This chapter argues for a systems approach to the challenges posed by, or amplified by, the Covid-19 pandemic. It examines how human and other systems interact to produce new situations and discusses the features of systems that policymakers and their advisors should consider when designing responses to current challenges, as well as strategies to deal with the risks and opportunities future challenges may present. Adopting a resilience approach means rethinking our priorities, and especially the relative importance of resilience and efficiency. The radical uncertainty associated with complex systems makes it impossible to predict where the next crisis will come from, but our influence on the evolution of our systems must be designed to have resilience as the primary objective, and the means to achieve that have to be constantly adapted over time to provide them with the capacity for recovery and adaptability regardless of the challenges they may face.
A Systemic Recovery
2. A Systemic Approach to Sustainable Recovery
Abstract
Introduction
As countries face the daunting task of economic recovery while still managing the public health risks of the SARS-CoV-2 (‘Covid’) pandemic, it is inevitable that our economies and societies ‘after Covid’ will be different from the ones overwhelmed by the virus. Human behaviours and incentives are changing, along with expectations of everything from consumer spending to workplaces, to government programming, to structural policies related to energy, health, and climate science. Calls to ‘build back better’ arise partly from problems which the crisis exposed, notably inequality: SARS-CoV-2 and its economic consequences have hit the poor and vulnerable the hardest. Simultaneously, our economies have proved less resilient than we had assumed. Reliance on globalised supply chains based on ‘just-in-time’ efficiencies has been called into question (Fraser, 2021). Many countries’ health and social care systems have not been able to cope. The notion that the private sector does things most efficiently fell apart in the middle of the pandemic, when public policy intervened to support health systems, individuals, companies and markets.
We are facing more than one crisis. The long aftermath of the financial crash of 2008 is still not over, with slow productivity growth, a global savings glut and continued financial risk—particularly in the non-bank sector—among the main concerns. The monetary policy response to the global financial crisis by major central banks—slashing interest rates and quantitative easing—punished savers and benefitted those who owned assets. This shifted the return of growth further away from labour to capital, and contributed to social strife and support for populist leaders. There is also the crisis of climate change and wider environmental breakdown.
It is no coincidence that financial, environmental, public health, and broader societal crises are occurring simultaneously. Modern society increasingly relies upon complex and interdependent systems, yielding greater efficiency, but increasing vulnerability to disruption cascading from one system to another. To safeguard global well-being, an understanding of the interrelationships between such complex systems is essential to build resilience to future crises and not just withstand them, but be in a better position after the recovery than before.
The accelerating global environmental crisis is among the most urgent. In 2018, a report of the Intergovernmental Panel on Climate Change (IPCC, 2018) made clear that to hold the average global surface temperature rise to 1.5 degrees Celsius, global emissions of greenhouse gases must be approximately halved by 2030, and reach net zero emissions by around the middle of the 21st Century. That is a transformative task of unprecedented proportions, made even greater by the need to tackle simultaneously a series of other worsening and inter-related global environmental problems, including biodiversity loss, soil degradation, and air and marine pollution.
Many economists and policymakers are hoping that these climate goals can be achieved with technological advances rather than fundamentally changed behaviour. Rapid technological progress may ultimately be the solution, but this will alter incentive structures and social activity within many aspects of our economies, and new patterns of globalisation will therefore emerge. Parallel to each of these trends is demographic change, notably population ageing, which will shift consumption behaviour and exacerbate the global glut of savings that has pinned growth, inflation and rates at lacklustre levels.
These challenges would be considerable in any circumstances, but they come after a period following the global financial crisis when productivity and economic growth were already fragile, still dependent on ultra-low interest rates and hugely expanded central bank balance sheets. Moreover, responding to the pandemic added USD 4 trillion to global debt over 2020, leaving it at a record USD 281 trillion (IIF, 2021). Government support programmes accounted for half of the rise, while global firms, banks and households added USD 5.4 trillion, USD 3.9 trillion and USD 2.6 trillion respectively. The global debt-to-GDP ratio rose by 35 percentage points to over 355% of GDP. This is higher even than the 2008 and 2009 increases of 10 percentage points and 15 percentage points respectively.
