John van Trijp* Kees Boersma and Peter Groenewegenkeesboersma.com/wp...paper-on-resilience-with-John.pdf · for organisational resilience based upon the quantitative model by van

Int. J. Emergency Management, Vol. 14, No. 4, 2018 303

Copyright © 2018 Inderscience Enterprises Ltd.

Resilience from the real world towards specific organisational resilience in emergency response organisations

John van Trijp* Libertas in Vivo v.o.f., Nabuccostraat 7, 7323 TE Apeldoorn, The Netherlands Email: [email protected] *Corresponding author

Kees Boersma and Peter Groenewegen Faculty of Social Sciences, Department of Organisational Science, Vrije Universiteit Amsterdam, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands Email: [email protected] Email: [email protected]

Abstract: In this paper, we present a quick overview of six types of resilience to present a minimalistic sketch of the resilience ‘landscape’ and show the definitions for resilience originally have a mechanistic point of view (bounce back after disaster has struck). This is in contrast to the present day approach, where adaptive learning capabilities embedded in strong network relationships are of vital importance for resilience. Eventually, we focus on organisational resilience for emergency response organisations. Organisational resilience is of great importance to an emergency response organisation to cope adequately with outcomes before or after a crisis emerges. We briefly introduce a quantitative organisational resilience model for Dutch emergency response organisations (Safety Regions). We present literature describing and clarifying the variables and attributes based on this quantitative model and draw relevant conclusions.

Keywords: organisational resilience; keystone vulnerabilities; situational awareness; adaptive capacity; quality; emergency response organisation; quantitative resilience model; emergency management; emergency response.

Reference to this paper should be made as follows: van Trijp, J., Boersma, K. and Groenewegen, P. (2018) ‘Resilience from the real world towards specific organisational resilience in emergency response organisations’, Int. J. Emergency Management, Vol. 14, No. 4, pp.303–321.

Biographical notes: John van Trijp is an external PhD candidate at the Department of Organisation Sciences of the Vrije Universiteit of Amsterdam. He received in 2000 an MSc in Environmental Sciences from the Open Universiteit Nederland. In 2010, he received an MPS (Master of Public Safety)

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from Delft University of Technology. His PhD research focuses on the role of Organisational Resilience on the Emergent Design of the Dutch Safety Authorities called ‘Safety Regions’. He published on the subject a peer-reviewed paper and a peer-reviewed book chapter in a prestigious book series. He also published three related conference papers. He is partner/researcher/consultant Public Safety at Libertas in Vivo v.o.f. in Apeldoorn, The Netherlands.

Kees Boersma, PhD, is an Associate Professor at the Department of Organisation Sciences of the Vrije Universiteit Amsterdam. He is the Project Leader of the Amsterdam Research on Emergency Administration (AREA) and the Coordinator of the NWO (The Netherlands Organisation for Scientific Research) project (2015–2018) on “Enhancing smart disaster governance: Assessing the potential of the net-centric approach”. He is (co)editor of several books and journals, including the Regional Editor-Europe of the International Journal of Emergency Services. In January 2016, he was awarded the bi-annual research prize of the Faculty of Social Sciences at the VU Amsterdam. In May 2016, the members of Information Systems elected him to become board member during the general assembly in Rio de Janeiro for Crisis Response and Management (ISCRAM) association. His current research is about the organisational and community response to crisis and disaster situations.

Peter Groenewegen, PhD, is a Full Professor of Organisation Science at the Department Organisation Sciences of the Vrije Universiteit Amsterdam. He received in 1988 his PhD from the University of Amsterdam with his thesis on “Scientists, Audiences and Resources”. His area of expertise is in social network theory and institutional theory. He is since 2013 Director Graduate School of Social Sciences, Faculty of Social Sciences, Vrije Universiteit Amsterdam and is responsible for the development of the Graduate School of Social Sciences and the quality of the PhD trajectory. He is also since 2013 Director of the Research Program in Organisation Sciences, which was evaluated 4.25 (out of 5) in the 2013 research evaluation.

