends to a great
extent on the assumption that the demand during lead time (a) is normally distributed.
Their analysis indicates that this approach cannot be used all the time. In particular, they
demonstrate that for service levels situated between 50% and a certain threshold (they
chose a 70% threshold), the prescriptions of the normal approximation are flawed, and
that in fact, reducing lead time variability increases the required safety stock. For a
service level of 95%, however, using the prescriptions of the normal approximation is
correct.
The problem is that in most cases, companies' managers think that they operate at a
service level of at least 95%, when in fact they have a Fill Rate of 95% (the proportion of
demand that is met from stock), which is very different. Actually, their service level is
comprised between 50% and 70% (which corresponds to a fill rate of 95-99%).
So, contrary to what has been stated in the previous section, reducing lead time variability
does not necessarily have a greater impact than simply reducing lead time. However,
40
Chopra et al. conclude their study by the two following remarks: First, it makes sense to
use the demand normal approximation if the lead time follows a normal distribution, but
it absolutely does not if it follows a distribution closer to the gamma. Second, the flaws
are less pronounced if the coefficient of variation of the demand is low.
As a result, in our research, we will have chosen to study the impact of the lead time
reduction, and when studying the effect of lead time variability reduction, we will
consider only low coefficients of variation.
41
RESEARCH: INVESTIGATIONS AND RESULTS
4
Scope and approach
4.1
A "process-by-process" study
Simplifying the chart presented in Figure 10, we can represent the transportation process
as follows (see Figure 12). We have divided up the whole process into four processes:
Forecast, Plan, Execute and Reconcile. "Track" can be considered as a part of the
"Execute" process, as tracking is present in any of the execution elementary tasks.
I
SIMPLIFIED REPRESENTATION OF TRANSPORTATION PROCESS
plan (TL/LTL)
CD
0
0.
Forecast
orders
Forecast
shipments
process
final orders
0
Sh ments
capacity
E
E
00
CL
=0.
M L_
Forecast
orders
Create
'final
orders
orders
FORECAST
EXECUTE
PLAN
Concerns all
Tra
Tracein
Shipments
tasks involved
the execution
process
Figure 12
Distinction by type of carrier
This research focuses on TL and LTL carriers' processes. As mentioned in Chapter 2, TL
and LTL operations are different. If transportation management can be quite complex for
TL carriers (material positioning, drivers' management, backhauling and deadheading
management,...), the point-to-point physical operations are relatively simple to handle.
42
By contrast, LTL physical operations are composed of a succession of stages that must be
well coordinated. In particular, routing and tracking of shipments is more complicated,
while transportation management (notably assets and personnel management) is
relatively simpler for LTL, due to a better regularity of daily operations.
Knowing these differences, we will present the processes as follows:
" The Forecast and Planning processes described in the next section apply to TL
carriers, as these processes are more critical for them than for LTL carriers, whose
planning is more or less similar every day.
" Execution is quite different for the two types of carriers: the execution process will be
analyzed separately for TL and LTL carriers.
" Reconciliation process applies more or less identically for TL and LTL carriers. The
fundamental principles are the same, although it is more complicated for LTL carriers
due to their multiple stages.
Approach taken
In the sections below, we present a detailed analysis and evaluation of the four processes.
For each one, we aim to stick to the following I 0-step template:
1.
Mapping of the current process ("AS-IS")
2. Main issues we have to cope with
3. Identification of problems' causes
4. RFID capabilities that can address the problems
5. Mapping the RFID-enabled process ("TO-BE")
6. Main changes or improvements brought by RFID
7. Expected benefits
8. Prerequisites to RFID implementation (technical, financial, organizational)
9. Estimation of the value of proposed changes
10. Evaluation of the changes
43
4.2 From "Forecast" process to "Reconciliation" process
4.2.1 The "Forecastand Plan Transportation "process
We discuss here the "Forecast transportation" and "Plan transportation" processes
together. These processes have already been briefly described in the "Transportation
Management" section in chapter 2.
AS-IS "Forecast & Plan Transportation" process mapping
"AS-IS" - FORECAST & PLAN TRANSPORTATION
Un
Sdefine
Create shipts
by lane,
C(TULTL)
re
s
Forecast
F
FAnsszign
li
mode
blaecrir
Convert order
reg
Set pick-up
schedule
shipments
to one or
more carriers
n
lane volumes
h
No
CD
Q
Ernsi
at
FAcceps
Chnsemk
Yes
0
orders
L_
0
hstory'
4
z1
00
final orders
Pon of[
etdeivery
na
nr
0n
PLAN
FORECAST
Figure 13
Note on the terminology used: "orders" refers to "product orders", passed by the customer
to the vendor. The orders passed by a shipper to a carrier to transport products are
referred to as "transportation orders", "shipment orders" or simply "shipments".
Basically, the process is initiated by the creation of product order forecasts by the "owner
of the carrier relationship" (we will consider in this research that it is the shipper/vendor).
44
These forecasts are aggregated, converted into a shipment forecast and transmitted to the
carrier. This allows the carrier to have better visibility on its long and medium term
activity, and to check its capacity. On the short term, the customer sends firm orders to
the vendor. They are aggregated again, and incorporated into TL or LTL shipments.
Depending on the lane and/or on contracts that have been passed, the vendor tenders the
shipment to one (preferred) or several carriers. Carriers check if they can handle the
shipment. In case of negative response, the shipment is tendered to another carrier, and
so on until it is awarded. The chosen carrier then contacts both the vendor and the
customer to schedule the pick-up and delivery times.
Main issues we have to cope with
We see in Figure 14 that the feasibility of short term transportation directly stems from
the carrier's capacity forecast, itself drawn from the vendor's forecast. We also see that
short term shipments received from the vendor are based on actual customer's orders.
"AS-IS" - FORECAST & PLAN TRANSPORTATION
Craesipts
Fiaie
I
cOby
Assign
01w w
CL
oU
wek
schedule
or
Caecar
01 day)
Convert order
F
orders
ist
eek
Set pick-up
ents
byfnV
lane v
beso
(weeksi
(months)
No
raa
caca
h
by lane
(months)
consumer
E
o 0
3 0
salmmme
o
$
c
yln
Accept
hipme
(1day)(1dy
smmm.~eneee
history
(months 3
=0
(_eek_
03
Sr'
inetre
PLAN
FORECAST
I
---
)
) Customer / Vendor forecast & plan path
Figure 14
45
Vendor / Carrier forecast & plan path
Plan
shiprment
The dotted line corresponds to the forecast between the customer and the vendor, the
continuous line represents the process between the vendor and the carrier. These two
different paths merge extremely late in the process. At this particular moment, the carrier
has at its disposal a fleet that it had dimensioned according to vendor's forecast, and then
receives a firm order from the vendor, that corresponds to actual customer's orders. It is
only at this last moment that the carrier is asked to confirm whether or not its capacity
will match the shipper's next days' needs.
Needless to say, the carrier's ability to react to unexpected fluctuations is not optimum.
The consequences are negative for all players:
" The shipper is in trouble when confronted with a higher than forecasted demand, as it
cannot rely 100% on its usual carrier, and may be led, in the last instance, to resort to
an expedited shipment.
" The carrier may face two different problems. In case of higher demand (than
forecasted), it cannot respond to the shipper's needs, and therefore looses potential
revenue. In case of lower demand, it has idle assets which were "reserved" for this
shipper, and inherent immobilization costs.
" For the customer, the risk of unexpected higher volumes is that the shipper cannot
find alternate carriers quickly, leading to possible stock-outs.
Such situations are therefore not desirable for any of the players. In order to see if RFID
can resolve some of these problems, we list below the main causes of these difficulties in
forecast.
Identification of problems' main causes
The following cause-and-effect diagram lists the root causes of the problem.
46
Materials
Manpower
Variation
of customer
demand
Coordination
between
players
No rules on
information sharing
Variation of
consumer demand
Separate forecast
processes
Promotions,
seasonalities...
Different sources
infrequent
data update
information
No shared
access to data
Nof
Forecat horizon
too long
inappropriate
forecast
parameters
Synchronization
of
information
Methods
Machines
Figure 15
The primary cause of the variation is predictably the variation in customer demand,
which may depend on final consumers demand but also on promotions initiated by the
customer, or on seasonality. These causes cannot be addressed directly by the carrier,
and must be handled by customer and vendor. However, it is critical to inform the carrier
about these predictable variations.
A second cause may be the use of inappropriate parameters, like length of forecast
horizon and level of aggregation. Forecast accuracy is better within a shorter horizon and
a higher level of aggregation.
The third cause is a weak coordination between players and has been described earlier
(the "two parallel paths"). The cause is again organizational, as information sharing
between customers and vendors is generally poor. It seems to be even poorer with
carriers, at least on a long horizon.
The final cause we identify is feeble information synchronization between players. First,
data comes from different sources, and not surprisingly leads to different results when
processed. Second, even though it comes from different sources, information could be
shared, but this is rarely the case, perhaps for reasons of confidentiality. Finally, even
when data is shared, the update frequency is low, and players tend to work with old
information.
47
This review of poor transportation forecast's root causes shows that it is due to deficient
coordination between players and insufficient information sharing. However, even if
everyone were inclined to improve these two aspects, the limits both on information
homogeneity and current technology would not allow for a high level of data
synchronization, nor, consequently, a more efficient joint forecast process.
RFID capabilities that can apply to this process
One of the main capabilities of RFID is to provide visibility on every tagged object
across the extended network of customers and vendors, with high accuracy, and in real
time. It seems that it is exactly what would enable an efficient data sharing, and allow
the players to exchange on a common base.
TO-BE RFID-enabled "Forecast & Plan Transportation" process mapping
"TO-BE" - FORECAST & PLAN TRANSPORTATION
co
Creat
d0iemoe
&t
ipts
-
7
S(TLTL)
Finalize
freight plan
by lanelcarrier
epikp
shdl
Assign
--
shipments
to carrier
CL
0retailer
L- IX
Convert order
forecast to
lane volumes
sales
history
yrgn
No
$D )
hipmenh
*mmm8iw
conser u e
Eom
0CL
*m
a
am w
gmm
Vs
sales
ent
Create
final orders
0U
0o
eiv"r
Sescedue
06
*ge
PLAN
FORECAST
Impacted
data exchange
New
data exchan
Figure 16
48
Main changes or improvements
RFID-impacted processes include inventory management at Distribution Centers (DCs)
of both vendor and customer, and at customer's store's backrooms. Implementing RFID
will enable a real time visibility on inventory at these locations. Moreover, and most
importantly, RFID-generated data will be at customer's and vendor's disposal, so that
everybody has the same level of information. Finally, a strong relationship must be
developed between the customer and the vendor in order to fully take advantage of the
common data and develop "joint forecast orders".
Expected value
From a pure "product order" forecast point of view, a joint forecast should allow the
vendor to obtain a far better supply planning, with the ultimate goal for the whole channel
to better match the demand. Improvements should lead to a reduction of product order
forecast variability, which should reflect in shipment forecast variability.
From the carrier point of view, less variability in shipment forecast should enable a better
capacity planning, for the long term forecast, and a better asset utilization planning for
the short term shipments, with these two following direct consequences:
" A prevention of truck unavailability, avoiding shipper's dissatisfaction and possible
penalties because of missing trucks.
*
An avoidance of lost sales, preventing the shipper to turn to another carrier.
It should also be beneficial for the other players, as the shipper could avoid paying a
premium for an expedited shipment, and the customer should avoid a stock-out.
Prerequisites
Technically speaking, implementing this requires that products be tagged at the source by
vendors. However, item level tagging is not mandatory. Case level is sufficient, as we
need information only from DCs and stores' backrooms. Readers and appropriate
software must be installed at vendors' DCs and at customers' DCs and stores.
49
Financially, the burden is mainly on vendors, with tags' cost and investment in readers
and software. Customers must also invest in readers and software. We may note that no
investment is required from carriers.
It is from an organizational point of view that the challenge seems to be the greatest.
First, implementing an efficient RFID network and fully using the newly available
information requires that the players broadly agree to share information. Beyond
implying only tools and procedures, it necessitates trust and long-term relationship
commitment. Second, if information is used not only to forecast product demand, but
also shipments, RFID has to be comprehensively implemented by vendors. In other
words, a vendor cannot decide to tag some products (i.e. fast-moving or high-value
products) and not to tag other ones, as a shipment will be made of both types of products.
Evaluation of the changes
Our purpose is to briefly evaluate the value for the different players, by summarizing:
"
Who has to invest in RFID, what is the nature of the investment
" Who benefits from the investment, what is the nature of the benefit, is it quantifiable
" What is the value for each player in investing and/or using RFID
Value
Noe Comments
Tags at case level Information
Better supply planning = avoidance of premium
software
better service offered
(better matching of
customer's demand)
(comprehensive sharing on
tgging), readers, product forecast
eaders,
Aifware
Information
sharing on
product forecast
tagig) redes prdc foecs
o investment
+
for expedited shipments
Better demand planning Reduction of risk of
= better matching of final stock-out, avoidance of
consumer's demand
product lost sales
High
investment,
moderate gain
+++
Moderate
investment,
high gain
+++
No investment,
(bteIacigooeaegi
Better visibility on long-
Communication of N/A
shipment forecast
term capacity; better
ability to manage assets
in the short-term;
avoidance of penalties
by vendor
Carrier
and/or shipment lost
sales
Table 1
50
high gain
What is striking here is that investment required by the vendor is quite high while the
benefits are rather limited. The value for this player to apply RFID in its forecasting
process is not high. By contrast, the benefits generated for the customer are quite high
(less stock-out, less lost sales), with a moderate investment. It is even better for the
carrier, as it does not need to invest at all and can potentially significantly improve its
capacity planning and its short-term asset utilization (we remind the reader that for the
forecasting process, we consider only the TL carriers).
However, this value generated for customers and carriers leans on the assumption of a
perfect information sharing. RFID can technically enable it, but most importantly, what
is needed is a collaborative attitude between the three players. We will see later in this
research that Collaborative Transportation Management is a way to make this possible.
51
4.2.2 The "Execute Transportation"process - TL carriers
This process is composed of shipping, transportation and receiving
AS-IS "Execute Transportation" process mapping, for TL carriers
"AS-IS" - EXECUTE TRANSPORTATION
o Q
C
Sendntcickup
Schedule
P0k~
peni
shipment,
EDI 216
pick-up
,
Load trailer
--
TL CARRIER
-
Issue ASK
BOL &invoice,
BOL filed
i
0
Carrier
0
orANprdcs)noc
or
1
ickNu
for
Yes
aRecive
0
de
ED
856
products,
Unload
trailer
Shipment
status
EDI 214
Check again t
-+
1. & ASN,
Establish POD
Track I
trace
shipment
OK?
Sign BOL with
annotations,
File
PD
fil
0
FlPO
claim
Freight
claim
EDI 920
Figure 17
After having planned the transportation, the carrier contacts both the shipper and the
consignee to schedule the pick-up time and the delivery time. With this information, the
truck is dispatched to the shipper, where verification and documentation tasks are
performed and goods are loaded. The truck then leaves the facility and goes to the
destination point. Once arrived at the destination, goods are unloaded, and verification
and documentation tasks are performed by consignee.
52
Main issues we have to cope with
As shown in Figure 17, the number of documents handled is quite high (yet, it does not
include the Purchase Order, which initiates the whole process). Every document has the
specific purpose of describing and recording a transaction between at least two of the
three players. For this reason, some information is specific to these two players, while
the remaining data is common to the three. Consequently, even before the intervention of
any of the players, the primary challenge is to ensure that data is coherent in these various
documents.
In TL transportation, potential problems principally happen at the two ends, that is during
the shipping and the receiving operations, rather than during transportation itself.
Counting and verification tasks, which are very error-prone, must moreover be performed
at a fast pace. In addition, a number of documentation tasks have to be carefully
executed. By contrast, transportation, from a shipment's tracking perspective, is quite
simple for TL carriers, as products are not handled until they are unloaded (for carriers, it
is sufficient to locate the truck, which is nowadays simple and cheap with GPS).
Identification of problems' main causes
Materials
Manpower
IDocumentationi
Human errors
Spoiled
Mis-routing
code label
Hidden packet
Mis-counting
Data keying
orlabelMis-loading
Mis-labelling
Not reliable content
Documentation
No auto-detection
tasks complexity
Poor management
of priorities
Sequential reading
Shipping & receiving
procedures
Bar code
system
Methods
Machines
Figure 18
Since bar codes have been massively used almost everywhere that goods are handled,
problems due to misidentification have been significantly reduced. However, as long as
53
human intervention is needed, and because of some of its inherent limits like sequential
and line-of-sight reading, bar-code systems still present some flaws. Figure 18 presents
the root-cause analysis for delays and discrepancies within the current system.
