problems with root cause analysis - …...root cause analysis processes like the fabled and widely...

Jack Harich has a backgroundof twenty years business man-agement and consulting,with a BS in Systems Engi-neering from the GeorgiaInstitute of Technology, US.Presently he is systems engi-

neer at wink.org. Foundedin 2001, the goal of wink.org

is to help solve the environmentalsustainability problem using the most

efficient and effective methods available. is has involved anovel line of research. e article reports on this research.

I N T R O D U C T I O N

HERE ExIsTs A clAss Of PROBlEms THAT HAvE dEfIEd

solution for generations. is class includesenvironmental sustainability, over population,recurring wars, avoidable large recessions likethose of 1929 and 2008, endemic corruption,

and excessive wealth inequality. ese problems canbe characterized as systemic, difficult, large-scale,and involving social systems of multiple intelligentsocial agents. ey also involve systemic lock-in.for example, Garrett Harding, in his classic analysisof the environmental sustainability problem inTragedy of the Commons, found that: “Each manis locked into a system that compels him toincrease his herd without limit – in a world thatis limited.” e existence of this class of problems raises thequestion that sits foremost in the minds of mil-lions of global activists: How can we solve theseproblems? is question is so ubiquitous that thetheme of this journal issue is systemic change:“How and where does systemic change manifest?How does it unfold? What are the leverage points,the forces and dynamics at play?” However, what is the right question to ask first?Perhaps we should consider Albert Einstein’s view-point: “If I had an hour to solve a problem and mylife depended on the solution, I would spend thefirst 55 minutes determining the proper questionto ask, for once I know the proper question, Icould solve the problem in less than five minutes1.” is is the road wink.org has taken. Our workinitially focused on the environmental sustainability

problem and later broadened to the class ofproblems described above. Our 55 minutestook two years and led to a very different ques-tion: WHY are popular solutions failing? issubsequently led our research down a road lesstraveled. e answer, found in a matter of days,was that popular solutions are failing becausethey do not resolve root causes. We know thisto be so because all problems arise from theirroot causes2.is hypothesis, that popular solutions for thisclass of problems are failing because they do notresolve root causes, has defined our work eversince. If the hypothesis is true then we can makea prediction. We should be able to find root caus-es that are not being addressed by popular solu-tions, however elusive those root causes may be. Our research approach has been to develop a for-mal process, based on root cause analysis, that fitsthis class of problems. is parallels what the busi-ness world has successfully done with its own classesof problems. is approach led to the system Improvement Process(sIP). e remainder of this article reports on how sIPworks, describes the application of sIP to one particularproblem, and concludes with discussion of how theapplication results confirm or deny the prediction thatroot causes exist which are not being addressed by pop-ular solutions.

M E T H O D O F A N A L Y S I S :T H E S Y S T E M I M P R O V E M E N T

P R O C E S S

sIP was designed from scratch to solve the highlyintractable class of problems described above. let’spause to give the class a name. e problems listedabove are difficult and large-scale. ey involve thelock-in factor reported by Hardin and multiple intelli-gent social agents acting together in a social system.We need a meaningful acronym to identify this class.let’s label the class difficult Intelligent social multi-ple Agents large-scale lock-in (dIsmAll) problems.more than anything else, what makes dIsmAll prob-lems difficult is lock-in. deep, well hidden, poorlyunderstood forces exist that lock social agents intoself-destructive behavior and make it excruciatingly

J A C K H A R I C H

SOLVING DIFF ICULT LARGE-SCALE SOCIAL SYSTEMPROBLEMS WITH ROOT CAUSE ANALYS IS

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difficult to break free, despite the prolonged effortof problems solvers. erefore, if we are to success-fully effect systemic change we must understand thesystemic forces involved. for dIsmAll problems this requires root cause analy-sis, which is the practice of finding and resolving aproblem’s root causes. e driving principle is that allproblems arise from their root causes3. Evidence of theeffectiveness of root cause analysis is irrefutable. vastswaths of industry have adopted root cause analysis.Generic processes like six sigma, Total Quality man-agement, kaizen, and the IsO 9000 family of standardshave evolved from application of root cause analysis.Root cause analysis processes like the fabled and widelyemulated Toyota Production system lie at the veryheart of corporate success4. sIP works by breaking a problem down into smallerand hence easier to solve subproblems. for example,when solving the problem of how to put a man on themoon and bring him back, NAsA divided the probleminto six subproblems: how to achieve earth orbit, howto move to lunar orbit, how to land on the moon,how to achieve lunar orbit again, how to move toearth orbit, and how to land on the earth. Once sIPhas divided a problem into subproblems, each sub-problem undergoes analysis to find its one or moreroot causes and to identify the high leverage pointsfor resolving the root causes. solution elements arethen developed for pushing on the high leveragepoints. e solution elements are then imple-mented. for each subproblem the process lookslike this:1 ~ subproblem definition 2 ~ Analysis (is is complex so it contains fivesubsteps.)2.1 ~ find the immediate cause of the subprob-lem symptoms in terms of the system’s domi-nant feedback loops.2.2 ~ find the intermediate causes, low lever-age points, and superficial (symptomatic) solu-tions. (Intermediate causes are defined below.)2.3 ~ find the root causes of the intermediatecauses.2.4 ~ find the feedback loops that should bedominant to resolve the root causes.2.5 ~ find the high leverage points to makethose loops go dominant. 3 ~ solution convergence.4 ~ Implementation.

e purpose of the Analysis step is to find theimportant causal chains in a subproblem. causalchains work as shown below. An arrow meansone thing causes another. Intermediate causes aredefined to be causes in a causal chain that occurbetween root causes and symptoms.

