Risk, Reward, and Resilience

 

Risk, Reward, and Resilience Framework: Integrative Policy Making in a Complex World

I. INTRODUCTION

In recent years, many states around the world have faced a series of shocks to their economies—from lockdowns in response to the COVID-19 pandemic to the seizing up of global supply chains to the weaponization of trade and finance—that have catapulted concerns about how to strike a balance between risk, reward, and resilience into the center of public discussions and policy-making.

Take the COVID-19 pandemic as an example. Whether to order a lockdown or close a country’s borders in response to the pandemic reflects a judgment about how to weigh the importance of lives and livelihoods. Such a question cannot be answered satisfactorily through adopting exclusively either a health (risk) or economic (reward) lens—both elements matter and their interactions can create complex and often unpredictable synergies and trade-offs. Both are affected by, and in turn affect, resilience levels. As the pandemic wore on, the adaptability of many companies rose as they learned to navigate remote work, while the physical and psychological resilience of many individuals dropped, making lockdowns harder to impose and enforce.

Similarly, questions about whether to reshore supply chains are not just about balancing security risks and economic rewards in the present but also about ensuring resilience in the future. How should companies and countries weigh the economic rewards materializing from specialization, economies of scale and just-in-time manufacturing against the security risks resulting from lack of self-sufficiency, low levels of redundancy, and the possibility of weaponized interdependence? When seeking to ensure resilience, is reshoring, nearshoring, or ally-shoring the way to go? Or might stockpiling supplies and diversifying suppliers be sufficient? Does the answer depend on whether the goods play a ‘critical’ role in society and how will that concept be defined?

Addressing these complex challenges is difficult because they are inherently complex, crossing disciplinary silos and departmental divides. The twentieth and early twenty-first centuries were marked by academics and policymakers becoming increasingly specialized, typically within a particular discipline or domain, such as economics, security, health, or the environment. Yet many of the today’s challenges require insights from an array of specialties and an ability to understand and respond to their complex and often unpredictable interactive effects. Our tendency toward narrow and deep specialization often inhibits our ability to engage in broad interdisciplinary research and integrative policy-making.1

When siloed groups of experts collide, the outcome is frequently acrimonious, sometimes giving the impression of us-versus-them tribal fighting. These divisions played out in arguments between economists and epidemiologists regarding how to handle the coronavirus pandemic, for instance, or between treasury and defense departments regarding how to assess foreign investments in critical infrastructure or protect critical technologies. Different experts and departments often value different things, such as maximizing economic rewards or minimizing health or security risks, and they tend to bring with them their own assumptions, models, and language. Even when trying to be integrative, policy-making often looks more competitive than collaborative.

In recent years, I have watched government departments and academic commentators struggle to develop frameworks for thinking about cross-cutting issues across a variety of topics—from how to respond to economic coercion to how to build resilient supply chains, from foreign investments in 5G networks to rethinking approaches to critical minerals and technologies. Through these observations, I have come to realize that there is no good heuristic model for how to bring together thinking about risk, reward, and resilience into a single framework that could better structure policy discussions and decision-making. This Article seeks to fill that gap.

I put forward a novel Risk, Reward, and Resilience Framework (RRR) that synthesizes insights from diverse disciplines and fields and creates a simple, yet flexible, mental model for decision-making that can be applied across varied domains. To give actors and systems the best chance of surviving and thriving over time in a complex and uncertain world, we need to consider the dynamic interplay of three elements—risk, reward, and resilience—each of which has three drivers. Risk is the product of hazard or threat, exposure, and vulnerability. Reward is the product of opportunity, access, and capability. Resilience is a function of absorptive, adaptive, and transformative capacities (Figure 1).

RRR diagram. © Anthea Roberts.

RRR helps to move past unproductive debates on economics versus security or health versus the economy, for example, by using cross-cutting elements that can be applied across multiple domains. Risks could be economic, security, or health related; rewards could be monetary, diplomatic, or social; and resilience could be physical, psychological, or environmental. As no discipline or domain owns one part of the equation, this framing helps to bridge silos and create space for multidisciplinary communication to improve policy outcomes.

RRR is more comprehensive and impartial than many of our existing frameworks. We have risk-and-reward frameworks and risk-and-resilience frameworks, for instance, but no general framework that incorporates all three elements. Frameworks from security and risk management focus primarily on minimizing risk, often without paying sufficient regard to financial and opportunity costs of doing so. Economic frameworks often prioritize maximizing rewards without paying due regard to various drivers of risk and resilience. Climate change and disaster management frameworks typically include risk and resilience but neglect rewards.

RRR does not pass judgment on how to weigh various risks and rewards or how to balance these against resilience—such judgments require normative assessments about what to value, as well as empirical evidence about contextual facts and causal evaluations of the effect of different interventions. Instead, it creates a simplified and structured systems model for working through complex problems by identifying the drivers of each element, how they connect, what policy choices they enable, and what consequences they produce. It makes explicit many of the objectives, trade-offs, and assumptions upon which policy-making depends.

Importantly, RRR does not tell people and policymakers what to think about complex problems. Instead, it provides a framework to help individuals and groups in how to think about complex problems. It allows complex and sometimes competing hypotheses to be included on a single diagram, enabling experts from different disciplines to see that their insights and values have been taken seriously, while making it clear that other experts bring different perspectives to bear that need to be assessed and weighed. In this way, RRR aids the decision-making process to help find the best outcome from the realm of politically feasible choices.

