Sensemaking for Security

Today’s security landscape is being shaped by an inherent Volatility, Uncertainty, Complexity, Ambiguity (VUCA). The threats and risks to safety and security derive from both man-made and natural circumstances. Events like Hurricane Michael (2018), Hurricane Maria (2017), COVID-19 pandemic (2020), Ebola Outbreak (2014–2016), Hurricane Katrina (2005), Fukushima Daiichi nuclear meltdown (2011), Typhoon Haiyan (2013) and global terrorist events illustrate the devastating effects of natural and man-made disasters on human systems and human security (Masys et al. in Procedia Econ Financ 18:772–779, 2014 [1]). As reported in Masys and Lin (Asia/Pacific security challenges—managing black swans and persistent threats. Springer Publishing, 2017 [2]), over the past four decades there have been a growing number of small and medium-scale disasters which have resulted in a total loss of over US$1.15 trillion. This threat and risk landscape challenges regional security along such lines as: national security; energy security; water security; food security; health security; human security; environmental security; economic security. Considering the current COVID-19 pandemic, as of November 2020, the COVID-19 pandemic has seen upwards of 60 million cases, 1.4 million deaths, and has significantly impacted the global economy and affected the most vulnerable. The impacts have seen the closure of borders, economic disruptions and failures, strained and overwhelmed health care systems, failure of supply chains all of which are contributing to a human and national security issue. The COVID-19 represents a national and global health security disaster revealing systemic vulnerabilities. A disease anywhere is a disease everywhere. Threats to global human security reside within disease vectors that are transnational making sensemaking an essential element of security. Sensing the threat and risk landscape that characterizes the security environment requires an understanding of the inherent systems, interdependencies, nonlinearity across the security domain. This chapter provides an overview of the complex security landscape and the inherent systemic risks that shape the security discourse.

OECD (A systemic resilience approach to dealing with Covid-19 and future shocks, p. 14, 2020 [1]) argues that ‘The excuse that dangers are clear only in hindsight does not stand up to objective scrutiny. Major simulation exercises in OECD countries predicted accurately how a crisis like Covid-19 could unfold, but they were not acted on, or not sufficiently, judging by what has happened’. Heyman et al. (Lancet 385:1884–1901, 2015 [2]) argue that, “the world is ill-prepared” to handle any “sustained and threatening public-health emergency”. The complex threat and risk landscape that shapes our security and safety experience is characterized by Volatility, Uncertainty, Complexity and Ambiguity (VUCA) conditions. For example the recent COVID 19 pandemic reflects how unexpected events often audit our resilience (Weick and Sutcliffe in Managing the unexpected: resilient performance in an age of uncertainty. Wiley, San Francisco, 2007 [3]). Such surprising events often reflect an organization’s inability to recognize evidence of new vulnerabilities, sense weak signals or the existence of ineffective countermeasures (Woods in Resilience engineering. Ashgate Publishing, Aldershot, 2006 [4]). Public health emergencies stemming from infectious disease outbreaks are creating a serious threat to global health security and have significant National Security implications. Viewed as a black swan or an elephant in the room, this pandemic point to the requirement to be sensitive to the extremes: to those events that lie outside of what we consider predictable (Masys in Homeland security cultures: enhancing values while fostering resilience. Rowman & Littlefield International, London/Lanham, 2018 [5]; Masys in Disaster forensics: understanding root cause and complex causality. Springer Publishing, 2016 [6]; Taleb in The black swan: the impact of the highly improbable. Penguin Books Ltd., London, 2007 [7]). Weick [8] refers to sensemaking in terms of ‘… how we structure the unknown so as to be able to act in it. Sensemaking involves coming up with a plausible understanding—a map—of a shifting world; testing this map with others through data collection, action, and conversation; and then refining, or abandoning, the map depending on how credible it is’ (Ancona in Handbook of teaching leadership. Sage, Thousand Oaks, pp. 3–20, 2011 [9]). Using the COVID-19 pandemic as a backdrop and context for this chapter, sensemaking thought leadership will be explored leveraging the seminal work of Weick [8].