R O O T C A U S E S À I N T E R M E D I A T E

C A U S E S À S U B P R O B L E M

S Y M P T O M S

If the root causes of a problem are unknown, prob-lem solvers have no choice but to attempt (usuallyin vain) to resolve the intermediate causes bypushing on their connected low leverage pointswith superficial solutions. If the root causes areknown, then problem solvers can attempt (usuallywith success) to resolve the root causes by push-ing on their high leverage points with funda-mental solutions5. for example, before the root cause of infectionwas known, treatment was directed to interme-diate causes like fevers (with cold baths), fester-ing wounds (with concoctions like mouldybread and warm soil), and speculated causes ingeneral (with trepanning, incantations, and allsorts of herbs and charms). e cure rate waslow. But once the root cause of infection wasfound to be infectious agents like viruses andbacteria, revolutionary treatments that usuallyworked could be directed to high leverage points,such as avoiding infection (by hand washing andvaccination) and killing bacteria once an infectionwas established (with antibiotics). e result hasbeen a high avoidance and cure rate.e most urgent dIsmAll problem is global environ-mental sustainability. ere have been countlesspractical ways offered for solving the problem, likeregulations, conservation, population reduction, andcarbon taxes. But society doesn’t want to change itsbehavior and adopt these practices. erefore how toovercome change resistance is the crux of the problem6. As an example of how root cause analysis can work ondIsmAll problems and to test the prediction that rootcauses exist which are not being addressed by popularsolutions, let’s review what the sIP analysis found forthe change resistance subproblem of the global envi-ronmental sustainability problem. e analysis wasbuilt using a feedback loop model of the subproblem.

T H E R A C E T O T H E B O T T O M

ere are two feedback loops in the human systemthat, in the large, affect citizen’s lives more than any-thing else. ey are the loops that politicians use togain supporters.Over time, social evolution has pared the many strate-gies available for gaining political support into just twomain types: the use of truth (virtue) and the use offalsehood and favoritism (corruption)7. for example,a virtuous politician may gain supporters by stating,“I know we can’t balance the budget any time soon,but I will form a panel of experts to determine what

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the best we can do is.” meanwhile, a corruptpolitician is garnering supporters by saying, “Eco-nomics is easy. You just put a firm hand on thetiller and go where you want to go. I can balancethe budget in four years, despite what the expertsare saying. ey are just pundits. don’t listen tothem. A vote for me is a vote for a betterfuture.” e corrupt politician is also saying tonumerous special interest groups, “Yes, I can dothat for you. No problem.” Guess who will usu-ally win?falsehood and favoritism have long dominatedpolitical strategy. most politicians use rhetoric,half truths, glittering generalities, the sin ofomission, biased framing, and other types ofdeception (propaganda) to appeal to the greatestnumber of people possible for election or reelec-tion. Once in office many politicians engage inacts of favoritism, also known as patronage. for example many politicians use the ad hominem(latin for against the man) fallacy to attack anddemonize their opponents, particularly as an elec-tion draws near. A prominent instance was the use

of the swift boat ads in the2004 us presidential cam-paign to attack John kerry’scharacter. e ads were anad hominem fallacy, becausethey had nothing to do withkerry’s political reasoningor positions. Other termsfor the ad hominem fallacyare demagoguery, shootingthe messenger, negativecampaigning, smear tactics,and sliming your opponent. Politicians are forced to usefalsehood and favoritism togain supporters, because ifthey do not they will lose outto those who do. is causesthe Race to the Bottomamong Politicians to appear,as modeled using systemdynamics8 in fIGuRE 1. Oncethis loop takes hold a soci-ety’s leaders are locked into asystemic race to the bottom.ey will make poor deci-sions on problems whosesolutions would benefit themajority of the population,i.e. the common good.

To understand how theloop works, let’s start at false

memes. (Node names are italicized.) A meme is a men-tal belief that is transmitted (replicated) from one mindto another9. Rather than show falsehood and favoritism,the model is simplified. It shows only the larger factor,falsehood.e more false memes transmitted, the greater the decep-tion infectivity rate. e model treats arrival of a memethe same way the body treats the arrival of a virus: itcauses infection. After the “mind virus” incubates for aperiod of time, the infection becomes so strong thatmaturation occurs. is increases the deception matura-tion rate, which causes supporters to move from thepool of Not Infected Neutralists to the pool of SupportersDue to Deception as they become committed to the falsememes they are now infected with. Supporters Due toDeception times influence per deceived equals deceiversinfluence. e more influence a deceived politicianhas, the more false memes they can transmit, and theloop starts over again. As the reinforcing loop goesaround and around, each node increases in quantity,often to astonishing levels. e loop stops growingwhen most supporters are committed.


fIGuRE 1 ~ e structure of the Race to the Bottom. e reinforcing loop grows instrength by using corruption in the form of highly appealing falsehood and

favoritism. is increases the number of supporters of corrupt politicians, whichincreases their influence, which in turn increases their power to peddle still morefalsehood and favoritism. Over time the loop can grow to tragically high levels.

Once a supporter becomes deceived, they becomedeceivers themselves in order to spread what to themis the truth to others. e deceivers influence nodereflects this behavior. e race to the bottom loopcreates a giant political echo chamber, as deceiverscompete to see who can do the best job of spreadingmore (false) beliefs. is maximizes the number of falsememes, minimizes defection, and ensnares additionalneutralists into their fallacious paradigm. ese effectsexplain the high level of (false) proselytization and dog-matism seen on the far right in many political systems. e behavior of the race to the bottom is of considerableimportance. A deceived person has fallen (degenerated)from the norm of discerning the truth. e health of asociety whose leaders are elected relies on the majority ofits voters to be able to discern the truth about whowould make the better leader. ey can’t do this perfect-ly, but they should be able to satisfice10 and do it most ofthe time. If the majority can be routinely deceived intosupporting those who have used falsehoods to garnertheir support, then that society is in serious trouble.