In Section II, I identify building blocks for developing RRR, noting both contributions and limits of existing frameworks, which point to the benefits of developing a more integrated approach. In Section III, I sketch how the Framework could be used to analyze two current dilemmas in international economic policy-making: international supply chain shocks and economic coercion. These case studies provide useful bookends because one involves a hazard affecting imports and the other involves a threat affecting exports. In Section IV, i.e. Conclusion, I consider RRR’s limitations and what recent recalibrations between risk, reward, and resilience might mean for international economic law.

II. RRR BUILDING BLOCKS

A. Risk

RRR starts with classic frameworks for understanding risk derived from security and risk management studies. Risk can mean uncertainty about whether a particular event is likely to eventuate or not.2 That event could be positive or negative, so risk is sometimes defined as ‘positive risk’ and ‘negative risk’. Economists work with notions of ‘expected value’ that include the sum of all possible positive or negative outcomes multiplied by their respective probabilities. It is more colloquial to use risk to talk about uncertainty over whether negative events will come to pass. In RRR, the word risk is used in this negative way—that is, ‘risk of harm’, while positive risks are captured through the notion of rewards.

Risk frameworks developed in security and risk management settings focus attention on both threats and hazards, which are sometimes grouped together as ‘all hazards’.3 Threats come from intentional actors with examples, including terrorist attacks, military confrontations, economic coercion, and cyber-attacks. Hazards refer to harms caused by sources other than intentional threat actors, including severe weather events (floods, cyclones, and bushfires) and pandemics. Hazards can come from natural sources, anthropogenic sources, or a combination of the two. For instance, some weather events arise from nature but result, at least partially, from human-caused climate change.

1. The drivers of risk

Risk sits at the intersection of hazard/threat, exposure, and vulnerability (Figure 2). The level of risk depends on a combination of the seriousness of an external hazard or threat and how it intersects with the exposure and vulnerability of a given actor or system. On this approach:

RRR diagram. © Anthea Roberts.

  • Hazards and threats refer to the seriousness of an external threat;

  • Exposure refers to whether a particular actor or system is or becomes exposed to that hazard or threat; and

  • Vulnerability refers to the internal characteristics of that actor or system that are likely to exacerbate or reduce the harm suffered.

Threats and hazards do not generate risk when considered in isolation. Instead, risk arises from the interaction of a threat or hazard with an actor’s or a system’s exposure and vulnerability. If an actor or a system is not exposed to a threat or hazard, or is invulnerable to it, no risk arises. If the target is exposed and is especially vulnerable, the harm suffered may be extensive—for example, harm resulting from an ‘eggshell skull’.

Threats and Hazards

The severity of hazards is typically understood as a function of their intensity (e.g. category 4 or 5 storms) and frequency (e.g. how often does a storm of that intensity occur?). Hazards are often understood through the notion of exceedance probability, which refers to the probability that a hazard exceeding a particular severity will occur over a given time period. This notion is captured in phrases such as ‘a once in a hundred-year flood’ or ‘a once in a lifetime storm’.

The severity of threats also depends on their intensity and frequency, but these are determined by a function of the intention and capability of threat actors. Intention captures the desire of the threat actor to harm an actor or system, while capability refers to the capacity of that threat actor to perpetrate harm. Cyber threats, for instance, rely on a threat actor having malevolent intentions and having the capability to cause harm through its knowledge of computer networks and codes.

Exposure

In the context of hazards, exposure refers to the presence of people, livelihoods, species or ecosystems, environmental functions, services, and resources, infrastructure, or economic, social, or cultural assets in places and settings that could be adversely affected. Low-lying towns are exposed to climate change–related risks caused by rising sea levels, for instance. Buildings in earthquake-prone areas are exposed to the possibility of structural damage that those built elsewhere are not.

In the context of threats, exposure refers to an opportunity for a given actor or system to be targeted. Having a computer and connecting it to the internet creates exposure to cybersecurity threats. Installing a 5G network creates exposure for that network to be weaponized through spying, cutting-off supplies, or degrading services. Trading relationships create exposure to economic coercion as those links can be weaponized through politically motivated trade restrictions.

B. Reward

The failure of risk frameworks to focus adequately on rewards is problematic in general. However, this failing is particularly problematic where the same action drives both risks and rewards. For instance, economic globalization may create or exacerbate certain risks, such as international supply chain shocks or economic coercion, but it also drives rewards by increasing efficiency. Where risks and rewards are connected, focusing primarily on minimizing risks (a good outcome) may have the effect of also minimizing rewards (a bad outcome). To understand how to weigh these concerns, we need a better understanding of the drivers of reward and how they connect to risk.

1. The drivers of reward

Economic models tend to focus on how to maximize well-being by increasing output and reducing costs. In the case of private goods without significant externalities, the actions of self-interested market actors allow this to happen without explicit intervention. In the case of public goods or the management of unpriced externalities, tools of cost–benefit analysis have been developed to guide the actions of a ‘benevolent planner’. Business models, which operate at the level of the firm rather than the market, often talk in terms of risk-versus-reward trade-offs and SWOT (Strengths, Weaknesses, Opportunities, and Threats) analyses for individuals and companies.

Modifying and combining these ideas to develop a more generalizable framework, I suggest that it is helpful to conceptualize rewards as being a function of opportunity, access, and capability (Figure 3). On this approach:

Opportunity refers to the potential gains that might be achieved by undertaking a particular action.

  • Access refers to the circumstances, channels, rules, or institutions through which a particular actor or system is able to take advantage of those opportunities.

  • Capability refers to the internal characteristics of that actor or system that affect the gains an actor or system is likely to achieve from accessing those opportunities.7