# Full Text: Emergent Teams for Complex Threats

> Extracted from `2020_EmergentTeams.pdf`

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Emergent Teams for Complex Threats 
 
May 15th, 2020 
 
Richard J. Cordes 1,2  
(1) Remotor Consulting Group, 
(2) Cognitive Security and Education Forum 
richardj.cordes@gmail.com 
Daniel A. Friedman, PhD  1,3 
(1) Remotor Consulting Group, 
(3) University of California, Davis, Dept. of Entomology 
danielarifriedman@gmail.com 
 
A B S T R A C T
 
While the underlying, fundamental principles of warfare have long remained unchanged, recent 
social and technological developments have necessitated new approaches to conflict 
management. Specifically, the introduction of nuclear weapons and the maintenance of large 
military budgets during peacetime in the latter half of the 20th century have changed the risk 
calculus of conflict among state and non-state actors. Consequently, the operating environment 
has changed. Extant, centralized actors have experienced new adversities such as ideological 
warfare and sustained low-intensity and gray zone conflict while new, decentralized participants 
have emerged and evolved. Nation states, as a part of normal operations, now have to contend 
with the potential for novel, emergent hazards from a myriad of Complex Threat Surfaces in 
littoral and other environments. We highlight how Complexity Science has been of use in the 
analysis of Complex Threat Surfaces in the military and within civilian organizations, 
particularly High Reliability Organisations or HROs. This paper discusses the intersection of 
Complexity Science and Military Science by focusing on analysis of counterinsurgency and 
counterterrorism operations. We highlight rapid reorganization, pooling collective expertise, 
and the assembly of novel organizational components as a potential basis for developing 
spontaneous expertise, actionable intelligence, and solutions to the aforementioned novel, 
emergent hazards.  
Introduction 
This paper uses a Complexity Science 
framework to understand how the rapid 
assembly 
of 
teams 
and 
successful 
counterinsurgency and related efforts 
are linked. Beginning with a vignette of 
the 2008 attack on Mumbai by Lashkar-
e-Taiba, general ideas and trends in 
Military 
Science 
related 
to 
counterinsurgency efforts and Complex 
Threat Surfaces will be discussed. This 
introduction 
to 
Complex 
Threat 
Surfaces will be followed by a discussion 
of Complexity Science as an approach 
for modeling and de-risking Complex 
Threats. In alignment with literature on 
both High Reliability Organizations and 
Complexity Science, reorganization and 
adaptation are addressed as potential 
avenues 
for 
responding 
to 
novel, 
emergent 
problems. 
Finally, 
Rapid 
Team Assembly is presented at the 
intersection of Complexity and Military

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Emergent Teams for Complex Threats, 2020 
 