T H E I M P O R T A N C E O F G R A P H S

A N D A N A L Y T I C A L T H I N K I N G

Authors of this journal issue were invited to considerthese questions: “How and where does systemicchange manifest? How does it unfold? What are theleverage points, the forces and dynamics at play?What are the conditions for its empowerment andenablement? How do agency and structure comeinto the picture?” ese questions can be systemati-cally answered with root cause analysis of the prob-lem, construction of a model of the problem’sstructure, and close study of how the forces in themodel dynamically play out over time. esedynamics are best presented in the form of graphs. A time based graph shows how various factorsbehave over time. e classic example of amodel and its graphs for understanding a pub-lic interest problem is the Limits to Growth11.e book is built around its graphs. e thirdedition uses ten scenarios and thirty graphs toexplain how a system dynamics model of theenvironmental/economic system behaves whenvarious leverage points are pushed on withsolutions. What people remember about theLimits to Growth is its stunning graphs. for thefirst time these graphs showed, in a convincingfashion, approximately what would happen ifbusiness as usual continued or various solutionswere implemented.is article takes a similar approach. Ten graphs(one for each scenario) are used to explain how theanalysis model works. is is a generalized model

so the graphs extend over an arbitrary period oftime. e Limits to Growth graphs use 200 years.We have chosen 500 years, but this could just aswell be 500 months, weeks, or days, depending onthe particular problem. On these graphs most ofthe interesting behavior occurs in the first fewhundred years. is is about how long it has his-torically taken civilization to address past dIs-

mAll problems, like slavery, universal suffrage,civil rights, and conversion from autocracy todemocracy beginning in the 18th century. e article speaks in terms of politicians andtheir behavior to hold positions of power.from that perspective the graphs should havea short time scale. However, for a dIsmAlproblem the graphs should be interpreted asrepresenting the entire system (often global) ofpoliticians and its macro behavior over theperiod of time it takes to solve the problem. Atthat level of thinking long time scales of hun-dreds of years become appropriate.

T H E R A C E T O T H E

B O T T O M G R A P H

Our first graph appears in fIGuRE 2. is showshow the race to the bottom loop behaves overtime. e behavior is simple because the modelhas only a single main loop. corrupt politicians exploit the power of the race tothe bottom by broadcasting as much falsehood andfavoritism as possible to potential supporters. is isdone with speeches, articles, biased media outlets,books, jobs, lucrative contracts, special considerationsin legislation, etc. e lies and favors are a cunningblend of whatever it takes to gain supporters. e endjustifies the means. e more influence a politicianhas, the more falsehood they can afford to broadcast,and the greater the amount of favoritism they can plau-sibly promise and deliver.e race to the bottom employs a dazzling array ofdeception strategies. ese are usually combined toincrease their power. Here are four of the most popular:1 ~ fAlsE PROmIsE – A false promise is a promise that ismade but never delivered or never delivered fully. falsepromises are widely used to win the support of seg-ments of the population, such as organized specialinterest groups, industries, and demographic groupslike seniors or immigrants. false promises flow likewine during election season. 2 ~ fAlsE ENEmY – creating a false enemy worksbecause it evokes the instinctual fight or flight syn-drome. e brain simply cannot resist becomingaroused when confronted with a possible enemy.


false enemies may be internal or external. Examplesof internal false enemies are negative campaigning,the salem witch trials, mccarthyism, Hitler’s per-secution of the Jews, and anti-semitism and racismin general. A recent example of an external falseenemy was George W Bush’s painting of saddamHussein as evil incarnate, behind the 9/11 terroristattack, and concealing weapons of mass destruc-tion, which falsely justified the second Iraqwar12. A current example is vladimir Putin’sunilateral creation of the second cold War, jus-tified by “lies and conspiracy theories “13.3~ PusHING THE fEAR HOT BuTTON – When apolitician talks about almost everything in termsof terrorism, or communism, or crime, or threatsto “national security” or “our way of life,” and soon, that politician is pushing the fear hot button.It’s very easy to push. Just use a few of the righttrigger words (like “big” government, “radical”environmentalist, or axis of “evil”), throw in adash of plausibility, and the subconsciousness isautomatically hoodwinked into a state of fear, orat least into wondering if there is something outthere to fear. Whether or not an enemy actually isout there doesn’t matter – what matters is that wethink there might be one. 4 ~ WRONG PRIORITY – Wrong priorities stem fromhidden agendas. A hidden agenda is a plan or goala politician must conceal from the public, due to

an ulterior motive. e low priority that environ-mental sustainability receives from most govern-ments today is rapidly becoming the textbookexample of how devastating wrong priorities can be.e next time you see any of these strategies ofdeception, think of it as proof the Race to the Bot-tom among Politicians exists, and as proof that fewpoliticians can escape the pressure to join the race tothe bottom.

T H E B A S I C D U E L I N G L O O P S

Opposing the race to the bottom is the race to the top.e two loops are joined together as shown in fIGuRE 3.Because each loop competes for the same Not InfectedNeutralists, they are “dueling loops”14.In the race to the top virtuous politicians compete forsupporters on the basis of the truth (called true memeson the model) about what is best for all (how to opti-mize the common good). No favoritism is used becausethose who tell the truth treat everyone equitably. virtu-ous politicians can help improve things so that societybenefits as a whole, but they cannot promise or giveanyone more than their fair share. e race to the top works in a similar manner to therace to the bottom because the two loops are sym-metrical, with one crucial difference: in the race tothe top, the size of the truth cannot be inflated.corrupt politicians can use false meme size to inflate


fIGuRE 2 ~ Run 1. e simulation run begins with one deceiver and 99 neutralists. Over time the percentage of deceiversgrows to 75% and stops. What keeps it from growing to 100% is the way deceived people can recover from their infection,

after a deception infection lifetime of 20 years.

the appeal of what they offer their supporters.But virtuous politicians cannot use falsehood topromise more than they can honestly expect todeliver. Nor can they use favoritism to inflateexpectations of how well they can help particularsupporters.