Inequalities were already rising in most advanced countries before Covid, but the wealth of the planet’s 2 365 billionaires increased by USD 4 trillion, or 54%, during the first year of the pandemic, even as global GDP fell by 3.5% (IPS, 2021. Angus Deaton (2021) shows that when countries are weighted by population, international income inequality also increased. Deaton attributes this to a fall in Indian incomes that was not offset by rising incomes in China.
Most developed economies have seen an increase in under-employment and insecure and precarious work of different kinds, from self-employment and part-time work, typified by the gig economy and very short-term contracts. In some countries, average earnings stagnated, with living standards for many households barely above those of a decade ago, or maintained only via rising household debt. In many cases, the gap between richer regions and those on the periphery has widened. Income inequality did though fall in some European countries after rising initially, perhaps because the policy responses focussed on those towards the bottom of the income distribution who were potentially the most affected by the pandemic (Clark et al., 2020)
Not all high-income countries experienced all of these problems, but many have experienced the political consequences of a decade of economic under-performance and the accompanying global pressures. Popular discontent with politicians and the political system has been rising over a long period in many countries. Trust in established institutions, in experts, and ‘elites’ has declined, with, according to Edelman (2021), “an epidemic of misinformation and widespread mistrust of societal institutions and leaders around the world … leaving the four institutions – business, government, NGOs and media – in an environment of information bankruptcy”. Societies which once experienced high levels of social cohesion are now widely felt to be more fragmented, prone to cultural as well as economic divisions. In many countries large numbers of people report a sense that society has become less fair, with a widening gap between the lives of the richest and the majority, and that in a more globalised world, national societies have somehow ‘lost control’ of their own destinies. In a Pew survey, participants with different views on globalisation “highlighted their alienation and confusion about what it means to be part of their nations today”, with many feeling left behind (Pew, 2020).
At the time of writing, there is still no consensus on the origins of the Covid-19 virus (Zarocostas, 2021), but the mechanisms through which the disease caused such devastation had been considered by the OECD. Before Covid-19 was detected, the New Approaches to Economic Challenges (NAEC) initiative, established by the Organisation in 2012 to draw lessons from the 2008 Global Financial Crisis, brought together policymakers and experts to discuss the fact that “a new crisis could emerge suddenly, from many different sources, and with potentially harmful effects” (NAEC, 2019). NAEC warned that: “Systemic threats are a particular challenge to governments due to their stochastic and relatively low frequency nature”, capable of provoking cascades that can trigger systemic degradation or collapse.
In the case of Covid, the initial health crisis soon sparked an economic downturn with impacts on a range of other systems as well, including global value chains, travel, the retail sector, education, and the environment. The World Meteorological Organization’s State of the Global Climate 2020 (WMO, 2021) underlines that “climate-related events already pose risks to society through impacts on health, food and water security, as well as human security, livelihoods, economies, infrastructure and biodiversity”. The report concludes that while the drop in emissions due to the economic downturn had little impact on the climate, cuts in food production, transport and economic activity caused by the pandemic exacerbated the effects of extreme weather on communities, particularly those already vulnerable to other risks.
The OECD had been analysing complex systems and their likelihood of generating systemic risks since the late 1990s, as part of its International Futures Programme (IFP). In 2003, the IFP’s Emerging Systemic Risks concluded that: “In today’s highly interdependent and networked world, even a local event can have substantial repercussions in distant regions of the world through its impact on technological or financial networks…” (OECD, 2003). This was borne out five years later when the US subprime crisis evolved into a global financial crisis, resulting in the Great Recession and political and social crises across the globe.
The dynamics of recent crises are similar, as are the governance and political economy questions they raise. In both cases, the warnings were ignored, or at least not acted on sufficiently to avert the considerable damage that followed. At another NAEC conference, one of the most knowledgeable actors in the 2008 crisis, Lehman Chief Global Economist John Llewelyn, expressed concern that the lessons of 2008 had not been learned, in that as the subprime situation evolved, experts were alarmed by what they saw coming, but decision makers preferred to delay significant action (Llewelyn, 2020). He stressed that while in 2008 this concerned the financial system, today it applied to planetary emergencies such as climate change.
