logistics everywhere

8/12/2019 Logistics Everywhere

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Since it began to be used by certain

large US manufacturing firms after

World War II, logistics management

has become increasingly effective.

After the initial attempts which met

with varying degrees of success,

both the definition and applicationsof logistics management now seem

to be quite settled: Logistics refersto the systematic management of thevarious activities required to movebenefits from their point ofproduction to the customerTheconcept of benefits is a multifacetedone that goes beyond the product orservi ce itself to include issues regardi ng

tim ing, quantity, suppor ting services,location and cost. So a basic definiti on

of logi stics is the conti nuous process

of meeting customer needs by ensurin gthe availabil ity of the right benefitsfor the ri ght customer, in the quantity

and condition required by thatcustomer, at the tim e and pl ace thecustomer wants them (Gourdin,2001:2). Our aim is therefore not to

try to question the traditional

approach of logistics management,

but rather to expound the thesis

that it is possible to significantly

enlarge the scope of logistics

management in order to include

other fields. These comprise some(and probably many) issues that

have an important bearing on the

management sciences as a whole.

More precisely, we claim that there

are several examples of disciplines

which could each be reformulated,

at least in part, and which should

be reexamined as problems in

logistics management. In this first

paper devoted to expounding thisthesis, we focus for the most part

on two aspects of management

sciences chosen essentially

at random: advertising and

knowledge management. These

disciplines, or domains of activity,

are usually considered to be

quite far removed from logistics as

well as from each other. However,

we claim that the basic problems

in these disciplines can be

represented as instances of a quite

basic and general formulation oflogistics management, where one

can focus even more than usual on

the basic concepts of optimization

and flows. Defending such a thesis

requires two components: one

analytic and the other synthetic.

For the whole approach to make

sense, the analysis needs to reduce

logistics management to its very

core, and this core needs to be

expressed in a way that is universal

enough for it to be detected as an

essential part of the make-up ofother disciplines. At this very

early stage of our thinking, the

synthetic part is limited to the

It is now an accepted f act th at logistics man ag ement a ims to provide

service qua lity, cost reduction an d eff icient a ft er-sales suppo rt th roug h

an eff ective monito ring o f supply chain operat ions. In order to achieve

these goals, logisticians have learned to define clearly the problems they

have to ma nag e in terms of product f low s optimization and t o use

metho ds that a re both rigorous and rational in order to solve them.

In this pap er, we pro pose tha t it shou ld be possible to a pply and to

generalize the logistical approach to other fields, including those as

improba ble as advertising and know ledge mana gement

Logistics Everyw here:Can a Logistical Approach

help Tackle the Majorityof Managerial Problems?

36Supply Chain Forum An International Journal Vol. 4 - N1 - 2003 www.supplychain-forum.com

Charles Tresser

M athematical Sciences Department

IBM Thomas J. Watson Research C enter, USA

tresser@ us.ibm.com

Gilles Pach

Centre de Recherche sur le Transport

et la Logistique

Universit de la M diterrane

A ix M arseille II, France

pache@ iut.univ-aix.fr


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37Supply Chain Forum An International Journal Vol.4 - N1 - 2003 www.supplychain-forum.com

case study of the two examplesthat have been previouslymentioned.

This paper examines thefoundations of logistics management,

starting with the original aimsand continuing up to the

most recent approaches andstrategies (including supply chainprocess integration). More than

just reviewing the subject, we willexplain our belief that, despite its

obvious evolution and the progressthat has been made, logisticsmanagement has not changed in a

fundamental way, and has notundergone any radical change sinceit began to be considered as

belonging to the managementsciences. A typical MBA course

on logistics management wouldp ro fes s t o i n c reas e t hemanufacturing firms profitability,

t h u s r es p o n d i n g t o t heexpectations of the shareholdersbut this motivation hides the basic

thinking behind it. In other words,l o gi s t i c s ( s up pl y c hai n )

management, which today is stilllimited to playing a supporting rolein helping to improve

manufacturing and selling, is inessence organized around the

concepts of optimization and flows.One must also identify theobjectives that are to be optimized

and under what constraints suchan optimization must be performed(or approximated). We would like

to emphasize that the twodisciplines which are taken as

examples have been chosen atrandom. We simply wanted oneunusual example to discuss briefly

and one example which we could

discuss at greater length at thisearly stage of the research and

which would provoke a debate. Asthis paper is interdisciplinary, we

have made an effort to spell out alltechnical acronyms, even thosethat are standard in logistics

management. 1

An or thodox v iewof lo gistics

Logistics management, which hasbeen subjected to a slow

maturation process, firstly in theUSA and then in Europe, is deeply

rooted in the military sciences, thetransition happening when thesoldiers who had been working on

its development as a modernscience came back to civilian

business life after World War II.Until quite recently, it was foundedon product flows optimization, a

perspective that has beenchallenged by the new trendstowards supply chain process

integration advanced by someresearchers. We take the view that

this challenge is not motivated by

any serious breakdown in the role

of logistics management, as itsevolution over recent years has

confirmed the presence of onemajor objective: to optimize

inbound and outbound logisticaloperations in order to increase thefirms profitability and thus

respond to the shareholdersexpectations. In fact, thecommonalities of the problem

solving methods of logisticsmanagement are so broad that not

only do they apply to both recentand historical trends, but they alsoapply to fields quite distant from

product flows optimization.