By far, human errors are the greatest sources of errors: wrong data entry, miscounting and
mislabeling of cases and pallets, loading of pallet on a wrong truck. Moreover, the "raw
material" necessary to handle these tasks (labels, delivery notes, bills of lading,...) may
be damaged and often leaves room for interpretation. In addition, the sequential
functioning makes fast work more difficult and more error-prone.
Documentation procedures may be complex and time consuming, as they refer to various
documents with various formats and information. Errors are easy to make but hard to
detect. Procedures that handle exceptions are and will remain complicated, as long as
"manual" identification and location of goods are needed.
RFID capabilities that can apply to this process
RFID technology, can be very useful here, maybe more so than anywhere else. Coming
back to its main capabilities - visibility, accuracy and speed - most of the problems we
have identified above should be solved by the use of RFID.
RFID can acquire automatically the data without keying it, creating errorless documents
(ASN, BOL, POD,...), and storing them. It suppresses counting, checks if loading is
done on the right trailer, suppresses some labeling. Tasks are performed quickly, leading
to a significant time reduction in staging, loading and unloading. Finally, the technology
allows for the detection of goods' location and provides time stamps at every (equipped)
place and at every moment.
54
TO-BE RFID-enabled "Execute Transportation" process mapping, for TL carriers
"TO-BE" - EXECUTE TRANSPORTATION
0
10 0
a)0
C
Schedute
pCiokup
Sn
-TL
CARRIER
iku
Sn iku
notice
EDI 216
a)
>0
0
a)
Tranap.
oEder
0
orI 204
Dispatch
ruck
for pick-up
4a)
___
0 0
0
CD
E
0
0
*C 0
Schedule
delivery
0
*
Impacted
data exchange
Figure 19
Main changes or improvements
Obviously, this is one of the most impacted of the four processes. RFID can be used
fully here, allowing labor reduction, data accuracy, speeding up and global visibility.
Suppressed
task
Transportabton
Figure20
Figure20 shows how RFID capabilities can lead to suppress or improve some tasks.
55
At receiving, as data can be collected automatically when a pallet passes through a portal,
the need for scanning shipments' bar codes is eliminated, potentially leading to a
suppression of the scanning task. At the same time, the data captured can be compared to
what is expected to be received (what has been sent by shipper through an Advanced
Shipment Notice - ASN), avoiding manual verification, and reducing the possible
mistakes.
At shipping, documents such as ASN and Bill Of Lading (BOL) can be automatically
generated when trailers are loaded. At the receiving end, data captured at unloading can
be compared automatically with the RFID-generated ASN and BOL, and an automatic
Proof of Delivery (POD) can be created.
Finally, by systematically passing through a portal before being loaded, shipment's
destination can be checked, avoiding the goods to be misrouted.
Expected value
Early detection of loading and routing errors, as well as speeding up of documentation,
loading and unloading tasks should allow for a reduction of delayed deliveries. Delays in
TL transportation may be a few hours, but also days (if a shipment is mis-loaded, or
because of hours of service,...). This may lead to a delivery in two days instead of one,
or three instead of two. By reducing delays, the average lead time and the lead-time
variability should decrease, allowing shippers and consignees to reduce their safety
stocks.
The automatic verification and generation of documents at shipping (ASN, BOL, invoice)
and at receiving (POD) will reduce auditor and clerk cost, improve accuracy and
therefore allow further savings in reconciliation for all players. Elimination of misshipments will result in less need for expedition. Tracking will offer a better service to
shippers and consignees, through shorter and more consistent transit times.
Finally, automatic generation of documents as well as automatic detection of staging
locations will also help to reduce loading, unloading, searching and waiting times for the
driver, helping to comply with the new Hours Of Service (HOS) regulations.
56
Prerequisites
Basically, the technical prerequisites for using RFID in transportation are no different
than in forecast or planning: it requires that products be tagged by the vendor at the case
level, and that readers and software be installed by shippers and consignees.
Financially speaking, we are in a similar situation, meaning that the burden falls mainly
on the shipper, with tags, readers and software, and on the consignee with readers and
software. Again, no investment is specifically required from the TL carrier, as there is no
break load between the shipping and receiving stages.
Organizationally, the prerequisites are quite different from forecasting. Some agreements
will also be required between players to share information, and here too, it implies trust
and long-term commitment. But whereas implementation had to be comprehensive to be
effective in forecasting (at least for carriers), it can be more selective in transportation.
Selectivity can be applied at several levels:
" Not all of a specific vendor's products necessarily needs to be tagged. The vendor
may decide to target only sensitive or expensive items.
* Not all "routes" need to be followed: some facilities can be equipped with readers,
and others not. For example, only routes from factories to DCs, or from vendor's
DCs to customer's DCs can be followed up; or only the Northeastern region can be
targeted.
" Finally, it may also be selectively implemented with certain customers (for a vendor)
or certain vendors (for a customer).
Estimation of the value of proposed changes
RFID can generate the following value when applied in TL transportation. We will try to
quantify the gains for the two first points, and give estimates for the others.
1.
Reduction of vendors' and customers' safety stocks
2. Reduction of labor cost, for all players
3.
Faster and more regular service offered to vendors and customers
57
4. Help for carriers to better comply with Hours of Service
1. Reduction of vendors' and customers' safety stocks
Delays should be reduced thanks to early detection of loading and routing errors, and to
the acceleration of several operations, leading to a reduction of average lead time and
lead-time variability, then to a reduction of safety stock (see Chapter 3).
Approach used to quantify the potential safety stock reduction
Assumptions:
"
If a shipment is delayed, the delay will never be more than one day. For example, if a
one-day trip (announced lead time) is delayed, the delivery will be done in two days;
for a two-day trip, it will take three days, etc...
" Thanks to RFID capabilities, a certain proportion of delayed deliveries will be
avoided. For example, instead of delivering 92% of the shipments on time, RFID will
permit a 96% on-time delivery performance.
Method:
*
For three different TL transportation lead times (we make the study for a 1, 2 and 3
day lead time), we calculate the corresponding average lead time and the lead time
variability, for different values of on-time delivery rate (OTD rate). To do so:
o We use a large population of trips: 100 trips/day during 20 days = 2000 trips.
o We then fix an OTD rate objective, generate 100 random numbers between 0 and
1, and identify the proportion of trips that are "above the on-time rate": these trips
are considered late.
o For example: we set a global OTD rate at 96%. We then generate 100 random
numbers, and identify which ones are above 0.96 (a table with this example is
displayed in Appendix A). For this particular day, 6 trips were late, leading to an
OTD rate of 94%.
58
*
We repeat this 20 times, running the model as long as we reach the desired average
OTD rate on the 20 days. We obtain for each day a specific rate, with a specific lead
time and lead time variability.
" In our example (see Appendices B), day 1 has an average lead time of 1.03, a
variability of 0.171, and an OTD rate of 97%; for day 2, it is 1.06, 0.239 and 94%; for
day 3, 1.07, and 0.256 and 93%; etc... Appendices B displays the 20-day average
lead time (1.04) and lead time variability (0.189), for a theoretical lead time of 1 day
and an OTD rate of 96%.
We repeat the same operation for each lead time (1, 2, 3 days), and for OTD rates
spanning from 90% to 100%, which correspond more or less to the current range of
performance, from the poorest to the best TL carriers. Results are displayed below in
Table 2.
On-time delivery
rate
Standard deviation
Coefficient of
SL
variation CVL
1.10
1.08
1.06
1.04
1.02
1.00
0.297
0.268
0.234
0.190
0.125
0.000
27%
25%
22%
18%
12%
0%
2.10
2.08
2.06
2.04
2.02
2.00
0.298
0.269
0.232
0.191
0.123
0.000
14%
13%
11%
9%
6%
0%
3.10
3.08
3.06
3.04
3.02
3.00
0.297
0.267
0.232
0.189
0.125
0.000
10%
9%
8%
6%
4%
0%
Actual Lead time
L
TL Lead time 1 day
90%
92%
94%
96%
98%
100%
TL Lead time 2 days
90%
92%
94%
96%
98%
100%
TL Lead time 3 days
90%
92%
94%
96%
98%
100%
Table 2
Effect of lead time reduction on the safety stock
As shown in chapter 3, the safety stock is equal to z*T* .[ (z= safety factor, a-=
standard deviation of demand, L = lead time). For given demand variability and service
level, the safety stock is proportional to the square root of the lead time.
59
I
Actual Lead
time L
On-time
delivery rate
r
Safety
stock
Safpotetia
Safety stock reduction de to
transportation lead time reduction
reduction
TL Lead time I day
1.10
90%
1.08
92%
1.06
94%
1.04
96%
1.02
98%
1.00
100%
TL Lead time 2 days
2.10
90%
2.08
92%
2.06
94%
2.04
96%
2.02
98%
100%
2.00
TL Lead time 3 days
3.10
90%
3.08
92%
3.06
94%
3.04
96%
3.02
98%
3.00
100%
5.0%
0.0%_
0.9%_
1.8%_
2.8%
3.7%
4.7%
1.05
1.04
1.03
1.02
1.01
1.00
4.5%
o
4.0%
3.5%
3.0%
2.5%
1.45
1.44
1.44
1.43
1.42
1.41
0.0%
1.76
1.75
1.75
1.74
1.74
1.73
0.0%_
0.3%
0.6%
1.0%_
1.3%
1.6%
, 2.0%
S1.5%
0.5%
1.0%_
1.4%
1.9%_
2.4%
. 1 .0 %
0.5%
0.0%
4
100%
98%
96%
94%
92%
90%
On-time delivery ratio
--
--
TL Lead time 2 days
---
TL Lead time 1 day
TL Lead time 3 days
Figure 21
Table 3
Effect of lead time variabilityreduction on the safety stock
As shown in chapter 3, when we take into account the variability of the transportation
lead time, the safety stock is equal to z* (L*2 +
g 2 *SL 2 )
(g - average demand, SL
standard deviation of lead time). Using the coefficient of variation of the demand
(c.v.demand
7/g), we can quantify the safety stock as z*T*I(L +
=
(SL 2
given service level, the safety stock is then proportional to (L + (SL 2 /
On-time
Actuai
delivery rate
TL Lead time
Lead
1
time
Lead
standard
time L
(L + (S
/ CVa))
deviation SL
I da
_
Safety stock
potential
2
(L + (S, / cv ))
reduction
ay
Safety stock
potential
/
2
Cv
Cv
2
)). For a
)).
I cv ))
2
(L + (S
reduction
Safety stock
potential
reduction
C__._-_
"100%
1.82
1.70
1.56
0.0%
1.21
1.17
1.13
0.0%
3.0%
6.2%
1.09
1.07
1.06
0.0%
6.7%
14.3%
0.125
1.39
1.19
23.3%
34.7%
1.09
1.04
9.7%
13.7%
1.04
1.02
4.8%
6.6%
1.00
0.000
1.00
45.0%
1.00
17.0%
1.00
90%
2.10
0.298
2.08
0.0%
1.57
0.0%
1.48
0.0%
92%
94%
96%
98%
100%
2.08
2.06
2.04
2.02
2.00
0.269
1.97
1.85
1.72
1.55
1.41
5.1%
11.2%
17.3%
25.5%
32.0%
1.54
1.51
1.48
1.44
1.41
1.8%
3.7%
5.6%
7.9%
9.7%
1.47
1.45
1.44
1.43
1.41
0.8%
1.7%
2.6%
3.6%
4.4%
2.30
0.0%
1.86
0.0%
1.79
2.21
4.3%
1.83
1.3%
1.78
2.10
8.9%
13.9%
1.81
1.78
2.6%
4.0%
1.76
1.75
19.8%
24.8%
1.76
1.73
5.5%
6.8%
1.74
1.73
90%
92%
94%
96%
98%
100%
0.297
1.10
1.08
1.06
0.268
0.234
0.190
1.04
1.02
TL Lead time 2 day
TL Lead time 3 da
0.123
0.000
_
90%
3.10
92%
3.08
94%
96%
3.06
98%
100%
0.232
0.191
3.04
3.02
3.00
77
0.125
0.000
1.98
1.85
1.73
Table 4
60
8.3%
100%
_
0.297
0.267
0.232
0.189
1.5%
3.1%
1
0.0%
0.6%
1.2%
1.8%
2.4%
3.0%
lead time variability reduction,
Safety stock reduction due to
lead time variability reduction,
Safety stock reduction due to
lead time variability reduction,
cv(demand)=20%
cv(demand)=50%
cv(demand)=100%
Safety stock reduction due to
18.0%
9.0%-
16.0%
C
0
.0
8.0%_
14.0%
0/7.0%
12.0%
C6.0%
10.0%
5.0%
4.0%-
8.0%_-
3.0%
6.0%
5
4.0%
2.0%
2.0%
1.0%
0.0%1i
0.0%
90%
92%
94%
96%
98%
100%
On-time delivery ratio
-- TL Lead time 1 day
-U-TL Lead time 2 days
-4- TL Lead time 3 days
-e-TL Lead time 1 day
-TL Lead time 2 days
-TL Lead time 3 days
-
90%
92%
94%
96%
98%
1000/
On-time delivery ratio
-TL
Lead time 1 day
-U-TL Lead time 2 days
-TL Lead time 3 days
Figure 22
Comments
On the graphs represented in Figures21 and 22, it is important to note that the "point
zero" for the reduction corresponds to an initial OTD rate of 90%. That means that if the
situation were initially worse than 90%, the potential safety stock reduction would be
greater, whereas it would be smaller if the situation were better than 90%.
Examining Table 3 and Figure21, we see that the gain on safety stock due to lead time
reduction is not very high, going from a maximum of 1.5% (for a 3-day lead time trip) to
4.5% (for a 1-day trip), when we pass from on OTD rate of 90% to 100%. It seems to be
too low to be considered as a strong reason to invest in RFID.
If we analyze Table 4 and Figure22, which represents the safety stock reduction due to
lead time variability reduction, the results appear to be more promising. We must recall
here what has been said in Chapter 3 (Chopra et al., 2004) concerning the validity of the
model: 1) the lead time is normally distributed (this is what we assumed), 2) this model
applies well for low coefficient of variation (c.v.): in order to be cautious, we will not
examine c.v. that are greater than 20%.
61
Under these constraints, we find that the safety stock could potentially be reduced by
25% (if we consider a 3-day trip) up to 45% (if we consider a 1-day trip), if we pass from
a 90% OTD rate to a 100% one. Even if we consider that attaining 100% is not likely to
occur, because of unpredictable events like severe weather conditions or traffic jams, a
98% OTD rate would lead to 20% (3-day trip) to 35% (1-day trip) reduction of the safety
stock, if the current performance is 90%.
However, if the current OTD rate is rather around 95% or 96%, which actually is the case
now for "good carriers", using RFID in order to pass from a 95-96% to a 98-99% OTD
rate would lead to a 10% to 20% safety stock reduction for shippers and consignees.
Depending on the goods' value, this gain may be significant (for expensive goods) or, on
the contrary, insufficient (for cheap goods), to justify an investment in RFID.
2. Reduction of labor cost
In this section, we will consider RFID benefits separately for each player. We will not
precisely quantify the gains, as we could find as many different organizations as there are
companies in the US. Instead, we will give some qualitative gain or estimated ratios.
Labor cost reduction for the shipper / vendor
The function that is the most beneficially impacted is the auditor. Auditors are in charge
of verifying the shipments either on the staging area or during the loading process. We
can consider that this cost will be eventually 100% suppressed.
The second labor cost that should greatly benefit from RFID is related to clerical
activities. Many documents (ASN, BOL, invoices, POD) should be automatically
generated, as data will be directly drawn from the tags and related networked
information. Moreover, the resulting documentation should be sent and stored
electronically, reducing paper manipulation. As the transition time should be quite long,
we cannot expect to reduce the workforce by more than 30 to 50% in the short term.
62
Finally, all the work associated with reconciliation, and more broadly, with customer
relationship (including shipment tracking), should also be positively affected. Access to
information should be faster and easier, and allow disputes to be solved more quickly.
This workforce will not necessarily decrease largely, but the personnel could be assigned
to more proactive and value-added tasks in dealing with customers.
Labor cost reduction for the customer / consignee
We find almost the same sources of labor cost reduction as for shipper, but these
reduction may not come from the same functions. It could be for example difficult to
suppress 100% auditors at receiving, because there will always be exceptions to handle.