1 Introduction

Emergency services worldwide are ever more challenged by major incidents with natural causes like the 2013 wild fires in Australia and California in the USA in 2014; hurricanes like Katrina which hit Louisiana in 2005, superstorm Sandy that created havoc at the Eastern Seaboard of the USA in 2012 and the severe flooding in 2012 and 2013 in Germany and Romania. Another type of threat consists of infectious diseases with the risk of becoming pandemic like SARS in 2002, H1N1 Swine Flu in 2009 and in 2016 the spreading of the Zika virus in the Americas. Lastly, also manmade activities lead to incidents that are of great challenge to the emergency response services as well. Some examples in 2014 and onwards are industrial fires and explosions like the blaze at a chemical distribution and mixing plant in 2011 in Moerdijk, the Netherlands. Transport incidents (Fire, Explosion) involving pipe, rail and road of which some recent examples are the explosion of a natural gas pipeline in Ghislenghien, Belgium, 2004; in 2013, the derailment and subsequent blaze of a hazardous material freighter train in Wetteren, Belgium and a run-away freighter train loaded with crude oil exploded in the Canadian

Resilience from the real world towards specific organisational resilience 305

town of Lac-Mégantic, Quebec. All these incidents caused numerous deaths, material and economic damage.

To cope in an adequate way for emergency services confronted with these types of incidents and the subsequent aftermath it is very important to possess resilience. Resilience is regarded by emergency response organisations as a coping strategy that enhances the capabilities of those organisations to deal with the aforementioned types of incidents (Boin and McConnell, 2007; Comfort et al., 2001; McCreight, 2010; Paton et al., 2000; Somers, 2009).

We will show in this review the classic mechanistic way to describe resilience is followed up by a modern process version in which a learning component like a feedback loop is used and where a complex network enhances resilience of the observed system.

We present a short overview of different types of resilience to give an impression of the diverse nature ‘resilience’ is today. Next, we introduce important factors that make up for organisational resilience as a marker. These insights will lead to the introduction of a quantitative organisational resilience model designed for Dutch emergency response organisations Safety Regions (a Safety Authority that is responsible for crisis and risk management and – mitigation in the safety domain). In this paper, we first will give the (historical) background of the concept resilience and outline its operationalisation in the crisis management literature. Next, we describe resilience in different systems; and in doing so, we will show that organisational resilience has been under-researched so far in the context of crisis and emergency management. Finally, we will discuss how organisational resilience will help us to understand the relevant aspects (attributes) by which it may be described and what is of importance for a Dutch Safety Region to function in a resilient way.

2 Methodology

We performed a Meta search on the web via Google Scholar® and in addition searched through 88 databases worldwide. Although we did pay attention to older types of papers to show the evolution of resilience, we finally focused on the period 2010–2016 to obtain more recent literature references. We used the keywords: resilience, organisational resilience, adaptive capacity, keystone vulnerabilities, awareness and quality. Followed by a search in the respective libraries and journals decided on basis of relevance, which references to incorporate and use in the review. The relevance was determined by the number of citations the reference yet received and by the uniqueness of the reference itself ultimo with respect to emergency response.

The chosen keywords: find their origin in a designed quantitative model for organisational resilience, which is also known as operational resilience (van Trijp et al., 2012, 2013a). See the right-hand side of Figure 1.

In this paper, we intentionally went beyond the sole definitions of resilience related to emergency response alone, in order to show the wide variety of definitions and applications of resilience in existence today. This means we also applied extra search strings with the keywords based on the different types of resilience as shown on the left-hand side in Figure 1.


Figure 1 Schematic of the different types of resilience discussed in this paper and the attributes for organisational resilience based upon the quantitative model by van Trijp et al. (2012, 2013a) (see online version for colours)

3 Resilience, it started off as a mechanistic system

In the early 19th century, resilience as such was only defined as a construct leading to the present concept of resilience. In particular, this construct appeared as a psychological phenomenon a part of human resilience: the possibility of an individual to thrive in the case of adversity. Until the early 1950s, the construct of resilience was regarded as an unconscious defence mechanism (Jackson et al., 2007; Tusaie and Dyer, 2004). Soon for man, it was recognised the mechanistic approach was too simple. The construct of resilience is a process rather than the bounce back reaction of an individual or an entity in the case of adversity. Within the field of human psychology, a lot of ground breaking work was done by Werner (1997) and Werner and Smith (2001).