Product flow s optim ization

Historians have recently shown

that supplying cities with food fromdistant lands in order to avoid

famine is a problem with a clearlogistical nature, which arose inEurope at least as far back as theMiddle Ages (see, for instance,

Abad [2002]). Should we take this,therefore, as the first step towards

the development of a logisticalapproach? Certainly not, as it isimpossible to identify any real

global thinking aiming towards thebetterment of the means ofdistribution of provisions: mankind

was at that time most oftenpowerless in the face of random

factors over which it had nocontrol. So, while it is certain thatlogistical problems existed, and to

some extent were routinely solvedlocally through necessity, the veryidea of logistics managementwas

still to be born. It appears muchlater and its origins are

undoubtedly military. Anyencyclopedia would refer to itprimarily as the combination of

transportation, provisioning, andaccommodation designed to ensurethe success of troops in combat. If

detailed enough, the encyclopediawould probably add that the father

of military logistics is theNapoleonic General Antoine-Henri

Jomini, the author of the famousPrcis de lart de la guerre, ounouveau tableau analytique des

principales combinaisons de la

stratgie, de la grande tactique et dela pol i t ique mi l i ta i re, published in

1838, in which he presents logistics

1. After a first version of the paper had been

circulated, we received very encouragingcomments from Alan Hoffman, Bill Grey,

Nicholas Zissos, and from an anonymous

reviewer of Supply Chain Forum: An

Internati onal Journal. We also received useful

informati on from Naoki Abe, John Forrest, and

John Tomlin about v ario us uses of the methods

of logistics in aspects of advertising operati ons.

What these colleagues, now all from IBMsResearch Center, hav e taught us is that several

authors have, for instance, used optim izati on

techniques to make a better choice in the

distribution of advertisements, in classical

settings and mor e recently on the World Wide

Web. However, it seems that here we are

postulating a new approach, whi ch in the case

of advertising aims to reformulate the

discipline in a holistic way as a problem of

logistics management. On the other hand,

these comments given to us on the appli cationsof optimi zation methods in advertising lead us

to expect that the approach developed here

should bear frui t at some stage in the future and

not just remai n a philosophical perspective.

When considering

disciplines where the

methods of logistics

(supply chain)

management have not

previously been

applied, it is

necessary to identifythe entities that need

to flow, to where they

must flow and to

what benefit.


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as being one of the six parts of the

art of war (Jomini, 2001).Throughout the twentieth century,

the field of military logisticsunderwent spectacular developments,

culminating in Operation Overlord,the landing of the Allied troops on

the occupied European Continent

on June 6, 1944. The French

coastline was fortified and

defended by particularly well-equipped German troops, therefore

it was essential to plan the different

stages of the invasion meticulously

in order to avoid a repeat of the

cruel failure of Operation J ubilee,

which was attempted on the

beaches of Dieppe in March 1942.

To this effect, the Anglo-American

Joint Command assembled theorganizational and logistical means

necessary to anticipate and

overcome the constraints of the

terrain. More recently, during

Operation Desert Storm in 1991, the

media referred frequently to the

importance of the role played

by logistics as an essential

complement to the firepower of theAllied armies in the successful

outcome of the military operation.

What is more, the quality of

logistics improved dramaticallyduring the 2003 Iraq war. In a

recent study for the Institute of

Comparative Strategy, Richardot

(2002) also referred to the crucially

important role played today by theCombat Logistics Force (CLEF) in

the organization and efficiency of

the US Navy. Therefore, the link

between logistics and the success

of military operations remains

particularly strong; even if today it

is widely acknowledged that

logistics is also (and mainly?) a

part of management. We mustremember, however, that the

application of logistics in

manufacturing firms just after

World War II was a direct result of

what had been learned from

Operation Overlord and the overall

process of winning the war. The

distances which had to be covered

in the liberation of Europe obligedthe formalization of re-supply and

transport processes, which were

recognized as being applicable to

American firms needing to supplycustomers located hundreds or

thousands of miles from the

factories.

This explains why logistics

management was first perceived

by the American Marketing

Association (1948) as the planningof the operations linked to the

dispatch of goods from the factoryto the consumer (transport,

handling and warehousing). The

goal was to adapt and apply the

tools from Operational Research,

tools that had initially been

conceptualized in a military

context. We will refrain fromdelving further into the history of

logistics management (see for

instance Lambert et al. [1998]), but

we want to stress that its military

origins strongly influenced its

development until the 1970s.

During that time span, the mainquestions continued to revolve

around the implementation ofconstrained optimization methods

to help in the dispatching of goods

from their origination points to

their destinations. One of the best

known examples of such a problem

is the design of the delivery round

that minimizes the total distance

covered as a function of the

stores to be served in a givengeographical area. This is an

example of the Traveling SalesmanProblem, simple to formulate but

which quickly becomes too difficult

for any computer to solve when

the number of stores increases!

Logistics management was thus

limited to the one best way in

terms of product flows monitoring.

This focus was justified, as markets

that were previously local and

national became progressivelyglobal for multinational corporations,

a fact which accentuated the

problem of dispatching goods atlow cost and with high service

quality. As well informed observers

of logistics management will know,

Magee (1968) made a significant

step forward by introducing the

concept of logistical processes and

the three systems:(1) the procurement system;

(2) the operating system; and

(3) the physical distribution system.

However, we believe that a

continuity exists between theapproaches of the American

Marketing Association (1948) andof Magee (1968), as the analysis

remains based upon product

flows optimization. Magees (1968)fundamentally important contribution

is to stop limiting the role

of logistics management to

that of a physical distributionsystem. Contradicting the formerreductionistviews, he argued that

the manufacturing firm must also

optimize product flows inside the

production cycle (work inprogress [WIP] management) and,

downstream to the operating

system, inside the physical supply

cycle (materials management), if it

wants the total logistics system or

pipeline to function correctly. But

is it possible to view this as a truly

radical departure when, for Magee

(1968), the issue remains theoptimum planning of logistical

operations using increasingly

sophisticated tools, such as

program evaluation and review

techniques (PERT) and material

requirement planning (MRP)? By

the time his book appeared, the

world had grown more complexand the markets where goods were

consumed had become larger and

more distant, creating the need

for an even more effective

coordination of transport, productionand warehousing activities. More

than ever before, logistics

management experienced an urgent

need for managerial proceduresthat would use mathematical

algorithms to bring about the best

solution at the right moment.