This chapter examines how human and other systems interact to produce new situations, and discusses the features of systems that policymakers and their advisors should consider when designing responses to current challenges, as well as strategies to deal with the risks and opportunities future challenges may present. The conclusions will then be discussed in relation to the recovery from the Covid pandemic, and how to make that recovery more sustainable.
Natural and human system interactions
The notion that there are complex systems has long been employed in the natural sciences (for example, cell biology) and the social sciences (for example, to study phenomena such as urbanisation (Harrison, 2017). The idea is not brand new in economics, either. As NAEC Senior Advisor Alan Kirman points out, the view that the economy is a complex system “can be traced back at least to Adam Smith and a long chain of economists leads from him to Hayek and Simon” (Kirman, 2017). Recognising the complexity of the economy requires paying greater attention to “interactions, unintended consequences, stability, resilience, policy buffers and safeguards” (Hynes, 2017). This applies to other complex systems too, and to the interactions between them.
To best understand the implications of the pandemic, we have to look at system interactions and how social, economic and natural systems can interact to produce unintended consequences. Zoonotic diseases are on the rise, and 600,000 to over 800,000 unidentified viruses exist that have zoonotic potential (Carroll et al., 2018). Virus transmission risk is highest from animal species that have increased in abundance and even expanded their range by adapting to human-dominated landscapes (Johnson et al., 2020). Zoonoses already comprise a large percentage of all newly-identified infectious diseases (as well as many existing ones) according to the WHO (2020).
Seven human-mediated factors are contributing to the emergence of zoonotic diseases according to a joint report by UNEP and the International Livestock Research Institute (2020): increasing human demand for animal protein; unsustainable agricultural intensification; increased use and exploitation of wildlife; unsustainable utilisation of natural resources accelerated by urbanisation, land use change and extractive industries; increased travel and transportation; changes in food supply; and climate change.
The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) also concludes (IPBES, 2020) that the underlying causes of pandemics are the same global environmental changes that drive biodiversity loss and climate change, including land-use change, agricultural expansion and intensification, and wildlife trade and consumption: “These drivers of change bring wildlife, livestock, and people into closer contact, allowing animal microbes to move into people and lead to infections, sometimes outbreaks, and more rarely into true pandemics that spread through road networks, urban centers and global travel and trade routes. The recent exponential rise in consumption and trade, driven by demand in developed countries and emerging economies, as well as by demographic pressure, has led to a series of emerging diseases that originate mainly in biodiverse developing countries, driven by global consumption patterns”.
Systemic properties
Complex systems are impossible to understand using tools developed to analyse a simple system, which oscillates around an equilibrium and has actors that behave in a linear fashion such that decision-making can be predicted by extrapolating from a typical agent. In complex systems, the environment constantly changes and, in response, actors’ strategies evolve as well. New behaviours also emerge with scale; you cannot extrapolate how the system will operate from one actor or a group of actors. It may be possible to know everything about parts of a system at the individual level, but still be impossible to predict on that basis what will happen when the individual is part of a greater whole. A typical example is a flock of starlings. The complex patterns that thousands of birds generate when they form a “murmuration” could never be predicted from observing one bird.
Moreover, complex systems necessarily involve radical uncertainty. This is also called Knightian uncertainty, after Frank Knight, who distinguished between risk—for example, gambling in a casino where we don’t know the outcome but can calculate the odds—and what he called “true uncertainty,” in which we can’t know everything that would be needed to calculate the odds (Knight, 1921). Or, as Keynes (1937) put it, “There is no scientific basis to form any calculable probability whatever. We simply do not know.”
Radical uncertainty does not prevent us from taking decisions and performing actions, as individuals, societies or governments. We cannot know the future, but we can imagine it and try to influence it. And the imagined, probable or expected outcomes in turn influence our decisions and actions in the present, which is why we talk of “adaptive complex systems”. Even things that may never happen or will only happen decades from now can have an impact on what we do today. As individuals we buy insurance and pay into pension funds; as societies we try to forecast GDP or the impacts of climate change.