The contemporary strategic operating environment is increasingly characterized by increasing complexity and dynamic change, leading into new vulnerabilities and uncertainty. Whilst global information and transparency have reached unparalleled levels, we still seem to be taken by surprise with sudden shocks and crisis. In some cases this is due to the deep or extreme uncertainty, i.e. in case of events that are so unique that they are genuinely unprecedented or extremely rare (think of a ‘planet killer’ meteorite striking Earth), or high impact—low probability risks that do not get prioritized by political decision-makers as preparedness priorities. The COVID-19 pandemic appears to be a good example of the latter. Whilst experts were warning governments (for instance the Global Preparedness Monitoring Board in a September 2019 report [1]) about an influenza pandemic involving a high-impact respiratory pathogen and criticized them about the lack of preparedness for such an event, the exponential spread of COVID-19 took governments around the world by surprise. The initial excuse was that COVID-19 was an unexpected ‘black swan’, which it of course was not. Either the thinking as it relates to pandemic threats is in too linear terms, or the message from the experts was not sufficiently convincing to political decision-makers to spring into action. This begs the question—why do we either ignore such risks or fail to take decisive action in face of a large-scale disaster? The purpose of this chapter is to review and examine methods and approaches that could enable governments and organizations to integrate security and preparedness decision-making from monitoring and detection to action through improved sensemaking. In other words, it seeks a path to being less taken surprise by the perils of deep uncertainty and taking the appropriate actions in a timely and sufficient manner.

The COVID 19 pandemic has resulted in significant national and global public health impact. The mortality and morbidity statistics associated with COVID-19 has become a key impact metric. As of 26 June 2020, globally upwards of 10 million cases of COVID 19 have been reported and 500,000 deaths. In the US alone there have been upwards of 2.5 million cases and 125,000 deaths. The EU/EEA and UK have reported 1.5 million cases and 176,000 deaths. The viral effect associated with COVID 19 is well tracked stemming from the direct effects of the virus. However, there are secondary and tertiary public health effects stemming from the COVID 19 pandemic that requires attention and management. These include: psychological distress, loneliness, mental health issues, and domestic violence. Developing public health strategies associated with the COVID-19 pandemic requires sensitivity to unexpected outcomes, to sensemaking that explores beyond the direct effects but considers the second and third order effects. This chapter will examine these secondary and tertiary public health effects and will highlight the requirement for improved public health surveillance and awareness regarding these effects.

Cholera remains a public health issue in regions around the world. ‘The epidemiology of cholera in the areas of Asia, Africa and the Americas where the disease occurs, continues to evolve’ (Deen et al. in Vaccine 38:A31–A40, 2020 [1]). In managing public health crisis stemming from Cholera outbreaks, epidemiological data are crucial for decision-making pertaining to tactical and strategic interventions. Sensemaking as a process is key in surveillance, modeling, weak signal detection, mapping of high-incidence areas and design of intervention strategies across the spectrum of disaster management (mitigation, preparedness, response and recovery). Weick (Weick in Sensemaking in organizations, Sage, Thousand Oaks, CA, 1995 [2]) refers to sensemaking in terms of ‘…how we structure the unknown so as to be able to act in it. Sensemaking involves coming up with a plausible understanding—a map—of a shifting world; testing this map with others through data collection, action, and conversation; and then refining, or abandoning, the map depending on how credible it is’ (Ancona in Handbook of teaching leadership. Sage Publications Inc, Thousand Oaks, CA, pp 3–20, 2011 [3]). Public health disaster events require leaders and planners to engage in making sense of the impact and inherent vulnerabilities. As articulated in (Nowling et al. in J Appl Commun Res, 2020 [4], ‘they scan their environments for cues of changes and operational threats. After identifying the threat or change, they communicate and work collaboratively to determine the most plausible meaning of these cues (Weick in Admin Soc 38(4):628–652, 1993 [5])’. This chapter explores Cholera epidemics and the critical role sensemaking places in both tactical and strategic interventions. Systems thinking plays a key role in the sensemaking process and approach and is central to the discussion.

