[Maarten Van Horenbeeck] [Risk Management]

The concept of “revolution” in political risk management

Maarten S.L.J.Vanhorenbeeck


Revolution is an important aspect of the contemporary business risk environment as it is fairly unpredictable and may have a significant impact on the operations a business undertakes, especially in a foreign context. This paper will review how revolution may signal itself in a society and which approaches have been developed to predict it. In addition, it will make a basic case that the Social Amplification of Risk framework could be a useful parameter in assessing the ‘plunging point’ where revolution is likely within a society. Two brief case studies are presented: Iran in the 1970s, which went through a significant revolution, and contemporary Zimbabwe, in which none has yet taken place, despite similar concerns regarding its leadership among the population.

Keywords: Revolution; Political Risk; SARF; Amplification; Risk Management

“The most radical revolutionary will become a conservative the day after the revolution.”
- Hannah Arendt (1906-1975)

Introduction: The concept of “revolution” and its impact on business

A clear definition of revolution was missing until 1999, when Arthur L. Stinchcombe clarified it as being “periods in which the rate of change of power positions of factions, social groups, or armed bodies changes rapidly and unpredictably” (Stinchcombe, 1999). This entails that quite a few social phenomena could lead to revolution, such as ‘coup d’état’, mass protests or legitimate elections, as was the case with the “Green revolution” in Palestine (Halevi, 2006). As such it is perhaps more safely considered as the political expression of societal change.

Revolution does not always seem an unwelcome change to businesses operating abroad. In some cases, revolution could lead to a more open society allowing for more business opportunities to exploit. By itself however it can also not be considered positive: a great deal of risk is involved.

From a risk management perspective, “revolution” is quite important exactly due to its unpredictable nature. While some changes, such as the green revolution can be predicted, their impact is systemic and cannot completely be foreseen. Another such example is Bolivia.

President Evo Morales, the leader of Bolivia’s grassroots cocalero movement which supports the indigenous peoples, decided on his one hundredth day in office to nationalize Bolivia’s hydrocarbon industry. The army quickly took over production facilities and their original owners were given a six month timeframe to negotiate new energy contracts with the state. Morales’ also indicated that organizations which had recuperated their initial investment in Bolivia would not be compensated. Some organizations heavily affected were Petrobras, the Brazilian government-owned oil company and Repsol YPF, a major Spanish hydrocarbon player (Council on Foreign Relations, 2006).

Bolivia, ruled by five different presidents in the period 2002-2006 has never been a particularly “conventional” state. With the election of President Morales, one part of a wider Latin American “socialist revolution” had however taken place – with far reaching repercussions for foreign companies operating in the region.

Risk management approaches

From a risk management perspective, it is important to understand how organizations identify political risk, and how they are able to deal with it. A qualitative study of political risk management in international Swedish companies indicates that the majority of those organizations predominantly relied on external organizations to assess risk, such as insurance companies (Lindeberg & Mörndal, 2002). While this may be specific to northern European culture, most organizations shied away from risk and insured operations abroad as much as possible.

This could indicate a move away from an evolution identified by Jeffrey D. Simon, who, in 1982 identified a “trend towards in-house systems for identifying political risk”. This trend became visible after major losses due to political unrest in the 60s and 70s, culminating in the overthrowing of the Pahlavi regime in Iran (Simon, 1982) and the Iranian hostage crisis.

Lindeberg and Mörndal came to the conclusion that most of the organizations within their sample used either Export Credit Agencies (ECAs) or insurance agencies to prevent losses from political instability. As part of defining their rate, these organizations measure the political risk involved by operating in a certain country, leaving merely project specific risk to the organization. Only one of the organizations explicitly mentioned using integrative risk management, or decision-making based on the changes that decision could have on the risk profile of a project (Lindeberg & Mörndal, 2002).

This situation can prove problematic. While ECAs and insurance agencies mainly use risk profiling of countries to state their initial rates and keep their clients abreast of the amount of coverage to expect, they focus on the assured assets – not necessarily on the ‘dynamics’ resulting of revolution that may impact the wider organization: for example, unions may launch a propaganda campaign as employees are at risk. There is also the issue of macro- and micro- risk: macro-risk affects all organizations operating in a certain country, while micro-risk may only affect a limited number (Kobrin, 1979). ECAs naturally focus on the former risk as the latter can only be assessed in detail by organizations themselves.

Once identified, five generic risk treatment methods are available (Brooks, 2004). In the below summary, one example is added to each that indicates how this method could be applied in a situation of political risk:

Predicting Revolution

Predicting the risk of revolution is an intelligence function. However, history is filled with examples of revolutions that were not forecast accurately, such as the fall of the USSR. Intelligence’s most common methodology, use of Trends and Patterns, is not equipped to predict revolutions as they are not preceded by many of the large “radar blips” by which most intelligence targets are accompanied (Segell, 2005).