In fact, even a few years later,

and despite its revolutionary

contributions, the way Heskett

( 1977) en vi s i o ns l o gi s t i c smanagement remains captive to the

same product flows optimizationparadigm. The economic landscape

has changed since the beginning

of the recession in the Western

countries, and in the particularly

difficult context of price competition,

firms must adjust their logistics (in

the physical distribution system,the operating system and the

procurement system) to adhere as

closely as possible to the

downstream demand in order to

reduce costs. Long before such

reasoning became fashionable,Heskett (1977) indirectly introduced

the idea that efficiency dependedon a double paradigm: lean



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production and agility. From aconcrete standpoint, it is the actualsales, and no longer the sales

forecast, that must trigger theoperations of the supply of raw

materials, production, transport,etc. Thus, Heskett (1977) implicitlyconceptualized the just-in-time

(J IT) strategy, at the very sametime as it first began to be appliedin Japan by Toyota! But while that

vision was incontestably aninnovative one, it remained

centered on manufacturing firms,whose survival depended on theoptimization of their own logistics

systems. A good JIT strategy willfirst induce a reduction in the stocklevels of goods and materials, while

it may also be the case that stocklevels abruptly increase at the

retailer or wholesaler locations.

Supply chain processintegration

Do the recent trends in logisticalthinking challenge the orthodox

vision in terms of flowsoptimization? It is possible toanswer yesand noat the same

time. According to the majority of

authors (see, for example,Underhill [1996], and Mentzer et al.[2000]), all of the firms involved invertical exchange relationships

insist on the importance of the newintegrative dimension of thelogistical processes: specifically,

that in order to bring the rightproduct at the right time and at the

right place to the consumer, it isnecessary to coordinate all of thelogistical operations along the

supply chain. Effective logisticsmanagement thus becomes the

means to generate a close anddurable collaboration betweensuppliers, manufacturers, retailers,

and third party logistics (TPL)service providers, so that togetherthey create value for the customer

(Grey et al., 2003). However, wemust also admit that the aim of asupply chain process integration

remains to create value for theshareholders, which in turn

requires enforcing product flowsoptimization.

At a fundamental level, even if thisvision is sometimes disputed, asupply chain corresponds to aset of operations supporting: (1)

the logistical activities of the

procurement of materials in anetwork of first-tier and second-tierproviders; (2) the transformation of

materials into semi-finished orfinished goods; and (3) the physicaldistribution of the finished goods

to customers. The basic idea isthat these activities and operations

must be perfectly synchronizedwithin the framework of supplychain management (SCM), so that

customers can benefit from thebest possible service quality at the

lowest possible cost. Stevens(1989) suggested the existence offour steps leading to the emergence

of genuine SCM: Step 1 is distinguished by

complete functional independence

in so far as each functionoperates quite separately from

all the others, protected bybricks (stocks) allowing fordifferences between their

operating rhythms. In step 2, manufacturing firms

recognize the urgent need for aminimum coordination betweenrelated functions, e.g. marketing

and physical distribution, so asto eliminate a number ofmalfunctions.

Next, step 3 is there to improvethe process of coordination by

implementing the comprehensive

planning of internal flows fromdownstream to upstream,

leading to: Step 4, when supply chain

members finally become aware

that they are merely part of awhole.

The virtue of this evolutionaryapproach is to highlight the fact

that SCM refers to a succession of

trade-offs (Lambert et al., 1998).Trade-offs occur within a firm (e.g.,

between purchasing and materialsmanagement, materials management

and production, etc.). The purposeis to find overall solutions, which,through intra and inter-organizational

collaboration, will avoid a wasteof resources and will increasethe profitability of supply chain

members. An interesting exampleis that of convenience goods

manufacturers, where largeretailers and TPL service providerswork together to create the

packaging for a new product toreduce logistical costs from thefactory to the store shelves. One

could also quote the example of anautomotive manufacturer and itsmain suppliers deciding to

implement a common milk-rounddelivery system: a collection of

vehicles that visit suppliers in apredetermined and negotiatedorder, at pre-agreed times during

the night, from which there followsa reduction of congestion at theassembly plant (Lamming, 1983).

I n h i n d s i gh t , an d w h i l e

acknowledging the progress madein logistics management over thelast fifteen years or so up until now

in 2003, it is clearly appears thatSCM does not represent a radicaldeparture. Of course, SCM

emphasizes the importance of theindispensable collaboration

between supply chain members inan extended enterprise (Naccaratoet al., 2000), but the object of

analysis still remains the product and information flows. On

the other hand, thanks totechnological progress, andnotably computer technologies

(from core hardware to softwareand algorithms, and more recently,pervasive computing, which

considerably enhances reach andcommunication), it is now much

easier to optimize under constraintthan it was, for example, fifteenyears ago, and this is where the

essential change resides. Forinstance, a small and medium-sizedenterprise (SME) can now in real

time tackle certain optimizationproblems that would have been too

complex for most large companiesin the 1980s. Thanks to these newtechnologies, the supply chain

members can adapt faster to all

sorts of environmental changes andexecute effective time-based

strategies, where the object is toconceive new products faster than

the competition and then tomanufacture and deliver them tothe customer more quickly and

with no mistakes. For over half acentury, logistics management hasthus proven its capacity to improve

the performance of manufacturingfirms and, on a more global level, of

networks of firms, by relying on alogistical approach with a universalambition. From this point of view,

might logistics managementbecome the means to help resolvemanagerial problems in areas far



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removed from product flowsoptimization?