Climate change has evolved from an environmental issue, to an energy problem, to a security threat with an impending sense of urgency. It is increasingly recognized as having national security implications with multifaceted national security risks. Climate change increases the intensity and frequency of extreme weather events that threaten nations’ territorial integrity and sovereignty. For example, rising sea levels cause both internal displacement within nations and climate-change refugees across national borders. Some of the climate change threats facing the world in 2020 include droughts, wildfires, floods and global pandemics. Each one has the potential to increase competition and conflict around the world, creating more instability than ever. With many military bases susceptible to these threats, the changing climate has been a focus of military planners for many years. The National Defense Strategy (NDS), the primary planning document that guides decision making within the United States military, emphasizes climate change as a major factor in an increasingly complex security environment. Climate change will likely increase instability and insecurity within already vulnerable regions, particularly in regard to its destructive impacts, as rising seas infiltrate coastal bases, hurricanes batter installations, and wildfires infringe on training ranges and impact readiness. This chapter provides an analysis of climate change as a national security issue in the context of climate science and climate change’s multifaceted security effects with an emphasis on the most disaster-prone regions of Asia and the Pacific.

The world is far from achieving security. The cold war came to an end 30 years ago and impressive progress has been made in terms of development (MDGs, SDGs), but regarding security it seems that the overall patterns have changed without tangibly improving security. So the question is: How to make better sense for security? From a humanitarian and development perspective security is not to be achieved by military means. Security starts with food security and ends with human security/peace. In between, many other dimensions, especially the development dimension come into play. This chapter discusses the importance of the Humanitarian-Development-Peace nexus to make sense of security.

Public health emergencies stemming from infectious disease outbreaks is creating a serious threat to global health security. For example, climate change and extreme weather events threaten to alter and affect geographic areas pertaining to disease vulnerability, such as greater risks of mosquito-borne diseases (dengue, malaria, yellow fever and Zika). The emergence of these disease outbreaks and their influence globally has sparked a renewed attention on global health security and the application of location intelligence. Persistent outbreaks characterize a ‘new normal’ that points to major deficiencies in preparedness, response and recovery initiatives. Malaria mosquito An. gambiae s.l., arabiensis s.s. and funestus s.s represent the main malaria mosquito vectors in sub-Saharan Africa. As reported in WHO (Jacob et al. in Open Remote Sensing 17:11–24, [1]), Malaria is a life-threatening disease caused by parasites that are transmitted to people through the bites of infected female Anopheles mosquitoes. It is preventable and curable. In 2019, there were an estimated 229 million cases of malaria worldwide. The estimated number of malaria deaths stood at 409,000 in 2019. Children aged under 5 years are the most vulnerable group affected by malaria; in 2019, they accounted for 67% (274,000) of all malaria deaths worldwide. The WHO African Region carries a disproportionately high share of the global malaria burden. In 2019, the region was home to 94% of malaria cases and deaths. Sensemaking lies at the heart of location intelligence. Location intelligence is defined as the collection and analysis of geospatial data that are transformed into strategic insights to support operations. Weick (Krizhevsky et al. in Advances in Neural Information Processing Systems, pp 1097–1105, [2]) refers to sensemaking in terms of ‘…how we structure the unknown so as to be able to act in it. Sensemaking involves coming up with a plausible understanding—a map—of a shifting world; testing this map with others through data collection, action, and conversation; and then refining, or abandoning, the map depending on how credible it is’ (Lin et al. in Proceedings of the IEEE International Conference on Computer Vision 2017, pp. 2980–2988, [3]). The application of machine learning algorithms are emerging as key public health intelligence approaches to support tactical, operational and strategic sensemaking. Recent advances that identify the reflective signatures of active mosquito breeding sites, and their temporal evolution, have made predictive algorithms possible to search and identify previously unidentified larval habitats from a Unmanned Aerial Vehicle (UAV), and monitor their activity in real time. Spectral signature is the variation of reflectance of a material (i.e., emittance as a function of wavelength) (www.​esri.​com). These real time aerial surveys can provide spatiotemporal data for targeting interventions to eliminate vectors before they become adult airborne biting mosquitoes, to reduce malaria transmission. Reference capture point habitats for Anopheles gambiae s.l., An. arabiensis s.s. and An. funestus s.s, the main malaria mosquito vectors in sub- Saharan Africa [www.​who.​int], may also be separately identified with this methodology. This chapter points to the application of predictive algorithms coupled with drone surveillance to support sensemaking in support of spatiotemporal data for targeting interventions to eliminate vectors before they become adult airborne biting mosquitoes, to reduce malaria transmission. The sensemaking applies not only to the targeted interventions to eliminate vectors, but also strategic sensemaking that contextualizes this intervention as part of a more holistic/systemic and strategic intervention encompassing a myriad of coordinated interventions across the disaster management spectrum (mitigation, preparedness, response, recovery).