As the goal of a revolution is to institute change into a social system, the people who value the current situation, its leadership, will attempt to prevent any such changes from occurring and to downplay its likelihood. When a revolution takes place in the form of a coup, only very few people will know in advance when and how it will take place. Its success rate is directly linked to its secrecy.

Revolution however can also take place in a more public setting, such as through elections. In this case, intelligence principles and models prove useful in identifying and predicting its likelihood. A wide variety of futures forecasting models exist that are applicable. Some popular ones are “genius forecasting”, Delphi and field anomaly relaxation (Aaltonen & Sanders, 2006):

Regardless of the model used, a major question is which parameters to use in the assessment. From the broader view of political risk, one argument is that “in attempting to recognize the precursors of these political actions, the forecaster must investigate the social and political conditions from which they result” (Bunn & Mustafaoglu, 1978).

They describe a separation between political risk events and political risk factors. A political risk event could be sudden expropriation, in which an organization’s assets are taken outside of its control, while a political risk factor leading to such event could be colonial identification of firm (Bunn & Mustafaoglu, 1978). If an organization is identified with colonial powers, it runs a higher risk of expropriation than its competitors which are not.

While it reflects organizational revolution from a corporate point of view, Zald and Berger hypothesize that there is a higher degree of coup risk “In corporate hierarchical organizations that (a) do not protect the positions of senior executives and (b) do promote within, (c) provide senior officers access to board members, and (d) experience poor performance or other undesired situations attributable to the CEO. (Zald and Berger, 1978).

This wide set of parameters shows that while ‘current intelligence’, the tracking of current items and short term analysis, may be useful in identifying risk of some overt revolutionary forms, it does not provide sufficient background knowledge to assess societal change. The concept of warning analysis could be of more use – more in-depth correlation between current events and deep background facts (Grabo, 2004). This in fact might explain why these activities are often outsourced by organizations. Retention of country specific specialists who are able to study topics in-depth and later re-assess continuously is not inexpensive.

Risk and Revolution

Revolution clearly poses a significant risk to either established parties that directly or indirectly benefit from the current situation. Could risk also be seen as a “driver” of revolution? The Zald and Berger study already mentioned that one risk factor for revolution could be the “poor performance or other undesired situations attributable to the CEO”. In order for a revolution to succeed, some form of support from the base population is generally required. When the current power ‘in force’ is dethroned, public support will be required for any new one to be viable, as existing power structures such as police enforcement may initially be scattered.

From this perspective, communication and perception of the current situation and its risk factors may prove important. Research by Schnijders and Raub identified through use of a prisoner’s dilemma experiment, that “risk aversion favours cooperation”. Their research gives at least some initial confirmation to a prior conclusion by Coleman that revolution is more likely to occur when conditions are improving “for at least part of the population” due to an increase of frustration and power (Schnijders & Raub, 1998). This frustration is ofcourse directly affected by how both the government attenuates, and other parties amplify, communication on the risk factors in contemporary society.

Social Amplification and Revolution: two case studies

The Social Amplification of Risk Framework was developed in 1988 to allow for interpretation of risk in a broader social context. It provides for a theoretical framework that explains how certain entities within society can amplify or attenuate perceptions of risk, leading to ‘ripple effects’ in the society at large (Pidgeon, Kasperson, Kasperson and Slovic, 2003). The first part of this paper has established that revolution closely interrelates with risk. Revolution itself poses risks to certain parties, but it could also function as a driver of support for revolution.

While this paper by no means constitutes a thorough study on the subject, two opposite situations will now be reviewed through the above principles. One of them is Iran, subject of two major revolutions in 1925 and 1979, the latter of which is covered here. Zimbabwe, on the other hand, is generally seen as a country that has spiralled down rapidly during the last few years. It currently ranks fifth out of 146 in the “Failed States Index” of 2006 (Fund for Peace, 2006). By applying the principles above, it is assessed why this country has not yet seen its ‘plunging point’, where society is no longer viable and revolution occurs.


At the end of the 1970s, the western Asian country of Iran was ruled by Mohammed Reza Shah Pahlavi. He was instated into his position in 1953 after a covert operation by the United Kingdom and United States to overthrow Iran’s first democratically elected regime, headed by Dr. Mohammed Mossadegh (Gasiorowski & Byrne, 2004).

During the 1960s and 1970s, Iran’s economic indicators were up, showing promise for the shah’s rule. Simultaneously, society however became more tightly controlled, changing the political system into a one-party state by 1975. Protest against Shah Pahlavi’s rule grew significantly at the end of the 70s led as oil wealth led to large changes and ‘modernization’ of society. Wealth was however concentrated in the upper classes and did not flow down to the mostly rural population.