The central t hesis anda f irst e xample

Clearly, the goal we have set toourselves is quite ambitious and

challenging, but the rewards couldbe enormous for most of themanagement sciences. The process

began with a strong hunch thatlogistics was extremely prevalent,

with possible examples to be foundin most of the sciences, from thePrinciple of Least Action in physics,

to the way a cell works in biology.We will refrain from formulating ourthesis on such general grounds and

instead, we will concentrate beforehand on a formulation that focuses

on the management sciences. Theformulation we provide is still quitebrief but we expect that many

people will join us in the comingadventure, and will help us todevelop the fundamentals as well

as the applications of the ambitiousprogram implicitly outlined in our

thesis. We have randomly picked adiscipline from within or close tothe field of management that would

be as improbable a subject aspossible to use, namely advertising,which will be considered as the

very first example, albeit quitesuperficially at this stage. However,

the reader may already see apossible benefit of the logisticalapproach, such as the generation of

a logistical language, a formulationof goals that would permeate all

divisions of the manufacturing firm,and the provision of qualitativeframeworks. We are among those

who believe that qualitative

analysis is important when it is notdone merely as a gesture. After all,

arent qualitative improvementsoften far superior to quantitative

ones? 2

Logistics everywhere :

analysis and the thesis ina nutshell

Having taken a vaguely reductionist

ap pr o ac h , w hi c h , l o o sel yspeaking, condenses logistics to

the optimization of certain flows,we had to alter our approach whenpassing from pre-SCM to SCM.Considering SCM forced us to refer

to product and information flows

rather than just to product flowswith regard to what needed to beanalyzed and then optimized. This

is where the yes and noanswers to the question of whether

or not SCM has brought a radicalchange to the field of logisticsmanagement converge. If one

believes that the flows referring toproducts in pre-logistics management

are essential, then one has to

consider SCM as a revolution.Otherwise, it becomes more of a

quantitative progress, where oneoptimizes over as many parametersas the available technologies

permit and as far as the efforts ofoptimization provide returns thatbenefit the shareholders.

The point of view we have adopted

and pushed to its limits as the basisof our thesis is that to some extent,the logistics management approach

can be omnipresent in the way onetackles all sort of problems, fromthose found in the sciences to

those encountered in management.Moreover, while restricting ourselves

to the issues covered in this paper,we believe that most, if not all, ofthe issues relating to decision support,

organization, processes and indeedeverything pertaining to the

running of the manufacturing firm,both as an individual entity and aspart of a wider web of networks,

can benefit from the language andmethods of logistics management.In particular, we believe that the

transition to SCM was mostly dueto the emergence of technologies

permitting the processing of biggerand bigger optimization problemsand the collection of more and

more information that could help in

the optimization process. But weintend to go much further and, in

what we think is a natural nextconceptual step, we propose to

tackle most other problems inmanagement as if they wereproblems in logistics management.

Once the other aspects of the life ofa firm, or of networks of firms, have

been dealt with in this way, weexpect that a large scale integration

of the scope of logisticsmanagement will take place, but wewill refrain from making any

attempt to do that here: the bricksmust be made before a wall can bebuilt. In fact, we will limit ourselves

for the time being to providing twoexamples that will hopefully shownthe broad community of people

interested in all aspects ofmanagement an illustration of the

sound basis for our ambitiousprogram. Our aim for now is torepresent certain classical problems

as examples of logistics. A widerange of expertise may be neededto describe how to manage these

logistical problems by themselves,even before the grand unification

across the board takes place. It maybe the case that the logisticalapproach only brings qualitative

changes to certain problems. Webelieve that this may still be quitevaluable, and we will begin with the

field of advertising that mayprovide one of the toughest challenges

to our thesis. We expect that if wecould stimulate even the possibilityof a discussion about advertising as

an example of logistics, it wouldprovide some justification for thevalidity of our proposal.

Before we get to the first example,

we want to state our belief that itwould be unfair to condemn ourapproach just because a disciplineonly permits a qualitative discourse,

and for instance, only qualitativeoptimization after being reinterpreted

as a form of logistics. In fact, evenin the most traditional applications

of logistics management, to reduceits impact to optimization in themost mathematical and formal

senses would be an importantmistake. Thinking about using

empty trucks for new services on


2. This is the idea defended notably by

Wil liam s (1986, 1990), where he indicates that

when confronted with combinatorial problemsthat are too complex, mathematical

optimization fai ls because the computing

power that w ould be needed is way beyond our

reach, and in some cases will be forever so

(the computation would last many tim es the

life of the uni verse with the fastest machi ne

that could ever be buil t). Mathematical

optimization must then give way to some form

of heuristics (which may then possibly use

mathema tics). Willi ams (1986, 1990) il lustrates

this point in the context of the Traveling

Salesman Problem alr eady mentioned. We are

indebted to John Tomli n for telli ng us about the

work of Paul Willi ams after this paper was first

circulated, and to Paul Willi ams for helping us

gain access to hi s work so quickly. Some of

Paul Willi amstheses do indeed seem rathersimil ar to ours, but he promotes a perspective

of optimization everywhere, a point ofview that now has many supporters, rather

than our position of logistics managementeverywhere, which m ight assume a smallereverywherebut seems to not have beenexpli citly advocated before.