2 
 
Science as a basis for developing 
spontaneous 
expertise, 
actionable 
intelligence, and solutions to novel, 
emergent problems. We conclude with a 
discussion 
of 
best 
practices 
and 
opportunities for future work. 
Lessons from Mumbai 
To understand how Complexity Science, 
the 
rapid 
assembly 
of 
teams, 
counterterrorism, 
counterinsurgency, 
and other related efforts are linked, we 
begin with a recollection of the 2008 
attack on Mumbai. On November 23rd, 
2008, ten men in their early twenties left 
the Pakistani port city of Karachi by 
boat. They carried light armament, 
some 
fire-starting 
material, 
fake 
passports, 
and 
satellite 
phones 
(Haberfeld & Hassell, 2009; PTI, 2020). 
They set out for Mumbai, the seventh 
most populous city in the world, a mega-
city of more than fourteen million 
people, the capital of the Indian State 
Maharashtra (United Nations, 2018). 
Enroute, they hijacked a fishing vessel 
registered in Mumbai, murdered its 
crew (Haberfeld 
& 
Hassell, 
2009; 
Marwaha, 2017), and forced the captain 
to re-introduce the vessel into normal 
fleet 
traffic 
(Kilcullen, 
2012). 
On 
November 26th, seven kilometers from 
Mumbai’s coastline, the captain was 
killed. With the vessel fully under 
control, the ten men begin their 
approach toward the shore. By 8:10 
p.m. that evening, the group of ten split 
into two groups, one going ashore and 
the other continuing by boat. By 8:30 
p.m., both groups have split again, 
resulting in five teams. Now dressed in 
casual clothes to blend with the local 
population, each of the five teams make 
their approach toward their respective 
targets (Haberfeld & Hassell, 2009; 
Marwaha, 2017; Shahrzad Rizvi & Kelly, 
2015). By 9 p.m., IEDs (improvised 
explosive devices) had been left in the 
taxis which transported the individuals 
to these locations (Ministry of External 
Affairs India, 2009). Upon arriving, they 
maneuvered and fired indiscriminately 
into restaurants, train stations, and 
social 
establishments 
near 
their 
respective locations. At 9:38 p.m., a pair 
assaulted the Taj Mahal Hotel from the 
main lobby, twenty non-combatants 
were left dead within the first few 
minutes (Ministry of External Affairs 
India, 2009). 
By 10 p.m. there were explosions at gas 
stations, 
civilians 
had 
been 
taken 
hostage, and police, accompanied by 
three senior counterterrorism agents, 
had not only been counterattacked but 
successfully 
ambushed 
before 
even 
arriving on the scene. The van they were 
ambushed in was then hijacked and used 
to carry out attacks with a surviving 
officer sitting paralyzed in the backseat 
(Burton & West, 2008; Haberfeld & 
Hassell, 2009). It is around this time 
that Zabiuddin Ansari, a phone-operator 
working from a command post in 
Pakistan made a call by satellite phone 
to a subunit which was hardening its 
position in a hotel. It is on this call that 
he states the following: 
“Tell [the Indian Media] 
this is just the trailer. The 
real movie is yet to come”  
This message, in retrospect, could be 
viewed as hauntingly accurate (Glanz et 
al., 2014; Haberfeld & Hassell, 2009; 
Ministry of External Affairs India, 2009;

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Emergent Teams for Complex Threats, 2020 
 
3 
 
PTI, 2020; Shahrzad Rizvi & Kelly, 
2015).  Despite the deployment of a 
counterterrorism 
force 
which 
had 
superior 
training, 
equipment, 
and 
support, the attackers, acting as semi-
autonomous 
groups 
with 
minimal 
equipment, managed to keep a city of 
over fourteen million people under 
siege for three days. By the end of the 
conflict, 172 people were dead and 308 
were wounded (Haberfeld & Hassell, 
2009). Some background on the group 
and the basis for their relative success 
will be discussed. 
The group responsible for training the 
young men in the attack was Lashkar-e-
Taiba (Haberfeld & Hassell, 2009), 
meaning “The Army of the Pure” 
(Spindlove & Simonsen, 2010; Tankel, 
2013). Lashkar-e-Taiba is primarily 
concerned 
with 
removing 
Indian 
military presence from Jammu and 
Kashmir and is composed of religious 
radicals affiliated with an ultra-orthodox 
form of Sunni Islam. In compliance with 
their beliefs, the group is known for 
foregoing suicide missions, in favor of 
“dare-devil” missions (Haberfeld & 
Hassell, 2009). Despite being a banned 
terrorist organization within Pakistan, 
they maintain multiple training and 
operational camps in the Pakistan-
controlled sub-regions within Kashmir 
(Spindlove & Simonsen, 2010) and their 
operations frequently result in links to 
the ISI, or Inter-Services Intelligence, 
the primary intelligence agency of 
Pakistan 
(Dill, 
2012; 
Fair, 
2011; 
Kambere et al., 2011; Rotella, 2012; 
Wirsing, 1998). This is unsurprising, 
given the ISI’s involvement in the 
dismantling of the Soviet occupation of 
Afghanistan and the resulting close ties 
with liberation movements and guerilla 
operations in the region (Kambere et al., 
2011; Sen, 1992). 
ISI has nurtured a thriving market for 
illegally trafficked goods for decades, 
even going as far as using the National 
Logistic Cell (NLC), a logistics company 
nationalized by the Pakistani Army 
which was used to supply arms to the 
Mujahideen in Afghanistan, to run drugs 
over the same routes (Haq, 1996; Sen, 
1992). Intelligence estimates in 1992 
suggested that Pakistani drug dealers 
had 
amassed 
the 
world’s 
largest 
stockpile 
of 
opium 
and 
heroin 
(Kambere et al., 2011; Sen, 1992). As 
indicated by their use of the NLC, ISI 
does not just passively allow this 
environment of criminality, they are an 
active part of it. Apprehended drug 
traffickers and scouts from Norway and 
Japan admitted that their handlers had 
close ties with generals in the region 
(Haq, 
1996; 
Sen, 
1992). 
The 
insurgencies in the neighboring regions 
made the arms trade lucrative, and, as 
stated earlier, ISI has been involved in 
trafficking directly. While access to 
funding, munitions, and armament and 
lack of meaningful government oversight 
in the regions in which they operated 
enabled Lashkar-e-Taiba’s operations in 
2008 (Haberfeld & Hassell, 2009; 
Spindlove & Simonsen, 2010), they were 
not the primary factors in the group’s 
success. Across all notable analyses 
reviewed, there was a conclusion in 
common regarding the causes of their 
success: 
superior 
information 
and 
exploitation of OSINT, or open-source 
intelligence, as a basis for rapid, 
spontaneous 
planning 
and 
for 
reorganization (Burton & West, 2008;