In the following, we will look at a number of characteristics that can influence policy thinking and the outcomes of policy decisions, emphasising how the characteristics of complex systems can be both positive and negative
Interconnectedness
The 2008 crisis showed how interconnectedness can have benefits and drawbacks. Global linkages across borders help the world to grow richer, but they also serve as transmission mechanisms for shocks. What started as a financial crisis in the United States sub-prime housing market degenerated rapidly into a global economic crisis with a dramatic collapse of international trade and foreign direct investment. We witnessed the same with the Covid pandemic. Globalisation allowed businesses to optimise and bolster their bottom lines but also became a transmission mechanism for the virus and caused an immediate supply shock in a number of industries.
The impact of interconnectedness on system stability is not straightforward, and can change dramatically over time. In energy grids, for instance, interconnectedness allows electricity to be switched to parts of the network that cannot meet demand from their local power stations. But in February 2021, severe winter storms in Texas caused failures in natural gas equipment that was insufficiently weatherproofed, causing gas production to fall drastically. Power plants did not have backup sources of thermal energy to power the grid, resulting in cascading blackouts and system-wide disruptions (Linkov et al., forthcoming). The state could not import energy from its neighbours because it had implemented a policy of energy autonomy to avoid federal oversight and deregulate its energy sector (Englund et al., 2021). In Europe around the same time, it was interconnectedness rather than a lack of that caused problems. A circuit protector in a substation in Croatia shut down a power line, causing another line to overload and provoking a system imbalance that propagated across the grid and almost caused the electricity system to collapse across the continent (ENTSO-E, 2021).
Multiple scales
We highlighted earlier that system behaviour can change with scale. In addition, many scales may be operating at once. The pandemic presented numerous examples of how multiple scales have to be addressed simultaneously to tackle systemic problems. Measures to fight Covid-19 only work if they go from individual behaviour (wear masks, wash hands, social distance, minimise trips), to cities and regions (cancel public events and concerts, restrict capacity in spaces, close parks), to countries (restrict travel, impose quarantines), to large international blocks (share data, pool resources for a vaccine).
There are different scales in time as well, from the millennia-long geophysical shifts that created the earth, its climate and its creatures to the nanosecond response times in financial markets. Here too, the concurrent operation of these different scales may be important—for example the fast pace of technological change and the much slower pace of regulatory innovation can create vulnerabilities in the system.
Moreover, the pace of systemic change can accelerate rapidly when a tipping point is reached, causing a regime shift. A system may change slowly and steadily over a number of years, then suddenly collapse. This happened to the Northeast Atlantic cod fishery that collapsed in the early 1990s with the loss of 50,000 jobs, and never recovered, despite a ban on fishing seeing some fish come back for a short time (Worm et al., 2009). The short term is therefore no guide to the long term, and the eventual tipping point may occur decades or more after a small change sets an evolutionary process in motion (Chaparro-Pedraza and de Roos, 2020).
The scale of the system may also play a role. Intuitively, one may expect a larger system to be more stable, and it does seem to be the case that larger systems take longer to reach a tipping point that can trigger a regime shift. However, there is some evidence from ecosystems that once the tipping point is reached, change is disproportionately faster in bigger systems because of a domino effect, with habitats and species impacting each other and provoking rapid, cascading collapse (Cooper et al., 2020).
Efficiency
Colloquially, efficiency may be understood as achieving maximum productivity with minimum wasted effort or expense, encapsulated in expressions such as “doing more with less”, applied to health and other services subject to budget restrictions (Harlock et al., 2018). Where waste is treated as ‘lost opportunity’ or ‘unrealised potential’, actors ranging from private businesses to urban planners to economic policy analysts all seek to identify ways of increasing systemic efficiency by either reducing waste or increasing output per unit of energy invested within a given activity. Generally, efficiency measures are based on eliminating unneeded redundant systems or resources that have little or no discernible value in the short to medium term.