By examining how the basic dueling loops modelbehaves in the series of simulation runs shown infigure 4, we can better understand why the politicalpowerplace works the way it does.


figure 3 ~ e basic structure of the Dueling Loops of the Political Powerplace. ere are many variations. is structureis the fundamental cause behind the behavior of all political systems, both ancient and modern. it explains the ubiquity ofthe left right political spectrum. More importantly, it explains why corruption is what dominates politics, no matter how

hard society tries to stamp it out.

in these runs, true meme size is fixed and alwaysequals one. A false meme size of 1 contains nodeception, while a false meme size of 1.1 contains10% lies. e graphs have four lines. Percent rational sup-porters equals rational supporters divided by(rational supporters plus deceived supporters).Deceived, neutralists, and rationalists equal thenumber of those types of social agents in thethree stocks (boxes) on figure 3. e total num-ber of social agents always equals 100, so thenumber of each type is the same as its percent. ruN 2 – in run 2 false meme size is 1 and thenumber of initial deceived supporters and initialrationalist supporters are both 1. Because neitherloop has an advantage over the other loop, theresult is both loops behave the same. each loopattracts the same 37% of supporters, so thedeceived graph line sits on top of the rationalistsline. Percent rational supporters stays the samethroughout the run at 50%.ruN 3 – is shows what happens if we give oneside a head start. False meme size remains 1. Ini-tial deceived supporters is 1, while initial rational-ist supporters are 5. is time the rationalists pullaway and end up with 63% of supporters. ruN 4 – Now things get interesting. e numberof initial rationalist supporters is set back to 1 andfalse meme size is increased from 1 to 1.1. is isonly a tiny bit bigger, by 10%. it would seemthat itsy bitsy lies and favors wouldn’t makemuch difference, but no – they make a huge dif-ference over a long period of time. As the run 4graph shows, the good guys get wiped out. Atthe end of the simulation run the rationalists aredown to about 12%. A small advantage, if all elseis equal, can over time lead to a large advantage.in run 4, notice how slowly the lines for deceivedand rationalists diverged for the first 50 years.What might happen if the bad guys decided totell bigger lies and give out bigger favors?ruN 5 – if false meme size is increased from 1.1 to1.3, system behavior changes dramatically. it onlytakes about 50 years for the deceived line to pullaway from the rationalists. Now the rationalist lineflattens out much faster. e lesson is that the big-ger the lie, the faster a corrupt politician can takeover a political system. i wonder if that explainsanything we might be seeing in politics today?ruN 6 – finally we see what happens if a corruptpolitician decides to tell real whoppers, also knownas “big lies.” False meme size is increased to 2. inother words, every false promise, every falseenemy, and so on is now twice as big as they reallyare. e results are no surprise. Now the systemresponds so fast the good guys never even makemuch of an impact on politics. ey are smotheredso fast by such big lies that the graph line for ratio-nalists is starting to look like a pancake. At the endof the simulation run there are no rationalists leftin the system. ey have been exterminated.


figure 4 ~ Duelling loop simulation. runs 2 to 6.

ere is a limit to how big a lie can grow before itstarts to make detection easy. in figure 5 we willadd the effect of size of lie on detection variable to themodel, which imposes diminishing returns on thesize of a lie. is is the basic structure of the dueling loops of thepolitical powerplace. e two loops are locked in a per-petual duel for the same Not Infected Neutralists. in addi-tion, each politician has his or her own loop, and battlesagainst other politicians for the same supporters. it isthese many loops and the basic dueling loops structurethat forms the basic structure of the modern politicalpowerplace. e outstanding feature of this structure is:

the inherent advantage of the race to the bottom.

Because the size of falsehood and favoritism can beinflated, and the truth cannot, the race to the bottomhas an inherent structural advantage over the race tothe top. is advantage remains hidden from all butthe most analytical eye. A politician can tell a bigger lie, like budget deficitsdon’t matter. But a politician cannot tell a biggertruth, such as i can balance the budget twice as wellas my opponent, because once a budget is balanced,it cannot be balanced any better. from a mathemat-ical perspective, the size (and hence the appeal) of afalsehood can be inflated by saying that 2 + 2 = 5, or7, or even 27, but the size of the truth can never beinflated by saying anything more than 2 + 2 = 4.Because the size of falsehood and favoritism can beinflated and the truth cannot, corrupt politicianscan attract more supporters for the same amountof effort. A corrupt politician can promise more,evoke false enemies more, push the fear hot but-ton more, pursue wrong priorities more, and usemore favoritism than a virtuous politician can.e result is the race to the bottom is normally thedominant loop. is finding completes SiPanalysis substep 2.1: “find the immediate causeof the subproblem symptoms in terms of thesystem’s dominant feedback loops.” is alsoexplains why “Power corrupts and absolutepower corrupts absolutely15.” e reason is notso much that power itself corrupts, but that thesurest means to power requires corruption.Due to lack of analysis of the root causes ofchange resistance, problem solvers have longbeen intuitively attracted to the low leveragepoint of “more of the truth.” On the DuelingLoops model this is the true memes node. etruth is discovered by research on technical waysto live more sustainably, such as population con-trol, alternatives to fossil fuels, and reduce, reuse,and recycle. e truth is then spread by scientificreports, popular articles, environmental magazines,