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the return journey, or imagining newshapes of parts to improve packagingby allowing much better weight-to-

volume ratios are just someexamples of how qualitative inputs,

that are facilitated by formulating theright problems, can have dramaticimpacts. Therefore, the strategy

which we propose to use in order toshow the benefits of our thesis innew disciplines is to map the

principles of logistics managementas completely as possible to the new

discipline (or vice-versa), and inparticular, to try to make an earlyidentification of the quantities that

need to be optimized and of theconstraints that are to be found.

Advertising as an exam pleof logistics

In order to represent advertising as a

logistics problem, one needs to thinkof: (1) the message as the equivalentof the product to be transported; (2)

the minds of the people who are thepotential customers as the points of

delivery (e.g., for certain products

for which a recognition is sought

beyond the existing customer base),and (3) the advertising media as the

vehicles of transportation. Of course,it may be appropriate to distinguishbetween the message that was

intended and the message that wasreceived. This is good news for us! Infact, we interpret this example of

discovering a natural distinctionbetween messages as being aninstance of a phenomenon that we

expect to encounter quite often.In the case at hand, thanks to such a

rethinking, the intended messagebecomes the product to be delivered,

while the slogans, trademarks, etc.,become the package. This may haveimplications regarding the relativeimportance of the elements which

constitute the problem and forthe ways they are dealt with. Oneshould remember that in complex

logistical problems: those that arenot examples of simple linear

optimization problems, substantialchanges in approach are sometimesnecessary before one can proceed

with any form of systematicoptimization. For instance, building avery expensive new road may be the

best solution in certain typicallogistical problems. We leave thedescription of any novel advertising

solutions to the experts, but existingpractices such as advertising during

the Super Bowl or the World Seriesmight be considered as theadvertising equivalent of that sort of

expensive road building. We willdevote the next few lines toexamining whether one can identify

constraints and objective functionswhich would permit a more effective

mapping of advertising to thelogistics framework. Essentially, wehave shown so far that the parallels

exist, but to little commercial or evenconceptual advantage. Further

consideration reveals that we may

need metrics to even start viewingadvertising as a case foroptimization.

Arriving at a point where metrics can

be used may be the hardest task eachtime one wants to seriously applylogistics management methods to a

new discipline. If performances ofthe whole system are the onlymetrics that are easy to apply, then

empirical trials are a possible meansto derive benefit from thelogistical/optimization approach. For

instance, the methods found inexperimental economics could be

used, permitting the measurement ofthe performances of logisticsmanagement methods in a new

discipline. Then, the correlation ofthese measurements to acceptedsigns of success could be evaluated.

However, there might be cases, withadvertising being possibly one of

them, where one should not be tooambitious to begin with, and insteadbe content with using a logistical

perspective to help teach andotherwise communicate aboutcertain fields of human thought or

activity, (although Remark 1, below,is much more optimistic). We may

also find that in cases where tasksare accomplished instinctively, butwhere hard decisions also have to be

made at times, the language oflogistics might allow experts andprofessionals to better formulate

their responses to the questionswhich confront them. It also seems

reasonable to expect that unifyingthe language will help communication

within the firm as well as betweenfirms.

From know ledge management

to logistics

Knowledge management (or KM), asit is known, at least in the circles of

information technology (IT), whereeverything of any importance isreferred to by an acronym, is an

interesting field. Facilitating accessto knowledge when it is neededfor the good of the firm or to

benefit humankind, or even moreambitiously, to help generate the

knowledge needed to solve

previously unsolvable problemssounds like an impossible dream.

Who would not want themanagement of knowledge to work

Conjecture: A fundamental

reinterpretation of a problem as

a logistical issue should often

necessitate a rethinking of

its definition in order to map the

discipline in question to a

f ra me wo r k o f l o g i s ti c s

management. Such attention

devoted to the mapping of the

problem would improve the

benefits of the logistical

approach.

Remark 1: As mentioned

previously, we have learned ofwork that uses optimization

techniques to improve the

distribution of advertisements on

the World Wide Web (see, for

instance, Langheinrich et al.

[1999], and Tomlin [2000]). John

Forrest told us that he was involved

in trying to use optimization

techniques to distribute advertising

in the UK as early as 1967.

Magazines were the vehicles used

for the advertisements in question,

but the results were unsatisfactory,

probably because of the limited

power of the computers available

at that time. This work was not

preceded by a full reformulation of

the advertising problem in terms of

logistics management, but it

certainly helps support the idea

that our proposed approach most

probably has a direct commercial

value in addition to its

philosophical implications and to

the way it may facilitatecommunication inside the firm and

between firms.


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better? KMs place in the toolkit of

the trend setting executive probably

disappeared in 2001, after enjoying a

period of tremendous popularity.

This followed the publication of two

books in 1995 whose titles signaledthe initial hopes for the success of

the new field: The know ledge-creating

company (Nonaka and Takeuchi,

1995), and Wellsprings of k nowl edge

(Leonard, 1995).

A snapshot of how the field evolved

can be seen in the reprinted

collection of some major

management articles on the subject

of KM (Harvard Business Review,

1998), starting with an early article

by Drucker (1988). The author

claimed that within twenty years, thetypical (large) business would

be knowledge-based. Contemporary

with that review, let us also mention

the monograph Working knowledge

(Davenport and Prusak, 1998). Most

contributors to the KM literature

were also the people who benefited

most directly from KM, e.g., through

conferences, consulting, or teaching.

