WHOLE SYSTE

WHOLEEARTH

MODELS &SYSTEMS

by Donella H. Meadows

WANT to describehere just one para-digm or way of look-ing that reveals just

some aspects of reality. I do notbelieve it is the right or bestway, since I cannot settle onany one way as right or best.But it is a perspective that isunfamiliar and thus revealingto most people. And it is, Ibelieve, a useful way of lookingat some of humankind's mostpersistent problems - hunger,poverty, environmental degra-dation, and war - problems thatdo not seem to be solvable whenlooked at from older and morefamiliar viewpoints.

This paradigm has many names.I will call it the "systems para-digm," knowing that the wordsystems has disparate meaningsbut intending to clarify what Imean primarily through examplesthroughout this paper.

I will begin with what might beconsidered the state of the art -the seven complex computermodels of the global system thathave been constructed and

documented so far. I willdescribe how the world systemlooks when it is seen from thecomprehensive and sophisticatedviewpoint of those models.Then I will backtrack to the verybeginning, to what any school-child can see and know aboutcomplex systems and to thekinds of examples I use to teachsystems thinking. Having com-pleted the introductory course, Iwill progress immediately tomore advanced but still com-puter-free systems insights thatany adult can carry in his orher head to deal with the persist-ent, system-dependent malfunc-tions of a complicated society.And finally I will come back toan overview of the entire planetand speculate on how it wouldbe different if more of itsinhabitants saw it from asystems point of view.

The Globe as Seen throughComputer Models

To most people the wordsystems implies massive com-

puters containing vast arrays ofinformation about everythingthere is to know. But the firstwell-known computer simulationon a global, long-term scale wasin fact relatively simple. It waspublished only about ten yearsago by M.l.T.'s Jay Forrester.iSince then seven other widelyrecognized "global" modelshave been completed, with atleast 20 more still under develop-ment. Sore major characteris-tics of the completed models aresummarized in Figure 1.

As you can see, global modelshave been made in many parts ofthe world, using many differenttechniques, to answer quitedifferent questions. Even witha computer a modeler is severelylimited in the amount of infor-mation that he or she caninclude, and each of thesemodels contains only a fractionof what is known about theworld. Most of them focus on

1. Jay W. Iorrcstcr, World Dynamics,MIT Press, Cambridge, Massachu-setts, 1971.

To my surprise it appears that systems and computer modeling lore is moving rapidly beyond smart toward wise. Acoauthor of the famed The Limits to Growth (with Dennis Meadows and Jay Forrester), Dana Meadows gave thispaper at an education and environment conference in Budapest. Hungary. in November 1980. Site updated thematerial for CQ and at our request expanded the systems-perversities section at the end. For still further expansionsee her new book Groping in the Dark (The First Decade of Global Modeling), coauthored with John Richardson andGerhart Bruckmann; $29.50 postpaid from John Wiley and Sons, One Wiley Drive, Somerset, NJ 08873. TheMeadows family works a small farm near Dartmouth College, New Hlampshire, where they also teach. -Stewart Brand

317 THE CoEVOLUTION QUARTERLY SUMMER 191298

I

* About one-fifth of the complete diagram of a computer-model ofthe world. This one, from Forrester's World Dynamics, showsnegative loops which adjust population levels to the maximumnumber of people who can survive their own pollution.

Figure 1CHARACTERISTICS OF GLOBAL COMPUTER MODELS

Model Institution Where Major Modeling Basic Problem Principal References.- Constructed Technique Focus

MassachusettsInstitute ofTechnology (USA)

WIM (WorldIntegrated Model)

Latin AmericanWorld Model

MOIRA (Modelof InternationalRelations inAgriculture)

SARUM (SystemsAnalysis ResearchUnit Model)

FUGI (Futureof GlobalInterdependence)

United NationsWorld Model

Case WesternUniversity (USA) andTechnical University,Hannover (FederalRepublic of Germany)

Fundacion Bariloche(Argentina)

Free University ofAmsterdam andAgriculturalUniversity ofWageningen(Netherlands)

Department of theEnvironment (U.K.)

Tokyo'University,Soka University(Japan)

New York UniversityBrandeis University(USA)

System dynamics

Multilevel hierarchicalsystems theory, com-ponents includesimulation, input-output, econometrics

Optimization

Econometrics,optimization

Simulation, systemdynamics,econometrics

Input/output,econometrics

Input/output

The pattern ofapproach of thegrowing populationand economy to thelimited physicalcarrying capacity ofthe planet

Global interdepen-dence, populationand economic growth,resource depletion

Maximization ofbasic human needs,improvement ofquality of life ofthe poor

World food tradepatterns, policies toeliminate hunger

Consequences of andstresses on economicdevelopment

Co-development ofindustrial andindustrializingeconomies

Effect of develop-ment policies onequity and theenvironment.

Forrester, WorldDynamics, MIT Press,1971. Meadows et al..The Limits to Growth,Universe Books, 1972.Meadows et al., TheDynamics of Growth ina Finite World, MITPress, 1974.