The impact of the opioid crisis is significant resulting in not only rising mortality and morbidity but also significant social and economic costs. As detailed in Felbab-Brown et al. (The Opioid Crisis in America Domestic and International Dimensions. Brookings Paper Series, [1]), ‘Since 2000, there have been 400,000 opioid-involved deaths in the U.S. In the United States of America the number of people dying from opioid overdose increased by 120% between 2010 and 2018’. Stemming from a 2018 survey, it is estimated that upwards of 2.35 million Americans are suffering from an Opioid Use Disorder (OUD). Today’s public health crisis associated with opioid use is characterized by complexity requiring more than one discipline to address the issues. Healthcare professionals must therefore work in inter-professional teams in order to better communicate and address these complex and challenging needs (Bridges et al. in Medical Education 16, [2]). Systems thinking is an approach to better understand the interconnectivity and interdependencies associated with public health issues including how to intervene to improve individual and population health. Inter-professional experiences thereby support development of skills facilitating opportunities to become ‘…collaborative inter-professional team members who show respect and positive attitudes towards each other and work towards improving patient outcomes’ (Bridges et al. in Medical Education 16, [2]). This chapter examines the application of systems thinking and participative model building in an Interprofessional Education (IPE) event held in November 2019 by USF Health, University of South Florida. The IPE event focused on the opioid crisis and was comprised of a learning journey of concept development, collaborative model building and shared sensemaking across healthcare professionals.

Hurricane Maria hit the United States (U.S.) territory of Puerto Rico on September 20th, 2017 as a Category 4 storm. An estimated 2,975 people died in Puerto Rico due to the storm and in many ways the island was devastated from the disaster. The U.S. federal government mounted a large-scale disaster response to mitigate damage by addressing basic needs. However, two years after Hurricane Maria, Puerto Ricans were still reporting difficulties in daily life, including access to health care. Puerto Rico’s higher poverty levels, aging population, and struggle to provide social services have made the effects of Hurricane Maria that much more profound for its residents. The purpose of this chapter is to understand the irreparable damage to Puerto Rico’s infrastructure, population, and health care system caused by Hurricane Maria compared to how other parts of the US have recovered from similar overwhelming natural disasters. Additionally, this chapter will evaluate how these incidents impact security and how sensemaking can be used to increase disaster resilience.