But, what is the mechanistic approach that started of resilience? An example from ecology is a drought causing heavy strain on an ecosystem from which the system has to recover by ample rainfall, restoring the original appearance and capabilities of the ecosystem. Imagine similar types of strain as part of a mechanistic process on other systems: rising inflation disrupting a financial system and subsequent reactions of the financial system to stop or decrease inflation. Or for example, civil unrest causing disturbances in a community system. The natural reaction of the authorities is to quell the civil unrest as a mitigating sanction in order to restore the peace. One notices an action – reaction response that is truly mechanistic in nature. In the literature, many definitions of


a mechanistic type of resilience exist, which all share the same basic denominator: to function properly in times of distress or adversity. Distress or adversity come in many variations and manifestations and are all dependent on the system they relate to. Organisations may suffer from distress or adversity as well when put under pressure by external demands or internal ambitions. In the case of an emergency response organisation, we may imagine emerging stress or adversity that arises when the organisation has to deal with a major incident or crisis. Often, resilience is described by a variety of definitions like a passive mechanistic perspective in which an organisation reacts to an external stimulus and restores the original internal order after the incident seized to exist. Some examples are “to sustain normal development despite long-term stress or adversity” (see te Brake et al., 2008), “The capacity to cope with unexpected dangers after they become manifest” (Wildavsky, 1988). “Resilience, that is a measure of the persistence of systems and of their ability to absorb change and disturbance and still maintain the same relationships between populations or state variable” (Holling, 1973). “Resilience is the potential (of organisations and individuals) to adapt to changing circumstances in the face of adversity, and the ability to recover after a disaster or other traumatic event” (Rutter, 1985). “Resilience is the magnitude of disturbance that can be tolerated before a socioecological system (SES) moves to a different region of state space controlled by a different set of processes” (Carpenter et al., 2014). Currently, the use of ‘resilience’ has spilled over to other fields including emergency and organisational management (Martin-Breen and Anderies, 2011).

4 Resilience as a process

To position organisational resilience into the concept of resilience, we will discuss a non-limitative number of other types of resilience chosen to underscore the presence of resilience in the literature. We are aware a number of excellent review papers are published over time. Like resilience in socioecological systems (Folke, 2006, 2016; Folke et al., 2010; Walker et al., 2006) resilience in systems (Haimes, 2009; Levin et al., 2012) and overall resilience (Bhamra et al., 2011; Haigh and Amaratunga, 2010; Ingirige et al., 2008; Martin-Breen and Anderies, 2011; Seville, 2008; Tusaie and Dyer, 2004). Hence, we limited this review to the seven types of resilience as depicted in Figure 1. As organisational resilience is one of the focuses of this review, we also present in Figure 1 on the right-hand side the relevant variables for this type of resilience that include those variables chosen on the basis of their presence in a postulated quantitative model. One the right-hand side, one recognises ‘resilience’ as one of the variables that is used as an attribute that is specifically part of the model and not a duplicate of ‘resilience’ shown in the centre of the diagram. The mentioned model describes in particular organisational resilience for Dutch emergency response organisations or Safety Regions (van Trijp et al., 2012, 2013a). We shall discuss this model briefly under Section 5.

4.1 The descriptor physical resilience addresses several type of subjects: soil, humans and nations

It is in use as a descriptive factor to describe the resaturation of the quality of a soil after this soil underwent several types of stress, either man induced or caused by nature. Some examples are hydraulic and mechanical stress by heavy vehicles compacting the


soil, cultivation or the weather. The changes in the soil porosity caused by mechanical stress, made it possible to quantify physical resilience as such (Dörner et al., 2011; Gregory et al., 2009; Griffiths et al., 2005). Next to this direct application in geological environments, physical resilience is also in use to describe the resilience in humans during or after chronic or intermittent stress. The latter, intermittent stress, is thought to enhance the physical resilience while chronic stress just undermines it (Epel et al., 2010). Physical resilience may also describe the resilience of nations, cities and communities in the case of adversities caused by climate change or disasters. One may think of droughts; earthquakes; flooding by rising sea level; hurricanes and landslides (Fernandez et al., 2012; Sovacool, 2012; Toft et al., 2013).

4.2 Ecological resilience describes the behaviour of natural systems other than man-made systems

Those natural systems are of a biological type of ecosystem in which the development and adaptation of populations is observed under several types of stress. Ranging from natural and non-natural origin like predation by animals or plants and man induced stress by hunting, fishing and the direct or indirect impact of climate change (Holling, 1973, 1987; Hughes et al., 2005; Ostrom, 2004).