Mesarovic & Pestel,Mankind at the TurningPoint, Dutton, 1974.

Herrera et al., Catas-trophe or New Society?,International Develop-ment Research Centre,1976.

Buringh et al., Compu-tation of the AbsoluteMaximum Food Pro-duction of the World,Wageningen, 1975.Linnemann et al.,MOIRA - Model ofInternational Relationsin Agriculture, North-Holland, 1979.

Roberts et al., SARUM76 - Global ModellingProject, UK Depart-ments of Environmentand Transport, 1977.

Kaya et al., Future ofGlobal InterdependenceIIASA, 197k

Leontief et al., TheFuture of the WorldEconomy, Oxford, 1977.

All-Union Institute forSystem Studies (USSR)

WissenschaftszentrumBerlin (FederalRepublic of Germany)

GLOBUS

Effect of social andpolitical factors onglobal development

International relations,trade, and conflict

(still in progress)

(still in progress)

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World 2World 3

economic factors, population,and agricultural production.Only two of the seven containany mention of resources or theenvironment. None say anythingabout war, politics, new ideas, ornatural disasters. Most assumeeither that technology does notchange or that it changes auto-matically, exponentially, andwithout cost, to allow more andmore to be produced from lessand less. Some of the modelsrepresent the world as a singleunit, others divide it into 10 to15 regions or as many as 106separate nations. Some run intothe future as far as the year2100, others only to 1985.Several, especially the first ones,have been highly controversial,and some of the later modelswere made expressly to refute orimprove upon earlier ones.

I am introducing you to thesemodels to make several basicpoints that are often misun-derstood by a public that iseither too easily awed or tooeasily cynical about computertechnologies.

I The models are highly diverse.They were made by peoplewith different political andcultural persuasions and allare extremely biased, but invery different ways. There isno such thing as an "objec-tive" socioeconomic model.

2 Simultaneously, the modelsare tremendously compli-cated in what they represent(detailed population agestructures, multiple econom-ic sectors, complex tradepatterns, various incomeclasses) and surprisinglysimplistic in what they omit(armaments, capital agestructures, nearly all values,motivations, social norms,political structures, thesources and sinks of mostmaterial flows).

3 No model is (or is claimed tobe) a predictive tool. At besteach one is a very explicitmathematical rendering ofsomeone's view of the world,tied down as much as possiblewith statistical data, logicallyconsistent, and able toproduce statements of thissort: "If all these assumptionsare correct, complete, andextended into the future,

100

The modelers themselves, who generallystarted out hostile and critical of oneanother, have been surprised at the extentto which their conclusions overlapped.

then the logical consequenceswill be..."

To me these models are instruc-tive not singly but as a set. Al-though they were made bypeople of different continentsand ideologies, the nature ofthe exercise forced those peopleto a similar and not-very-ordi-nary viewing point. All werelooking at the globe as a wholeand at the relatively long-termimplications of the interconnect-ing web of population, capital,and economic production thatlinks all nations. All were im-mersed in the global statisticsand had to construct a modelthat captured the global situa-tion with fullness and consist-ency - every seller must have abuyer, every birth must eventu-ally be matched by a death, onceproductive capital is in place itcannot shift its purpose from atractor factory to a hospital.Despite many differences inemphasis and detail, viewing theclosed system somehow pro-duced some basic findings thatare common to every one of themodels. The modelers them-selves, who generally started outhostile and critical of oneanother, have been surprised atthe extent to which their conclu-sions overlapped. The followingstatements would be agreedupon, I believe, by everyoneinvolved in global modelingso far: 2

1 There is no known physicalor technical reason whybasic needs cannot be sup-plied for all the world'speople into the foreseeablefuture. These needs are not

2. The list is taken from Groping inthe Dark: The First Decade of GlobalModeling, Donella Meadows et al.,Editors (1982; $26.95 postpaid fromJohn Wiley and Sons, 1 Wiley Drive,Somerset, NJ 08873).

being met now because ofsocial and political struc-tures, values, norms, andworld views, not because ofphysical scarcities.

2 Population and physical(material) capital cannotgrow forever on a finiteplanet.

3 There is, quite simply, noreliable and complete infor-mation about the degree towhich the earth's physicalenvironment can absorb andmeet the needs of furthergrowth in population,capital, and the things thatthis population will generate.There is a great deal ofpartial information, whichoptimists read optimisticallyand pessimists readpessimistically.

4 Continuing "business-as-usual" policies through thenext few decades will notlead to a desirable future -or even to meeting basichuman needs. It will resultin an increasing gap betweenthe rich and the poor,problems with resourceavailability and environ-mental destruction, andworsening economicconditions.

5 Because of these difficulties,continuing current trends isnot a likely future course.Over the next three decadesthe world socioeconomicsystem will be in a period oftransition to some state thatwill be not only quantita-tively but also qualitativelydifferent from the present.