lobbying, pilot projects, lawsuits to enforce the legaltruth, demonstrations to shock the public into see-ing the real truth, and so on. is works on prob-lems with low solution adoption resistance (lowchange resistance), such as local pollution prob-lems. But it fails on those with high change resis-tance, like climate change, because environmen-talists simply do not have the force (wealth,numbers, and influence) necessary to makepushing on this point a viable solution.Substep 2.2 of the SiP analysis says: “find theintermediate causes, low leverage points, andsuperficial (symptomatic) solutions.” e inter-mediate cause of high change resistance is theuniversal fallacy that growth is good16, i.e.economic growth trumps all other priorities,including solving DiSMALL problems. To combatthat fallacy problem solvers use the low leveragepoint of “more of the truth” to promote superfi-cial solutions as described above.Because of its overwhelming advantage, the raceto the bottom is the surest way for a politician torise to power, to increase his power, and to stay inpower. But this is a faustian bargain, becauseonce a politician begins to use corruption to winhe joins an anything goes, the-end-justifies-the-means race to the bottom against other corruptpoliticians. He is “locked into a system” where hecan only run faster and keep winning the race byincreasing his corruption. is explains why the raceto the bottom frequently runs to excess, causing itsown demise and collapse. is collapse ends a cycle as old as the first two politi-cians. A cycle ends when corruption/exploitationbecomes so extreme and obvious that the people riseup, throw the bums out, and become much harder todeceive for awhile. But as good times return, peoplebecome lax and another cycle begins. ese cycles neverend because presently there is no mechanism in thepolitical systems to keep ability to detect political decep-tion permanently high17.

T H E R O O T C A U S E O F H I G H

C H A N G E R E S I S T A N C E

Substep 2.3 of the SiP analysis says: “find the root caus-es of the intermediate causes.” is follows from thestructure of the model. e root cause of high changeresistance is the same as the root cause of why the raceto the bottom is the dominant loop most of the time.e cause of loop dominance is high political decep-tion effectiveness, which is the root cause. As long asthis root cause force stays high the world’s politicalsystems will tend to favor solving problems that


benefit powerful special interests (notably largecorporations and their owners, the rich) and willresist solving problems whose solution wouldbenefit the common good.is is a significant finding. It confirms theprediction that root causes exist, which are notbeing addressed by popular solutions to dIs-mAll problems.e next step in the process is to determinehow to resolve the root cause.

T H E H I G H L E V E R A G E

P O I N T S M O D E L

A high leverage point is a place in a system’sstructure that when “pushed on” with solutionelements resolves its connected root cause. find-ing the high leverage points to resolve the rootcause of high political deception effectivenessrequires the expanded model of fIGuRE 5. Here’show the model works:

We have extremely goodnews. ere is a promisinghigh leverage point in thehuman system that has notyet been tried. It is generalability to detect politicaldeception. Pushing thereappears to give problemsolvers the greatest possiblechance of overcoming resis-tance to systemic change.currently general ability todetect political deception islow. e lower it is thelower detected false memesare. e lower that is, thehigher undetected false memesare and the lower repulsionmemes are. is causes moredeceived and fewer rational-ists, which is bad news. currently repulsion to cor-ruption is also low. elower it is, the lower therationalists infectivity rateand the lower supporterdesertion due to repulsion.is is because repulsion tocorruption times detectedfalse memes equals repulsionmemes. is makes sense,because detected corruptionis a good reason to decide tosupport virtuous politiciansand to desert corrupt ones.

for the system to react correctly to deception, twosteps must take place. e deception must be detected,which is handled by general ability to detect politicaldeception times false memes equals detected false memes.en those detected false memes must cause people to berepulsed enough by the corruption to either defect fromthe supporters due to deception, which is what thesupporter desertion due to repulsion variable does, or tomove from neutralists to rationalists, which is handledby adding repulsion memes to true memes to calculate therationalists infectivity rate. In addition to this, falsememes minus detected false memes equals undetected falsememes, which reduces the deception infectivity rate. let’s summarize how the You can’t fool All of thePeople All of the Time loop works, focusing on thehigher leverage point. currently the loop is weak.low ability to detect deception and the fact that thesize of falsehood and corruption can be inflated butthe truth cannot combine to cause more supportersto be attracted to the race to the bottom. us if


fIGuRE 5 ~ e High leverage Points of the dueling loops. e two high leveragepoints are underlined.

ability to detect deception is low, corruption worksbecause most false memes flow through the systemunimpeded. is causes undetected false memes to behigh and detected false memes to be low, which favorsthe race to the bottom.But if problem solvers can raise ability to detect decep-tion from low to high, most false memes will flow todetected false memes. is greatly decreases undetectedfalse memes, which destroys the power of the race to thebottom. At the same time this increases repulsion memes,which increases the rationalists infectivity rate andincreases the deception recovery rate due to supporter deser-tion due to repulsion. e result is corruption doesn’twork anymore, which causes the race to the bottom tocollapse as most people suddenly see the real truth andflee for their lives to the stock of Supporters Due to Ratio-nality. is is precisely what happens when massiveamounts of corruption are suddenly exposed. substep 2.4 of the sIP analysis says: “find the feedbackloops that should be dominant to resolve the rootcauses.” e loop that should be dominant is clearlythe You can’t fool All of the People All of the Timeloop. e more dominant that loop is, the less peo-ple are fooled and the more dominant the race to thetop becomes. Transition to a permanent race to thetop will usher in the equivalent of the Age of Rea-son in the electorate of nations18. such a transitionhappened long ago to science, so it can be done.Imagine what it will be like when a similar transi-tion happens to voters and hence entire nations. finally, substep 2.5 of the sIP analysis says: “findthe high leverage points to make those loops godominant.” ere are two high leverage points,repulsion to corruption and general ability to detectpolitical deception. currently both are low, solet’s examine in fIGuRE 6 another series of simu-lation runs to see how these high leveragepoints behave. e results show that at last we have the behav-ior in the model we would like to see in thereal world, because percent rational supportershas risen to a blissful 100%. e destructiveopposition is eliminated and virtuous politi-cians can now focus completely on society’sproper priorities. If the model is correct, thenraising general ability to detect political deceptionfrom low to high is all it takes to make the raceto the top go dominant and solve the changeresistance side of the problem. We won’t get per-cent rational supporters to rise to 100% in the realworld, but we can get it close enough. In run 11, repulsion to corruption and general abili-ty to detect political deception were both 20% andpercent rational supporters leveled out at 20%. In

run 12, raising repulsion to corruption to 80%caused percent rational supporters to rise from 20%to 59%, a 195% increase. But in run 14 raising gen-eral ability to detect political deception to 80%caused percent rational supporters to rise muchmore, from 20% to 100%, a 400% increase. usgeneral ability to detect political deception hasabout twice the leverage of repulsion to corrup-tion and is the highest leverage point.