4.3 Community resilience is just like physical resilience wide in expression as communities may differ by definition

Community resilience characterises a social system that has boundaries and shared common values. A typical example shows when a community is subject to disasters followed by the way how the community handles the effects in order to regain or restore its shared common values and integrity. To do so a community relies not only on resilience rooted in a networked adaptive system of adaptive capacities (Norris et al., 2007) but also on inherent resilience capabilities based upon conditions and characteristics of a society which can be mobilised in case of adversity (Tierney, 2014). Shared common values can take the shape of a conceptual framework in social–economic–human–physical and natural capital, which can act as indicators or health indices for community resilience (Houston, 2014; Magis, 2010; Mayunga, 2007; Norris et al., 2007). Community resilience is in the literature also described as a blanket term which contains all types of resilience which are of significance to community resilience as a whole in case of natural disasters (Cutter et al., 2008). The authors show community resilience is just more than a definition; it is networking strategy that helps communities to overcome adversities.

4.4 Urban resilience relates closely to community resilience but with a focus on cities and regions

Cities that possess urban resilience are able to cope with severe natural; economic; biomedical; social; technological or political hazards. As cities are very complex with a great variety of networked infrastructural systems combined with large human communities, it is obvious cities incorporate both systems and communities alike that are vulnerable to the effects of hazards. Urban resilience defines the sustainability of these systems and communities when struck by the hazards. They vary in spatial and temporal


scale: just on street level or citywide and may last a few seconds (e.g., road congestion) to months or years (e.g., population issues) (Bosher and Coaffee, 2008; Godschalk, 2003; Lang, 2011; Müller, 2011). As with community resilience, Müller (2011) points out a city or a region with a strong and diversified economy along with good governance as better possibilities to overcome adversities than those cities or regions who have not. This indicates a networking strategy is likely to be effective when discussing community resilience. We notice that urban resilience and community resilience share common values about networking and are additional to each other in terms of focus (infrastructure and infrastructure users).

4.5 Human resilience

When we focus on the users (humans), we find the term ‘human resilience’ also named ‘resilience in human development’ or ‘personal resilience’. This definition is in order to those situations where humans face large-scale trauma like pandemics, war, terrorist attacks or non-man-made disasters where the integrity (or physical and mental health), or everyday type of trauma like workplace adversity where humans are challenged to overcome this traumatic event. This challenge may show itself as a short spike of discomfort or distress when the individual faces the challenge or by a prolonged period needed to recover to the original state of equilibrium. All related to the severity and type of trauma suffered coupled to the individual characteristics of the person involved (Bonanno, 2005; Jackson et al., 2007; Masten and Obradovic, 2008). Masten and Obradovic (2008) describe a multitude of factors which play a key role in the resilience of young people varying from systems functioning inside a person (e.g., immune system) to ones outside like a peer group or family relationships. They conclude young people find themselves in a strong network of relationships, which provides resilience in relationship with adaptation.

We note resilience as such should be envisaged to be in a permanent state of flux where resilience is enhanced by strong networking conditions instead of viewing it as a mechanistic coping strategy relying on ‘bounce back’ system features.

This permanent state of flux was first described by Holling (1973) for social–ecological systems in which he described the behaviour of interacting populations of species in self-contained ecosystems like fresh water lakes. He and co-authors later expanded their view to a permanent state of flux capable of learning from events happened. This model shows as a lemniscate in which an adaptive cycle depicts four ecosystem functions (rapid exploitation and collection of resources, accumulation of biomass and increased connectivity and rigidity, collapse and reorganisation). The cycle reflects the changes in “the potential that is inherent in the accumulated resources of biomass and nutrients” (Y) and “the degree of connectedness among controlling variables” (X). A combination of autonomous cycles along a vertical scale connected with a learning loop (remember) which feed information from one upscale cycle into a downscale cycle, the reverse is also possible (revolt): the whole system received the name ‘panarchy’ (Allen and Holling, 2010; Holling, 1987, 2004; Walker et al., 2004).

4.6 Resilience engineering

When we look at definitions and descriptions about resilience engineering found in the literature, we find not only is it an approach in system safety that focuses on the presence


of failures and successes, but also it contains learning capabilities as well to anticipate on upcoming adversities or failures. As such, a resilient system should be capable to follow the changes that occur which during adversities. It is also monitoring and acting upon the changing boundaries of the system that result in an optimised system capable to handle the next disruption (Branlat and Woods, 2010; Hollnagel, 2008; Woods and Hollnagel, 2006; Woods, 2007).