6 The exact nature of thisfuture state, and whether itwill be better or worse thanthe present, is not predeter-mined, but is a function of

THE CoEVOLUTION QUARTERLY SUMMER I2

Some problems consistently resist solutionin many cultures and over long periods oftime. These are the problems for which anew way of looking is required.

decisions and changes beingmade now.

7 Owing to the momentuminherent in the world'sphysical and social processes,policy changes made soonare likely to have moreimpact with less effort thanthe same set of changesmade later. By the time aproblem is obvious to every-one, it is often too late tosolve it.

8 Although technical changesare expected and needed,no set of purely technicalchanges tested in any of themodels was sufficient initself to bring about adesirable future. Restruc-turing social, economic, andpolitical systems was muchmore effective.

9 The interdependenciesamong peoples and nationsacross time and space aregreater than commonlyimagined. Actions taken atone time and on one part ofthe globe have far-reachingconsequences that areimpossible to predictintuitively, and probablyimpossible to predict(totally, precisely, maybe atall) with computer models.

10 Because of these interde-pendencies, single, simplemeasures intended to reachnarrowly defined goals arelikely to be counterproduc-tive. Decisions should bemade within the broadestpossible context, acrossspace, time, and areasof knowledge.

11 Cooperative approaches toachieving individual ornational goals often turnout to be more beneficialin the long run to all partiesthan competitive approaches.

12 Many plans, programs, andagreements, particularlycomplex international ones,are based on assumptionsabout the world that areeither mutually inconsistentor inconsistent with physicalreality. Much time andeffort is spent designing anddebating policies that are,in fact, simply impossible.

To nearly anyone with theeducation and time to thinkabout the world as a whole,these statements are not surpris-ing. We all have an intuitive feelfor how the complex systemsin which we are embedded work,and the statements above areabout the working of a complexsystem. Many of them followdirectly from general systemstheory. They were bound toemerge from any systematiclook at the global economy.

What is surprising is the lack ofcongruence between thesedescriptions of the world andthe view of the world reflectedin policy - nearly every policyof every nation, enterprise, andindividual. Those policies arevirtually all based on suchimplicit assumptions as:

There is not enough of any-thing to go around.We know that any physicalor environmental limits arefar away and can be ignored.

Competition works better thancooperation; if everyonelooks out for her or himself,the result will be satisfactory.

Any change in policy should bepostponed as long as possible.

The future will be very muchlike the past, only biggerand better.

The poor will catch up withthe rich someday if we pursuebusiness as usual.

The bottom line message of theglobal models is quite simple:The world is a complex, inter-connected, finite, ecological-social-psychological-econo micsystem. We treat it as if it werenot, as if it were divisible,separable, simple, and infinite.Our persistent, intractable,global problems arise directlyfrom this mismatch. No onewants or works to generatehunger, poverty, pollution, orthe elimination of species.Very few people favor armsraces or terrorism or alcohol-ism or inflation. Yet thoseresults are consistently producedby the system-as-a-whole,despite many policies andmuch effort directed againstthem. Many social policies work;they solve problems permanently.But some problems consistentlyresist solution in many culturesand over long periods of time.Those are the problems forwhich a new way of lookingis required.

A Child's Guide to theSystems Viewpoint

So what is this "systems view-point" - what can you see fromit that you can't see from any-where else?

1 The Concept of a System.A system is any set of intercon-nected elements. In our usualreductionist-scientific view ofthings the emphasis is on theelements. To understand things,we take them apart and studythe pieces. In the systems viewthe interrelationships are impor-tant. A corporation is a corpora-tion even when every person andmachine in it changes, as long asthe hierarchies, purposes, andpunishments remain the same.You can't understand theessence of a symphony orch-estra just by looking at theinstruments and players - it isalso the set of relationships thatcauses it to produce beautifulmusic. The human body, thenation of Hungary, the eco-system of a coral reef are allmore than the sum of theirparts. As an ancient Sufi sagesaid, "You think because youunderstand one you must under-stand two because one and one

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Myon101

When you see whole systems, you startnoticing where things come from and wherethey go. You begin to see that there is no"away" to throw things to.

make two. But you must alsounderstand and."

To see not only things but alsorelationships opens your visionimmensely. You never confusehastily constructed governmentapartment blocks with realcommunities. You never makean urban policy separate from arural policy. You begin to losethe distinction between human-ity and nature or between eco-nomic benefits and environ-mental ones. You also begin tosee new solutions - the trafficproblem may be affected by thehousing sector, economic growth'may be enhanced throughincreasing capital lifetimes,cancer may be prevented byprotecting the integrity of thecell membrane and the wholetissue, not the individualnucleus. It is often easierand more effective to act onsystem relationships ratherthan on system elements.