This may explain why, during its few

years of intense success, KM

depended, not only, as was often

stated, on cultural factors, but alsoon the models for national politics

and economics, the attitudes of Wall

Street, on whether long term success

was expected from the firm, on

whether or not the firms that paid

most for KM consulting had a

strategy which looked beyond the

end-of-quarter bottom line, the

morality in corporate board rooms

and more factors of this kind, which

were mostly hidden from view.

At least one other element thatwould have helped cement the place

of KM has been ignored: namely, an

effective and authentic form of

artificial intelligence (AI). As we will

see, this more than anything else

explains KMs fall from grace (while

less ambitious sub-disciplines such

as unstructured data analysis began

to flourish). A logistical approach

leads us to rethink what should be

the fundamental concepts of KM, as

we shall describe in the first

paragraph. In the second paragraph,

in terms of what we consider to befundamental concepts, we shall re-

examine the usual building bricks of

the KM discourse: data, information,

and knowledge. Then, in the third

paragraph the logistics approach is

explicitly invoked, although we

consider that the approach has

already been beneficial in the way

the logistical perspective conditionsthe whole problem (see Remark 5

below, in particular).

Fundame ntal concepts

The basic objectives of KM first need

to be defined. The list can be

extended, but it has to contain the

following three elements, to which

we will restrict our analysis: data,

information, and knowledge. Indeed,

several authors also recognize that

some classification of these three

basic elements is a necessaryprerequisite to any serious

discussion. Our approach is to

consider that these three elements

are not fundamentals, but refer to

some real or also perhaps to some

virtual or imaginary universe. We

also consider that these elements

depend on who attempts to describe,

understand, exploit, improve, or in

general transform such a universe,

and for what reasons. The underlying

rationale for this is that we are

not only interested in the worldo f b u s i ne s s , b u t a l s o i n

interdisciplinary issues (even if we

are not considering the physical and

natural sciences in this paper). The

importance of data, information and

knowledge is not restricted to the

business world and we want to

comprehend their wider significance.

Here are the elements we consider

necessary to define the basic

concepts that need to be governed

by KM:

World elements. These compriseobjects (including living entities

and people), or at least the

objective aspect of them, which in

some cases may be all that is

accessible or necessary. Also

included are entities that allow a

spatial description: (1) reports or

stories that need space-time

descriptions, with a specific time

span, (2) events or records of

events which are essentially

instantaneous, and (3) a mixture of

the above, which might be needed

to describe a personality, forexample.

People and groups. Groups have

concurrent interests, but people in

groups may also have divergent

interests, some supporting thegroups goals and some quiteindependent of them. There may

be neutral entities, and groups orindividual whose position is wellestablished but unknown to some

or all of the other parties. Groupsusually come with explicit

structures that are partly orcompletely hierarchical, althoughsometimes these may be hidden.

Cultural models. These includepolitical trends, opinions, public orsecret agendas, etc., which directly

condition the ways of thinking and

the actions of both the sending and

receiving parties. Messages sent and received . It is the

communication between partiesthat allows them to develop theirinterests in a particular direction.

Messages should also bedistinguished according to theirformal contents, intended contents

and perceived contents. Scales. This refers to the scales,

precision levels, and/or granularityat which one expects tounderstand a problem.

Revisiting data , inform ationand know ledge

At this early and fundamental stage

of the logistical approach to KM, wefeel that from the above list, the

world elements and scales are thecrucial dimensions on which to base

the analysis. This explains why weplace so much emphasis on the pairWeS (World element, Scale). A strong

indication of its importance is thefact that we believe it allowed us toarrive independently and quickly at

concepts central to KM, whilebringing to light ideas which may go

beyond what has been done before.

The data set attached to a WeS is the

collection of everything that isrequired to provide a full

Remark 2: Already, the reader

will probably detect some effects

of logistical thinking in the above

list of basic concepts: a reflection

of the desire to describe the

problem in terms that facilitate its

mapping to the framework of

logistics.


8/11


description of the world element inquestion at a given scale. A dataelement, data point, unit of data, or,

sometimes-just data, is an atom ofdescription. For instance, a stockname, a time and a price say

$102.23 of the Alpha stock at thattimeforms a data set, in fact a data

set of a special kind, as it fullydefines a WeS. In this example, theprice ($102.23) is a data point.

However, the digit zero is not data,while the collection (0, third digit indecimal notation) is data, of limited

value, which is contained in theprice.

A more ordinary data set, as it isdifferent form the WeS, is attachedto a bottle of milk at a macroscopic

scale. This data set comprises abottles shape, the volume it

contains, the volume it is supposedto contain, its condition andcleanliness, whether or not the

closing device is intact, theproduction date and the expiry

date. To this, one could add anydescription of the product (e.g., is it

regular or low fat?), the quantitiesof nutrients, the nutrients listed onthe bottle, the region of provenance

of the particular batch of milk inquestion, the findings of theveterinary examination of the

cows, an assessment of theveterinarians competence and of

the competence of the person

responsible for evaluating theveterinarian, the historical basis for

trusting the judgment of the

veterinarian, etc., and the list isprobably far from complete!Information has several meaningsthat should be clearly differentiated.