5 Organisational resilience and emergency response organisations

Organisational resilience of the Dutch emergency response organisation (a Safety Region) is defined by van Trijp et al. (2012, 2013a, 2014), as the mathematical outcome of situational awareness, resilience as a generic, keystone vulnerabilities, adaptive capacity and quality. These variables are part of a quantitative model, which provides the opportunity to express organisational resilience as a figure. In its most simple and generic form, it looks like this (1):

f(Rero) = Rero(Rawa + Rkv + Rac + Rq + ε), (1)

where f(Rero) = the dynamic organisational resilience of an emergency response organisation; Rero = the level of resilience of an emergency response organisation; Rawa = the level of awareness of an emergency response organisation; Rkv = the level of importance of keystone vulnerabilities of an emergency response organisation; Rac = the level of adaptive capacity of an emergency response organisation; Rq = the level of quality of an emergency response organisation and ε = the level of unspecified data and items which are a function of resilience too. The full version of the equation is based on a specific type of a multi-criteria analysis: a value tree, see Figure 2. When focused on the Dutch emergency response organisations, called a safety region, the model allows for a quantitative representation of organisational resilience by means of resilience units (RU). Under the given circumstances for a Dutch Safety Region, a maximum of 22.54 RU is feasible.

A Dutch Safety Region is a complex organisation that provides emergency response. By law, the Safety Regions came into effect on 1 October, 2010 (Anonymous, 2010). A Safety Region consists of originally local fire departments, the regional fire service, medical emergency service and municipal medical departments into one Safety Authority under one command and management structure. The Netherlands has 25 Safety Regions. The purpose of those regions is to provide better protection of the society from risks and hazards, offer improved emergency management during and after major incidents and crises. Act as one administrative organisation that coordinates and controls the medical services, the disaster mitigation service, the fire service, operational use of law enforcement, operational use of local authorities and enhanced operational and administrative mitigation capabilities.

A case study about a 2011 industrial blaze in the Netherlands using this model was published in van Trijp and Ulieru (2014), where the organisational resilience of the Safety Region involved was found to be only 20% of the maximum achievable dynamic organisational resilience possible. A complicating factor was that the effects of the incident transgressed the borders between three neighbouring Safety Regions, creating complex command and control issues between the three Safety Regions and other stakeholders involved. Hence, the authors found the Safety Region where the incident


took place was not prepared and resilient enough to deal properly with this particular type of incident.

Figure 2 Value tree describing dynamic organisational resilience f(Rero) with attributes plus weight factors (shown as boxes with values on top) and undetermined utility values (shown as spheres at the right hand side of the box). Maximum achievable dynamic organisational resilience is reached when all utility values equal 1.00. When ε is nullified: f(Rero)max = 22.54 RU; f(Rero)max = maximum achievable dynamic organisational resilience. RU = resilience units

Source: Adapted from van Trijp et al. (2012; 2013a). See Appendix A for a full declaration of the attributes.

When we observe organisational resilience in an emergency response context, it is important to realise emergency response is more than just mitigating an incident or crisis. A Dutch Safety Region has also duties to prevent the occurrence of incidents and crises as stipulated in the Netherlands Safety Region Act. This is a very important observation with respect to organisational resilience as such. We will show in this paper resilience is not only associated with activities associated with the period after an incident or crisis occurred but also with the period before they happen. A good graphical representation around the incident is the Bow Tie model (Ale, 2009). The Bow Tie model shows on the left-hand side all the pathways that lead up to the incident (reduction and readiness) and on the right-hand side all the pathways that originate from the incident (response and recovery). It is possible to block the pathways by lines of defence (LOD). Hence, either preventing an incident from happening or mitigate the effects after the incident occurred. We will show a major factor to facilitate this is the capacity of an organisation to learn from previous experiences.