This may be a reasonable strategy if externalities are low and disruptions are minimal and predictable. When conditions change, or a sudden disruption occurs, a lack of redundant capacity or alternative systemic configurations may leave a business, government, household, or other unit unable to cope with losses in core system functions, as the Covid pandemic showed. The concentration of industrial capacities and economic activity into smaller and more efficient sectors produced highly lucrative yet fragile supply chains and economic exchanges. While this provided considerable opportunities, it also made economic and other systems such as health services vulnerable to sudden and unexpected disruption, as the result of either an external shock, the way the system has self-organised, or a combination of both (Juttner and Maklan 2011; OECD and FAO 2019). The pandemic is not the first example of how extremely efficient supply chains can also be fragile at the same time. The 2011 earthquake and tsunami in Japan, for example, exposed the limits of just-in-time supply chain organisation, and highlighted the importance of flexibility, diversification, and adaptability (Fujimoto 2011; Golan et al., 2020).
Risk and resilience
All systems require a certain level of resilience to function, with that level changing according to the needs and degree of importance of such systems to society. In financial systems for example, data is backed up to more than one place, while power supplies for the servers may have what is called 2(N+1) architectures, meaning they have double the capacity needed for uninterrupted operation plus an extra capacity. Other data centres may only have N+1, the capacity to support a single failure. A core problem is that risk and resilience are fundamentally different concepts, yet are often conflated. The risk framework considers all efforts to prevent or absorb threats before they occur, while resilience focuses on recovery from losses after a shock has occurred. The US National Academy of Sciences (and others) define resilience as “the ability to anticipate, prepare for, and adapt to changing conditions and withstand, respond to, and recover rapidly from disruptions.” (NAS, 2012). In this definition, adapt and recover are resilience concepts, while withstand and respond are risk concepts, thus the risk component is clearly added to the definition of resilience.
Risk assessment and management is typically undertaken on a threat-by-threat basis in order to derive a precise quantitative understanding of how a given threat exploits a system’s vulnerabilities and generates harmful consequences. Such an exercise works well when the universe of relevant threats is thoroughly categorised and understood, yet is limited when reviewing systemic risk to complex interconnected systems because it does not consider how linkages and nested relationships with other systems leave a given system vulnerable to cascading failure and systemic threat. In other words, risk analyses usually fail to consider the third and fourth round effects of events transmitted through systems, which can be even more dramatic than the original.
Resilience-based approaches, which inherently review how the structure and activities of systems influence one another, help us to understand and even quantify a web of complex interconnected networks and their potential for disruption via cascading systemic threat. Resilience emphasises the role of recovery post-disruption as much as absorption of a threat and its consequences. This mindset is grounded upon ensuring system survival, as well as a general acceptance that it is virtually impossible to prevent or mitigate all categories of risk simultaneously, and before they occur. Resilience practitioners seek to use limited financial and labour resources to prepare their system for a wide variety of threats, all the while acknowledging that, at some point, and regardless of how well the system plans for such threats, disruption will happen.
For systemic threats, balancing efficiency and resilience is a matter of survival, where critical systems (water, energy, communications, security, food, etc) must be maintained above a basic needs level in order to ensure that a disruption in one area does not cascade to many others. It could also be argued that resilience is a dynamic form of efficiency, allowing the system to continue functioning to some extent rather than collapsing. It is clear that resilience is desirable (like efficiency), but the question arises of how to confer resilience on a system.
There are two broad approaches to answering that question: resilience by intervention and resilience by design (Linkov et al., 2021; Hynes et al., forthcoming). Social and economic systems should strike a balance between the two, but economic recovery from the 2008 crisis and the Covid pandemic has relied mainly on massive government interventions to shore up the financial sector and protect businesses. From January to October 2020, fiscal stimulus packages against SARS-CoV-2 totalled 3.4% (Saudi Arabia) to 28.31% (Japan) of GDP (IMF, 2021). These interventions allow governments to prevent systems from collapsing, and influence how society might ‘bounce forward’ after the crisis. A ‘hands-off’ approach to economic recovery may yield structural reforms, fiscal consolidation and creative destruction.