Firstly, it is possible to analyze it asa collection of data intended

(by those who select and/or

communicate it) to provide usually

partial, but sometimes full,knowledge about a WeS. Therein

lies a strong cultural dependence.One can also see it as a collection ofdata that is thought (by those who

receive and/or use it) to providesome, again usually partial, butsometimes full, knowledge of a WeS;

and therein also resides a strongcultural dependence. In addition,

information is presented primarilyin the form of a message, or moregenerally, in the form of a vehicle to

store or communicate knowledgeabout a WeS.Finally, when it becomes knowledge,

information can be split into twotypes, passive knowledge (PK) and

active knowledge (AK), a division

that could be the first of further orconcomitant dichotomies as we will

soon discuss:

The PK of an individual or of agroup is the set of data and

information that can be used bythis individual or group. Some ofit may be inaccessible to anyone,

so long as its existence is knownand provided it can be retrieved

when needed; Implicit PK is the knowledge that

could be generated from a given

data and information set. Thisknowledge may be arrived atvery easily or possibly only after

very detailed analysis;

AK is knowledge that can helpdecide, act on or generate new

knowledge.

The three concepts of data,

information, and knowledge as wehave developed them so far are

considered in a different way to theorthodox KM approach. Remember

that we have taken the statement ofDrucker (1988) to be a lemma,

instead of a definition, which is astrong argument in favor of our

approach. The following dichotomybetween tacit and explicit

knowledge is, on the other hand,pretty much central to the

development of KM in the 1990s.The notions of tacit knowledge

versus explicit knowledge wereintroduced by Polanyi (1983) in the1960s, and used by Nonaka (1991)

and Nonaka and Takeuchi (1994,1995) to formulate a theory of

organizational learning aroundthe theme of the conversion of

knowledge between these twoforms. To us, these notions appear

more obscure than but essentiallyparallel to AK and PK, although this

may not be the case for KM expertswho have worked with them for along time.

Calling logistics to the rescue

We want to demonstrate that thelogistical perspective helps gives

KM some structure, and that thispoint of view gives a clear

indication as to why KM failed (orat least has failed so far). What we

really hope for is to help breathenew life into KM (whether or not its

name remains the same), as webelieve (and everyone agrees) that

the management of knowledge willbe essential in years to come, be itonly because so many firms

accumulate massive quantities ofdata and information, often

accompanied by massive quantitiesof knowledge. It is clear that those

who are the most able to make useof some of these commodities will

have a decisive advantage. So wefirst need first to ask the

fundamental question What iswhat? in order to map standard

logistics to KM. Such a mappingexercise should be a basicrequirement for any new incursion

of logistics into the intellectualworld, and it will often be

Remark 4: Receiving any

information changes the degree

of knowledge about a WeS,

possibly to the extent of

revealing the previously

unsuspected existence of that

WeS, or of any type of that

particular WeS. Information can

also change comprehension,

and further high functions of thebrain, but we will make every

effort to avoid discussing such

matters here.

Remark 5: According to

Davenport and Prusak (1998:2),

the remark that information is

data endowed with relevance

and purpose can be traced at

least as far back as the paper by

Drucker (Harvard Business

Review, 1998) that we have

mentioned previously. We fully

agree with Druckers statement

(1988). However we consider it

to be a lemma, instead of a

definition, as we think it fits in

logically with the definitions of

data and information we have

provided.

Remark 3: No one will

probably ever need, nor ever

be able to determine the data

set of any WeS except for

simple ones such as those

given in the first example.


9/11


necessary to repeat the exercise,sometimes frequently, when trying tointensify the logistical approach. As

well as understanding the logisticalequivalents in the KM field, it will

also be necessary to do this for eachnew field. Here are some elements ofthe mapping:The goods: the data, the

information, and more generallyany element pertaining to

knowledge (some have expirationdates, others long-shelf lives);

The shelves: the heads ofpersonnel, at various levels in the

organizations hierarchy; Other shelves (for goods with long

shelf-lives): the vehicles for the

transmission of knowledge, i.e.,items that contain it;

The packages: the form in whichdata, information, and knowledge

will be stored, retrieved, and shared

or used in some form or another;

The transport vectors: the variousmeans to transport or transfer

knowledge, from lectures tovideotapes and training, etc.

Next, we shall look at the

optimization problem(s) that mayoccur with the elements that are the

equivalents of traditional logisticalentities according to the mapping.

Then, if not sooner, we must

consider the objectives of the

companies involved, the nature ofthese companies, the economic

system to be used, etc. Somequestions arise simply as a result of

trying to discover the companysobjectives as in any logisticalproblem; for instance: Is the firm only working for the

shareholders; is it a familybusiness built to last a few

generations or something inbetween?

Are there any ambitious goals, or isthere a non-financial/non-economicagenda that also needs to be part

of the objective function design?

Does it operate in an environmentof harsh, unadulterated capitalism,or in a more socially oriented

environment? Is the company only interested in

the end-of-quarter bottom line? Ifnot, what are the firms otherpriorities?

Are the long-term aims establishedonly for the sake of credibility andto defend short-term stock price,

or is there a genuine long-termstrategy?3

Depending on a combination of

choices and constraints, an obviousquantity to be optimized could besomething like the profit, the

efficiency, or the long-term averaged

profit of the company. However, athorough consideration of the large-scale components of the objectives isnot enough to help, or to justify the

existence of KM: the personalobjective functions of people in thefirm have to also be taken into

account. In fact, not everyone maywant all knowledge to circulate

freely, especially if freely also meansfor free (i.e., free from benefits to thesources of knowledge). Let us now

mention a fact that is worthy ofconsideration: everyone is happy to

receive knowledge, if they are notobliged to prove how that knowledgewas acquired. However, being a free

source of knowledge may bedangerous, besides being potentiallypainful and unrewarding. It will be

essential to figure out the rightmetrics, rewards, related incentivesand deterrence systems in order for

things to evolve properly.4 So webelieve that the merely thinking in

terms of logistics managementwould bring considerable

improvements to the design of KMstrategies.

