or and decision aidingbouyssou/orp3_bouyssou.pdforp3 – september 2005 – 4 some unanswered...

ORP3 – September 2005 – 1

OR and Decision Aiding

Denis BouyssouCNRS – LAMSADE

Some (personal) thoughts on our field and its future


Operational ResearchYoung discipline

ORQ, Vol. 1, n° 1, March 1950Many scientific and practical achievements… butA discipline not without problems…

Without pressThat has not worked on its historyThat has been vigorously attacked

The future of Operational Research is past, JORS, 1979, R. L.Ackoff: “In my opinion, OR is dead even though it has yet to beburied”

That started as being applied and interdisciplinary andevolved differentlyGame Theory, Decision under uncertainty


Some Unanswered Questions

What is OR?What does it mean to be interdisciplinary?What does it mean to be an applied science?Does this call for a specific epistemology?

How to teach OR and train OR analysts?What should be the standard curriculum in OR?

Should we remain isolated or try to ally with some sisterdisciplines (Computer Science, Statistics, Management, etc.)?

ROADEF: around 200 members

Should OR societies try to organize the profession?“Labeled” OR consultants?


Outline

A view on OROR in historyWhat to do?


Outline



OR main modelBuild and solve models of the type

Solving:Finding an optimal solutionFinding all optimal solutionsFinding solutions “close” to theoptimal solutionsFinding robust solutions

How are such models built?What is their relation to realdecision processes?


Example

Workforce Scheduling at Aéroport de ParisHigh cost of laborStrong unionsMany legal and technical regulationsDemand highly variable throughout timeHighly competitive industry

One category of persons“bagagistes”persons taking care of luggage from planes to customers


0

20

40

60

80

100

1205 6 8 10 11 13 15 16 18 20 21 23

Demand Curve (normal weekday)


Classic problemCover demand with a minimum of operators


Solve the problem

Minimiser x

s c

a x C t T

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020406080

100120140

5 6 8 10 11 13 15 16 18 20 21 23

An optimal solution


“Data”

Definition of candidates shiftsImplicit Constraints

Legal / Union agreements / Habits / ConvenienceHard / Soft constraints

Dealing with perturbationsIllness / Late / Strikes / Overload

In practice?Who decides? When?Affectation of shifts to persons (auctions, seniority, etc.)?

Days / Weeks / MonthsOne model or several models?Combination?


“Data”

Demand curveHow is it built?

Implicit Rulestype of plane × destination × time of the day

Implicit StandardsQuality?What is an acceptable waiting time?

Coping with uncertaintyLate planesChanges of planes


What is the “problem”Why is it raised now?

MalfunctioningOpportunity

What objective(s)?Increased productivity?

How to share the gains?Negotiations?

Possible ShiftsTimetable of fights

ImplementationWho handle the problem?How is it handled?

Who will use the model?How often?To do what?


Use of optimization modelOptimal solution is not necessarily central

Many unforeseen constraintsMany constraints difficult to modelHigh uncertainty / Many implicit aspectsMultiple heuristic adjustments of the solution

Model as an exploration toolcurrent practices / frontiers of system / objectives

Indirect use of modelPossible, frequent and legitimateModel as a tool to understand and/or dialogue

Necessary contextualization of solutions outside themodel


In summary

OR analysts have a very naive strategy ofinterventionOR has no specific doctrine of implementation


Strategy of the OR analyst

Faced with the complexity of real decisionprocesses and organizations, the answer of the ORanalysts is essentially pragmatic et non-formalized

Workforce scheduling (what to formalize and what toleave outside the model?)

Two “heroic” hypothesesIt is possible to have a positive role in organizationsusing a decision model that is essentially individual(optimization)Use “common sense” and “know how” to deal withimplementation issues


Doctrine (lack of)

OR is an applied science…But OR analysts have not elaborated a doctrine ofintervention let alone an autonomous discourse onorganizations

How to justify the naive strategy?How did we react to the transformation of organizations?What have we learnt on organizations?How to train OR analysts

Supply chain, IS, Marketing, Strategic Management


Outline



OR is not an isolated caseAim of OR

put reason and efficiency in the conduct of humanaffairs

Scientific Management (1910)OR (1950)Strategic Management (1960)Expert Systems (1970)MRP (1980)Supply chain Management (1990)Knowledge Management (2000)


Models as “rational myths”

Unavoidable conflict between the logic of the modeland the logic of the organizationThe model is a porte d’entrée in the organization anda lever for change

OR models are good for doing so because they are rationalmyths

Myth: “Symbolic fable that is both simple and striking”Rational: “Performance” + high internal consistency

Models used unfreeze and recompose organizationalstructures

Learning / Contextualization / Implementation

Hatchuel & Molet, 1986, EJOR


What does this view bring to OR?