2 The Limiting Factor.Growth in a complex systemmay require hundreds of inputs,but at any given time only oneinput is important - the onethat is most limiting. Bread willnot rise without yeast, and addingmore flour will not help. Cornwill not grow without phosphateno matter how much nitrogen ispresent. This concept is childish-ly simple and widely ignored.American economists haveclaimed that energy cannot bean important factor of produc-tion because it accounts for lessthan 10 percent of the GNP(yeast accounts for much lessthan 10 percent of the bread -that doesn't make it unimpor-tant). Agronomists assume theyknow what to put in fertilizerbecause they have identified the20 major chemicals in good soil(how many chemicals have theynot identified?). Rich countriestransfer food or capital or tech-nology to poor ones and wonder

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why they don't grow. In eachcase attention may be on everymajor factor but the crucialone - the limiting one.

Real insight comes not onlyfrom recognizing that the im-portant factor is the limitingone, but from seeing thatgrowth itself depletes andenhances factors. The interplaybetween a growing plant and thesoil or a growing economy andits resource base is dynamic,everchanging. Whenever onefactor ceases to be limiting,growth occurs and changes therelative scarcity of factors untilanother becomes limiting. Toshift attention from the abun-dant factors to the next poten-tial limiting one is to gain realunderstanding of and controlover the growth process.

3 Boundaries. When you seewhole systems, you start notic-ing where things come from andwhere they go. You begin tosee that there is no "away" tothrow things to. You can nolonger ignore the connectednessbetween an automobile's exhaustand your nose. You see that theproducts of a coal-burningelectric plant are electricity,fly ash, particulates, SO 2 , CO2NOx, and heavy-metal aerosolsand that there is no real boundarybetween the economic productand the "byproducts." Youwonder why some effects of apolicy are called "side effects"when they are as real and directas the "main effects." Younotice how beautifully designednatural systems are so that theoutputs and wastes of oneprocess are always inputs toanother process, and you beginto think of new designs forindustrial systems.

4 Feedback. Whenever youpostulate that A causes oraffects B

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look for all theways that B inturn affects A. A B

When you turn a faucet to con-trol the level of water in a glass

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P0IRP AMOUNTOF WATFR IN GLAO6

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A closed chain of causal relation-ships that feeds back on itselfis called a feedback loop. Thewater-glass system is a negativefeedback loop that draws thesystem to a goal (desired amountof water). Negative loops act toadjust systems toward equi-librium points or goals, just as athermostat loop adjusts roomtemperature to a desired setting.When your country acquiresmore armaments to catch upwith the competition

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THE CoEVOLUTION QUARTERLY SUMMER 19E2

This is a positive feedback loop,a vicious circle that builds uponitself more and more. Positiveloops cause growth, evolution,and also collapse in systems.

Of course most systems, especi-ally socioeconomic ones, aremade of hundreds of intercon-nected positive and negativefeedbacks and their behaviorbecomes very complicated.

The concept of feedback is apowerful one because it allowsone to link causal structure todynamic behavior. If a systempersistently oscillates or equili-brates or fails to grow, onecan identify the structuralreasons for that behavior andlearn how to intervene in thefeedback loops to alter it. Thatis what I do for a living, and mycolleagues and I have appliedthese concepts to problems asvaried as fluctuating inventory,unstable grain prices, diabetesand cancer, rising oil prices,and economic development.

But the most powerful aspectof the feedback concept, a trulyprofound and different insight,is the way you begin to see thatthe system causes its ownbehavior. Country A perceivesthe arms race as "caused" bycountry B and vice versa, butone could equally well claimthat country A causes its ownarms buildup by stimulating thebuildup of country B. Or, moreaccurately, there is no singlecause, no credit or blame. Therelationships in the system makean arms race inevitable, and Aand B are helpless puppets(until they decide to redesignthe system). Similarly oil-pricerises that are blamed on OPECcould equally be blamed on theheavy consumption of the non-OPEC countries, but moreaccurately, the price rises arean inevitable result of a growingeconomic system dependent ona depleting nonrenewableresource base. Similarly, from asystems point of view, businessesmake up a system that is struc-tured to generate recessions anddepressions, the decisions offarmers make fluctuating com-modity prices inevita' le, and theflu doesn't invade you - youinvite it.

Seeing the source of a problem

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within the system that suffersthe problem is never politicallypopular. It is much moreappealing to find a "cause" foryour problems somewhere "outthere" than to contemplatechanging the relationships.between the elements "in here."It is comforting to view some-thing outside the system as theproblem, but it isn't very effec-tive. There is real opportunityfor action in learning to viewevery system as the cause of itsbehavior. First of all, if theentire concept of blame isremoved, you can stop arguingabout who is at fault and get onwith solving the problem. Andsecond, if a system is the sourceof a problem, it is also themechanism for a solution. Todemonstrate that, I would liketo proceed to the advanced-levelsystems course and talk aboutmultiple-feedback systems.

Advanced Understanding -Making Complex Systems Work

I Policy Resistance. Why dosome problems persist in spite ofcontinuous efforts to solve them?