In the quantitative model for organisational resilience by van Trijp et al. (2012, 2013a); the potential of organisations and individuals to adapt to changing circumstances before a crisis occurs is of vital importance for optimal resilience. Since the 1990s in


New Zealand like in other countries, there has been a change to monitor organisational resilience in the reduction and readiness phase instead of just looking at the response and recovery phase. Hence, introducing some kind of feedback mechanism is inherently part of resilience (McDaniels et al., 2008; McManus et al., 2008; Paton et al., 2000). This aspect is a major change with respect to the older definition of resilience that is truly mechanistic in origin (bounce back). This also means organisations proactively have to identify risks and vulnerabilities (Seville, 2008). This is also known as situational awareness (Vargo and Seville, 2011). Vargo and Seville state in their paper that situational awareness stretches beyond just identifying risks and vulnerabilities but should include previous knowledge to form a solid and robust view to anticipate on any future adversities: introducing a learning or feedback loop. Hence, lifting organisational resilience above the mechanistic approach of the traditional meaning for resilience “to function properly in times of distress or adversity”. Others support this view in literature although definitions and approaches may differ to some extent. All authors agree previous experience plays a major role in situational awareness (Danielsson et al., 2014; Ross et al., 2014; Woods et al., 2015). As such, situational awareness is more a continuous process than a moment in time for the emergency response organisation and its staff. The leading theme, a common operating picture based on collating data, is the main objective followed by subsequent analysis and interpretation leading to situational awareness. This process is a feedback loop model and as part of organisational resilience, it has a thorough impact on organisational resilience as a whole. It is of a circular nature based upon learning capabilities of the organisation. Hence, we conclude organisational resilience in emergency response as such cannot be solely interpreted as a pure mechanistic approach. An approach where the capacity to cope with unexpected dangers after manifestation, coupled with the response of the organisation after the disruption has struck is prevalent. It is also of great importance to observe organisational resilience before the incident or crisis occurs and learn from incidents and crises that did occur (feedback loop).

The quoted quantitative model consists of several variables, of which the variable ‘resilience’ consists of five different attributes. Three of those address the situation before an incident or crisis occurs:

• The potential – of organisations and individuals – to adapt to changing circumstances in the face of adversity, and the ability to recover after a disaster or other traumatic event”.

• “The sustenance of normal development despite long-term stress or adversity”.

• “The readiness of an organisation before the shock or disruptive event”.

In addition, two address the situation after the occurrence of an incident or crisis:

• “The capacity to cope with unexpected dangers after they become manifest”

• “The response of the organisation after the disruption has struck”.

So far, we discussed in this paper the concept of resilience extensively, next we focus on the other variables in the following paragraphs (see also Figure 1, right-hand side).


5.1 Adaptive capacity

Adaptive capacity as such, suggests an organisation can respond to changes in its external environment in by changing its internal organisation in order to recover from any damage caused in its internal structure. It suggests the harm is done first and the subsequent recovery is a reaction to the inflicted harm: a reactive process (Dalziell and McManus, 2004). Dalziell and McManus (2004) describe various ways by which an organisation can adapt: the use of an existing solution to address the problem, the use of an existing solution in a new innovative way to address the problem and the use of a novel solution to address the problem. These ways can either evolve organically when an organisation has sufficient self-organising capacity or in a mechanistic way when the response of the organisation is directed and coordinated by formal in house structures like communication channels. By Folke et al. (2005), a thorough review of adaptive governance in social–ecological systems is presented. In addition to the reactive process according to Dalziel and McManus (2004), they describe the possibilities of adaptive capacity to be part of strong reciprocal feedback systems. This suggests the presence of a feedback loop system is active as well: active adaptive management that stretches beyond the mechanistic approach. By the introduction of the terms novelty and innovation, the definition of adaptive capacity progresses a step further. Although formulated for complex systems within an ecological framework, one sees readily similarities with complex systems like emergency response organisations (Allen and Holling, 2010; Tierney, 2014). They state the capability to learn and introduce new insights is necessary for organisations to remain dynamic and functioning. Otherwise, systems may become non-evolving, mechanistic systems excluding the internal capital within. Adaptive capacity of social–ecological societies as emergency response organisations need four main requirements to maintain social–ecological resilience or in our case, organisational resilience. They are: the will to maintain resilience; impact knowledge of current behaviour and direction of change; proaction and the capacity to change behaviour (Fazey et al., 2007). Again, we find a strong emphasis on the capacity to learn which is of vital importance to the adaptive capacity of an organisation as a whole. Further refinement of adaptive capacity is presented by McManus et al. (2007, 2008) by the following elements: ‘silo mentality’, ‘communications and relationships’, ‘strategic vision and outcome expectancy’, ‘information and knowledge’ and ‘leadership, management and governance structures’. Addressing those elements may enhance adaptive capacity. With further enhancement possible when information sharing and relationships with external stakeholder are addressed and optimised.