Mowlana studied communication during the revolution, concluding that government media was tightly controlled and did not allow for messages regarding local concerns, focusing on advertising and support for existing government structures. Simultaneously, Iran was fairly unique in the sense that due to its common ethnicity and faith - a large majority of 51% Persians and 89% Shia Muslims - it had a large number of unofficial communications channels, amongst which are bazaars, masjids (mosques), e-ellmieh and hey-ats, or religious schools and gatherings (Mowlana, 1979).

Similarly important was the appearance of one more player, being Ayatollah Ruhollah Musavi Khomeini, an influential Muslim cleric who held the office of Supreme Leader. While within the shah’s secular state this position had little influence, it was considered by most Iranian Shiah’s to extol absolute secular and religious authority. While in exile in Paris, Khomeini sent messages by tape and telephone to Iran, that were subsequently distributed through the unofficial networks of communication that existed among the populace. These messages were very risk oriented, spreading news on for example “conspiracies” against Muslims going on the Hajj (IRIB, 2006).

By popular distribution of these messages, a risk which in reality was very limited was amplified to constitute a significant problem for the “population”. Simultaneously, the significantly improving financial situation of the upper classes increased frustration, while slightly trickling down to the general population.

While the 1979 revolution was not a “coup”, as it involved large societal action instead of a small, discrete overthrowing of the government, it does show us how the amplification of a “risk” message can have significant ripple effects in society – being a potential driver of revolution.


Zimbabwe is quite a different story. As one of Africa’s best educated countries, with a literacy rate of 90.7% in 2000, it could be expected to be a thriving nation. However, this number stands in sharp contrast to an average life expectancy of 39, among the lowest in Africa (CIA, 2006).

Ruled by President Robert Gabriel Mugabe, the country has been sliding into a totalitarian regime since 1980. Though his entry in Zimbabwean politics was marked by rife competition between his party ZANU-PF and ZAPU, elections since have been troubled. In 1987, Mugabe abolished the post of Prime Minister, declaring himself both President and Head of State. Recently, Mugabe has issued a proposal to change the constitution so elections for both the presidential as parliamentary elections are postponed till 2010. This would give Mugabe an additional two year’s in the drivers seat (Muleya, 2006).

As with Iran, Zimbabwean media is tightly controlled by the state. Ethnic composition is also similar to the Asian country, with 82% of the population a member of the Shona tribe. There is however no strong religion binding the inhabitants and as such limited common ideology. In addition, national communication is often disrupted due to lacking maintenance on the telephone system.

Foreign assessment of the country’s inflation is at 1042% (Strategic Forecasting, 2006) with a per capita gross domestic product of $2,300 (CIA, 2006). In addition, new bank notes were recently issued, which due to time and capital limitations on the exchange nullified savings above $16,000. The only class of the population that is profiting are soldiers and police officers – whom recently received significant pay raises. It is generally assumed that this was an effort to increase their support for the regime and decrease their understanding of the common Zimbabwean’s issues (International Crisis Group, 2006).

Politically, there is much strife within both the ruling party, ZANU-PF and the leading opposition party MDC, which recently split into two factions. No strong ruler has yet emerged. While Christian leaders called for massive uprising in 2005, there was no significant response from the population (BBC News, 2005).

Reviewing this state of the union provides us with a virtually inverse situation to Iran in the 1970’s. The communication mechanisms that might lead to amplification of societal risk do not seem to exist. However, two other parameters are in fact similar: a small part of society is becoming slightly more affluent, while there is significant frustration amongst the populace.

There is some indication that Mugabe considers a certain risk of revolution to be present, such as the recent pay raise for enforcement officials – nevertheless, in 2005 the regime launched “Operation Murambatsvina”, rendering some 700 000 people Harare citizens homeless – adding to frustration but not leading to resistance. Despite international outrage, there was little effect on the activities of the ruling party (International Crisis Group, 2005).


Political risk management within contemporary business is a complex concept, consisting of both quantitative and qualitative risk assessment each with its own goals and models. While quantitative risk management is often offloaded to insurance companies or Export Credit Agencies, there is still a need for qualitative risk analysis by organizations themselves.

Assessment of the likelihood of ‘revolution’ is a prime dilemma within political risk management. While ‘public’ revolutions can be assessed through intelligence collection efforts, some forms of revolutions such as the ‘coup d’état’ are much less likely to be forecast correctly. Here identifying the societal state of a country proves useful. Revolution is often closely interrelated with the perception of risk by a society, and as such the Social Amplification of Risk Framework can be useful. In this paper it was briefly applied to the Iranian revolution of the 1970’s and contemporary Zimbabwe.

Further research in this field is required, mainly to empirically assess the validity of the link between these concepts on a wider sample, as well as define more exact parameters on which the state of a society and its proximity to revolution’s ‘plunging point’ can be established.


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