However, the verifications at receiving are generally more difficult and time consuming
than at shipping, and necessitate more forces. So, even if only 75% of the workforce is
suppressed, as opposed to 100% for shippers, the absolute cost eliminated could be
higher.
Clerk labor cost is less important than for the shipper, as fewer documents are created.
Moreover, administrative treatment of received documentation should disappear in the
long run. Concerning customer service oriented functions (shipment tracking,
reconciliation), benefits should be equivalent to those of shippers.
Labor cost reduction for the carrier
For the carrier, driver-related costs and support function costs are affected by RFID. If
RFID can effectively reduce the loading and unloading time, the driver's productivity will
be enhanced. It does not apply however to cases in which the driver comes to drop an
empty trailer and hook a filled one. It may apply if RFID can provide information about
the presence or readiness of goods (or lack thereof), and may therefore keep the driver
from waiting (and to be paid for waiting). In any case, labor savings for drivers, and
especially TL drivers, will not be very high, certainly no more than a few percentage
points
63
Concerning transportation support functions, RFID should bring the same benefits for the
reconciliation tasks that it brings to shippers and consignees. For tracking, RFID should
remove a great burden, but it would require a perfect information sharing on the part of
vendors and customers. In this case, the tracking function at carriers' should be
significantly lightened, far more than a few percentage points.
3. Faster and more regular service offered to vendors and customers
We have assumed that RFID can entail a lesser variability in lead time. In addition to
potential safety stock reduction, it may also significantly impact shippers and consignees
from an organizational point of view. Actually, the work schedule of DCs' and store's
backrooms' personnel is often based on shipping and receiving tasks. Delays in pick-ups
and deliveries can disorganize these schedules, resulting in useless labor expenses, and
probably in a worse level of service, as tasks may then be fulfilled in a hurry or with less
personnel.
From this point of view, an investment in RFID by shippers and customers, associated
with a willingness on their part to share RFID-generated information with carriers should
be beneficial from a service point of view to the three players.
4. Help for carriers to better comply with Hours of Service
As we noted earlier, by speeding up loading, unloading and documentation tasks, as well
as by reducing waiting time, RFID should help drivers to use their available time more
effectively and to better comply with new Hours of Service regulations.
Evaluation of the changes
Our purpose here is to briefly evaluate the RFID-changes' value for the different players,
rather qualitatively, but also quantitatively when possible. In Table 5, we summarize:
" Who invests in RFID and what is the nature of the investment.
"
Who benefits from RFID, what is the nature of the benefit, is it quantifiable.
" Confronting investments and benefits, what is the value for each player.
64
Tags,
readers,
software
10 to 35% Better
reduction organization
of workforce,
better quality
of service
Suppression
of auditors,
reduction of
clerks
Reduction of
reconciliation costs,
redeployment of
customer service
workforce
Better
visibility on
outbound
shipments
Readers,
software
10 to 35% Better
Reduction of
reduction organization auditors,
of workforce reduction of
clerks
Reduction of
reconciliation costs,
redeployment of
vendor relationship
workforce
Better
visibility on
inbound
shipments
Nothing
N/A
Reduction of
Compliance
reconciliation costs, to Hours of
redeployment of
Service
customer
relationship
workforce
Better
productivity
N/A
Carrier
++
Hg
investment,
high gain
+++ Moderate
investment,
high gain
+
No
investment,
moderate
gain
Table 5
A particularly interesting characteristic of RFID in TL transportation is that its
implementation can be quite selective.
A shipper, a customer, or both, can decide on which products they want to use RFID, that
would maximize benefits while minimizing investment. For example, it could be
interesting to tag very expensive item in order to reduce inventory carrying cost. It may
be interesting too to tag sensitive items in order to provide better service.
Other products will not be tagged, reducing RFID-related investment costs. Selectivity
could also apply to facilities (some will be equipped, others not), in order to reduce
investment in readers and software.
65
4.2.3 The "Execute Transportation "process - LTL carriers
In this section, we will deal with what is specific to LTL carrier compared to TL carriers.
Figure 23 depicts which LTL tasks are almost the same or resemble TL tasks, and which
ones are "new activities" that concern only LTL carriers.
Shipper
TL transportation
SConsignee
Ship.
Rec.
Almost
the same
Almost
the same
Shipper
Consignee
Ship.
Rec.
/
Sh
Rceiving
S Receiving
Unloading
\
Verification ,
Resembling"\POD (1St term/
receivingat
,,**
consignee
Staging
Waybill
Sorting
Pooling
Staging
New activities
e,
\
p n
Verification*
Loading
Delivery receipt
\(last terminal) Resembling
'b Shipping ,'
shippingat
shipper
Figure 23
Even if the size of shipments and appointment scheduling (less tight for LTL) are
different, the basic physical and administrative operations of shipping at vendor and
receiving at consignee are quite similar, involving verification of goods and creation
and/or verification of documents. Receiving and shipping within the LTL carrier
terminals are also very comparable to operations at vendor and consignee, with maybe
less emphasis on the verification stage, as it is assumed that initial verifications and
documentation has been performed well, and that there is no subsequent need to spend
additional time re-verifying. Consequently, we will not describe these tasks in detail
again.
66
It seems more interesting to focus on the different types of LTL carriers. We mentioned
in Chapter 2 that regional LTL carriers generally provide an overnight or a two-day
service, while long haul LTL carriers propose 2-day to 5-day services. Organization of
transportation does not differ very much, but the physical path is different as it is
constituted by a number of stages from initial pick-up to final delivery. We can see, from
Figure24 to Figure 26, how different and complex LTL transportation can be.
LTL 1-day Lead Time
Shipper
Terminal
9am
Consignee
3pm
9pm
0.5 day
9am
0.5 day
Figure24
Figure24 represents the simplest LTL "overnight" operation, in which the products pass
through only one terminal before being delivered to the customer.
At the other end of the spectrum, we find the long haul LTL carrier, with lead times of
three to five days (Figure25). A shipment going from Massachusetts to California will
typically go through all these stages.
LTL 3 to 5-day Lead Time
Shipper
9am
EOL terminal
I
3pm
0.5 day
Regional hub
9pm
I 3am
0.5
day
Regional hub
9am
9am'
I to 3 days
3pm
0.5 day
EOL terminal
Consignee
1
112am
6pm
0.5
I 9am
day
Figure25
Between these two extremes, we can find multiple configurations. Figure 26 depicts a
two to three day lead time trip, which involves two intermediary terminals, and are
typically used for deliveries within the boundaries of a region (Northeast, Midwest,...).
67
Shipper
LTL 2 to 3-day Lead Time
Terminal
I 9am
9pm
3pm
Terminal
12am
0.5 day
6am
I to 2 days
Consignee
9am
0.5 day
Figure26
AS-IS "Execute Transportation" process mapping, for LTL carriers
"AS-IS" - EXECUTE TRANSPORTATION
o
-
LTL CARRIER
- part I
Send pick-up
*
Plan pick-up
4)
B
Go from ouigin
Verify
ED]D21
in
O
tria
simn-D
1
.
t
Figure 27
Figure27 to 29 present the LT L transportation execution process. As seen in the TL
process, execution tasks start after a transportation order has been passed and pick-up and
delivery times have been scheduled. It then follows the same steps of verification,
documentation and loading, before being shipped to the first LTL terminal.
Figure 28 depicts the route from the first to the last LTL terminal. The important (and
different from TL) task here is the creation of the waybill, an internal document that will
follow the shipment from its reception at the first terminal to its shipment to the final
customer at the last terminal. During a VICS Logistics Committee meeting (VICS,
2002b), Roadway reported that 90% of all bills of lading are tendered to the carrier as a
68
piece of paper, 30% of which are hand-written! (October 2002). This information,
comprised of hundreds of characters (including key information such as PO number,
customer references, SKU number, quantities, etc...) must be manually entered. A single
error at this step is thus carried through the multiple stages of the LTL path.
"AS-IS" - EXECUTE TRANSPORTATION
.
'70i
E
.
E
2
S-c
0 _j
--
0
- LTL CARRIER
- part 2
Cross-
Receive,
Create -ayll
waybill
ck,
Ship
Verify,
Receive,
Break-
-
bulk,
Ship
.=
(I iEne-I f
dsia
1)Tasot
~
Trnr Tr
an
Transport
sp
ort
raspr
--
de
IEOL
Sto WI
V
___
2
retailer
Shp
I
n
terminaI
I
0
C
bulk,
I
ME
0 0I
It
I
-
Receive,
Cross-
delivery
receipt
Verify,
create
dock,
It
Ship
Track /trace shipment
Figure 28
Figure 29
"AS-IS" - EXECUTE TRANSPORTATION
-part
3
I
Carrier
CL
invoice
SEDI
>0
210
SFn
OL
File POD
Send
SInvoice
2
E
CARRIER
I
T
0 T
-LTL
ST
408products,
Unload trailer
Receive 2OL
-
--
against
&ASN
Establish POD,
Sign delivery
receipt
tcCheck
-
OK?
*
S
ignBlO ,
Fl
Track /
trace
shipment
Sign
POD
file
2
No
Shipment
status
ED 214
PDfile
BOL with
annotations,
File claim
69
Freight
claim
EDI 920
Main issues we have to cope with
The first specificity of LTL is that pick-ups and deliveries are made in a sequential way.
Any delay occurring at one stage of the cycle may have an impact on following stages.
For example, because of an accumulation of delays during a single cycle, it may be
impossible to pick-up or to deliver a shipment to the last facility in the cycle, as this one
may be closed.
Another specificity of LTL carriers is the sorting and pooling made at the terminals. The
risk of misloading and misrouting is here very high, as each terminal has to deal with
several dozen inbound and outbound trailers every day. Moreover, the sorting and
pooling operations must generally be performed in short time slots, and at high speed.
Finally, LTL transportation faces the same problems that TL faces, in counting,
verification and documentation tasks. As mentioned earlier, the verification and
documentation tasks made at the first terminal are critical. Moreover, these problems
may occur at each break load between the initial pick-up and the final delivery. Actually,
while the sources of the problem are identical, the risk of discrepancies is multiplied.
Identification of problems' main causes
The reader can refer to the root-cause analysis diagram presented earlier in Figure 18.
The causes are almost identical (human errors, wrong initial documentation, complex
procedures, rudimentary systems,...), but errors can potentially be repeated at each
terminal, multiplying the risk that problems might occur along the whole chain.
RFID capabilities that can apply to this process
Here again, the basic capabilities of RFID, in particular accuracy and visibility, will be
extremely useful to enhancing operations within the terminals. By automatically
acquiring data without keying it, the initial waybill will be far more accurate and will
greatly reduce the risks of initial misrouting. At the other end of the trip, the RFID
70
system will automatically generate a delivery receipt with the exact content of the
shipment, reducing the risk of dispute with the final customer.
Use of RFID within the terminals will help to eliminate or reduce misloadings, first by
directing shipments to the right docks, second by verifying while loading if a shipment's
destination corresponds to trailer's destination. Moreover, by providing the content and
location of any shipment staging in the terminal, RFID may help to know how the various
docks are utilized, and to quickly locate any shipments (that may have been "lost").
Finally, if vendors and customers are RFID-equipped and are willing to share information
about RFID-tagged product staging on their docks, LTL carriers will have very useful
information that would permit dynamic changes in the scheduling of pick-up or delivery
cycles, if they are informed of delays in shipment availability, or docks' unavailability.
TO-BE RFID-enabled "Execute Transportation" process mapping for LTL carriers
"TO-BE" - EXECUTE TRANSPORTATION
0
V
CD
CDrasp
a
o
) Schedule
pick-up
order
or ALN
EDI 20
LTL CARRIER - part I
Send pick-up
ntc
ED[ 216
Plan pick-up
in a
pick-up cycle
G frmogn
"na
!teri
to ved,
Dr to
EOL[<
00
0
E
0 o
M
-
Schedule
delivery
Impacted
data exchange
Figure 30
71
"TO-BE"
- EXECUTE TRANSPORTATION
- LTL CARRIER - part 2
Impacted
0
data exchange
1.0
(U1
M
0
rJ
.0
.! .c
C)
C
0
ICm
CD0
U
Figure 31
UTE TRANSPORTATION
Cmpc7e
- LTL CARRIER
- part 3
impacted
*0I
data exchange
4
-0
CL
>1.
Kr
2*Y
C
0
Figure32
Main changes or improvements
72
Suppressed
task
Receiv in g
Cross-docking
Shipping
Figure 33
RFID capabilities can suppress some tasks. Automatic reading when a pallet passes
through a portal can suppress the tasks of bar code scanning or manual counting, and the
data collected can be automatically verified by comparing it with what was expected (for
example, comparison with an ASN at receiving). Documents, which previously required
some manual data entry before being printed or electronically created, can be generated
automatically, in coherence with what was read from the tags. Finally, in cross-docking
operations, mis-sorting and mis-pooling can be avoided.
Expected value
More than for TL carriers, elimination or early detection of loading and routing errors, as
well as information allowing a prioritization of shipment unloading and loading, should
allow delays not to pile up. In Figures 34 to 36, we show the case of a trailer's late
arrival in a hub or at an EOL terminal (a pick-up cycle being highly dependant on the
time spent at each shipper, a delay at one or several locations may have a negative impact
on trailer's on-time arrival at the terminal). The time spent to unload a late trailer, to
generate shipment waybills, to sort the goods and to load them may be very long, and
some products may miss the outbound departure. RFID, can help in two ways: first,
waybills may be created very quickly, and sorting may be very fast; second, using a
specific software (that has to be developed) that could compare the actual arrival time of
goods and the planned departure time of these goods, "late or urgent shipments" could be
easily identified, and information could be sent to handle and load the critical goods in
73
priority, in order for them to catch the outbound departure and not remain one additional
day at the cross-docking terminal. This is illustrated in the 3 figures below.
1Oam
12pm
4pm
2pm
10pm
8pm
6pm
Nrmal schedul
Pick-up cycle or;
Inbound arrivals
[
Outbound deparqures
Figure34
1Oam
12pm
4pm
2pm
8pm
6pm
Probable
10pm
schedule without
RFID
Orgent shipmebts not
LATE 2hv/
Pick-up cycle or
-----------
Inbound arrivals:
identified and elayed
24 hour
Outbound deparqures
Figure35
1Oam
6pm
4pm
2pm
12pm
8pm
10pm
Probable schedule with RFID
Urgent shlpments identified
and haddled in priority,
shipmehts not delayea
LATE 2h1/2
Pick-up cycle or
:---i.
Inbound arrivals
Outbound deparures
Figure36
In the end, the reduction of delays will lead to a reduction of the average lead time and
lead-time variability, allowing shippers and consignees to reduce their safety stocks.
74
Another benefit is the automatic generation of documents at terminal (waybill at the first
terminal, delivery receipt at the last). More than only reducing auditors' and clerks' costs,
it will greatly reduce the error rate and improve accuracy, allowing a further reduction in
reconciliation costs. Being able to track the shipments at every intermediary point will
permit carriers to offer a better service to shippers and consignees.
If shippers handle tagged products and are equipped with RFID readers, it should allow a
faster, or least a more regular shipping process (thanks to automatic generation of
documents, reduction of loading, unloading and waiting times), that will benefit the entire
pick-up cycle as it will reduce random delays.
Prerequisites
We will not repeat the prerequisites for shipping at vendor and receiving at customer.
We will focus here on the prerequisites for LTL carrier'sinternalterminaloperations.
One of the problems a LTL carrier may face is that only a small proportion of its shippers
will use RFID. If these shippers tag their products, LTL terminals may then have "only"
to invest in readers and software. For these shippers, the service should be enhanced,
with fewer risks of misrouted goods, a more consistent lead time (and then, less safety
stock), and the ability to track their shipments. However, for the LTL carrier, as long as
the number of "RFID-shippers" remains low, this investment will not necessarily lead to
other potential benefits like reduction of dock, clerical and reconciliation costs.
At this point, the LTL carrier may have two choices:
" Wait for a greater number of shippers to be equipped, before investing in RFID
readers and software in its terminal (which will then allow to reduce its labor cost).
"
Invest in readers and software, but also in tagging capabilities, in order to apply tags
to products that would not have been tagged prior to their arrival at the terminal.
This second - obviously more costly - option would nevertheless allow the terminal to
fully benefit from RFID. However, it will not eliminate the need for initial data entry
75
(i.e. creation of the EPC and its associated information), which has been identified as one
of the most error-prone tasks.