However, although these interventions may improve national and international economies, cascading disruptions, as seen in the Covid pandemic, mean that losses snowball. While financially quantifiable, these losses are not easily recovered and their cost may become unbearable politically or for markets, or both. Moreover, the success of interventionist policies depends on impeccable timing and a precise identification of where to intervene. A badly-targeted intervention may yield poor returns or even inhibit long-term sustainability in job creation, sectoral growth, and international trade.
Resilience by intervention must therefore be complemented by resilience by design to incorporate intentional resilience into economic systems without compromising long-term efficiency or other economic goals. This approach sees resilience as a practical philosophy and methodology to analyse complex adaptive systems and systemic risks and understand how systems absorb threats and maintain their inherent structure and behaviour. More specifically, resilience is used as a global state of preparedness, where targeted systems can absorb unexpected and potentially high consequence shocks and stresses (Larkin et al., 2015).
Towards a systemic recovery
In order to promote positive social and economic change post-Covid, a range of policies have to be integrated, including education, demographic, employment, well-being, and technology and innovation policies. Lifelong education, for example, will keep populations healthier, more physically and cognitively active, and more connected to society and the labour market (Hynes et al., 2020). Some authors go further, arguing that a “brain capital strategy” is required in the post-Covid economy since most new jobs will demand cognitive, emotional, and social skills, not manual skills (Smith et al., 2021).
Once again, the OECD was already looking at issues that the crisis would highlight before the Covid pandemic struck. In 2018, Secretary-General Gurria convened a high-level Advisory Group to examine the converging planetary emergencies linked to the environment, the economy, and social and political systems, and invited them to rethink the role of the economy in improving the well-being of people and the planet. The Advisory Group’s report concluded that we have to stop seeing growth as an end in itself, but rather as a means to achieving societal goals, including environmental sustainability, reduced inequality, greater wellbeing and improved resilience (OECD, 2020). This requires updating the philosophy, tools and methods underpinning the analysis that influences economic decision-making, and adopting an approach which recognises the rootedness of economic systems and behaviour in the relationship between people, social institutions and the environment.
In consequence, economic policy should have four paramount objectives:
Environmental sustainability – understood as a path of rapidly declining greenhouse gas emissions and environmental degradation, consistent with avoiding catastrophic damage and achieving a stable and healthy level of ecosystem services.
Rising wellbeing – understood as an improving level of life satisfaction for individuals, and a rising sense of improvement in the quality of life and condition of society as a whole.
Falling inequality – understood as a reduction in the gap between the incomes and wealth of the richest and poorest groups in society, a reduction in rates of poverty, and a relative improvement in the wellbeing, incomes and opportunities of those experiencing systematic disadvantage, including women, members of ethnic minorities, disabled people, and those in disadvantaged geographic communities.
System resilience – understood as the economy’s ability to withstand financial, environmental or other shocks without catastrophic and system-wide effects.
States and markets
Implementing such an approach would have profound implications for the role of the state. In 1986, US President Ronald Reagan joked that “The nine most terrifying words in the English language are: I'm from the Government, and I'm here to help” (Reagan, 1986). A year later, UK premier Margaret Thatcher would argue that “there's no such thing as society… people must look after themselves first” (Keay, 1987). The sentiment underlying these remarks was in tune with an approach that promoted deregulation, government disengagement and free market-based solutions to problems. However, by the time the Covid pandemic broke out, this thinking had changed, in part because of the massive government help provided during and after the 2008 crisis. In March 2020, French President Emmanuel Macron declared that: “What this pandemic reveals is that there are goods and services which have to be made independent of the laws of the market. To delegate our food, our protection, our ability to take care of our way of life to others is a folly. We have to take back control” (Macron, 2020).
The question is not state versus market, but how to create synergies between them. Governments are the only human system big enough to coordinate the response to global systemic threats and planetary emergencies, while businesses and markets can provide the goods, services, and expertise needed to transform policy visions into concrete improvements in well-being. Speaking at a NAEC seminar in 2018, Marianna Mazzucato suggested a way to harness the strengths of both (NAEC, 2018). Mazzucato argued that missions can provide the means to focus research, innovation and investments on solving critical problems, while also spurring growth, creating jobs and resulting in positive spill-overs across many sectors. By promoting public research and innovation, and investments in new strategic areas that have the possibility to bring together different actors across different sectors, it is possible to galvanise private sector investment by defining growth opportunities.