A systems analyst would explainit this way (see Figure 2). Anysocial system is made up of

hundreds of actors, each with hisor her (or its in the case of aninstitution) own goals. Eachactor monitors the state of thesystem with regard to any im-portant variable, income orprices or housing or whatever,and compares that state withhis, her, or its goal. If there is adiscrepancy, if the system is notmeeting the goal, each actordoes something concrete tocorrect the situation. Usuallythe greater the discrepancybetween the goal and the actualsituation for any actor, the moreemphatic will be the actiontaken on the system. Thecombination of all actors tryingto adjust the system to achieveall the different goals produces asystem state that is often notwhat anybody wants. And yeteveryone is putting great effortinto keeping it there, because ifany single actor lets up theeffort, the others will drag thesystem closer to their goals andfarther from his/hers.

Examples of such system con-figurations come to mind fartoo readily. Farmeis, consumers,and farm suppliers pursue variousincome goals and produce eco-nomic conditions unfavorable forproduction and also unfavorablefor protection of the soils and

Figure 2 Policy Resistance

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waters. Government, laborers,and producers act together toproduce inflation that damageseveryone. Rich and poornations trade basic commodities,each nation pursuing overridingdomestic political and economicgoals, with a resultant instabilityon the world market thatsystematically penalizes the poor.Or, closer to home, individualmembers of a family or of aworking group, each concentrat-ing on personal goals, canproduce an uncoordinated ordisconnected entity that furthersthe goals of no one.

Suppose a government inter-venes in such a system with astrong policy that actuallymoves the state of the systemtoward the'government's goal,That will open up greater dis-crepancies for other actors withdifferent goals, which will causethem to redouble their efforts.If they are successful, the systemis likely to equilibrate very nearits previous state, but witheveryone working harder to keepit there. Think, for example,of efforts to improve trafficflow (by widening streets oradding control lights or buildingmass transit systems) thateventually result in the sametraffic densities as before. Orlook at the results of onecountry's attempt to raise itsbirth rate by prohibiting abor-tions (Figure 3). Abortions were

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legal until 1967, when theybecame unavailable. The birthrate rapidly tripled, but thencame slowly back down nearlyto its previous level. The indi-vidual families, pursuing theirown family-size goals, foundsome other way to achieve them,perhaps through dangerousillegal abortions.This systems view of policyresistance suggests some interest-ing new approaches to previouslyintractable problems. At thevery least, it suggests letting upon an ineffective policy, so thatall the resources and energyspent on enforcing and resistingthe policy could be released forsome more constructive purpose.One might also look moreclosely at the goals and actionswithin the system, to understandthem and to look for a way theycould be used instead of beingcombatted or subjugated. Theprinciple is similar to that ofkarate: use the force and energyof your opponent instead ofresisting it. For example, anation wishing to increase itsbirth rate might study thereasons for families to want fewchildren, discover that crampedhousing conditions may be aprime motivating factor, anddevise a housing policy thatallows young couples to achievetheir goals for peace and privacywhile also achieving the nationalgoal of more births. This policy

has b"en followed in Hungary,with much better results thanthose of Romania's policy ofabortion restrictions.

The most effective way ofdealing with policy resistance isto find an alignment of the goalsin the system, so that all actorsare working harmoniously andnaturally toward the same out-come. If this can be done, theresults can be amazing. Themost familiar examples of thisare mobilization of economiesduring wartime or recovery afterwar or natural disaster. Anotherexample was Sweden's popula-tion policy during the 1930s,when the Swedish birth ratedropped below replacement. Thegovernment assessed its goals andthose of its population carefullyand decided that the real basis ofgoal-agreement was not the sizeof the population but itsquality. 3 Every child should bewanted and cared for, preferablyin a strong, stable family, withaccess to excellent educationand health care. The govern-ment and the Swedish peoplecould align on that goal. Theresulting policies included freecontraceptives and abortions,sex and family education, easierdivorce laws, free obstetricalcare, support for families withchildren not in cash but in kind(toys, clothing, etc.), andincreased investment in educa-tion and medical facilities.Some of these policies lookedstrange in a time when birthrates were thought to be toolow, but they were implementedanyway, and since then birthrates have risen, fallen, andrisen again.

2 Drift to Low Performance.Some systems not only resistpolicy and stay in their normalstate, they actually worsen 'gradually over time, despiteefforts at improvement. Ex-amples could be falling pro-ductivity or market share of abusiness enterprise, reducedquality of service at a repairshop or hospital, continuouslydirtier rivers or air, or increasedfat on a person in spite ofperiodic diets.

3See Alva Myrdal, Nation andFamily, MIT Press, 1968 (reprint).

THE CoEVOLUTION QUARTERLY SUMMER IMl104 'ff1,

A system that takes its goal from its ownperformance is very likely to drift downhill.

The structure that produces sucha behavior is shown in Figure 4.The actor in this system (enter-prise, repair station, environ-mental agency, fat person) has aperformance goal (desired state)that is compared to the actualstate. If there is a discrepancy,action is taken to restore thesystem state to the goal. So farthat is a simple negative feed-back loop that should keepperformance at a constant,high level.