Financially speaking, the burden of implementing RFID in LTL terminal is now
displaced onto the carrier. It may be a relatively low investment if it concerns only
readers and software, but in this case, there will be also few benefits. It may be a higher
investment if products are tagged at the terminal, here with higher rewards.
We may note in the latter case that for shippers that had decided not to tag their products,
the fact that the carrier does it for them would provide them a far better service: fewer
mis-shipments, more regular deliveries, less safety stock.
From a collaboration perspective with vendors and shippers, either the LTL carrier does
not invest and therefore does not need to coordinate with shippers and consignee, or the
LTL carrier invests, mainly in order to enhance its own internal operations, and in this
case too, it is not an obligation for it to cooperate with vendors and customers. However,
in the latter case, it would be an excellent service to offer them.
The last question we may address is if the implementation of RFID in terminals needs to
be comprehensive or can be selective, i.e. done in certain terminals and not in others.
In the case of a "full investment" (tagging capabilities + readers), it appears that it does
not make sense to be selective. First, it will not permit the LTL carrier to track shipments
from initial pick-up to final delivery. But most importantly, if only a few terminals are
fully equipped (with the goal of efficiently reducing these terminals' costs), they should
be able to track 100% of the products, but that will not be the case, as products coming
from "non-RFID-equipped terminals" will not be tagged, and will consequently not be
tracked. The full investment in tagging capabilitiesin terminal also requires this
investment to be geographicallycomprehensive.
On the other hand, a "partial investment" (readers only) will not profoundly change the
way terminals work (because all the non-RFID tagged products will need to be handled)
but will only improve the routing and tracking of shipper-tagged products. As the carrier
does not have any obligation towards its partners, but rather wants to propose them an
76
additional service, the LTL carrier is not "obliged" to install readers comprehensively and
may choose selectively the terminals for which the "soft" benefits should be the highest.
Estimation of the value of proposed changes
Obviously, the greatest interest for a LTL carrier to implement RFID in its terminals are
to reduce its labor cost, to improve its accuracy (which, at the end, will also lead to a
reduction of reconciliation costs and of deductions applied by the owner of carrier
relationship), to maximize its asset utilization, and to propose a better service in terms of
shipment tracking to the shippers and the consignees.
We will again quantify the potential reduction of safety stock for vendors and customers.
Use of RFID in LTL terminals should permit delays to be avoided even more than for TL
carriers and to reduce mis-shipments, and consequently to reduce average lead time and
lead time variability, leading to gains on safety stocks.
As we have done with TL transportation, we will try to quantify the gains in term of labor
cost and safety stock reduction, and to estimate the qualitative gain in terms of service.
1.
Reduction of terminal overhead's costs for the LTL carrier
2. Reduction of drivers' costs for the LTL carrier
3. Better asset utilization
4. Reduction of vendors' and customers' safety stocks
1. Reduction of terminal overhead costs for the LTL carrier
We have already assessed which labor cost reductions RFID could enable for shippers
and consignees. We will focus here on labor cost reduction that a LTL carrier can achieve
within its terminal.
For the terminal's receiving and shipping functions, we have the same gain as described
for shippers and consignees: less verification of shipments, fewer clerical activities, less
77
time spent on reconciliation. As we estimated before, auditors' jobs may be suppressed
or reduced by 75% in the long run, and clerical activities by 30 to 50% in the short term.
2. Reduction of driver costs for the L TL carrier
Thanks to a reduction of searching time (looking for the right person, the dock, the
products to load,...), waiting time, and loading / unloading time, the driver's cycle time
should decrease.
As shown in Figure37, the daily schedule of a driver working at a LTL End-Of-Line
(EOL) terminal is composed of a delivery cycle and a pick-up cycle. The delivery cycle
consists of delivering the products arriving from other terminals during the night
(inbound arrivals). When deliveries are done, leaving the trailer empty, the driver starts
the pick-up cycle, which consists in loading products at various places in the same local
area. After the last pick-up, the driver comes back to the terminal and unloads the trailer.
Goods are sorted in order to be sent the same evening to other terminals (outbound
departures).
12am
6pm
6pm
12pm
6am
Delivery
6am
12am
cycle
Deliy cycle
Pick-up cycle
Day 0
Day 2
Da 1
Driver's cycle
Figure37
In order to evaluate the possible benefits of RFID in this operation, we will use some
information that we have obtained from a medium-sized LTL terminal (76 doors). The
terminal receives on average 15 trailers a day (inbound arrivals), which are transferred in
approximately 450 deliveries to customers. The drivers picks up an average of 300
shipments a day at shippers, which then constitute about 12 trailers a day (outbound
departures).
78
Each driver operates its delivery cycle and pick-up cycle in a row, generally in 8 hours,
but in some cases in up to 10 hours, being then paid overtime. An average delivery takes
30 minutes (this includes: time on the road, searching the dock, waiting, unloading and
dealing with documents). A pick-up takes longer than a delivery, about 45 minutes, and
is composed of the same tasks. Table 6 presents the nominal times for each task, based
on interviews at the LTL terminal, and on our own experience.
Delivery operations
Time on the road
Time searching (person, dock)
Time waiting
Time unloading
Time spent on documentation
Total
Minutes
10
5
5
5
5
30
Hours
0.17
0.08
0.08
0.08
0.08
0.50
Pick-up operations
Time on the road
Time searching (person, dock, goods)
Time waiting
Time spent on documentation
Time loading
Total
Minutes
10
10
10
10
5
45
Hours
0.17
0.17
0.17
0.17
0.08
0.75
Table 6
In this terminal, a driver makes on average 10 deliveries and 5 to 6 pick-ups every day.
Our assumption is that RFID should not reduce the unitary time of the basic tasks (the
mileage will not change, the loading time will not be faster, etc....). Rather, RFID should
reduce the "time variability" in performing these tasks. We have been told during our
interviews that each task performed during deliveries and pick-ups may commonly last
up to 30% more than its nominal time, because of poor information or lack of
information. For example, searching for the right person to deliver a shipment may take
6.5 minutes instead of 5 minutes, or dealing with documentation at pick-up may take up
to 13 minutes instead of 10. We estimate that with real time and accurate information
provided by RFID, drivers should be able to perform these operations more efficiently.
For example, goods can be found more quickly, as their staging location can be deducted
79
from the tags reads. Or a carrier can be informed by the shipper that goods are not ready,
the shipper being able to see what is on its dock, or, even more efficiently, the carrier
could be able to see that the goods are not ready by consulting the EPC network; the
carrier's dispatcher could then divert the truck to another facility, avoiding long waiting
time. As no pilots have been performed, it is hard to estimate what the gain could be.
We make an arbitrary rough estimate here, and consider that variability of extra time
(relative to the nominal time) spent at shippers or at consignees could slightly decrease,
passing from a 0-30% range to 0-10% range.
To assess the effect of this improvement, we use a method similar to the one we have
used to assess the effect of transportation lead time on safety stocks. For the deliveries,
we have built a table with 450 deliveries, the time of each delivery being the sum of
elementary tasks (road, loading,...), with a nominal time being randomly increased from
0 to 30% (if no RFID) or from 0 to 10%" (if RFID). We simulate a month of activity,
and then obtain the average time and the standard deviation for delivery, for both cases
(no RFID: nominal time + 0-30%; RFID: nominal time + 0-10%).
The first rows of the table are displayed below (see Table 7 and 8).
Deliv.
Number
Average
Std dev.
4501
34.
11.26
4
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Road Search
Wait Unload
Doc.
5
30.0
10
5
5
5
35.9
37.1
34.9
34.3
35.8
35.1
34.4
33.2
36.3
35.9
35.5
35.1
32.8
34.5
35.9
35.7
35.6
35.8
36.1
35.3
11.5
12.3
12.1
10.4
12.9
12.9
10.8
12.6
13.0
11.8
12.7
12.4
10.2
11.1
12.7
11.3
12.8
12.3
12.6
10.7
6.2
5.9
5.7
6.4
6.0
6.0
6.2
5.1
5.4
6.2
5.3
5.9
5.4
6.3
6.3
6.2
5.8
6.1
6.2
5.9
6.3
6.5
5.1
6.2
5.8
5.6
5.4
5.2
6.4
5.2
6.0
5.1
5.4
5.6
5.3
5.8
5.0
6.0
6.1
6.0
5.8
6.4
5.9
5.5
5.5
5.3
6.3
5.2
5.3
6.5
5.6
5.4
5.6
6.2
5.3
6.1
6.2
6.4
5.4
6.4
Table 7
80
6.1
6.0
6.2
5.8
5.61
5.2
5.6
5.1
6.31
6.1
6.0
6.3
6.2
5.3
6.3
6.3
5.7
5.0
5.7
6.31
Road Search
Wait Unload
Doc.
Random (+ 30%)
1.15
1.23
1.21
1.04
1.29
1.29
1.08
1.26
1.30
1.18
1.27
1.24
1.02
1.11
1.27
1.13
1.28
1.23
1.26
1.07
1.24
1.19
1.13
1.28
1.20
1.20
1.25
1.03
1.08
1.24
1.05
1.17
1.08
1.26
1.26
1.25
1.16
1.21
1.24
1.19
1.26
1.30
1.01
1.24
1.15
1.12
1.07
1.04
1.27
1.05
1.19
1.02
1.08
1.13
1.05
1.16
1.00
1.21
1.23
1.19
1.16
1.28
1.18
1.10
1.11
1.06
1.27
1.04
1.06
1.30
1.12
1.08
1.12
1.24
1.06
1.21
1.24
1.28
1.08
1.28
1.22
1.20
1.24
1.16
1.12
1.05
1.13
1.03
1.26
1.23
1.20
1.26
1.24
1.06
1.25
1.26
1.14
1.00
1.14
1.25
I Defiv.1 Road|Searchl
Number
450
Average
Std dev.
31.
30.01
#
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
0.41
Doc.I
I RoadiSearchi
WaitUnloadi
Doc.I
I
101
31.5
31.8
31.5
31.6
31.3
31.4
31.4
31.7
31.8
31.0
31.4
31.6
31.1
31.9
31.6
31.7
31.6
31.7
31.7
31.4
WaitiUnloadi
51
10.3
10.4
10.6
10.0
10.6
10.4
10.2
10.7
10.9
10.1
10.1
10.5
10.1
10.9
10.8
10.7
10.4
10.7
10.9
10.7
51
5.5
5.4
5.5
5.1
5.4
5.0
5.5
5.3
5.2
5.1
5.2
5.5
5.0
5.2
5.3
5.3
5.3
5.5
5.1
5.1
5.1
5.3
5.1
5.5
5.0
5.2
5.1
5.3
5.2
5.3
5.4
5.3
5.2
5.5
5.1
5.2
5.2
5.1
5.2
5.1
51
51
5.3
5.4
5.0
5.5
5.1
5.4
5.2
5.0
5.3
5.3
5.3
5.4
5.5
5.2
5.2
5.2
5.4
5.4
5.2
5.2
5.2
5.3
5.3
5.5
5.2
5.4
5.4
5.3
5.25.2
5.4
5.0
5.2
5.1.
5.1
5.3
5.3
5.0
5.3.
5.3
Random (+ 10%)
i
1.03
1.04
1.06
1.00
1.06
1.04
1.02
1.07
1.09
1.01
1.01
1.05
1.01
1.09
1.09
1.09
1.09
1.02
1.07
1.01
1.10
1.07
1.03
1.01
1.03
1.09
1.00
1.05
1.02
1.06
1.01
1.10
1.01
1.04
1.02
1.05
1.04
1.07
1.08
1.06
1.03
1.10
1.07
1.07
1.01
1.10
1.03
1.08
1.04
1.01
1.05
1.07
1.06
1.08
1.10
1.05
1.05
1.05
1.06
1.10
1.03
1.07
1.08
1.07
1.04
1.05
1.08
1.00
1.05
1.01
1.08
1.06
1.02
1.04
1.03
1.07
1.06
1.04
1.03
1.07
1.04
1.06
1.04
1.08
1.06
1.07
1.09
1.07
1.09
1.03
1.02
1.02
1.03
1.02
1.08
1.05
1.04
1.00
1.05
1.06
Table 8
The same method is applied for the 300 daily pick-ups. The results are displayed below in
Table 9 and 10.
Pick-up Road
Number
300
Average
Std dev.
51.8
1.85
#
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Search
Wait
Load
Road Search
Doc.
45.0
10
10
10
10
5
50.4
52.2
54.1
55.8
51.0
50.0
52.2
51.9
47.6
52.1
52.5
51.0
51.5
48.6
53.7
52.3
55.2
53.3
50.5
55.2
11.6
10.3
11.7
11.7
12.0
10.0
10.2
10.1
10.6
10.5
10.8
12.0
11.4
11.3
12.2
10.3
12.8
11.8
12.6
11.5
10.4
12.5
12.2
12.8
12.3
12.5
12.6
12.8
10.2
11.5
11.9
11.5
10.1
10.8
12.5
11.9
11.8
11.4
10.3
12.0
11.9
12.5
12.7
12.2
10.5
11.1
12.3
12.0
10.1
12.2
11.1
12.0
12.5
10.0
12.9
12.2
12.2
12.4
10.3
13.0
10.1
11.9
11.3
12.8
10.1
10.5
10.9
11.5
10.6
12.7
12.7
10.4
12.3
10.9
10.9
12.2
12.1
12.6
12.1
13.0
6.4
5.1
6.2
6.3
6.21
5.9
6.2
5.4
6.21
5.2
6.0
5.1
5.3
5.5
5.2
5.6
6.2
5.1
5.2
5.61
Table 9
81
Wait
Load
Doc.
Random (+ 30%)
1.16
1.03
1.17
1.17
1.20
1.00
1.02
1.01
1.06
1.05
1.08
1.20
1.14
1.13
1.22
1.03
1.28
1.18
1.26
1.15
1.04
1.25
1.22
1.28
1.23
1.25
1.26
1.28
1.02
1.15
1.19
1.15
1.01
1.08
1.25
1.19
1.18
1.14
1.03
1.20
1.19
1.25
1.27
1.22
1.05
1.11
1.23
1.20
1.01
1.22
1.11
1.20
1.25
1.00
1.29
1.22
1.22
1.24
1.03
1.30
1.01
1.19
1.13
1.28
1.01
1.05
1.09
1.15
1.06
1.27
1.27
1.04
1.23
1.09
1.09
1.22
1.21
1.26
1.21
1.30
1.29
1.02
1.25
1.26
1.23
1.19
1.25
1.09
1.24
1.05
1.20
1.02
1.07
1.10
1.04
1.13
1.24
1.03
1.04
1.13
I
Pick-up Road Search
Number
300
Average
Std dev.
47.2
0.60
#1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Wait
Doc.
45.0
10
10
10
10
47.0
47.4
46.9
46.9
47.0
48.1
47.7
47.4
47.1
47.4
47.2
47.3
46.8
48.3
46.9
47.1
47.4
47.0
47.7
47.5
10.6
10.8
10.4
10.3
10.2
10.8
10.4
10.4
10.8
10.7
10.5
10.6
10.3
10.5
10.3
10.3
10.9
10.9
10.0
10.6
10.2
10.1
10.3
10.3
10.6
10.9
10.4
10.4
10.2
10.5
10.5
10.4
10.2
11.0
11.0
11.0
10.6
10.1
10.8
10.7
10.5
10.5
10.7
10.5
10.6
10.4
10.9
10.8
10.6
10.4
10.9
10.0
10.5
10.8
10.0
10.3
10.6
10.5
11.0
10.2
10.7
11.0
10.5
10.8
10.1
10.8
10.7
10.8
10.3
10.8
10.1
10.8
10.9
10.9
10.4
10.2
10.1
10.3
10.4
10.9
Road Search
Load
5
5.0
5.1
5.1
5.1
5.51
5.2
5.2
5.0
5.1
5.1.
5.2
5.4
5.0
5.2
5.2
5.3
5.3
5.1
5.5
5.1
Wait
Doc.