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Emergent Teams for Complex Threats, 2020 
 
4 
 
Goodman, 2011; Haberfeld & Hassell, 
2009; Ministry of External Affairs India, 
2009; Shahrzad Rizvi & Kelly, 2015). 
The group made notable efforts prior to 
the 
event 
to 
develop 
actionable 
intelligence and a working knowledge of 
the intended area of operations. The 
terrorists applied for jobs in the kitchen, 
booked rooms at the hotel, and visited 
and mapped buildings. Most of the 
information they used to plan and 
modify operations was open-source and 
available to the public. The groups made 
use of back entrances and corridors not 
open to civilians and barely known by 
the reacting counterterrorism force and 
used these areas, discovered in prior 
reconnaissance, to counterattack the 
counterterrorists, ambush civilians, and 
escape and evade when outmatched 
(Burton & West, 2008; Haberfield & 
Hassell, 2009; Shahrzad Rizvi & Kelly, 
2015). During the event, a command 
center in Pakistan was in contact with 
the group using satellite phones. The 
command center used live news and 
Twitter to inform decision-making and 
to inform personnel on the ground of 
counterterrorism operations (Goodman, 
2011). In one notable incident, a tweet 
with a picture posted by the BBC 
revealed the position and intent of a 
counterterrorism unit on the ground in 
real-time, resulting in a counterattack 
(Shahrzad Rizvi & Kelly, 2015). Marc 
Goodman, an authority on terrorist use 
of open-source data, in a talk on the 
topic, noted that while terrorists had 
used public-access tools such as Twitter 
and Google Earth before, this was the 
first notable event in which they mined 
social media data in real time and did so 
at such a scale (Goodman, 2011). The 
groups confirmed potential high value 
targets by using Google and social 
media, 
remapped 
operations 
using 
tweets, GPS devices, and Google Earth, 
and even intercepted communications at 
the hotel, alerting the terrorists to room 
numbers 
of 
high-value 
targets 
(Goodman, 2011; Haberfield & Hassell, 
2009; Ministry of External Affairs India, 
2009). 
In 
contrast 
to 
Lashkar-e-Taiba’s 
OSINT-informated improvisation and 
spontaneous planning, counterterrorist 
forces were continuously delayed by 
lack of flexibility. The Indian emergency 
planners had planned for events like the 
2008 Mumbai attack, but “lacked a 
modular and flexible structure when it 
came to communicating and responding 
in a non-routine fashion” (LaRaia & 
Walker, 2009). In some cases, the lack 
of a QRF (quick reaction force) in 
Mumbai was noted as a basis for failure 
(Shahrzad 
Rizvi 
& 
Kelly, 
2015), 
however, the Indian Navy was actually 
stationed in Mumbai at the time of the 
attack but lacked the necessary signed 
release to use military assets in civilian 
domain. A special forces unit with the 
Indian Army was delayed as well 
because they did not have “their own air 
assets” to travel to the site (Kronstadt, 
2008; Shahrzad Rizvi & Kelly, 2015). It 
may be important to note that the Indian 
Government had access to all of the 
same information the terrorists did but 
failed to attempt to assemble specialists 
who could have made use of the data 
(Goodman, 2011; Haberfeld & Hassell, 
2009; Shahrzad Rizvi & Kelly, 2015). 
Shivshankar 
Menon, 
India’s 
Prime 
Minister at the time of the attack, noted