The problem comes in the con-nection between the actor'sperception of the system stateand his or her desired state. Iffor some reason performancefalters, and if the lower per-formance becomes the standard,then less corrective action istaken for any given discrepancyand the system state is perma-nently lowered. Another short-fall can produce another drop instandards, and so on untilperformance is nearly totallydegraded. A system that takesits goals from its own perform-ance is very likely to driftdownhill.

Some examples: In the U.S. 4percent inflation used to beconsidered unacceptable andwould generate strong correctiveaction. That standard hasslowly changed so that nowinflation below 10 percentlooks good, 12 percent is almostnormal, and it takes rates of 20percent or more to raise greatpublic concern (and we'rebeginning to get used to those).Also, in the U.S. air qualitystandards are set at differentlevels for different areas; placeswith dirty air have far lessstringent standards. Anotherexample: I live in a beautifulrural area where the streets ofthe small village are kept quiteclean and unlittered. I findmyself bothered when I go tobig cities and see all the trashlittering the streets. My friendswho live there are almost uncon-

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Fig. 4 Drift to Low Performance

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scious of the trash - and aftera few days there I am too.

An obvious antidote to thedrift to low performance is tokeep standards absolute -never let past performancebecome a guide to present goals.Another is to make goals sensi-tive to overperformance as wellas underperformance. The sameset of feedback loops couldactually pull the system state tobetter and better levels, if goodperformance were taken asreason to reset standards butbad performance were consideredonly bad luck, not to be takenseriously.

3 Addiction. The structure ofa system that produces addictionis shown in Figure 5. Again theactor has a goal and comparesthe goal with a perception of

the actual state to determinewhat action to take. But herethe action chosen has the effectof making the system appearbetter to the actor, while actu-ally over the long term it ismaking it worse. As the effectof this action wears off, theproblem reappears, probablymore insistently, so the actorapplies even more of the "solu-tion," thereby worsening theproblem and making it necessaryto use more "solution" inthe future.

Consumption of alcohol, nico-tine, heroin, caffeine, and sugarare obvious examples of addic-tive actions. A less obviousexample is the use of pesticides(removing the immediate pest,but also eliminating naturalcontrol mechanisms, so that thepest is likely to surge back inthe future). Another is thepricing of a depleting resourcesuch as oil at average ratherthan replacement costs (therebykeeping price artificially lowand postponing the pain but alsoencouraging further use andmore rapid depletion and dis-couraging the shift to otherresources that will eventuallybe necessary).

Policy choices with addictiveeffects are insidious becausethey look good in the shortterm, but once chosen theyare very difficult to reverse.Obviously, the best procedure isto be alert for options thatimprove the symptoms butworsen the problem and toavoid them, whatever theirpolitical appeal. Once caught inthe addictive cycle, one must

Figure 5 Addiction

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almost inevitably prepare tosuffer short-term difficulties inorder to get out, whether thatmeans the physical pain ofheroin withdrawal, a suddensharp price rise to reduce oilconsumption, or an invasion ofpests while natural predatorpopulations are being restored.Sometimes the reversal can bedone gradually, or an alternativenonaddictive policy can be putin place first to restore thesystem state with a minimum ofturbulence (psychiatric help torestore the self-image of theaddict, home insulation toreduce oil expense, crop rotationand multiculture to reducevulnerability to pests). But it isalways less expensive to avoidthe addiction in the first placethan to get out of it once it hasstarted - as anyone with a long-term systems viewpoint can see.4 Official Addiction - Shiftingthe Burden to the Intervener.As I grew older and spent mostof my time reading, I slowlybecame more and more near-sighted. Finally I couldn't readwriting on a blackboard orslides on a screen anymore. SoI got contact lenses. Within ayear my uncorrected visiondeteriorated far more than ithad in the previous 30 years.Now the lenses are necessary notonly for reading distant fineprint but for everyday navigation.Apparently the muscles aroundmy eyes had been doing a fairjob of compensating for anincreasingly misshaped naturallens. But when they no longerhad to do that job, they losttheir tone, their ability to do it.Soon I needed a newer, strongerprescription.That is a classic case of shiftingthe burden to the intervener-a benevolent form of addiction(Figure 6). In this sort ofsystem a natural corrective forceis doing only a so-so job of main-taining the system state. A well-meaning, benevolent, and veryefficient intervener decides tohelp out by taking on some ofthe load. A new mechanism isestablished to bring the systemto the state everybody wants itto be in. This new mechanismworks beautifully.But in the process, whether byactive destruction or simple

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neglect and atrophy, the originalcorrective forces within thesystem are weakened. Thesystem slips away from thedesired state. So the intervenerincreases his, her, or its efforts.The natural system weakens oratrophies still more.. The inter-vener picks up the slack. And soforth. Finally, most or all ofthe -original job carried out bythe natural system has, gladlyor reluctantly, been accepted bythe intervening system. Theability of the original systemto do the job has been severelyand perhaps irreversiblyweakened.