Load
Random (+ 10%)
1.06
1.08
1.04
1.03
1.02
1.08
1.04
1.04
1.08
1.07
1.05
1.06
1.03
1.05
1.03
1.03
1.09
1.09
1.00
1.06
1.02
1.01
1.03
1.03
1.06
1.09
1.04
1.04
1.02
1.05
1.05
1.04
1.02
1.10
1.10
1.10
1.06
1.01
1.08
1.07
1.05
1.05
1.07
1.05
1.06
1.04
1.09
1.08
1.06
1.04
1.09
1.00
1.05
1.08
1.00
1.03
1.06
1.05
1.10
1.02
1.07
1.10
1.05
1.08
1.01
1.08
1.07
1.08
1.03
1.08
1.01
1.08
1.09
1.09
1.04
1.02
1.01
1.03
1.04
1.09
1.01
1.02
1.01
1.01
1.10
1.04
1.05
1.01
1.03
1.01
1.04
1.09
1.01
1.04
1.05
1.05
1.06
1.02
1.09
1.01
Table 10
We see in these tables that the average time spent per delivery and pick up is above the
nominal time. Expectedly, the average time is 34.5 minutes, but if we want to take 95%
of the deliveries in account, we must add to this mean approximately twice the standard
deviation (Y = 1.26). Then we should plan 37.0 minutes for each delivery. With RFID,
and a 0-10% range instead of 0-30% range, the average time is 31.5 minutes, and the
standard deviation T being 0.41 minutes, we should plan 32.3 minutes for a delivery.
Applying the same rationale for the pick-ups, we find respectively 55.5 minutes for the 030% range, and 47.2 minutes for the 0-10% range. Compiling delivery and pick-up times
in Table 11, we obtain the following results:
82
0
Best possible situation
ossi e vanation A eac stage:
Delivery
Pick-up
Number of stops per day
450
300
Unit average time spent (hours)
0.50
0.75
225.00
225.00
Total time spent (hours)
Driver's work day, minimum hours
Theoretical number of driversl
Minimum number of drivers requiredi
Current situation without RFID
[Possible variation at each stage: 30%Y
Delivery
Numberofstopsperday
Unit average time spent (hours)
Total time spent (hours)
Driver's work day, minimum hours
Theoretical number of drivers
Minimum number of drivers requiredJ
JPick-up j
450
300
0.62
0.93
277.50
277.50
Total
750
450.00
9.50
47.37
48
Total1_
750
555.00
9.50
58.42
59
Situation with RFID
[Possible variation at each stage: 107
Delivery
Number of stops per day
Unit average time spent (hours)
Total time spent (hours)
Driver's work day, minimum hours
Theoretical number of driversj
Minimum number of drivers requiredj
Pick-up
450
300
0.54
0.80
242.25
239.00
Total
750
481.25
9.50
50.66
_51
Gain from 30% to 10% 1
13.6%
Table 11
The "theoretical calculation" (using the "nominal times") indicates that the terminal needs
48 drivers. With an uncertainty on task times up to 30%, the number of drivers increases
up to 59, and with an uncertainty up to 10%, we need "only" 51 drivers. The gain
compared to the + 0-30% is 13.6%, which is not inconsiderable.
However, it is very important to note that this potential reduction implies a 100%
implementation of RFID at shippers and consignees. This will certainly not be the case
before several years, if ever. Yet, if we consider that 20% of the "big customers"
represent 80% of the activity, and that these 20% are solid enough to invest in the next
two to five years, the potential gain in drivers could pass from 2-3% in 2 years to 10% in
5 years, corresponding, for this particular terminal, to a reduction of 2 to 6 drivers.
83
3. Better asset utilization
The "assets" we are talking about in this section are the trucks and trailers used in the
End-of-Line terminals (and not the long haul trucks or trailers used between terminal and
hubs; for those, we had estimated in a previous section the reduction of lead time, that did
not appear to be high enough to entail a significant reduction of assets).
The number of drivers and number of tractors are quite similar in an EOL terminal, each
driver (with a few exceptions, due to flexibility needs) being responsible of his tractor.
We may then apply the study we performed for drivers in the previous section to the
assets: basically, the gains we found there can apply for tractors.
4. Reduction of vendors'and customers' safety stocks
Even more than for TL transportation, because LTL transportation is composed of
multiple successive stages, delays should be reduced in LTL transportation. Misshipments will be detected earlier, and errors will be fixed more quickly (according to
what we have learned during interviews, it may currently take days to find a shipment
that has been lost without documentation). This reduction of delayed shipment will lead
to a reduction of average lead time and lead-time variability, which will entail, as seen in
Chapter 3, a reduction of safety stocks.
The approach used to quantify the potential safety stock reduction, the assumptions and
the method are almost the same as those used in the previous section for TL
transportation. One difference is in the lead times. We have here studied three different
lead times: 1, 3 and 5 days (see lead time decomposition in Figures24 to 26).
"
1-day lead time: 0.5 + 0.5
" 3-day lead time: 0.5 + 2 + 0.5
" 5-day lead time: 0.5 + 0.5 + 3 + 0.5 + 0.5
84
In order to set an on-time delivery (OTD) rate for the whole trip, we set various OTD
rates on each section of the trip. For example, for the 3-day lead time, if the first section
(0,5 day) has a 90% OTD rate, the second section (2 days) a 94% OTD rate, and the third
section (0,5 day) a 92% OTD rate, then the overall on-time delivery is 78%.
You can see in Appendices C, D and E the results for the three lead times, for different
OTD rates (1-day lead time for a global OTD rate of 90%, 3-day lead time for a global
OTD rate of 78%, 5-day lead time for a global OTD rate of 85%), with the average lead
time and the lead time variability for each case.
We repeat the same operation for each lead time (1, 3, 5 days), and for on-time delivery
rates spanning from 70% to 100%, which correspond more or less to the current range of
performance, from the poorest to the best LTL carriers. Results are displayed in Table 12.
Standard deviation
On-time delivery A
jActual Lead time L
rate
LTL Lead time
70%
75%
80%
85%
90%
95%
100%
LTL Lead time
70%
75%
80%
85%
90%
95%
100%
LTL Lead time
70%
75%
80%
85%
90%
95%
100%
I
[Lcf
Lead time
vaition ofL
variation cvL
day
1.33
1.27
1.21
1.15
1.10
1.05
1.00
0.52
0.47
0.42
0.38
0.30
0.22
0.00
39%
37%
35%
33%
27%
21%
0%
3.33
3.27
3.21
3.16
3.10
3.05
3.00
0.55
0.51
0.45
0.39
0.32
0.22
0.00
17%
16%
14%
12%
10%
7%
0%
5.34
5.28
5.22
5.16
5.11
5.05
5.00
0.55
0.51
0.45
0.39
0.32
0.22
0.00
10%
10%
9%
8%
6%
4%
0%
3 days
5 days
Table 12
Effect of lead time reduction on the safety stock
As seen in chapter 3, the safety stock is equal to z*Y*
1L . For given demand variability
and service level, the safety stock is proportional to the square root of the lead time.
85
On-mdeliyJAdjLead tire
LTL Leadtim 1 d*y
70%
75%
800/
85%
90%
95%
100%
LTL Load tIm 3
70%
75%
80%/o
85%
3.33
3.27
3.21
3.16
3.10
3.05
3.00
stock
.
1.15
1.13
1.10
1.07
1.05
1.02
1.00
2.3%
4.6%
7._0%__
9.1%
11.1%
13.3%
1.82
1.81
1.79
1.78
1.76
1.75
1.73
0.0%
0.9%
1.8%
2.6%
3.5%
4.3%
5.1%
2.31
2.30
2.28
2.27
2.26
2.25
2.24
0.0%
1.33
1.27
1.21
1.15
1.10
1.05
1.00
900/0
95%
100%
LTL Led tinme
70%
75%
80%/0
85%
90%
95%
100%
JSafety
0.0/
5dys
5.34
5.28
5.22
5.16
5.11
5.05
5.00
Safety stock reduction due to
transportation lead time reduction
14.0%
12.0%
S
S10.0%
4.0%
2.0%--2
0%
0%
0.0% i
0
70%
0.6%
1.1%
1.7%
2.2%
2.8%
3.2%
75%
80%
85%
90%
95%
100%
On-time delivery ratio
-LTL
-+-
Lead time 1 day -.-
LTL Lead time 3 days
LTL Lead time 5 days
Table 13
Figure 38
Effect of lead time variabilityreduction on the safety stock
As seen in chapter 3, the safety stock is equal to z*I(L*(2 + g2*S L) when we take into
account the variability of the transportation lead time. Using the coefficient of variation
of the demand
(c.V.demand
= T/g), we can quantify the safety stock as z*1*/(L + (SL2 /
cv2)). For a given service level, the safety stock is then proportional to
Ch-
timne delive
Actual Lead
rattie
LTL Lead time I day_
L
Stnar
devatin S.
)
4L +(SL /cv2))
(L +(SL 2 / cV2)).
Safety stock
Safety stock
potential
(L+(t2/c2)
potential
(L +(S
/
cv2))
Waety stock
potential
_____
70%
1.33
0.52
2.84
0.0%
1.55
0.0%
75%
80%
85%
1.27
1.27
1.21
1.15
0.0%
0.47
0.42
0.37
2.61
2.37
2.14
8.4%
16.7%
24.8%
1.47
1.38
1.30
5.5%
10.9%
16.1%
90%
1.10
1.22
1.18
1.13
3.5%
6.9%
10.3%
0.30
1.83
35.7%
1.21
22.2%
1.09
95%
1.05
0.22
1.50
47.1%
100%
1.12
1.00
28.2%
0.00
1.05
1.00
17.2%
64.8%
1.00
35.6%
1.00
21.0%
3.33
3.27
3.21
3.16
3.10
3.05
3.00
0.55
0.51
0.45
0.39
0.32
0.22
0.00
3.30
3.13
2.88
2.64
2.38
2.06
1.73
LTL Lead time 5 days
70%
5.34
75%
5.28
80%
5.22
85%
5.16
90%
5.11
95%
5.05
100%
5.00
0.0%
5.3%
12.9%
20.0%
27.9%
37.5%
47.5%
2.13
2.08
2.00
1.94
1.87
1.80
1.73
0.0%
2.6%
5.9%
8.9%
12.1%
15.5%
18.7%
1.91
1.88
1.85
1.82
1.79
1.76
1.73
0.55
0.51
0.45
0.39
0.32
0.22
0.00
3.59
3.43
3.21
2.99
2.77
2.50
2.24
0.0%
4.4%
10.7%
16.7%
22.9%
30.3%
37.7%
2.56
2.51
2.46
2.40
2.35
2.29
2.24
0.0%
1.8%
4.1%
6.2%
8.2%
10.5%
12.6%
2.38
2.35
2.33
2.30
2.28
2.26
2.24
LTL Lead time 3 day.
70%
75%
80%
85%
90%
95%
100%
-
13.8%
100
Table 14
86
C.V
0.0%
1.4%
3.1%
4.5%
6.1%
7.6%
9.1%
100%
0.0%
0.9%
2.0%
3.0%
3.9%
4.9%
5.9%
time variability reduction
Safety stock reduction due to lead
time variability reduction
cv(demand)=20%
cv(demand)=50%
Safety stock reduction due to lead
70.0%
40.0%
60.0%-
35.0%
50.0%
30.0%
-
-
--
Safety stock reduction due to lead
time variability reduction
cv(demand)=100%
25.0%
-
-
20.0%
O 25.0%-
15.0%
40.0%
3
30.0%
20.0%-
_
10.0%
15.0%
200%
10.0%
5.0%
10.0%
0.0%
70%
75%
80%
85%
90%
95% 100%
0.0% i
70%
On-time delivery ratio
i
75%
i
80%
i
85%
i
90%
0.0%
95%
On-time delivery ratio
-*-LTL Lead time 1 day
-*-
LTL Lead time 1 day
-U-LTL Lead time 3 days
-4- LTL Lead time 5 days
---
LTL Lead time 3 days
LTL Lead time 5 days
--
100%
70%
75%
80%
85%
90%
95%
100%
On-time delivery ratio
-- LTL Lead time 1 day
-- LTL Lead time 3 days
-+- LTL Lead time 5 days
Figure 39
Comments
Preliminary remark:
In the graph represented on Figures38 and 39, the "point zero" for the reduction
corresponds to an initialon-time delivery rate of 70%. This may seem very low. The
LTL carrier we have interviewed has reported an average on-time delivery rate of 90%,
but this carrier is known as one of the best in its industry. Information we have gathered
from numerous articles - which never cited official surveys or sources, though - rather
gave us an average rate comprised between 65% and 75%. Again, this may seem low,
but if we consider a 5-stage LTL trip with an OTD rate of 95% at each stage, we obtain a
final OTD rate - on the whole trip - of only 77%). Anyway, if a carrier has actually a 80
to 90% OTD rate, it will be possible for it to use the table, starting from this level.
Examining Table 13 and Figure38, we see that the gain in safety stock due to lead time
reduction is going from a maximum (corresponding to a 100% on-time delivery rate)
reduction of 3% for 5-day lead time trips to 4.5% for 3-day lead time trips and 13% for
the 1-day lead time trips. It is not very high, but it is however higher than the gain we
obtained for a reduction of lead time in TL transportation (1.5% for the 3-day lead time,
4.5% for the 1-day).
87
Analyzing Table 14 and Figure39 (reduction due to lead time variability), the results are
far better than those due to lead time reduction, as it was the case for TL. Applying what
we have said in Chapter 3, we will only examine c.v.'s not greater than 20%. We then
find that the safety stock could potentially be reduced by around 40% for 5-day trips up
to 65% for 1-day trips. We must consider that it is extremely difficult to reach a near100% rate for a LTL carrier. Our studies and interviews have shown that good rates are
around 90% for LTL nowadays (with an average close to 70-75%). Starting from the
already good result of 90% to reach, thanks to RFID capabilities, a rate from 95% to
98% would lead to a 10% (5-day LT) to 20% (1-day LT) reduction of the safety stock.
Again, depending on the goods' value, this gain may be significant, or may be
insufficient, to justify an investment in RFID.
Evaluation of the changes
As has been done for TL carriers, Table 15 summarizes:
" Who invests in RFID, what is the nature of the investment, what is its weight
"
Who benefits from RFID, what is the nature of the benefit, is it quantifiable
"
What is the value for each player in investing and/or using RFID
Value
Note Comments
Tags,
10 to 65% IBetter
Suppression Reduction of
Better
readers,
reduction
of auditors,
visibility
software
Readers,
software
Tags,
readers,
software
Carrier
organization
reconciliation costs,
Iof workforce, reduction of redeployment of
better quality clerks
customer service
of service
workforce
++
on
outbound
High gain,
but high
investment
shipments
10 to 65% Better
reduction organization
of workforce
Reduction of
auditors,
reduction of
clerks
Reduction of
reconciliation costs,
redeployment of
vendor relationship
workforce
Better
visibility on
inbound
shipments
+++
High gain,
moderate
investment
N/A
Reduction of
a uditors,
reduction of
Clerks
Reduction of
reconciliation costs,
redeployment of
customer
relationship
workforce
Better
service to
customer
(tracking)
++
Moderate
to high
gain, high
investment
Better
productivity of
drivers and
better
utilization of
assets
(2-3 to 10%)
Table 15
88
For the shippers and the consignee, the conclusions are quite similar to those of the
previous section, with even higher potential of savings on safety stock, depending on the
performance of their current carriers.
Concerning LTL carriers, contrary to what we concluded for TL carriers, RFID has to be
implemented in a quite comprehensive way to bring some value. Selectivity can help
LTL carrier to offer a better service to some of its customers, but at a cost (readers +
software in all terminals) that will certainly not be compensated by the benefits. On the
other hand, if the LTL carrier wants RFID to benefit its internal terminal operations, it
will have to invest both in tagging capabilities and in readers + software. This will imply
not only investments in tags, but also in tagging machines and personnel.
However, in addition to providing internal benefits, it will also allow carriers to propose a
very high end service offer to its customers, and will provide a certain competitive
advantage.
89
4.2.4 The Reconciliation process
We have noted throughout this chapter that reconciliation will certainly be the process
that will benefit the MOST from RFID implementation. Reconciliation consists of
looking for information and evidence regarding unclear events (that had or should have
been traced), and one of the purposes of RFID is to make information flow and resulting
documentation as clear and visible as possible. It thus seems obvious that RFID will
significantly help to make reconciliation easier and more efficient.
Our intent here is not to review all the capabilities that RFID could offer, but rather to
focus on "painful" reconciliation tasks in transportation that may become easier to handle
with RFID. We will follow the same template as earlier: issues, main causes, RFID
capabilities, proposed changes, expected value, prerequisites and evaluation of changes.
AS-IS " Reconcile" process mapping
"AS-IS" -
RECONCILIATION PROCESS
6
5
products,
Issue 801.