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Emergent Teams for Complex Threats, 2020 
 
5 
 
that “[the key was rapid analysis]… we 
didn’t have it.” (Glanz et al., 2014). 
While traditional metrics for readiness 
and capability might indicate that the 
conflict was significantly asymmetric in 
favor of the counterterrorists (e.g. 
monetary value of equipment, personnel 
count, extent of training), this vignette 
supports the findings of other analyses 
on asymmetry, which indicate that the 
stated metrics may not necessarily be 
representative of the balance of power 
or indicate probability of outcomes 
(Arreguín-Toft, 
2001; 
Berglund 
& 
Souleimanov, 2020). Asymmetry in 
resources having little correlation with 
success in conflict is acknowledged as a 
recurring 
phenomenon 
and 
is 
an 
important 
characteristic 
of 
conflict 
which developed in the latter half of the 
20th century, (Arreguín-Toft, 2001) the 
reasons for this emergent characteristic 
will be discussed further. 
Complex Threats in the 
Gray Zone 
More broadly, the introduction of 
nuclear weapons and the maintenance of 
large military budgets by the remaining 
geopolitical 
superpowers 
after 
the 
conclusion of World War Two (Roser & 
Nagdy, 2013) created an environment 
which changed the risk calculus of 
conventional conflict (Rauchhaus, 2009; 
Treverton & Posen, 1992). This shift in 
risk is sometimes interpreted as a cause 
of a “Long Peace” (Pinker, 2012) or 
“Nuclear Peace” (Rauchhaus, 2009), 
which, at a glance may be supported by 
data on battle deaths per year (Peace 
Research Institute Oslo, 2020). Though 
this may be true of direct, conventional, 
interstate 
warfare, 
this 
has 
not 
necessarily 
been 
true 
for 
military 
conflict in general. Instead, its “timing, 
intensity. and [outcomes]” have changed 
(Arreguín-Toft, 
2001; 
Rauchhaus, 
2009). Governments have adapted the 
way they conduct conflict, and as a 
result, nurtured a new domain of 
operations often referred to as “The 
Gray Zone” (McCarthy et al., 2019; 
Troeder, 2019). Actions which are 
aggressive in nature but moderated in 
order to prevent triggering discrete 
change 
in 
diplomatic 
status 
(e.g. 
declarations of war) vis-a-vis Article 5 of 
the North Atlantic Treaty or Article 51 
of the United Nations Charter are 
classified 
as 
Gray 
Zone 
Warfare 
(McCarthy et al., 2019; NATO, 1949; 
United Nations, 1945; Votel et al., 
2016). Intelligence agencies of many 
nations, not just superpowers, managed 
conflicts through proxy warfare and by 
sponsoring non-state actors with aligned 
goals (Acharya & Marwah, 2010). Often 
assisted by training from state actors, 
non-state actors used guerilla tactics and 
operated in a decentralized, networked 
fashion 
in 
the 
interest 
of 
self-
preservation. One of the results of this 
decentralization 
has 
been 
a 
deep 
embedding of these non-state actors in 
local networks, including Governments, 
illicit 
trafficking 
operations, 
and 
religious groups; this embedding blurs 
the line between licit, criminal, and 
guerilla networks, allowing groups to use 
this embedding as a form of camouflage 
and a basis to acquire resources without 
sponsors (Haberfeld & Hassell, 2009; 
Haq, 1996; Kambere et al., 2011; 
Kilcullen, 2012; Sen, 1992; Spindlove & 
Simonsen, 2010). As centralized state

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Emergent Teams for Complex Threats, 2020 
 