5.2 Keystone vulnerabilities and quality

The same authors who presented in the previous paragraph a further refinement of adaptive capacity plus McManus et al. (2008), present a list with components which make up for keystone vulnerabilities. These keystone vulnerabilities have the potential to have a large negative impact on the organisation’s organisational resilience. The components vary from planning strategies, exercises, internal and external resources to organisational connectivity. The negative impact may show itself by chronic features which linger on in time when not dealt with in the organisation, but can also present themselves in an instantaneous fashion when a system or organisation fails when confronted with a crisis or incident. On the basis of the presented definitions, it is obvious


for an emergency response organisation that knowledge of its keystone vulnerabilities is of vital importance. Hence, proper management of keystone vulnerabilities should be part of daily organisation performance to overcome them. Aleksić et al. (2012) present a fuzzy model for management of keystone vulnerability assessment. Although designed for small and medium business enterprises (SME) they use a similar set of components as described by McManus et al. whose perspective we just introduced in this review. The fuzzy model evaluates and ranks the management of keystone vulnerabilities on the level of processing and on the level of the enterprise itself. Hence, providing insight in the weight and importance in the keystone vulnerabilities. The more important a keystone vulnerability is (= a higher weight, importance), the more influential it is for the operation management of the enterprise at hand. In addition, Stephenson (2010) introduced two extra keystone vulnerability components:

• “Robust processes for identifying and analysing vulnerabilities” which are intrinsic processes that cover the vulnerabilities of the organisation and the environment it is situated within in order to manage those vulnerabilities properly.

• ‘Staff engagement and involvement’ which covers in depth the way organisational staff is engaged and involved in the development of the organisation’s resilience.

This also represents the quality of leadership and the empowerment of lower ranks as defined in her thesis by McManus (2008).

When we look at quality of organisations, in general we find a different approach. One of the aspects we find is high-reliability organisations (HROs). These are organisations which operate in hazardous conditions but experience less adverse effects than a non-HRO. The HRO’s perceive safety as a top priority. Safety in this aspect is safety as part of the organisation that has the possibility to influence the world it operates in Sutcliffe (2011). On the other hand, Sutcliffe suggests HROs should possess resilience as well. Weick et al. (2008) argue that next to the HROs preoccupation with safety, learning capabilities are just as important. In this paper, we show the capability to learn is also an intrinsic part of resilience and Weick, Sutcliffe and Obstfeld recognise resilience is part of a HRO. Weick, Sutcliffe and Obstfeld describe there is much overlap between HROs processes and quality programs intended to improve quality as such. Like the European Foundation for Quality Management (EFQM) Excellence Model designed for performance management based on retrospective learning capabilities (Wongrassamee et al., 2003). In this EFQM model, a feedback loop collects new information that is generated from four result criteria: people satisfaction; customer satisfaction; impact on society and business results. This information feeds into five enabler criteria to improve the quality of: leadership; resources; policy and strategy; people management and processes. As a result improved organisational innovation and learning occurs. Weick, Sutcliffe and Obstfeld note also that quality programs have the tendency to overlook complex emergent problems in contrast to HROs processes, which inherently promote resilience. In other words, quality programs are rigid with respect to new emerging complex issues in contrast to the fluid concept of resilience.

van Trijp and Breur (2014) found a similar type of outcome for the Dutch regional fire services on organisational resilience when the model was used to determine the effect of the introduction of a new occupational safety and quality management program according to the EFQM excellence model (Wongrassamee et al., 2003). As the regional fire services represent 90% or more of all staff of a Safety Region, they are representative


for the Safety Region as a whole (van Trijp et al., 2012, 2013a). The effect found was the introduction of the quality management program attributes just over 2% to the whole of organisational resilience. The origin of this low score was determined to be an over-presence of non-dynamic aspects like plans combined with a prime focus on “how the organisation is ready on paper”.