BOL
deduction
Yes
mu.t
No
Apply~ No
Cei~
Yes
Pay carrier
in1
InOiL
e
Isuagaso
POD
Receive
Chec
agapPO
D )invoice
Figure4ndo
products,
ASN
Chc
PODjn
inBI,
againstPOFile PO
-O
-i
-pp
-cas
-r -11)0
Sin
1
prod u
c
a itnoice
e Nodc hets
81)d
o vaper
Figurie 40
90
arefadn
-5--0 iiilB
d-ED
(E
Pa8y
inDic
E-
O: ro fDlvey(~nd 1
a euine(a rorE!20
t eno
Main issues we have to cope with
The issues we have to deal with can be easily drawn from Figure 40. Actually, each "test
box" (the diamonds) correspond to a comparison of either two documents or one
document with physical products. We list these "tests" below, in the same order as they
have been numbered (which corresponds actually to the chronological process).
The questions reflecting the issues are the following:
1.
Is the ASN coherent with the Purchase Order (PO)?
2. Are the received products coherent with the ASN?
3. Is the ASN coherent with the products' invoice?
4. Are the received products coherent with the products' invoice?
5. Is the initial BOL coherent with the POD?
6. Is the carrier freight invoice coherent with the BOL and/or POD?
Identification of problems' main causes
The causes are multiple and have been already addressed several times in the previous
sections. They span from human errors (in entering data, in counting - at shipping or at
receiving, in establishing documents - ASN, BOL, invoices, POD -, in not complying to
procedures, etc...), to system errors (bar code system dysfunction, reading or
transmission problem,...), to malpractice. All these causes have been identified for a
long time, but as long as operators have to perform repetitive and sometimes complex
tasks, or to follow constraining procedures, the risk of human error will not disappear.
RFID capabilities that can apply to this process
The RFID capabilities that can address these causes are quite obvious: automatic capture
of data, storage of data, universal (when rights granted) access to data through the EPC
network. Moreover, the development of software that would allow automatic verification
and coherence between documents will not only remove a burden from operators, but
should also lead to a proactive handling of detected mistakes and discrepancies.
91
A second big advantage that RFID provides is the building of huge databases, that may
be used to perform various analyses of problems in order to enhance processes.
TO-BE RFID-enabled "Reconcile" process mapping
0
4)
E
0
impacted
data exchange
PO: Purchase Order (EDI 850)
ASN: Advance Notice Shipment (EDI 856)
invoice (paper orEDI 810)
>
>
BOL Bi
POD: P
Carder
Figure41
A quick look at Figure41 shows that almost every task, and the links between tasks, are
impacted by RFID. Basically, that means that every "manual" or semi-manual process of
information acquisition and information comparison can potentially be automated.
Moreover, all documents (that often already exist as "EDI entities") should be not only
electronically captured, but also stored.
Prerequisites
The prerequisite is a massive investment in the technology by every player. A first
investment by vendors and customers should already bring a number of benefits:
coherence between physical shipments and related ASN, easier ways to check the
92
coherence between ASN and PO, ASN and invoice and physical products and invoices.
In addition, automatic generation of BOL at shipping and POD at receiving should allow
the carrier to enter into the reconciliation process. However, as long as the carrier itself
(in particular the LTL carrier) does not invest in RFID technology, the visibility of the
transportation section will be limited.
Expected value for transportation
Concerning transportation, implementing RFID will be particularly helpful for two
documents: the Bill of Lading (BOL) and the Proof of Delivery (POD). Automatic
generation of these documents and possible confrontation between the three involved
players (shipper, carrier, consignee) should greatly reduce the disputes, as all of them
would have access to tangible, and a priori neutral, information.
The generation, payment and follow up of freight invoices will also be greatly facilitated,
removing another burden for the players, mainly for the carrier.
Evaluation of the value
The first big value for all players will be a reduction of personnel in charge of handling
the claims. It is hard to estimate how much RFID will enable in terms of savings, but it
should certainly be more than 50% of the workforce dedicated to this task.
Another direct financial impact is on deductions. Having at one's disposal, in quasi realtime, up-to-date and accurate information will permit a quicker processing of all the
claims and an avoidance of painful automatic deductions and charge-backs. This will first
diminish the administrative work it entails, but also reduce the net losses resulting from
non-settlement of disputes.
Finally, the building of a huge database will permit further analysis of historical data,
detection of recurring problems and handling of these problems.
93
4.3 RFID and Collaborative Transportation Management
4.3.1 RFID - CTM: a mutual need
For all people who have expressed an interest in both CTM and RFID, the convergence
between the objectives of the first and the benefits of the second is quite clear. An
excerpt from our literature review stipulates that "a better visibility and more information
sharing contribute to lower uncertainties" (the management of uncertainties being one of
the greatest challenge that every supply chain faces today). This citation associates quite
naturally the expressions "information sharing", one of the cornerstones of CTM, and
"visibility", one of the major benefit of RFID.
Many statements issued by CTM adepts insist - with good reason - that a key factor of
success for collaboration is having such visibility. On the other hand, a majority of
announcements on RFID praise its wonderful capabilities, but seldom mention the level
of collaboration (or transparency, or willingness to share data,...) that its implementation
would require, or the way to obtain and to process RFID-generated data. Yet, everybody
knows that it is not sufficient to install a wonderful machine to automatically get all the
benefits it is supposed to bring.
Our point here is to highlight that regardless of how wonderful a new technology can be,
and RFID is in this category, it will not bring all the expected benefits as long as the
various organizations that will use it jointly will not set some rules to use the technology.
4.3.2 CTM and RFID at work, a few illustrations
To support the assertion we just made, we present a few cases, drawn from the previous
chapters, which illustrate first how RFID can be very helpful in providing data to various
players and facilitate collaboration between them, and second, how RFID data can be
94
used and bring benefits only because some prior collaboration between players has
permitted access to and processing of the data.
The "Forecast and Plan Transportation" example
We described earlier how shipment forecast (and consequently, capacity planning) was
performed while being totally disconnected from a customer order forecast, leading to
mismatch between vendor's requirements in terms of trucks and carrier's ability to
provide these trucks 100% of the time.
We assumed that newly available RFID data would flow from one player to another,
without any concern. Yet, beyond being a technical issue (RFID data should be
accessible through the EPC network), the transmission, sharing and use of the data is here
a real challenge. More than a single temporary agreement, such exchanges require that
the players trust each other, because of possible commercially sensitive data, and longterm relationship commitments may have to be set. In this case, it appears that RFID
without CTM (meaning: no transmission of forecast to the carrier) would still lead to
poor shipment forecast.
The "Execute Transportation, for TL carriers" example
We have seen in the previous example that CTM enabled an efficient use of RFID data.
The example we aim to present now shows that RFID can also be an enabler of CTM.
By installing RFID readers in strategic locations, every tagged object can be potentially
tracked, providing visibility all along the supply chain. This tracking information can be
accessed by all players, and may trigger different actions if information given by the
system is different than information awaited. The storage and access to historical data
should also facilitate the reconciliation process, reduce the number of disputes, and
consequently lead to a reduction of claims cost and deductions.
We can see with this example that the simple fact of having at one's disposal common
data can greatly help to collaborate on many tasks. With the current technology, many of
these tasks are processed separately and with non-coherent data, by the different players,
95
leading to discrepancies, disputes and inefficiencies. RFID here "helps" CTM because it
may provide data and tools that are critical to efficiently working together. However, it is
right that the players have to agree on information sharing rules, but contrary to the
forecasting process, it is rather easy and not risky to commit on that.
4.3.3 Difficulties and opportunities
It has been mentioned that retailers were not as interested as carriers and vendors in
implementing CTM. Similarly, it appears that carriers are not as interested as retailers
and vendors in implementing RFID. Understandably, we may notice that the players
with least incentive to invest and/or use these new procedures or technology are the ones
which are the more reluctant to adhere. One of the challenges of both CTM and RFID
project managers will be to convince the players that the joint utilization of CTM and
RFID will be beneficial for all.
As it has been recently reasserted in a Forrester report (Tohamy et al., 2004), everybody
must be aware that it is illusory to try to implement RFID in an environment where the
basics are not present. First, it is critical to have a good understanding and a perfect
mastery of the processes. Second, the rules of information sharing must be very clearly
defined. Third, the players must already have an efficient existing information system, in
particular for the tracking/tracing operations. If all these conditions are fulfilled, then
RFID will definitely help.
96
5
CONCLUSION
In this thesis, we have gathered and analyzed a significant amount of information on an
area that had not previously been the subject of a comprehensive and thorough analysis:
the use of RFID in transportation. We have mapped the core processes, found out some
possible improvements, figured out how these improvements may be enabled using RFID
technology, and assessed qualitatively the value generated by the changes.
The main purpose of the following sections is to evaluate our findings. We will first sum
up what we found and sort out, among the results we obtained, what is of importance and
brings a new or different perspective to the field. We will then list gaps and limitations
of the study, and questions that remain to be addressed. Finally, we will give some
suggestions for future work on the subject.
5.1
Research findings: analysis and significance
Each of the transportation main process as for both TL and LTL carriers has been
analyzed following an identical template, which included process description,
identification of main problems and their root causes, changes that RFID may enable,
results obtained, prerequisites to implementation and estimation of the value of proposed
changes (assessment benefits / investment). The processes are Forecast, Plan and
Execute.
5.1.1 Forecast and plan transportation
Difficulties in transportation forecast and planning, i.e. shipment forecasts / capacity
planning and short-term shipment-to-carrier assignments, mainly stem from a poor
coordination between shippers, consignees and carriers (the "two parallel paths" of
forecasting), poor data synchronization between players and use of old information.
RFID can bring some changes, intervening very upstream in the process.
97
The use of RFID will permit to more accurately inventory management at shipper's and
customer's DCs, and in store's backrooms. It will lead to a better product order forecast
(lowering its variability) and, as a result, will permit a more precise shipment forecast,
leading to better capacity planning and short term asset management. We must note that
better initial product forecast will be critically facilitated by CTM.
In terms of prerequisites, investments are mainly on the manufacturer/shipper side (tags
and readers), and partly on consignee's side (readers), but absolutely not on the carriers.
Organizationally, a hurdle could be the setting of rules on information sharing between
vendor and customer. Moreover, a carrier will benefit from shipment forecast only if the
products managed by vendors are comprehensively tagged.
If all these prerequisites are satisfied, benefits apply to shippers - better matching of
demand, less expedited shipments, to customers - fewer stock-outs, and to carriers better capacity planning and asset utilization, fewer lost sales.
If we assess the value for each player, comparing benefits to necessary investment, it
appears that it is moderate for shippers, high for consignees, and even higher for carriers
that do not have to invest at all, but must be very much involved in CTM processes.
5.1.2 Execute transportation - TL carriers
The root causes of problems in TL transportation are related first to human errors on data
keying, counting, and mis-loading, and second to various documentation errors.
The use of RFID in this process will permit the automation of some tasks, by reducing or
suppressing time spent on verification. It will also permit the automatic generation and
transmission of documents. Mis-loading and misrouting will be avoided thanks to readers
at portals, lowering the average transportation lead time and its variability.
98
The first benefit, ensuing from task automation, will be an important labor cost
reduction. However, this reduction will not apply identically to all players. Shippers
should be able to reduce their auditor costs by 100% in the long run, and their clerical
costs by 30 to 50%. Consignees should reduce these costs as well, but to a lesser extent. It
is not clear if carriers may be able to reduce drivers' costs, even in a moderate way. All
players, however, will see their reconciliation costs reduced.
A second benefit, due to the automatic generation of documentation, is the significant
improvement of data quality and shipment visibility. A better service will be provided,
and it will also help to better plan and manage the workforce at shippers' and consignees'
facilities.
A third benefit is linked to the reduction of mis-loading and mis-routing: the reduction
of mis-shipments due to these errors will improve the average on-time delivery rate,
which in turn will entail a diminution of both average transportation lead time and lead
time variability. This decrease will, in turn, lead to a reduction of shippers' and
consignees' safety stock levels. Our calculations show that for an OTD rate passing from
90% to 100%, the reduction of safety stock due to a lower lead time goes from 1.5% (for
a 3-day trip) to 4.5% (for a 1-day trip). More importantly, still for an OTD rate passing
from 90% to 100%, the reduction of safety stock due to a lower lead time variabilitycan
vary from 20% to 35% for a medium-performance carrier, and from 10% to 20% for a
high-performance carrier. What is shown here is that, more than simply reducing the lead
time, it is critical to reduce its variability if we want to reduce significantly the safety
stocks.
The prerequisites are the same as in forecasting, in technical and financial terms. But for
this particular process, RFID implementation will not need to be comprehensive.
Selectivity can apply on products, routes or targeted vendors or customers.
For this process, the value is high for the consignee, as its investment is moderate
(readers only) whereas its benefits are very high. For the shipper, the benefits are also
high, but the investment are higher too because of products' tagging: consequently, the
99
value for the shippers is not as high as for the consignee. Finally, the carrier does not get
much benefit, but does not invest either: its value is relatively small.
5.1.3 Execute transportation - LTL carriers
The root causes of problems in LTL transportation are quite different from those in TL,
and are mainly due to its multi-stage and sequential nature. At a local level, deliveries
and pick-ups are sequential, and delays are very prone to accumulation. Similar
phenomena apply at a shuttle and long haul level. Moreover, the causes already cited for
TL carriers (data keying, counting, and mis loading, and various documentation errors)
apply too.
The use of RFID in this process should suppress data entry for waybill, and automate the
verification of sorting and pooling within a terminal. If shippers and customers are also
equipped with RFID, it could allow for a dynamic change of delivery or pick-up cycles in
case of delays.
The labor cost reduction benefit will also apply to LTL terminals, with auditor and clerk
reduction, due to the automation of their tasks. Reconciliation costs will also decrease.
The results that can be obtained are almost identical to those seen in earlier sections.
A second benefit will be a far better handling of delays at terminals, as RFID will enable
a faster creation of waybills and delivery notes, ensuring errorless sorting of shipments
(fewer mis-loaded and mis-routed shipments), and prioritization management in case of
emergency. More than in TL transportation, the delays that produced weak on-time
delivery rates should significantly decrease, entailing a far better average lead time and
reducing considerably lead time variability, diminishing in turn the level of safety stock
at shippers and customers . The figures here are the following: If the OTD rate passes
from 70% to 100%, the reduction of safety stock due to a lower lead time goes from 3%
(for a 5-day trip) to 13% (for a 1-day trip). More realistically, i.e. with a current OTD rate
of 70% and a target OTD rate of 90%, the reduction should be between 2% and 9%.
100
Similarly, the maximum reduction of safety stock due to a lower lead time variabilitywill
be between 40% and 65% (if OTD rate passes from 70% to 100%), but more realistically,
it should be between 20% to 35% (OTD from 70% to 90%).
A third benefit is a better productivity for drivers who perform local delivery and pickups. We have shown in our study that realistic assumptions in terms of better regularity in
local operation led to a potential maximum reduction of the number of drivers of
approximately 10%. This reduction applies also to the assets the terminal manages.
The prerequisites in the case of LTL carriers are very critical parameters to consider.
Out of the three benefits cited above, the two first can be attained if all the LTL carrier's
terminals are fully equipped with RFID. That means that they must have the "basic"
readers and software installation, but they also need to implement tagging capabilities,
that would allow non-initially-tagged products to be tagged within the LTL facility and to
be further followed up through the LTL network.
Interestingly, the last benefit we have mentioned (drivers' productivity and reduction of
assets) could be reached even if terminals did not invest. However, reaching this benefit
would necessitate that all products be tagged at source, and that all shippers and
consignees included in the delivery and pick-up cycles be equipped.
For this process, the value for the carrier will differ according to its level of investment.
If the carrier invests massively in terminals (tags, readers and software), it will have high
benefits. But high investments + high benefits do not necessarily entail high value, as it
depends on the specific ratio benefits / investment. The critical parameter to evaluate here
a realistic potential workforce reduction level. In the long run, the value should be high, a
"one-time investment" generating durable gains in terms of personnel. But a specific
discounted cash flow analysis is necessary to back up this assumption.
If the carrier does not invest in terminals, but only takes advantage of shippers' and
consignees' investments, the value should be moderate (a few percentage points progress
in drivers' productivity and asset utilization). But as it will be obtained "at no cost", there
will be a value - even if moderate . The difficulty in this case will be to assess which
level of investment at shippers and consignees is likely to have a positive impact.
101
5.1.4 Assessment offindings
Table 16 below presents a synthesis of Table 1, Table 5 and Table 15 displayed earlier.