A N A L Y S I S C O N C L U S I O N S

Given this analysis, three important conclu-sions about the environmental sustainabilityproblem stand out:1 ~ Popular solutions to overcoming change

resistance push on the intuitively attractivebut low leverage point of “more of thetruth.” is fails because it does nothing toresolve the root cause. is explains whyproblem solvers have been unable to solvethe problem.

2 ~ e main root cause of successful changeresistance is high political deception effective-ness.

3 ~ A suitable high leverage point for resolvingthe root cause is raising general ability to detectpolitical deception.

suppose environmentalists shifted their strategy toroot cause analysis. ey might come to similar con-clusions. In particular, they might find that the highleverage point for overcoming systemic change resis-tance is raising general ability to detect politicaldeception. We need to raise political truth literacy.is can be done with a variety of solution elements,such as the nine sample solution elements found in thesIP solution convergence step19. However, because of no clear conception of the duel-ing loops (or any shared valid model of the problem’sroot causes and their high leverage points), problemsolvers are unable to focus their efforts and push on thecorrect high leverage points in unison. We are unable,as Helene finidori wrote in this journal, to find “waysto coalesce rather than dilute the diversity of ourefforts […]20.”is completes the sIP application example. e com-plete analysis found four subproblems, four mainroot causes, 12 sample solutions elements, and isavailable at wink.org21. e analysis presentedhere, with its one subproblem and one root cause,may appear simplistic or erroneous until the com-plete analysis is examined.


ree factors are adjusted in this simulation: falsememe size, general ability to detect political decep-tion, and repulsion to corruption. A false meme sizeof 1 means no falsehoods and equals a true memesize of 1. e truth cannot be inflated, so truememe size always equals 1. But false meme size canbe inflated by deception, aka spin, disinformation,propaganda, and lies. for each particular level ofrepulsion to corruption and general ability to detectpolitical deception, there is an optimum false memesize. in the real world this is set via trial and errorby intelligent social agents. in the model it’s set bytrial and error by the experimenter. run 11 – is represents approximately where weare today. Both high leverage points are low, at20%. e smarter the agent, the faster and better itadapts to changing circumstances. Corrupt politi-cians, via trial and error, have adapted their decep-tion strategies to the equivalent of a false meme sizeof 2.4. is is the optimum for these conditions.e result is corrupt politicians control the politi-cal system, which correlates with how well mostnations have been able to solve DiSMALL problems. run 12 – next let’s see which of the two highleverage points gives problem solvers the mostleverage. first let’s raise repulsion to corruptionfrom low to high, which is from 20% to 80%.en we experiment with the running model todetermine the optimum false meme size for theseconditions. it turns out to be 2. Will the resultbe good enough for the good guys to win or not?no. e results show that even 80% repulsion to cor-ruption is not good enough. e forces of good andevil are still so evenly matched that they would betotally unable to deal cooperatively and proactivelywith difficult problems like sustainability, becausethey would be too busy battling each other. Cor-rupt politicians and their deceived supporterswould also be engaging in promoting too manywrong priorities for the right priority of environ-mental sustainability to emerge as a top priority.run 13 – Here we rollback repulsion to corruptionto 20% and raise general ability to detect politicaldeception to 60%. e optimum false meme size is3.8. Compared to run 12 the results show thatability to detect deception offers much higherleverage than repulsion to corruption. ereforethis is the high leverage point that problemsolvers should be pushing on with their solutions.ere is, however, a problem with run 13. Per-cent rational supporters is 76%, which is probablyabout the bare minimum for a government tobegin to put aside political squabbling and beginworking on its backlog of problems. But 76% isstill not high enough for nations to focus effi-ciently on highly demanding DiSMALL problems,because solving these types of problems requiresa nation’s full attention and complete coopera-tion with other nations. We must do better.run 14 – To see if we can achieve a high enoughpercent rational supporters to solve the problem,let’s raise ability to detect deception from 60% to80%. Again we assume adaptation and changefalse memes size to its optimum of 4.7.


figure 6 ~ Duelling loop simulation introducing general ability to detect political deception. runs 11 to 14.

G E N E R A L C O N C L U S I O N S

e prediction, that root causes exist which are notbeing addressed by popular solutions to dIsmAllproblems, was confirmed for the environmental sus-tainability problem. due to its mind-boggling complexity and devilish diffi-culty of solution, the environmental sustainability prob-lem is the prototypical dIsmAll problem. erefore this

confirmation may be expected of the entire class.If other dIsmAll problems are subjected to a sim-ilar analysis, we can expect to find one or moreroot causes in each problem not being addressedby popular solutions.Indeed, this is what the full sIP analysis found.e full analysis contains four subproblems: A, B,c, and d. Each was found to have a single mainroot cause. One subproblem (d) was the envi-ronmental sustainability problem. e otherthree subproblems (one of which is change resis-tance) combine to form “the broken politicalsystem problem.” symptoms (aka side effects) ofthe broken political system problem include theenvironmental sustainability problem, the otherdIsmAll problems, and more, as seen in fIGuRE 7

is suggests a striking conclusion: e predic-tion holds for all dIsmAll problems. All dIsmAll

problems are symptoms of “the broken politicalsystem problem,” so they arise from its root caus-es. ese root causes are largely unaddressed bypopular solutions. at all dIsmAll problemsappear to be symptoms of a deeper problem was

an unanticipated discovery with implications thatmay be of some interest.e pattern of prediction confirmation for alldIsmAll problems lends considerable support toour central hypothesis, that popular solutionsfor dIsmAll problems are failing because they donot resolve root causes.is hypothesis points to a new strategy thatcould work. If present solutions are failing

because they do not resolveroot causes, then future solu-tions can succeed if theyshift to resolving specificroot causes. is strategy haslong worked for industry. Itcan thus work for dIsmAll

problems if a suitableprocess based on root causeanalysis is employed. dIsmAll problems are solv-able. If enough public inter-est activists adopt the newparadigm of root cause analy-sis, then systemic change isnot a pipe dream but a forth-coming practical reality.