Finding examples of burden-shifting systems is easy and funand sometimes horrifying. Hereis a beginning of a list, to whicheveryone will be able to add.

burdencare of the aged

bread-making

smallpox prevention

long-distancetransportation

arithmetic

grain storage

Shifting a burden to an inter-vener is not necessarily a badthing. It is usually done will-ingly, and the result is often anincreased tendency for thesystem to achieve desired states.But this system characteristiccan be problematic, for tworeasons. First, the intervenermay not realize that the initialurge to help out a bit can starta whole chain of events thatleads to ever-heavier loads onthe intervening system. TheAmerican social security systemis now experiencing the strainsof that chain of events. Second,the community that is beinghelped may not think throughthe long-term loss of control andthe increased vulnerability thatmay go along with the opportu-nity to shift a burden to a moreable and powerful intervener.

original systemfamilies, communities,accumulation ofpersonal wealth

intervening systemsocial security

households, local multinationalmillers, small bake-ies corporations

natural resistance,accidental cowpoxinfection

railroads

mental training

households, farmers,local merchants

vaccination

interstate highways,trucks

personal calculators

grain tradingcompanies, inter-national reserveagreements

Figure 6 Shifting the Burden to the Intervener

i we 9T

THE CoEVOLUTION QUARTERLY SUMMER 1982

F;T

Rebuilding a decayed system ofself-reliance and private enter-prise that long ago stoppedhandling its own burdens is along, difficult process, some-thing no Republican administra-tion seems to understand. Sud-den removal of an interveningsystem does not necessarilyshift the burden back; it maydrop the burden because thereis little left to shift it back to.Intervening in such a way as tostrengthen the ability of thesystem to shoulder its ownburdens is very possible andoften cheap and easy, somethingno Democratic administrationseems to realize. The secret isto begin not by taking over,but by asking why the naturalcorrection mechanisms arefailing to handle the problem,and how the obstacles to handl-ing it could be removed.

5 High Leverage, Wrong Direc-tion. Jay Forrester, my systemsguru, likes to tell of workingwith corporations to establisha systems view of management.He has often discovered, inmodeling the feedback loopstructure of a corporation'sdecision processes, that:

* Whatever the problem is (fall-ing market share, unstable in-ventory, inadequate qualitycontrol), it is nearly alwaystraceable to the way the corpor-ation does things - not to thecustomers, the competitors, theregulators, or any other con-venient scapegoats.* Often one small cl ange, in oneor a few simple policies, willsolve the problem easily andcompletely.* The high-leverage policy pointis usually far removed in timeand place from where theproblem appears. It is seldomthe subject of much attentionor discussion, and even when itis identified, no one will believeit is related to the problem.* If it happens that someonehas indeed identified and ques-tioned the high-leverage policy,that person has almost alwaysdecided to push the lever in thewrong direction, thereby inten-sifying the problem.

The peculiarity of high-leveragepoints lurking in unexpectedplaces and inviting counterpro-ductive policies is not one I

Policy choices with addictive effects areinsidious because they look good in theshort term, but once chosen they are very.difficult to reverse.

can illustrate with a simple feed-back diagram. It seems to occurin just about any system thatcontains enough interlockingfeedback loops to boggle one'scapacity for mental analysis(for me that means more thanfour feedback loops).

Here are a few examples ofsystems with high-leverage pointspushed the wrong direction.

A large engine company had aproblem with falling marketshare. Every four years or so,it would lose sales to the com-petition, and the lost customersrarely returned. The problemwas finally traced to the firm'sinventory policy. The com-pany was reluctant to buildlarge, expensive engines onspeculation to accumulate aninventory. It preferred to buildonly on definite orders. Thispolicy saved a lot of money,but on the upturn of eachbusiness cycle, the company wasswamped by new orders, whichit could deliver only after a longdelay. Customers turned to thecompetition who could supplyengines quickly "off the shelf."The firm habitually respondedto the loss in sales by cost-cut-ting measures, includingdecreases in its inventory.

Most people in Vermont areconcerned about the "disappear-ance of the family farm." Theypropose policies such as cuts inproperty tax, low-interest loansfor farm equipment, and subsi-dies on milk prices. It turns outthat if you really like the idea oflots of small farms, you shouldoppose all those measures. Themajor cause of farm loss is farmexpansion. Farmers try to in-crease their incomes by produc-ing more, logically enough.When all the farmers do that, themarket is flooded with milk, andthe price goes down (the priceis not currently subsidizedenough to hold constant regard-less of supply - if it were, it

BOX 428 SAUSALITO CA 9496

would shift the burden to anintervener!). Since the profitper unit of milk has gone down,each farmer must produce moreeven to keep the same income.Some do. Others don't, andeventually their incomes drop solow that they quit farming.

The leverage point in this systemis the farmers' ability to increasetheir production. Given thetreadmill of the system, theywill have to use any break thatgives them more cash to expandtheir output. And that drivesprices, profits, and farmnumbers down still faster. Thebest way to stabilize farm num-bers would be to restrict totalproduction in some way. If thatcould be done, all farmers wouldhave higher and more stableincomes (as many industrialsectors have discovered).