The world is becoming increasingly vulnerable to infectious diseases, creating a global health security issue. Over the last 2 decades, many global and national health crises have emerged such as SARS, H5N1, H1N1, and now COVID-19. The recent COVID-19 pandemic reflects how unexpected events often audit our resilience (Weick and Sutclifffe [10]. The mortality and morbidity statistics associated with COVID-19 has become a key impact metric. At the time of publication, in Canada, upwards of 675,000 cases of COVID 19 have been reported and 17,500 deaths (https://​health-infobase.​canada.​ca/​covid-19/​epidemiological-summary-covid-19-cases.​html?​stat=​num&​measure=​total&​map=​pt#a2). The pandemic has tested and left wanting the global ability to respond to such a threat. Heyman et al. [3] argue that “the world is ill-prepared” to handle any “sustained and threatening public-health emergency.” Such public health emergencies stemming from infectious disease outbreaks are creating a serious threat to societal well-being and national security. The inherent interconnectivity and interdependency within societal public health systems require analysis that provides a deep understanding regarding the potential impact of COVID-19 on populations in response to intervention strategies. In dynamic systems, the effects of an intervention are only evident after a time delay. Understanding the system and its inherent dynamics is a key requirement for sensemaking and is a game-changer in supporting crisis management of complex issues such as a global pandemic. This chapter examines a case study of early sensemaking about the COVD-19 pandemic in Canada through the application of System Dynamics.

Academics claim that past events hold important lessons for risk managers. This chapter is based on that premise, specifically on the possibility that those charged with meeting the challenge of the COVID-19 pandemic can learn lessons from the successes and failures of those who met the challenge of the 1918–1919 Spanish flu pandemic. One of the most interesting aspects of the United States of America’s (USA’s) experience of the Spanish flu pandemic was the degree to which political agendas shaped local responses. Some cities prioritised public health over almost every other consideration. Others prioritised the local economy and the war effort. Cities that prioritised public health generally experienced less death and suffering than those that did not. Early Twentieth Century politics influenced how the Spanish flu pandemic proceeded. Today, New Millennium politics is shaping the COVID-19 pandemic. Plus-ça-change. During the early stages of the pandemic, some countries prioritised public health. Others did not. Regarding numbers of excess deaths attributable to COVID-19, there are sharp differences between the best and worst performing countries. Academics have long argued that Modernity is Janus-faced, gifting us technologies that, contingent on how they are used, either enhance or erode public safety. Consider, for example, nuclear fission and dynamite. It is a sad irony that one of Modernity’s greatest achievements—affordable air service—helped seed COVID-19 across the globe. The COVID-19 pandemic is an echo from the past. Dark Age dystopias—and mentalities—persist. The promissory note that is Modernity is being questioned as never before.

The global health security landscape is characterized as ‘messes’ and ‘wicked problems’ that proliferate in this age of complexity. In designing global health security solutions, ‘…simple, quick fix solutions that flounder in the face of interconnectedness, volatility and uncertainty’ (Jackson in Critical Systems Thinking and the Management of Complexity. John Wiley and Sons, NJ, 2019 [1]) will not suffice and may create unintended consequences. For example, recent years have seen the threat presented by bio-risks heighten significantly. Infectious disease emergencies have included Severe Acute Respiratory Syndrome (SARS), Foot and Mouth Disease (FMD), Middle East Respiratory Syndrome (MERS), H1N1 influenza, Ebola, Zika and now COVID-19. These outbreaks have had significant global and public health impact. Considering the current COVID-19 pandemic, as of January 2021, the COVID-19 pandemic has seen upwards of 100 million cases, 2.1 million deaths, and has significantly impacted the global economy and affected the most vulnerable. The impacts have seen the closure of borders, economic disruptions and failures, strained and overwhelmed health care systems, failure of supply chains, all of which are contributing to a human and national security issue. Sensemaking is the activity that enables us to turn the ongoing complexity of the world into a ‘situation that is comprehended explicitly in words and that serves as a springboard into action’ (Weick et al. in Organ Sci 16:409–421, 2005 [2]). The importance of sensemaking as it pertains to individual and public health is that it enables us to plan, design and take action in real-time to events that affect or ‘shock’ our health and healthcare system. With advances in technology over the last decade, from robust cloud infrastructures, to artificial intelligence, to wearable devices, personalized health interventions are becoming increasingly accurate, accessible, and prevalent. As part of this shift, there has been a growing movement in the field of public health to include personalized medicine as an integrative element of public health which would have the potential to radically transform its methods and character (Evangelatos et al. in Int J Public Health 63:433–434, 2018 [3]). This is changing the landscape as it pertains to health ‘sensemaking’ at the individual and public health level. This chapter presents the research and operationalization of ‘biomarker’ wearable technology as a tool for personalized health to support effective public health responses. This is contextualized within the backdrop of the COVID-19 pandemic.