She quoted the example of the Apollo Program and the space race to show what it is possible to achieve by mobilising nations’ intellectual, financial and industrial resources. Even if Apollo had failed to land a man on the Moon, it would still have transformed modern life and the economy. In addition to the most obvious applications of space-based technologies such as computers, mobile phones or weather satellites, space R&D benefitted a wide range of products, from cordless tools to baby food (NASA, 1996). The development of vaccines against Covid is a more recent example of publicly-funded research being vital to the development of a new product.
Conclusion: Rethinking priorities
A fundamental challenge to governance is understanding the system as a complex network of individual and institutional actors with different and often conflicting interests, values, and worldviews. Superimposed on this governance network are potential risk events with ill-defined chains or networks of interrelated consequences and impacts. A resilience mindset acknowledges that the infinite variety of future threats (and opportunities) cannot be adequately predicted and measured, nor can their effects be fully understood. Adopting such an approach means rethinking our priorities, and especially the relative importance of resilience and efficiency. When you try to optimise one part of a complex system, you can end up destabilising the system as a whole. This principle is evident in global supply chains, surely one of the most efficient components of the international economy. When a highly optimised workflow is disrupted by shocks such as Covid-19, “Maybe just-in-time needs a dose of just-in-case” (Sodin, 2020).
There is a need to shockproof key global value chains to prevent a natural or political disaster triggering potentially catastrophic cascading collapse. This requires an understanding of corporate and market structures, and the effects of concentrations of financial and corporate power. It also means understanding how changes in competition policy and trade policy in recent decades contributed to making today’s systems so fragile, and how to use these same policy tools to devise solutions (Hynes and Lynn, 2021).
The system of regulation and subsidy should be designed to promote de-concentration and redistribution of key industrial capacities, such as semiconductors, chemicals, and other capital-intensive goods and components, as well as health-related products needed to cope with the next pandemic. The goal should not be national self-sufficiency, rather to distribute capacity so that a disruption only affects a minor portion of the total supply of any particular vital good or component.
The radical uncertainty associated with complex systems makes it impossible to predict where the next crisis will come from, but this should not stop us learning the lessons of the past to prepare a systemic response for the future. One lesson from Covid-19 is that crises do not repeat themselves. The fact that we were able to contain previous coronavirus crises such as SARS led to a sense of complacency in some instances about our ability to contain any future crisis. We cannot afford to be complacent about the other grave crisis we are facing: the climate emergency. In systemic terms, this is not a shock, with all that implies of a sudden, unexpected occurrence, but more like a stress. Systems analysis teaches us that stresses such as global warming are non-linear. The system may continue to function more or less normally for a long period and only degrade slowly, but it can then reach a tipping point from which it cannot recover, and collapse can then be extremely rapid.
Covid-19 shows that we have to act now, because we simply don’t know how changes in one system may evolve and impact other systems, or in this case how a mutation in a virus could cripple the world economy. We can anticipate, however, that serious damage to a natural system, such as biodiversity loss, or significant changes, such as sea level rise or increased occurrence of extreme weather, will have serious impacts on economic and social systems too.
As we recover and reconfigure systems, we must be aware that future systemic shocks and upheavals may arise from any number of origins, and in particular may be of our own making. While we have no reasonable way to anticipate and prepare for the broad universe of threats, we can analyse those to which we have contributed and diminish the practices that made this happen. This is particularly true of climate change. The basic lesson is that our influence on the evolution of our systems must be designed to have resilience as the primary objective, and the means to achieve that have to be constantly adapted over time to provide them with the capacity for recovery and adaptability regardless of the challenges they may face.
In the next stage of this work, NAEC will build on the insights from a systems approach to look at the forces shaping specific systems, including the environment, the financial system, employment, the agro-food system, global production systems, and communication networks. We will use the lessons from this analysis to discuss how to conceive an integrated approach to dealing with planetary emergencies.
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