6 
 
actors learned to react to the new tactics 
being used against them and to practice 
deterrence, 
decentralized 
non-state 
actors continued to evolve, solving 
complex informational problems such as 
the imperfect monitoring of cells, inter 
and 
intragroup 
communication 
of 
activities, and reducing risk and cost of 
operations (Dale E. Lichtblau, Brian A. 
Haugh, Gregory N. Larson, Terry 
Mayfield, 2006; Naftali, 2009). The 
smaller size and limited resources of 
non-state 
actors 
required 
them 
to 
become resilient and adapt where larger 
nations may have reinforced. More 
importantly, it required them to become 
more innovative in finding opportunities 
and exploiting weaknesses (Dolnik, 
2007). 
Based on analyses of the events in 
Mumbai, the attack can be characterized 
as a successful exploitation of Complex 
Threat Surfaces. In hardware security, 
attack surfaces can be defined as “the 
sum 
of 
all 
possible 
security 
risk 
exposures” (Bhunia & Tehranipoor, 
2011) and in practice refer to domains 
of risk exposure often described in 
layers (Torkura et al., 2019). The term 
may have equal value in describing 
surfaces of attack in Military Science 
and the study of counterterrorism, 
sometimes described as “The Long War 
on Terrorism” (LeRoy, 2008). However, 
non-adversarial 
events 
are 
also 
of 
interest to National Security, such as the 
response 
to 
natural 
disasters, 
pandemics, 
or 
even 
post-terrorism 
clean-up operations such as hazardous 
material removal post-9/11 (McEntire, 
2014). Thus, for the purposes of this 
paper we discuss “Complex Threat 
Surfaces” rather than “attack surfaces” 
to emphasize the need for an integrated 
management approach to various kinds 
of non-linear failure modes. As stated 
earlier, terror and insurgent groups have 
become 
more 
innovative 
in 
their 
approach 
to exploiting 
weaknesses. 
Groups are incentivized to maximize 
impact while minimizing risk and cost. 
This has resulted in targeting Complex 
Threat 
Surfaces 
which 
cannot 
be 
effectively defended linearly, intuitively, 
or by using certain established legacy 
measures (Dolnik, 2007; Haberfeld & 
Hassell, 2009; LaRaia & Walker, 2009; 
Troeder, 2019; Votel et al., 2016), as 
evidenced 
by 
the 
failure 
of 
counterterrorism 
measures 
which 
successfully red flagged behavior by 
Lashkar-e-Taiba 
(Shahrzad 
Rizvi 
& 
Kelly, 2015) to deter or reduce the 
efficacy of the Mumbai Attack, and 
those 
which, 
if 
successfully 
compromised, represent opportunities 
for cascading, non-linear failure (Lee et 
al., 2016; Salmeron et al., 2004; Sims, 
2018). We now turn to a discussion of 
the 
interdisciplinary 
paradigm 
of 
Complexity Science and highlight the 
role of rapidly assembled teams in 
responding to Complex Threat Surfaces. 
From Complex Threats to 
Complexity Science  
The 
science 
of 
Complexity, 
or 
Complexity Science, is the study of 
systems that are composed of many 
interacting subunits (Gershenson, 2013; 
Gordon, 2014; Lawson, 2013; Mantri & 
Thomas, 2019). Such systems, for 
example brains or battlefields, often 
exhibit characteristics such as adaptive 
capacity, 
radical 
historicity, 
self-
organization, 
non-linear 
dynamic

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Emergent Teams for Complex Threats, 2020 
 