Maintaining the physical security of an organization entails navigating an intricate landscape of threats, adversaries, systems, and policies. As organizations evolve, become more complex and spatially distributed, security risks increase exponentially and become difficult to fully understand. Organizations entrusted with critical missions and ownership of high risk/high value assets realize that physical protection systems and policies are crucial to prevent unacceptable consequences arising from harmful influences, whether deliberate, accidental or natural. The more serious the consequences, the more important it is to have a high degree of confidence that physical protection will be as effective as planned. The highest level of confidence in physical protection is best achieved through the design and implementation of protective measures that are linked to a thorough understanding of the threats and vulnerabilities. This is achieved through comprehensive and up-to-date analysis of the motivations, intentions, and capabilities of potential adversaries against which protection systems are designed and evaluated. This chapter presents the conceptual development of a Threat Risk Assessment (TRA) Methodology for physical security planning and design. The methodology addresses critical knowledge and capability gaps in TRA approaches, and aims to strengthen the transparency, robustness and defensibility of an organisational Security Risk Management program. The chapter concludes with a discussion of lessons learned and recommendations for future work.

Events such as 9/11, Fukushima Daiichi Nuclear accident, Deepwater Horizon Oil disaster, Hurricane Katrina, Ebola outbreak in West Africa, 2003 US/Canada Blackout, global financial crisis of 2008 and the COVID-19 pandemic all contain the hallmarks of a crisis event. Weick and Sutcliffe (Managing the unexpected: resilient performance in an age of uncertainty. Wiley, San Francisco, 2007 [1]) argue that ‘unexpected events often audit our resilience. Everything that was left unprepared becomes a complex problem’. Leadership plays a pivotal role in managing such crisis (whether they emerge as a black swan event (Taleb in The black swan: the impact of the highly improbable. Penguin Books Ltd, London, 2007 [2]), the ‘elephant in the room’ or as a ‘creeping crisis’ (Boin et al. in Risk Hazards Crisis Public Policy 11(2), 2020c [3]). The Covid-19 pandemic for example has resulted in considerable impact on global health security, human security and the global economy. As described in (OECD in A systemic resilience approach to dealing with Covid-19 and future shocks New Approaches to Economic Challenges, 2020 [4]), ‘…the pandemic has reminded us bluntly of the fragility of some of our most basic human-made systems. Shortages of masks, tests, ventilators and other essential items have left frontline workers and the general population dangerously exposed to the disease itself. At a wider level, we have witnessed the cascading collapse of entire production, financial, and transportation systems, due to a vicious combination of supply and demand shocks’. This highlights the volatility, uncertainty, complexity and ambiguity (VUCA) conditions that shape the crisis landscape and its effect on inherent vulnerabilities that exist within our systems. By drawing upon recent disaster events and more recently the COVID-19 pandemic, this chapter examines sensemaking within the context of crisis leadership and presents a crisis leadership framework focused on absorptive, adaptive and generative capacities (Castillo and Trinh in J Organ Change Manage 32(3), 2019 [5]) to support problem framing, solution navigation and innovation.