One of the leverage points inany growing economy is the life-time of the capital plant. Theeasiest way to stimulate econom-ic growth is to increase theuseful lifetime of capital (bybetter design, or better main-tenance). Yet the policy ofplanned obsolescence is pro-moted and defended for thesake of economic growth.

The way to revitalize the eco-nomy of a city and create moreupward mobility for the poor isnot to build subsidized housingin the inner city. It is todemolish substandard andabandoned housing, creatingopen space for the establishmentof more businesses, so the job/population balance can berestored.

I wish I could provide here somesimple rules for finding high-leverage points and for knowingwhat direction to push them.Some of my professional col-leagues would argue that this isthe point where I should stoprelying on innate systems under-standing and start hiring them.

107---r�c�---------·

Indeed, all of the examples Ihave given here came fromformal computerized analyses.I do respect and use the com-puter as a handy tool to helplearn about complex systems,but I also think one can go along way without it.

One's rational, figuring-outability seems to be a bad guidefor finding leverage points. Itleads one to look at pieces ofsystems, and to make judge-ments based on short-term andincomplete information. Itwould lead a company to cutback on inventory when salesare down, the state of Vermontto reduce farmers' propertytaxes, or a nation to invest innew machines instead of repair-ing old ones. All very reasonablepolicies. And yet there is some-thing in all of us that mightlead us to notice the customers'dissatisfaction with long deliverydelays, or to wonder whyfarmers always complain aboutthe pressure to expand, or tofeel that replacing a machinethat is still productive some-how doesn't make sense.

I think we do have within us theability to see whole systems andto sense leverage points. Whatwe don't seem to have is theability to win arguments, evenwithin ourselves, with that"reasonable" side of us. Wekeep expecting a solution to benear a symptom, a long-termgain to start off with a short-term gain, or a winning strategyto produce instant gratificationfor all players. We know com-plex systems don't behave likethat. But something within uskeeps insisting somehow thatthey should. And so we pursuedifficult policies that can't work,and miss seeing rather simplepolicies that can. We try tocompete instead of cooperating,to push against environmentallimits instead of noticing thatthere is already enough, to hangon to a deteriorating status quoinstead of welcoming changesthat take us where we reallywant to go. The results arehunger, weapons, pollution,depletion. And just within ourgrasp, accessible through ourinnate systems understanding,are sufficiency, peace, equity,and sustainability.

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We keep expecting a solution to be near asymptom, a long-term gain to start off witha short-term gain, or a winning strategy toproduce instant gratification for all players.

Back to the Globe

It is impossible to lay out awhole new way of viewing theworld in a short paper - it is liketrying to describe everythingthat can be seen through a tele-scope and comparing it system-atically to what can be seenthrough a microscope. I couldgo on about the role of delaysand nonlinearity in systems,about the structural homologiesacross systems, about otherbehavioral properties such asthe tragedy of the commons orthe worse-before-better syndrome.One could create whole under-graduate and graduate curriculaon the subject, and of course Iand many other people havedone so.

It should be clear that I amexcited by what I can see fromthe new viewpoint of systems.I find my entire sense of what ishappening, what is possible,what I identify with, and what isimportant is shifting. I wantto take others by the handand say "Look at that" - whichI do in my teaching. I believethat if more people could learnto see the world as a system,in addition to, not in place of,the ways they already see theworld, some remarkable thingswould happen. At the veryleast, like the global modelerswho started from very differentpositions, they would find acommon ground of understand-ing and would find that manycurrent proposals that are thesource of argument and divisive-ness simply cannot be effective.They would find themselveslosing interest in simple notionsof fault or blame. And thenthey would start seeing wholenew kinds of policies.

What would these policies looklike? Some people expect that

Eyo7

policies arising from systemsviews and computer analysisshould be precise, absolute,certain, and a bit inhuman. Inmy own experience, however,after ten years of trying tosimulte social systems, I findmyself becoming more humble,less certain, more experimental,and acutely aware of the uniqueand wonderful complicationshuman beings add to complexsystems. I am finding thatpolicies consistent with thesystems view would be:

1 Respectful of the system -designed to aid and encouragethose forces within the systemthat help it to run itself, ratherthan imposing on it from "out-side" or "above."

2 Responsible for the system'sbehavior, rather than tryingto blame or control outsideinfluences.

3 Experimental - recognizingthat nature is complex beyondour ability to understand; there-fore careful experiment andconstant monitoring are moreappropriate than certain, un-deviating directives.

4 Attentive to the system as awhole and to total system prop-erties such as growth, oscillation,equilibrium, or resilience, ratherthan trying to maximize theperformance of parts.

5 Attentive to the long term,realizing that in fact there is nolong-term short-term distinction;that actions taken now haveeffects for decades to comeand that we experience nowthe results of actions takendecades ago.

6 Comprehensive - above all,the systems view, as demon-strated by the global models,makes clear that no part of thehuman race is really separateeither from other human beingsor from the global ecosystem.We all rise or fall together. a

THE CoEVOLUTION QUARTERLY SUMMER 162

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