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AckNOWlEdGEmENTs

e author wishes to thank Philip Bangerter and GeorgeTurner for their insightful discussion of these concepts as theydeveloped, as well as thoughtful edits on drafts of this and pre-vious articles. Additional thanks go to Helene Finidori for herexceptionally constructive review of several drafts and her questto make the article more understandable.

8

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1 e Einstein quote is from the book by vogt and Isaacs, page 1. 2 We know from Newton’s third law that for every action there is

an equal and opposite reaction. Every effect has a cause and everycause has an effect. from this we can infer that all problems arisefrom their root causes, using the definition of root cause below:

3 A root cause has three identifying characteristics: (is defini-tion is from Harich 2010, with the definition of resolve added.)

1 ~ It is clearly a (or the) major cause of the symptoms. 2 ~ It has no worthwhile deeper cause. is allows you to stop

asking why at some appropriate point in root cause analysis. 3 ~ It can be resolved. Resolve means changing a system’s struc-

ture such that a root cause force no longer exists or is acceptably low,and the resolution introduces no new significant problems.is definition allows numerous unproductive or pseudo rootcauses to be quickly eliminated.


fIGuRE 7 ~ e Broken Political system Problem and its side effects. A is the changeresistance subproblem. due to the dueling loops of the Political Powerplace,change resistance is presently so high that all dIsmAll problems are insolvable.

e important thing is to not stop at intermediate causes. eseare plausible and easily found. Working on resolving what are infact intermediate causes looks productive and feels productive.Intermediate cause solutions, more accurately called symptomatic(or superficial) solutions, may even work for a while. But until thetrue root causes are resolved, powerful social agents will invariablyfind a way to delay, circumvent, block, weaken, or even rollbackthese solutions, because intermediate causes are symptoms of deep-er causes. One must strike at the root.

4 liker 2004, e Toyota Way: 14 Management Principles from theWorld’s Greatest Manufacturer. How vitally important a total processis to a company’s problem solving success may be gleaned from thebook’s organization. e book presents each of the 14 principles in achapter of its own. ese are organized into three sections, with thelargest containing 7 principles. e section is titled “Section II. eRight Process Will Produce the Right Results.” is is the main point ofthe book and the secret to Toyota’s success. It is also a principle thatmay be applied to dIsmAll problems.

5 for more on these terms see the glossary entry on superficialsolution at wink.org. for the classic article on the importance ofpushing on high instead of low leverage points (in the right direc-tion) see Leverage Points: Places to Intervene in a System by donellameadows, available at < http://bit.ly/1Bl4Bxb >.

6 at change resistance is the crux of the problem wasaddressed at length in Harich 2010, Change Resistance as the Crux ofthe Environmental Sustainability Problem.

7 let’s examine why the two main strategies for gaining politicalsupporters are truth versus falsehood and favoritism. In any form ofgovernment, historically there have been six methods for gainingsupporters: force, bribery, patronage, falsehood, favoritism, andtruth. In a democracy force and bribery are illegal. Patronage, thegiving of jobs as rewards for support, is legal unless a merit systemis present. However, in a political unit with a voting populationof a million people for example, there would be only a few thou-sand patronage jobs available at the most. is is not nearlyenough to sway the majority, so patronage is not a viable mainstrategy. is leaves the three main strategies of falsehood,favoritism, and truth.Next let’s examine why political systems have evolved intotwo main groups of supporters, where falsehood andfavoritism are used by one group and truth is used by theother. A population group is either a minority (a specialinterest, aka vested interest) or a majority (a general inter-est, aka the common good). If helping a minority will makethe majority worse off, as for example in tax cuts for therich or corporations and countless cases of special treat-ment, then the only way the minority can convince themajority to support the minority position is favoritism orfalsehood. On the other hand, a majority doesn’t have toconvince itself to support a majority position since it’salready convinced. e truth needs no embellishment orspin. e plain truth will do, since a majority by definitionalready supports its own position. finally, here’s why falsehood is used more than favoritism.favoritism is the giving of favors (excluding jobs) as rewardsfor support, such as favorable treatment in new legislationor in interpretation or enforcement of existing law. Howev-er, favoritism is mostly a zero sum game. Giving somethingto one group takes away from that available to all. Tax cutsfor some reduce the income for all. Weaker regulations andenforcement for some reduce the benefits of regulation andenforcement for all. In contrast, falsehoods are not a zero sumgame. ey are also considerably cheaper than favors, and canbe manufactured and distributed almost instantly via themedia. for these reasons falsehoods are preferred overfavoritism for race to the bottom politicians.

8 for an introduction to system dynamics and how to readsystem dynamics models like those in this paper see the glos-sary entry on system dynamics at wink.org.

9 e concept and word “meme” was created by Richarddawkins in one of the classics of behavioral biology, e Self-ish Gene, in 1976. see p. 192 of the 1999 edition.

10 e word “satisficing” was coined by Herbert simonin 1956. combining the words satisfy and suffice, the worddescribes the method of decision making commonly usedby people (including managers) in most decisions, evenimportant ones. ey satisfice with rough heuristics ratherthan use optimal decision making, which is so arduous it isseldom used.