Execute transportation LTL Carriers
ee note
High investment,
+
moderate gain
+++
Carrier
High investment,
high to moderate
++
++
High gain, but
high investment
+++
High gain,
moderate
investment
++
Moderate to high
gain, high
investment
gain
Moderate
investment, high
gain
+++
No investment,
high gain
+
Moderate
investment, high
gain
No investment,
moderate gain
Comments
Table 16
Note that it is only a qualitativeevaluation, as no real figures have been gathered,
processed and presented in our research, at least in terms of dollars (some ratios have
been estimated, though).
However, it gives a rough idea on where the value stands for RFID in transportation.
Table 17 gives an estimate of the repartition of the value, both between transportation
sub-processes and between players. Again, this is a qualitative and relative grading.
Execute
transportation LTL Carriers
+
carrier
++
I+ +++ j
5
+
++
6
6
7
20
I+
I
I
++
7
Table 17
102
Roughly, it appears that consignees are the most likely to benefit from implementation of
RFID in transportation. It is not very surprising, as it had been stated very often (actually,
some voices regularly denounced Wal-Mart and DoD as the great beneficiaries of RFID,
at the expense of other players). However, the announced benefits, like "better product
availability", "less out-of-stocks" and "increased revenue" were mainly supposed to come
from a better handling of the demand planning process, thanks to RFID, and not
necessarily from RFID-enabled transportation.
It is interesting, however, to note that carriers will not necessarily be the losers in this
game. It appears, at least through our qualitative reading, that they can benefit from RFID
as much, if not more, than shippers. Again, this has to be confirmed by a more
quantitative analysis. Table 17 also tends to show that a better RFID-enabled forecast
should greatly benefit transportation. On this latter point, we must remind the reader that
the technology alone will not be sufficient, and that Collaborative Transportation
Management is here a must if carriers want to fully take advantage of RFID technology.
5.2
Remaining gaps, questions, limitations
We have voluntarily led a "qualitative study". Therefore, the most important gap in our
research is the lack of concrete figures that may quantify the supposed benefits we
mentioned. The difficulties here were multiple:
" The scope was very broad, both in term of processes (forecast to reconciliation) and
players (shipper, carrier, consignee).
" Within each of these players, we find various situations (national or local TL firms,
regional or long haul LTL carriers, large or small vendors or retailers, etc...). Specific
studies should be done considering these differences.
*
Likewise, the processes differ from one player to another (for example, Wal-Mart
does not manage its inventory nor its relationships with carriers in the way other
stores do). Here again, further studies will have to take these differences into account.
103
"
It was also extremely difficult to put a cost on necessary equipment. One talks about
the five-cents tag, but tags are until now rather in a $0.5-$1 range, the cheapest cost
reported being around $0.40. We had the same problem when trying to quantify
readers' and software's cost, first because there are many types of readers,
corresponding to different capabilities (and our intent was not to perform a technical
study), and second because these costs are still far from being stabilized.
*
We did not rely on very specific metrics concerning companies' or carriers' logistics
performance (for example, the on-time delivery rates, or the number of workers in
terminals). We rather obtained our data from general studies or from "rough
assessments" made by the persons we interviewed, which were not drawn from
companies' official reports.
" We have not estimated either the impact or prerequisites on Information Systems used
in transportation, from ERPs to TMS, nor considered how the expected so-called
deluge of data would impact clerical or management tasks.
" Finally, we have assumed that information sharing was adopted by all players, even if
we know that this will certainly be one of the most difficult challenges the players
will confronted. Here again, implementation of CTM seems to be critical to enable an
effective sharing of information.
These various possible configurations, as well as many not-well-defined parameters
(costs,...) would have pushed us to make arguable assumptions, and forced us to perform
broad sensitivity analyses, which was not the purpose of our research.
5.3 Suggestions for future work
Our first suggestion is to go through the list of gaps and questions we covered in the
previous section and to evaluate which points are worthy of further research. To do so, it
would first be useful to divide the whole scope into more "manageable parts" (in term of
size).
104
We list below some additional leads that we find of interest, which could be studied in
order to better assess the place that RFID could take in transportation, and how it could
be efficiently implemented.
From a financial point of view, we have noted that sometimes an investment in RFID in a
field by certain players could mainly profit other players (for example, in forecast,
investments made by shippers and consignees can be very beneficial to carriers if
information is well shared; or a sizeable investment by LTL carriers in terminals may
highly benefit consignees). It will be interesting to study if they are some ways to share
both investment and benefits along the whole channel, and which incentives may be set
to reach a "win-win" situation or play a "non-zero-sum game". Here again, CTM should
have an essential role to play.
From an organizational point of view, studies will have to assess how the introduction of
such a new technology (RFID) and a new concept (sharing of information through the
EPC network) can be successfully implemented in the rather conservative and
technologically under developed world of transportation.
Finally, from a "supply chain concepts and tools" point of view, it would be interesting to
see how RFID capabilities may be used in the deployment of SCEM (Supply Chain Event
Management). By putting some triggers that indicate that something does not occur as it
was supposed to, and sending automatic alerts to the right persons or systems, SCEM
should be the next generation of tools that will give information that may automate or
facilitate decision making. RFID-generated data can be a great "input", and it may be
interesting to see how it could be applied in transportation.
Following the few leads we mentioned should contribute to better quantify the required
investments and the potential gains, and to address more deeply the collaboration and
implementation issues. Eventually, it should help to effectively implement and use RFID
in transportation.
105
6
APPENDICES
Appendix A
Random
#
Trip 1
Trip 2
Trip 3
Trip 4
Trip 5
Trip 6
Trip 7
Trip 8
Trip 9
Trip 10
Trip 11
Trip 12
Trip 13
Trip 14
Trip 15
Trip 16
Trip 17
Trip 18
Trip 19
Trip 20
Trip 21
Trip 22
Trip 23
Trip 24,
Trip 25
Trip 26
Trip 27
Trip 28
Trip 29
Trip 30
Trip 31
Trip 331
Tri 4
0.03
0.87
0.96
0.04
0.39
0.18
0.86
0.83
0.62
0.46
0.52
0.51
0.63
0.72
0.67
0.22
0.31
0.48
0.62
0.20
0.02
0.46
0.25
0.85
0.76
0.98
0.88
0.99
0.85
0.50
0.02
0.12
0.37
0.67
Late
Yes:1
No:0
Lead
time
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
2
1
1
1
1
1
1
Late:
Random
0
01
01
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
11
0
0
0
0
0
0
Tri 35
Trip 36
Trip 37
Trip 38
Trip 39
Tri 40
Trip 41
Tri 42
Trip 43
Trip 44
Trip45
Trip 46
Trip 47
Trip 48
Trip 49
Trip 50
Trip 51
Trip 52
Trip 53
Tri 54
Trip 55
Trip 56
Tri 57
Trip 58
Trip 59
Trip 60
Trip 61
Trip 62
Trip 63
Trip 64
Trip 65
Trip 66
Trip 67
0.27
0.22
0.43
0.76
0.65
0.65
0.72
0.83
0.73
0.03
0.54
0.59
0.50
0.74
0.74
0.57
0.29
0.68
0.39
0.23
0.08
0.69
0.91
0.82
0.47
0.83
0.60
0.35
0.58
0.14
0.93
0.03
0.97
Late
Yes:1
No:0
Lead
time
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
Late:
2
Random
Late
Yes:1
No:O
Lead
time
Trip 68
Trip 69
Trip 70
Trip 71
Trip 72
Trip 73
Trip 74
Tri 75
Trip 76
Trip 77
Trip 78
Trip 79
Trip 80
Trip 81
Trip 82
Trip 83
Trip 84
Trip 85
Trip 86
Trip 87
Trip 88
Trip 89
Tri 90
Trip 91
Tri 92
Trip 93
Trip 94
Trip 95
Trip 96
Trip 97
Trip 98
Trip 99
Trip 100
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
01
0
0
1
|
0.40
0.31
0.62
0.87
0.58
0.01
0.07
0.02
0.49
0.02
0.83
0.56
0.03
0.98
0.57
0.40
0.71
0.35
0.97
0.23
0.56
0.88
0.86
0.12
0.02
0.85
0.63
0.08
0.13
0.17
0.99
0.30
0.64
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
2
1
1
0
0
0
0
0
0
0
Late:
3
Total shipments late:
1
On-time delivery rate:
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
61
94% I
106
0
Appendix B
EZZZZtl
Monthly av
lead ti DL
100 trips on Day 1
100 trips on Day 2
100 trips on Day 3
100 trips on Day 4
100 trips on Day 5
100 trips on Day 6
100 trips on Day 7
100 trips on Day 8
100 trips on Day 9
100 trips on Day 10
100 trips on Day 11
100 trips on Day 12
100 trips on Day 13
100 trips on Day 14
100 trips on Day 15
100 trips on Day 16
100 trips on Day 19
100 trips on Day 18
100 trips on Day 19
100 trips on Day 20
Monthly average
lead time s-ddev SL
100 trips on Day 1
100 trips on Day 2
100 trips on Day 31
100 trips on Day 41
100 trips on Day 5
100 trips on Day 6
100 trips on Day 7
100 trips on Day 8
100 trips on Day 9
100 trips on Day 10
100 trips on Day 11
100 trips on Day 12
100 trips on Day 13
100 trips on Day 14
100 trips on Day 15
100 trips on Day 16
100 trips on Day 17
100 trips on Day 18
100 trips on Day 19
100 trips on Day 20
lead
Theoretical lead time
Theoretical
12
98% average on-time
98% averae on-time
Lead
time
1.04
1.03
1.06
1.07
1.07
1.05
1.04
1.05
1.01
1.05
1.03
1.00
1.01
1.04
1.03
1.04
1.04
1.04
1.06
1.02
1.06
%ontime
#trips
late
Lead
96.00%
4.
3
6
7
7
5
4
5
1
5
3
0
1
4
3
4
4
4
6
2
6
2.04
# trips
late
4.,0
2.04
2.07
2.02
2.03
2.02
2.04
2.04
2.02
2.05
2.03
2.03
2.05
2.06
2.06
2.04
2.02
2.08
2.01
2.04
2.05
4
7
2
3
2
4
4
2
5
3
3
5
6
6
4
2
8
1
4
5
tim
97%
94%
93%
93%
95%
96%
95%
99%
95%
97%
100%
99%
96%
97%
96%
96%
96%
94%
98%
94%
time
% ontime
96.00%
96%
93%
98%
97%
98%
96%1
96%
98%
95%
97%
97%
95%1
94%
94%
96%
98%
92%
99%
96%
95%
Thoretical
3
lead tirme
9% averae on-time
Lead
ti
F-7"
# trips
% ontime
late
4.00 96.00%
2
6
3
2
3
3
4
4
4
2
8
1
3
5
3
5
4
7
5
6
3.02
3.06
3.03
3.02
3.03
3.03
3.04
3.04
3.04
3.02
3.08
3.01
3.03
3.05
3.03
3.05
3.04
3.07
3.05
3.06
98%
94%
97%
98%
97%
97%
96%
96%
96%
98%
92%
99%
97%
95%
97%
95%
96%
93%
95%
94%
lead time
Theoretical lead time
Theoretical lead time
2
96% avera e on-time
96% average on-time_
96% average on-time
Lead time variability SL
Lead time variability SL
0.197
0.I90
0.197
0.141
0.239
0.171
0.141
0.171
0.171
0.197
0.197
0.197
0.141
0.273
0.100
0.171
0.219
0.171
0.219
0.197
0.256
0.219
0.239
Lead time variability SL
0.189
|
0.171
0.239
0.256
0.256
0.219
0.197
0.219
0.100
0.219
0.171
0.000
0.100
0.197
0.171
0.197
0.197
0.197
0.239
0.141
0.239
0.256
0.141
0.171
0.141
0.197
0.197
0.141
0.219
0.171
0.171
0.219
0.239
0.239
0.197
0.141
0.273
0.100
0.197
0.219
107
Teretical
3
j
Appendix C
LTL
1-day lead time
Input
Monthly average
lead time L
Theoreticallead time
Lead
time
0.56
0.56
0.57
0.58
0.53
0.58
0.54
0.56
0.54
0.61
0.56
0.54
0.57
0.62
0.54
0.53
0.54
0.55
0.58
0.56
0.56
Monthly average
SL
0.24
100 trips on Day 1
100 trips on Day 2
100 trips on Day 3
100 trips on Day 4
100 trips on Day 5
100 trips on Day 6
100 trips on Day 7
100 trips on Day 8
100 trips on Day 9
100 trips on Day 10
100 trips on Day 11
100 trips on Day 12
100 trips on Day 13
100 trips on Day 14
100 trips on Day 15
100 trips on Day 16
100 trips on Day 17
100 trips on Day 18
100 trips on Day 19
100 trips on Day 20
110.5
94% avera e on-time
100 trips on Day 1
100 trips on Day 2
100 trips on Day 3
100 trips on Day 4
100 trips on Day 5
100 trips on Day 6
100 trips on Day 7
100 trips on Day 8
100 trips on Day 9
100 trips on Day 10
100 trips on Day 11
100 trips on Day 12
100 trips on Day 13
100 trips on Day 14
100 trips on Day 15
100 trips on Day 16
100 trips on Day 17
100 trips on Day 18
100 trips on Day 19
100 trips on Day 20
lead time std dev SIL
Theoreticallead time
0.5
96% average on-time
# trips % on_late [time _
6.10 93.90%
6
7
8
3
8
4
6
4
11
6
4
7
12
4
3
4
5
8
6
6
1
94%
93%
92%
97%
92%
96%
94%
96%
89%
94%
96%
93%
88%
96%
97%
96%
95%
92%
94%
94%
Lead
# trips % ontime
late
time
0.541
4.05 95.95%
0.51
0.54
0.51
0.60
0.57
0.56
0.53
0.55
0.52
0.52
0.51
0.58
0.57
0.54
0.53
0.53
0.54
0.56
0.51
0.53
SL
0.24
0.26
0.27
0.17
0.27
0.20
0.24
0.20
0.31
0.24
0.20
0.26
0.33
0.20
0.17
0.20
0.22
0.27
0.24
0.24
108
1
4
1
10
7
6
3
5
2
2
1
8
7
4
3
3
4
6
1
3
99%
96%
99%
90%
93%
94%
97%
95%
98%
98%
99%
92%
93%
96%
97%
97%
96%
94%
99%
97%
Lead # trips % ontime
late
time
1.10 10.001 90.00%
1.07
1.11
1.09
1.13
1.15
1.10
1.09
1.09
1.13
1.08
1.05
1.15
1.19
1.08
1.06
1.07
1.09
1.14
1.07
1.09
SL
0.19
L 0.30
0.10
0.20
0.10
0.30
0.26
0.24
0.17
0.22
0.14
0.14
0.10
0.27
0.26
0.20
0.17
0.17
0.20
0.24
0.10
0.17
0.26
0.31
0.29
0.34
0.36
0.30
0.29
0.29
0.34
0.27
0.26
0.39
0.42
0.27
0.24
0.26
0.29
0.35
0.26
0.29
7
11
9
13
15
10
9
9
13
8
4
14
18
8
6
7
9
14
7
9
93%
89%
91%
87%
85%
90%
91%
91%
87%
92%
96%
86%
82%
92%
94%
93%
91%
86%
93%
91%
Appendix D
LTIL
3-day lead time
Theoretical lead time
2
10
Theoreticallead time
0.5
Inut
Monthly average
lead time IL
100 trips on Day 1
100 trips on Day 2
100 trips on Day 3
100 trips on Day 4
100 trips on Day 5
100 trips on Day 6
100 trips on Day 7
100 trips on Day 8
100 trips on Day 9
100 trips on Day 10
100 trips on Day 11
100 trips on Day 12
100 trips on Day 13
100 trips on Day 14
100 trips on Day 15
100 trips on Day 16
100 trips on Day 17
100 trips on Day 18
100 trips on Day 19
100 trips on Day 20
Monthly averagel
lead time std dev SLJ
100 trips on Day 1
100 trips on Day 2
100 trips on Day 3
100 trips on Day 4
100 trips on Day 5
100 trips on Day 6
100 trips on Day 7
100 trips on Day 8
100 trips on Day 9
100 trips on Day 10
100 trips on Day 11
100 trips on Day 12
100 trips on Day 13
100 trips on Day 14
100 trips on Day 15
100 trips on Day 16
100 trips on Day 17
100 trips on Day 18
100 trips on Day 19
100 trips on Day 20
90% average on-time
Lead # tripsI % onlate
time
time
2.07
6.50193.50%1
Lead # trips % on-i
time]
time
late
0.60 10.15 89.85%
0.59
0.63
0.61
0.63
0.61
0.59
0.60
0.60
0.61
0.59
0.56
0.62
0.58
0.66
0.63
0.56
0.59
0.56
0.61
0.60
SL
0.30
0.29
0.34
0.31
0.34
0.31
0.29
0.30
0.30
0.31
0.29
0.24
0.33
0.27
0.37
0.34
0.24
0.29
0.24
0.31
0.30
9
13
11
13
11
9
10
10
11
9
6
12
8
16
13
6
9
6
11
10
94% average on-time
91%
87%
89%
87%
89%.