Hence, it was concluded the EFQM excellence model as a quality program did not suffice in creating organisational resilience (van Trijp and Breur, 2013b) which, is in line with the described observation of Weick et al. McManus (2008) describes in her thesis a resilient organisation has three main qualities over non-resilient organisations: “a greater awareness as organisation and its environment, an increased knowledge of the organisations keystone vulnerabilities and the ability to adapt the tool an organisation already has when facing adversity”. Hence, we postulate these are the three cornerstones defining quality for an emergency response organisation from an organisational resilience perspective.

6 Discussion and conclusion

In this paper, we have focused on a limited set of aspects that primarily deal with organisational resilience and its attributes in relation to emergency response organisations. We mentioned and described other types of resilience without claiming we would present a full array of the literature available. The definitions found for resilience are clearly in motion: from a non-evolving mechanistic approach that focuses on the rebound effect the current trend is to formulate resilience as a process that is stimulated by adaptive learning. Resilience is also enhanced by a complex and diverse network in which an organisation or community resides. We found the latter to be true for emergency response organisations that inherently are network embedded. The use of organisational resilience in relationship to emergency response organisations is still rather new and is yet open for debate. When we look at the current trends for resilience (adaptive learning, networking), we foresee a greater role and impact of this topic to define the organisational capabilities of emergency response organisations. In the literature, this observation finds support (Burnard and Bhamra, 2011; Lundberg and Rankin, 2013; Lundberg et al., 2012; Sommer and Njå, 2012). Furthermore, Boin and McConnell (2007) point out in case of adversity it is necessary to achieve a spot on response by the emergency response organisation to identify and train first responders so they can act effectively on their own. Especially when the current command structure fails, they should seize the initiative and perform their duties. Somers (2009) identifies teams should be trained to improvise and find solutions on their own when operating under high resilience conditions which is rather similar to the findings of Boin and McConnell (2007). They are fine examples of what organisational resilience promotes: a dynamic process of learning, networking and adapting.

Aside from the presented case and quantitative model for Dutch Safety Regions that comprises all the mentioned aspects, the findings may be vital to any emergency response organisation today and in the future times to come. As such, upcoming research should have its prime focus on the organisation and first responder in order to determine whether enhanced organisational resilience does provide better task equipped emergency response organisations. This is in contrast to current practice where strict regulations, contingency


planning and protocols seem to be of prime importance for emergency response organisations today.

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Appendix A

a Sustenance of normal development despite long-term stress or adversity b Capacity to cope with unexpected dangers after they become manifest c Potential (of organisations and individuals) to adapt to changing circumstances in

the face of adversity, and the ability to recover after a disaster or other traumatic event

d Readiness of an organisation before the shock or disruptive event e Response of the organisation after the disruption has struck f Ability to look forward for opportunities as well as potential crises f(Rero) Dynamic organisational resilience of an emergency response organisation f(Rero)max Maximum achievable dynamic organisational resilience of an emergency response

organisation g Ability to identify crises and their consequences accurately h Level of enhanced understanding of the trigger factors for crises i Level of increased awareness of the resources available both internally and

externally j Level of better understanding of minimum operating requirements from a recovery

perspective k Level of enhanced awareness of expectations, obligations and limitations in relation

to the community of stakeholders, both internally (staff) and externally (customers, suppliers, consultants etc.)

l Level of importance of buildings, structures and critical supplies m Level of importance of computers, services and specialised equipment


n Level of importance of Individual managers, decision makers and subject matter experts

o Level of relationships between key groups internally and externally p Level of importance of communication structures q Level of perception of the organisational strategic vision r Level of importance of leadership and decision making structures Rac Level of adaptive capacity of an emergency response organisation Rawa Level of awareness of an emergency response organisation Rero Level of resilience of an emergency response organisation Rkv Level of importance of keystone vulnerabilities of an emergency response

organisation Rq Level of quality of an emergency response organisation RU Resilience units s Level of importance of the acquisition, dissemination and retention of information

and knowledge t Degree of creativity and flexibility that the organisation promotes or tolerates u Level of greater awareness of itself, its key-holders and the environment with which

it conducts business w Level of ability to adapt to changed situations with new and innovative solutions

and/or the ability to adapt the tools that it already has to cope with new and unforeseen situations

ε Level of unspecified data and items which are also a function of resilience

Documents

John van Trijp* Kees Boersma and Peter Groenewegenkeesboersma.com/wp...paper-on-resilience-with-John.pdf · for organisational resilience based upon the quantitative model by van