What KM seems to have mostseriously failed to fully acknowledgeis that the movement or transfer of

some forms of knowledge, especiallyof the tacit or active kinds, either

from brain to brain, or from brain tomachine (to brain), may range fromdifficult to impossible given current

capabilities and constraints. It alsomay be too costly (and cost becomes

a more obvious issue when one deals

explicitly with optimization issues).Too much of the KM literature has

very strongly advocated that there ismuch more to knowledge than just

data, information, and passiveand/or explicit knowledge. In doingso, the KM gurus have set impossibly

high expectations by promptingpeople to expect much more from

the field than is realisticallyachievable, given current constraintsand limitations. This issue, which

stands as an obstacle to the successof KM, is of course related to an issuementioned previously, namely, the

lack of an explicit description of theobjectives of the companies

involved.5

We believe that no serious

improvement can be made in themost significant aspects of KM before

major progress is seen in the field of

AI. This statement, in fact, seemsalmost superfluous, as it is

knowledge handling, and thereforesomething similar in nature tointelligence that we are talking about.

However, before AI makes realprogress, advances in KM can be

achieved by lowering expectations,and this is happening right now(often using dilute forms of AI such

as automated text analysis to theirmaximum effect given currentcapabilities. Another example is that

many tools have been developed thatallow the employee to find out useful

information about their own firm andabout global issues (mostly using theInternet). Most of this progress on

the effective management ofknowledge is not made under theumbrella of KM.

The packaging of information has

indeed begun to happen usingtechnologies such as the extendedmarkup language (XML), and we

expect that the combination of XML

and modern search engines,combining basic search,

categorization and prioritizationfunctions and substitutes with

3. One expects affordabi lity to be a necessary

conditio n for the firm to seriously consider long

term i nvestments, but it should not be the sole

factor.

4. This has certainly been understood by some,

although it is, to say the least, often very well

hidden in the KM literature.

5. For instance, the more the fi rm car es only

about its shareholders, the more it considers itsemployees as commodities, and the more

anxi ous it is to extract tacit knowledge from

these employees, then the difficulty in

managing thi s aspect of know ledge becomes

greater.

Remark 6: Some firms (e.g.,

technology companies) create

knowledge as value per se, others

create knowledge mostly as a

means to improve the production

of what the company manufacturesor sells (e.g., know-how, work

methods, controls, workflows,

etc.).


10/11

semantics, could now permit theefficient mapping of the

management of routine butessential knowledge to logistics.

Examples of such knowledge couldbe the identities of accountholders, how the damages on cars

rented for business are covered,who in the company is qualified tospeak about a particular aspect of

strategy, etc. The basicclassification of knowledge that we

have proposed, and the concept ofWeS in particular, will help in thisprocess. With the passing of time,

AI or related concepts will continueto develop, allowing, for instance,the better handling of unstructured

information.6 These improvements

allow complex mappings fromlogistics management to KM to beperformed. It is also clear that theissues in information handling have

already become so complex thatoptimization of this handling has

begun to help, and in fact is nowvital. The issues we haveexpounded in this discourse have

certainly started being usedimplicitly, as the recent progress inmilitary logistics cannot be

explained in any other way. Thisbrings us back full circle to where it

all started from.

Conclusion

For about twenty years, logisticsmanagement has undergone

important developments, both inmanufacturing and retailing firms.

At the same time, it has benefitedfrom a universally acknowledgedacademic recognition, as

corroborated by the proliferation ofinternational conferences and

specialized journals. Europe has, inpart, caught up with the USA, inparticular through the

development of organizationalinnovations regarding products andinformation flows management.

Today, the leading logisticalstrategies seem to be universalisticin nature and some authors are not

afraid to assert that there isundoubtedly one best way to

develop a sustainable competitiveadvantage. Somewhat provocatively,

this paper is aimed at showing that

logistics management is evenbroader in its application than

most, if not all, observers have

dared to propose so far. It offers away of thinking that, in terms of

logistical language, vision andmethods will allow us to

comprehend and solve managerialproblems that may be quite farremoved from the traditional field

of logistics management.

The position developed here might

have been operationallyunworkable until a few years ago

before the computing revolutionbegan, but it is hard to believe thatit will not bear fruit in a world

where the handling of informationhas evolved and improved to suchan extent. Hopefully, the rigid

treelike organizations will be

rearranged into more reasonableand supple structures or intoframeworks lacking rigidstructures using modern

communication methods to moreeffectively perform the roles ofcommunicating information,

knowledge, commands, andfeelings. To some extent, logistics

may help to redesign the veryorganization of the firm, if onefollows the practical implications of

our thesis. Of course, one does notneed to believe that logistics is

everywhere in order to hope forthis to happen (see, for instanceEvans and Wurster [2000]), but we

do believe that this point of viewwill help those involved by allowingthem to consider from a fresh

perspective the challenges theyface today and will face in the

future.

We cannot end without mentioningthat the Integrated Supply ChainManagement (ISCM) that IBM has

adopted, with earnings of $5 billionin the first year of implementation,goes a long way beyond SCM, evenif it still falls short of the ultra-global vision of logisticseverywhere that we advocatehere. The new view of logistics thatISCM represents is now wellaccepted, assuming, in short, thatlogistics is almost everywhere andin any event, is much moreimportant than ever before. Aftersharing its experience with itsmajor customers, IBM is already

proposing a properly scaled-downversion of ISCM to SMEs under thename of Integrated Supply ChainSolution.


6. Some observers argue that anything thatresembles AI is AI, so that, fo r i nstance, speech

recognition i s AI. Although we have taken the

opposite point of vi ew merely for the sake of

clarity, we wil l not enter into thi s debate, whose

outcome has no impact on our thesis.


11/11

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