11 e three editions of the Limits to Growth were pub-lished in 1972, 1992, and 2004. e book has become theall time best seller in environmentalism, even more thanSilent Spring, with somewhere over nine million copiessold. People are thirsting to understand how the environ-mental sustainability problem behaves at the global systemlevel. e book provides that understanding.

12 Prasad et. al. 2009, ere Must Be a Reason: Osama,Sadam, and Inferred Justification. “One of the most curiousaspects of the 2004 [us] presidential election was thestrength and resilience of the belief among many Americansthat saddam Hussein was linked to the terrorist attacks ofseptember 11. scholars have suggested that this belief wasthe result of a campaign of false information and innuendofrom the Bush administration.”

13 for example, e Economist reported that: “Yet for afew years after mr. Putin came to power he built close rela-tions with NATO. In his first two presidential terms, rising liv-ing standards helped buy acceptance of his monopoly on statepower and reliance on ex-kGB men; now that the economy isshrinking, the threat of war is needed to legitimise his rule. […]At home Russian media, which are mostly state-controlled,churn out lies and conspiracy theories.” e “threat of war” iscreated out of thin air by creating a false enemy using “lies andconspiracy theories.”

14 for an easy to follow video based introduction to the duel-ing loops model, please see e dueling loops video series atwink.org. is contains 12 videos averaging nine minutes each.

15 Baron Acton 1887, Historical Essays and Studies. e exactquote is “Power tends to corrupt and absolute power corruptsabsolutely.”

16 Why is Growth Is Good such a universal fallacy? Because eco-nomic growth benefits corporations by increasing potential sales,which increases potential profits. large corporations essentially con-trol the world’s political systems, especially its democratic ones, asreported in works like When Corporations Rule the World by davidkorten, Supercapitalism by Robert Reich, Captive State: e CorporateTakeover of Britain by George monbiot, and Suiting emselves: HowCorporations Drive the Global Agenda by sharon Beder. e corporatelife form achieves political control by exploitation of the inherentadvantage of e Race to the Bottom among Politicians. isrequires tremendous amounts of deception, as documented in GlobalSpin: e Corporate Assault on Environmentalism by sharon Bederand A Century of Spin: How Public Relations Became the Cutting Edgeof Corporate Power by dinan and miller.

17 e dueling loops are cyclic. see the complete duelingloops paper for an additional model showing this cyclic nature at<http://bit.ly/1EsxaZz>.

18 Transition to a permanent Race to the Top among Politi-cians appears to be in its early stages in the European union, amarvelous sign that it’s possible. A strong education system givesEuropeans truth literacy in their early years. ereafter they arenot as easily fooled as the rest of the world, on the average.

19i e nine sample solution elements for the change resis-tance subproblem may be found at <http://bit.ly/1PGWgQl>.


20 finidori 2014, Collective Intelligence Is a Commons thatNeeds Protection and a Dedicated Language: 79. finidori went onto say on page 88 that “In particular we need to acquire capabili-ties to examine the dynamics that lock us into structures that areunfit and detrimental to the thrivability and renewal of the systemthrough time.” We could not agree more.

21 The sIP analysis may be found at: www.thwink.org/sustain/analysis/index.htm.

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R E F E R E N C E S

BEdER, s. (2002). Global Spin: e Corporate Assault on Envi-ronmentalism, Revised Edition (White River Junction, vT:chelsea Green).

——. (2006). Suiting emselves: How Corporations Drive theGlobal Agenda (Abingdon, uk: Earthscan).

dAWkINs, R. (1976). e Selfish Gene. (Oxford: Oxford uP).dINAN, W., & mIllER, d. (2007). inker, Faker, Spinner,

Spy: Corporate PR and the Assault on Democracy (london:Pluto Press).

fINIdORI, H. (2014). “collective Intelligence Is a commonsthat Needs Protection and a dedicated language”, Span-da Jorunal, V(2), 79-89.

HARdIN, G. (1968). “e Tragedy of the commons”, Sci-ence, 162, 1243-1248.

HARIcH, J. (2010). “change resistance as the crux of theenvironmental sustainability problem”, System Dynam-ics Review, 26(1), 35-72. doi:10.1002/sdr

kORTEN, d. (2001). When Corporations Rule the World(West Hartford, cT: kumarian Press).

lIkER, J. (2004). e Toyota Way: 14 Management Prin-ciples from the World’s Greatest Manufacturer (NewYork: mcGraw Hill).

mEAdOWs, d., RANdERs, J., & mEAdOWs, d. (2004).Limits to Growth: e 30-Year Update (White RiverJunction, vT: chelsea Green).

mIllER, d., & dINAN, W. (2008). A Century of Spin:How Public Relations Became the Cutting Edge ofCorporate Power (london: Pluto Press).

mONBIOT, G. (2000). Captive State: e CorporateTakeover of Britain (london: Pan Books).

PRAsAd, m., PERRIN, A., BEZIllA, k., HOffmAN,s., kINdlEBERGER, k., mANTuRuk, kI., &POWERs, A. (2009). “ere must Be a Reason:Osama, sadam, and Inferred Justification”, Soci-ological Inquiry, 79(2), 142-162.

REIcH, R. (2007). Supercapitalism: e Transforma-tion of Business, Democracy, and Everyday Life(New York: vintage Books).

sImON, H. (1956). “Rational choice and the struc-ture of the environment”, Psychological Review,63(2).

sTAff. (2015). “from cold war to hot war”, e Econ-omist. Retrieved from <http://econ.st/1HfHW3o>.

vOGT, E., & IsAAcs, d. (2003). e Art of PowerfulQuestions: Catalyzing Insights, Innovation, andAction (mill valley, cA: Whole system Associates).

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