91%
90%
90%
89%
91%
94%
88%
92%
84%
87%1
94%1
91%1
94%
89%
90%
I
2.08
2.03
2.06
2.06
2.05
2.07
2.06
2.08
2.12
2.09
2.06
2.04
2.07
2.06
2.11
2.06
2.07
2.01
2.07
2.05
8
3
6
6
5
7
6
8
12
9
6
4
7
6
11
6
7
1
7
5
92%
97%
94%
94%
95%
93%
94%
92%
88%
91%
94%
96%
93%
94%
89%
94%
93%
99%
93%
95%
Theoreticalead time
92% average on-time
Lead #trips % onlate
time
time
0.58
7.7592.25%
0.56
0.57
0.57
0.60
0.60
0.57
0.57
0.57
0.58
0.57
0.60
0.56
0.61
0.55
0.55
0.58
0.57
0.61
0.56
0.60
6
7
7
10
10
7
7
7
8
7
10
6
11
5
5
8
7
11
6
10
94%
93%
93%
90%
90%
93%
93%
93%
92%
93%
90%
94%/
89%
95%
95%
92%
93%
89%
94%
90%
Lead
time
% ontime
3241 22.0078.00%
3.23
3.23
3.24
3.29
3.26
3.23
3.23
3.25
3.31
3.25
3.22
3.22
3.26
3.27
3.29
3.20
3.23
3.18
3.24
3.22
SL
SL
0.24
0.27
0A8
0.27
0.17
0.24
0.24
0.22
0.26
0.24
0.27
0.33
0.29
0.24
0.20
0.26
0.24
0.31
0.24
0.26
0.10
0.26
0.22
0.24
0.26
0.26
0.30
0.30
0.26
0.26
0.26
0.27
0.26
0.30
0.24
0.31
0.22
0.22
0.27
0.26
0.31
0.24
0.30
0.47
0.47
0.53
0.54
0.48
0.45
0.47
0.50
0.56
0.52
0.42
0.50
0.48
0.51
0.52
0.45
0.45
0.41
0.43
0.52
109
# trips
late
21
21
19
25
24
22
21
22
26
21
22
18
24
24
26
18
22
17
24
23
79%
79%
81%
75%
76%
78%
79%
78%
74%
79%
78%
82%
76%
76%
74%
82%
78%
83%
76%
77%
Appendix E
LTL
5-day lead time
In
Monthly average
lead time L
100 tripsonDay1
100tripsonDay2
100 tripson Day 3
100 trip on Day 4
100 tripson Day 5
100 trips on Day 6
100 trips on Day 7
10tri sonDay 8
100 trip on Day 9
100tri onDay 10
0trssonDay 11
100 tripson Da 12
100 trips onDa 13
100_tripsonDay 14
100t rips onDay 15
100 tripson
s
Day 16
100tripsonDayl7
100trips onDay_8
100 trips on Day 19
100 trips on Day 20
Monthly average
load time StddvS
100 trips on Da 1
100 trips on Da 2
100 trips on Day 3
100 trips onDa 4
100 trips on Da 5
100 trips on Day 6
100 tri sonDa 7
100 trips on Day 8
100 trips on Day 9
100 trips on Day 10
100 trips on Day 11
100 trips on Day 12
00 trips onDay 13
100 trips on Day 14
100 trips on Day 15
100 trips on Day 16
100trips on Day 17
100 trips on Day 18
100 trips on Day 19
100 trips on Day 20
Theoretical lead time
0.5
96% average on-time
Lead
time
0
0.530
0.550
0.520
0.550
0.540
0.570
0.520
0.510
0.560
0.550
0.530
0.520
0.560
0.520
0.520
0.530
0.540
0.560
0.530
0.550
# trips %onlate
time
. 96.2%
3
5
2
5
4
7
2
1
6
5
3
2
6
2
2
3
4
6
3
5
97%
95%
98%
95%
96%
93%
98%
99%
94%
95%
97%
98%
94%
98%
98%
97%
96%
94%
97%
95%
Theoretical lead time
0.5
97% average on-time
Lead
time
0.530
0.510
0.540
0.540
0.550
0.570
0.530
0.540
0.520
0.530
0.520
0.510
0.520
0.530
0.540
0.510
0.520
0.510
0.520
0.540
0.550
# trips % onlate
time
.0
%
1
4
4
5
7
3
4
2
3
2
1
2
3
4
1
2
1
2
4
5
99%
96%
96%
95%
93%
97%
96%
98%
97%
98%
99%
98%
97%
96%
99%
98%
99%
98%
96%
95%
Theoretical lead ti
3
Theoretical lead time
0.5
Theoretical lead time
0.5
98% average on-time
97% avrage on-time
Lead #trips % ontime
late
time
3.017
165 98.35%
Lead # trips %ontime
late
tme
0.532
3.2 96.80%
Lead
time
3.000
3.020
3.010
3.020
3.030
3.010
3.010
3.030
3.010
3.010
3.030
3.030
3.030
3.010
3.000
3.010
3.020
3.020
3.020
3.010
0.520
0.530
0.530
0.510
0.560
0.510
0.530
0.580
0.550
0.530
0.550
0.550
0.550
0.540
0.560
0.550
0.570
0.550
0.570
0.530
0.550
0.530
0
2
1
2
3
1
1
3
1
1
3
3
3
1
0
1
2
2
2
1
100%
98%
99%
98%
97%
99%
99%
97%
99%
99%
97%
97%
97%
99%
100%
99%
98%
98%
98%
99%
0.550
0.550
0.510
0.550
0.520
0.500
0.520
0.530
0.520
0.540
0.540
0.550
0.520
0.520
0.540
0.550.
0.560
0.520
____
2
3
5
5
1
5
2
0
2
3
2
4
4
5
2
2
4
5
6
2
98%
97%
95%
95%
99%
95%
98%
100%
98%
97%
98%
96%
96%
95%
98%
98%
96%
95%
94%
98%
96% average on-time
0.187
0.165
0.118
It.68
[ 0.203
0.17
0.22
0.14
0.22
0.20
0.26
0.14
0.10
0.24
0.22
0.17
0.14
0.24
0.14
0.14
0.17
0.20
0.24
0.17
0.22
0.10
0.20
0.20
0.22
0.26
0.17
0.20
0.14
0.17
0.14
0.10
0.14
0.17
0.20
0.10
0.14
0.10
0.14
0.20
0.22
0.00
0.14
0.10
0.14
0.17
0.10
0.10
0.17
0.10
0.10
0.17
0.17
0.17
0.10
0.00
0.10
0.14
0.14
0.14
0.10
0.14
0.17
0.22
0.22
0.10
0.22
0.14
0.00
0.14
0.17
0.14
0.20
0.20
0.22
0.14
0.14
0.20
0.22
0.24
0.14
0.17
0.10
0.24
0.10
0.17
0.27
0.22
0.17
0.22
0.22
0.22
0.20
0.24
0.22
0.26
0.22
0.26
0.17
0.22
0.17
L
L
SL
110
SL
SL
#trips % onlate
time
4 54
.50%
3
1
6
1
3
8
5
3
5
5
5
4
6
5
7
5
7
3
5
3
97%
99%
94%
99%
97%
92%
95%
97%
95%
95%
95%
96%
94%
95%
93%
95%
93%
97%
95%
97%
Lead
time
5.162
5.090
5.150
5.180
5.180
5.180
5.240
5.140
5.090
5.170
5.160
5.140
5.150
5.220
5.170
5.120
5.130
5.180
5.180
5.200
5.160
SL
0.396
0.32
0.39
0.39
0.46
0.41
0.49
0.35
0.29
0.43
0.37
0.38
0.36
0.50
0.40
0.33
0.34
0.44
0.41
0.43
0.44
#trips % onlate
time
15.0085
8
14
18
15
17
21
14
9
15
16
13
15
19
16
12
13
16
17
19
13
92%
86%
82%
85%
83%
79%
86%
91%
85%
84%
87%
85%
81%
84%
88%
87%
84%
83%
81%
87%
7
GLOSSARY
ALN
Advanced Loading Notice
ASN
Advanced Shipment Notice
BOL
Bill Of Lading
CPFR
Collaborative Planning, Forecasting and Replenishment
CPG
Consumer Packaged Goods
CTM
Collaborative Transportation Management
CV
Coefficient of Variation
DC
Distribution Center
EDI
Electronic Data Interchange
EOL
End Of Line (terminal)
EPC
Electronic Product Code
GPS
Global Positioning System
HOS
Hours Of Service
LT
Lead Time
LTL
Less Than Truckload
ONS
Object Name Service
OTD
On-Time Delivery
PML
Physical Markup Language
PO
Purchase Order
POD
Proof Of Delivery
POS
Point Of Sales
RFID
Radio-Frequency Identification
SCEM
Supply Chain Event Management
TL
Truckload
111
8
REFERENCES
Alexander, K., Gilliam, T., Gramling, K., Kindy, M., Moogimane, D., Schultz, M.
Woods, M., "Focus on the Supply Chain: Applying Auto-ID within the Distribution
Center", Auto-ID Center White Paper, IBM Business Consulting Services, IBMAUTOID-BC-002, 2002.
AT Kearney, "Meeting the Retail Mandate - A Discussion of the Issues Facing CPG
Companies", 2003
Auto ID Center, "Technology Guide",
http://archive.epcglobalinc.org/new_media/brochures/technologyguide.pdf.
Bradley, P., "LTL: Working Hard for Their Money", DC Velocity, March 2004.
Boushka, M., Ginsburg, L., Haberstroh, J., Haffey, T, Richard, J., Tobolski, J., "Auto-ID
on the Move: The Value of Auto-ID Technology in Freight Transportation", AutoID Center White Paper, Accenture, ACN-AUTOID-BC-003, 2002
Brock, D., "The Electronic Product Code (EPC). A Naming Scheme for Physical
Objects", Auto-ID Center White Paper MIT-AUTOID-WH-002, 2001.
Brock, D., Milne T., Kang, Y., Lewis, B., "The Physical Markup Language. Core
Components: Time and Place", Auto-ID Center White Paper MIT-AUTOID-WH-005,
2001.
Browning, B., White A., "Collaborative Transportation Management: A Proposal",
Logility, Inc. White Paper, 2000
CASPIAN, ACLU, EFF, EPIC, "Position Statement on the Use of RFID on Consumer
Products", 2003
Chapell, G., Durdan, D., Gilbert, G., Ginsburg, L., Smith, J., Tobolski, J., "Auto-ID on
Delivery: The Value of Auto-ID Technology in the Retail Supply Chain", Auto-ID
Center White Paper, Accenture, ACN-AUTOID-BC-004, 2002
Chopra, S., Reinhardt, G., Dada, M., "The Effect of Lead Time Uncertainty on Safety
Stock", Decision Sciences, Volume 35 Number 1, Winter 2004
Cooke, J.A., "Bringing Carriers into the loop", Logistics Management, Sept. 2000, pp.
77-80
Davenport, T., "Process Innovation: Reengineering Work through Information
Technology", Harvard Business School Press, 1993
112
Delaney, Wilson, " 1 4 th Annual State of Logistics Report", 2003
Dinning, M., Schuster, E.W., "Fighting friction", APICS - The Performance Advantage,
2003
Dutton, G., "Collaborative Transportation Management: Getting Closer to your
Supply Chain Partners Pays Off", World Trade, Feb. 2003, pp. 40-43
Engels, D.W., Sarma, S., Putta, L., Brock, D., "The Networked Physical World
System", Proceedings of IADIS International Conference, Lisbon, Portugal, November
2002.
Esper, T.L., Williams, L.R., "The Value of Collaborative Supply Chain Management
(CTM): Its Relationship to CPFR and Information Technology", Transportation
Journal, Vol. 42, Iss. 4, 2003
Field, A.M., "Coming of Age", Journal of Commerce, 1 March 2004
Fontanella, J., "Gillette and RFID part II: The Roadmap for Implementation", AMR
Research Report, May 28, 2003
Fontanella, J., Bilodeau, M., "Finding the ROI in RFID", AMR Research Report, Oct.
31, 2003
Frazelle, E., "Supply Chain Strategy : The Logistics of Supply Chain Management",
McGraw-Hill, 2001
Goyal, A., "Savant Guide", Auto-ID Center Technical Report MIT-AUTOID-TR-015,
2003.
Grover, V., Kettinger, W.J., "Business Process Change: Reengineering Concepts,
Methods and Technologies", Idea Group Publishing, 1995
Kambil, A., Brooks, J., "Auto-ID Across the Value Chain: From Dramatic Potential
to Greater Efficiency and Profit", Auto-ID Center White Paper, Accenture, ACNAUTOID-BC-00I, 2002
Karolefski, J., "Collaboration drives success: With a Shared Transportation Plan,
Partners Can Reduce Costs, Increase Revenues and Boost Customer Service", Food
Logistics, 15 April 2002
Kinsella, B., "The Wal-Mart Factor", Industrial Engineer, pp. 32-36, Nov. 2003
Mc Farlane, D., Sheffi, Y., "Speeding the Supply Chain", Information Economics
Journal, Dec. 2003
113
Nahmias, S., "Production and Operations Analysis", Fourth Edition, McGraw-Hill,
2001
Petersen, M., "VICS Logistics Model", Voluntary Interindustry Commerce Standards
(VICS), Logistics Committee, 1999
Powell, W.B., "Dynamic Models of Transportation Operations", Handbook in
Operation Research, Volume in Supply Chain Management, Princeton University, 2002
Russell, D.M., "Collaborative Transportation Management (CTM)", Voluntary
Interindustry Commerce Standards (VICS), 2002
Sarma, S., "Towards the 5# Tag", Auto-ID Center White Paper MIT-AUTOID-WH006, 2001.
Savi Technology, "Active and passive RFID: Two Distinct but Complementary
Technologies for Real-Time Supply Chain Visibility", White Paper, 2002
Swamy, G., Sarma, S., "Manufacturing Cost Simulations for Low Cost RFID
Systems", Auto-ID Center White Paper MIT-AUTOID-WH-006, 2003.
Sheffi, Y., McFarlane D., "The impact of Automatic Identification on Supply Chain
Operations", International Journal of Logistics Management, Vol. 14, No. 1, 2003.
Simchi-Levi, D., Kaminski, P., Simchi-Levi, E., "Designing and Managing the Supply
Chain", Second Edition, McGraw-Hill/Irwin, 2003
Singer, T., "Understanding RFID: A Practical Guide for Supply Chain
Professionals", Tompkins Associates, 2003
Sutherland, J., "Collaborative Transportation Management: The Missing Link of
CPFR", VICS/CPFR meeting, February 7, 2003
Sutherland, J., "Collaborative Transportation Management: Creating Value
Through Increased Transportation Efficiencies", Business Briefing at Pharmagenerics
2003, Sept. 2003
Tohamy, N., Kinikin, E., Cameron, B., Herbert, L., "RFID: Icing on a Half-Baked
Cake", Forrester, 2004
Urbanski, A., "The Masters of Their Freight: Retailers are Realizing They Must
Take Control of Their Freight if They are to Seize the Control of Their Destinies",
Progressive Grocer, 1 July 2002
114
Voluntary Interindustry Commerce Standards (VICS), Logistics Committee,
Collaborative Transportation Management Sub-Committee, "Collaborative
Transportation Management: White Paper - Wal-Mart, Procter & Gamble, J. B.
Hunt", Council of Logistics Management International Conference, 2001
Voluntary Interindustry Commerce Standards (VICS), "CPFR: Collaborative Planning,
Forecasting and Replenishment - Voluntary Guidelines V2.0 June 2002",
http://www.cpfr.org/documents/pdf/CPFRTabl.pdf, 2002
Voluntary Interindustry Commerce Standards (VICS), "Notes for October 17, 2002
Meeting, Atlanta GA", 2002
Voluntary Interindustry Commerce Standards (VICS), Logistics Committee,
Collaborative Transportation Management Sub-Committee, "Collaborative
Transportation Management - White Paper Version 1.0", 2004
115