Historical perspectiveSuccesses and failures of other rational myths

Doctrine: modeling and interventionModeling process

LearningConstructivism

ImplementationNot always requiredBeware of “compulsive implementation”


Anatomy of a “rational myth”Rationalization project: 3 main components

Formal structureWhat is the underlying logic?

Management perspectiveWhat aspects of organizations are concerned?

Simplified view of organizationsWhat is the implicit view of organizations?

ORFormal structure

Pure decision theoryManagement perspective

Rationalize decisionsOrganization

Organizations as collections of decision makers


Management perspectives:Evolution of rational myths

Work : TaylorDecisions : ORCosts : AuditMarkets : Strategic ManagementData : EIS / Data MiningFlows : Supply chainQuality : TQMProducts : ECRKnowledge : AI / KM?? : ??


OR in context

OR is part of a long history of “rationalizationprojects” in organizations

Competition between “rationalization projects”We may and should learn from other fieldsThey should be able to learn from our field

What to do?


Outline



Short termPay attention to competing “rational myths”

IS, Supply chain, TQM, AI, ECR, Data Mining, etc.INFORMS vs. EUROERP and OR

Work on history of OR

Pay attention to the evolution of organizationsDoctrine on organizations1st step: Who asks for OR?

Legal evolutions (deregulation / privatization)Technical evolutions (transports / NICT)

Classic techniques/models do not define ORThe nature of the rationalization project should govern the choice oftechniques


Short termBe proactive: “We know how to handle that”

Prevention of industrial risksEvaluation of public policiesElectoral reformsSecuritySocial Security reformsGlobalizationClimate changeetc.

Or do we want to leave that to others? (economists,political scientists, sociologists, etc.)

Are they really better equipped than we are?


OR’s competitive advantages

OR survived fashion effects50 years of experience

OR remains close to production processesScientific developments

Global Optimization, Heuristics, Complexity, Polyhedralanalysis, etc.

Prestigious journalsManagement Science, Operations Research


Long Term

Formal structure: Pure decision theoryManagement perspective: Rationalizing decisionsOrganizations: Collections of Decision Makers

Theoretical challengeWhat is the present state of decision theory?

Practical challengeIs decision the right concept?


Pure decision theory

The very idea of a “rational behavior” undergoes amajor crisis in decision theoryGoing from individual to collective model is aformidable challenge


Independence axiom

z1

1/2

1/2

x

y

is preferred to

If

then (for p > 0)

is preferred to

z

k

p

1–p

1/2

1/2 x

y

k

p

1–p


Independence axiom: Mom’s choice

Peter1

1/2

1/2

Peter

Mary

Preferred to

1/2

1/2

Peter

Mary

Preferred to

1/2

1/2 Mary

1/2

1/2

Peter

Mary

BUT


(1 ; 1)

A

B

(0 ; 3)

(2 ; 2)

Games with perfect andcomplete information

(1 ; 1)

[A ; B]


There are other possible and interestingmanagement perspectivesThe bulk of management literature is not aboutdecisionsIt is not at all obvious that “decisions” are centralany more in organizations

Rationalizing decisions?


How CEO spend their time?15 % transports5 % visits5 % individual meetings30 % internal collective meetings10 % external collective meetings10 % meals15 % telephone5 % mail2 % writing2 % reading1 % thinking alone (6 min /day)0 % computer usage

20 %

55 %

25 %


Rationalizing collective action

Deciding

StructuringPlanningCoordinatingControllingInventing incentivesContractingManaging risks


Possible (necessary?) widening ofOR’s rational myth

What decision should I take?How to

Be organizedCoordinate with othersPlan while remaining reactiveControl resultsManage risksRemain informed

in order to be efficient?


Possible New Key Words

ProductionConception / Quality /Environment

PlanningControl / Incentives /Contracts

SchedulingEquity / Motivation /Robustness

MarketsCompetition / Pricing /Strategy

TransportsSustainable development /Spatial equity

Rationalizing collectiveaction

Politics

or and decision aidingbouyssou/orp3_bouyssou.pdforp3 – september 2005 – 4 some unanswered...

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