7 
 
behaviour. To manage and de-risk these 
challenging attributes of Complexity 
Science is an interdisciplinary field that 
studies the patterns and principles of 
complex adaptive systems (CAS) in 
general and specific (Gershenson, 2013; 
Mantri & Thomas, 2019; Massari, 2019; 
Mitchell, 2009). Robert Maxfield, a 
trustee of the Santa Fe Institute, which 
was founded to study complexity, at a 
symposium 
on 
complexity 
for 
the 
National Defense University stated that: 
“The scientifically significant results [of 
Complexity Science] are so far mostly in 
the physical and biological domain, but 
the metaphors have proven to have 
tremendous 
appeal 
and 
utility 
in 
studying humans and human social 
systems” 
(Maxfield, 
1996). 
Indeed, 
recent decades have seen increased 
interest in research and applications of 
Complexity approaches in Military, 
Informational, 
and 
Geopolitical 
contexts (Dittmer, 2014; Rosenberg, 
2017). Specific examples here illustrate 
the point that Complexity Science 
approaches can add significant value, 
reflected by unique explanations or 
predictions, when considering Military 
Science (Lawson, 2013; Williamson, 
2009), counterinsurgency approaches 
specifically 
(Ford, 
2012; 
Miralles 
Canals, 2009), and team formation 
approaches. 
Complexity Science has been used to 
help 
model 
and 
characterize 
the 
behavior and structure of insurgencies 
and terrorist organizations. Results of 
these 
analyses 
provide 
utility 
in 
understanding their nature, as noted by 
Maxfield and others (Maxfield, 1996). 
Work 
has 
been 
done 
to 
model 
insurgencies and terrorist organizations 
as complex adaptive systems, revealing 
evolutionary 
tendencies 
already 
modeled in natural and computational 
systems (Dale E. Lichtblau, Brian A. 
Haugh, Gregory N. Larson, Terry 
Mayfield, 
2006; 
Ilachinski, 
2012). 
Beyond terrorist groups, Complexity 
Science has been used to model 
domestic military forces as well, such as 
interpreting 
frigate 
crews, 
littoral 
(coastal) forces, and air forces as 
complex adaptive systems (Bar-Yam, 
2003; Ellis, 2017; Murphy, 2014). 
Across different types of military forces, 
the manifested behavior or “phenotype” 
of a group arises emergently from the 
interaction 
between 
the 
guiding 
principles of the group, and the specifics 
of the environmental context. The 
variable 
expression 
of 
underlying 
characteristics 
of 
terrorist 
groups 
provides them with adaptive flexibility 
across environmental context. In order 
to help predict surfaces of attack and 
tactics, strategists must identify both 
essential characteristics of a group and 
relevant elements of the environment. 
For example, terrorist groups with 
similar characteristics are more likely to 
engage in frequent violence in regions 
which have higher press access (Chai, 
1993). Here there are striking parallels 
to the findings and implications in the 
literature on genetics and epigenetics 
(Frisch, 2011; Grisogono & Ryan, 2003; 
Maleszka, 2016; Weyrich et al., 2018). 
This “epigenetic” spread of insurgencies 
thus may be modeled as following 
principles found in collective behavior 
models (Friedman et al., 2020; Gordon, 
2016), resulting in patterns of spread 
and behavior that look remarkably 
similar to the results of ant-colony

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Emergent Teams for Complex Threats, 2020 
 
8 
 
optimization 
algorithms 
(Dorigo 
& 
Stützle, 2019; Shiwakoti et al., 2011; 
Vodák et al., 2018; Wood, 2015). 
Decentralized terrorist groups appear to 
have self-organizing and autopoietic 
(self-meaning-generating 
(Allen 
& 
Friston, 2018; Dos Santos, 2018)) 
characteristics. These attributes are 
especially apparent in recruiting spaces, 
littoral 
environments, 
and 
volatile 
battlefield situations (Kilcullen, 2012). 
Destroying 
central 
leadership 
of 
terrorist 
groups 
in 
cases 
where 
leadership is highly centralized may 
result in the collapse of the organization. 
For example, the offer of an amnesty 
deal to the leaders of Al Aqsa by the 
Israeli Government caused a nearly 
immediate, systemic collapse of the 
organization (Chai, 1993). However, 
destroying central leadership when the 
organization is decentralized may just 
result 
in 
fracture 
and 
increased 
complexity, as groups may fracture 
along hidden or pre-existing ideological 
lines just as easily as they may fracture 
on a basis of geography or methodology 
(Abdallah, 2019; Chai, 1993; Nessel, 
2012). Separation from intellectual or 
political leadership can result in groups 
over-imitating 
their 
parent 
organizations, resembling well-studied 
social and psychological phenomena 
such as cargo cults and over-imitation. 
This over-imitation can lead to senseless 
violence detached from any notable 
purpose (Chai, 1993; Eliade, 1965; 
Lyons et al., 2007; Nessel, 2012; 
Stanner, 
1958). 
Understanding 
the 
autopoietic and self-organizing nature of 
these groups prevents a false sense of 
security which can so often come from 
material victories, such as the breaking 
of a stronghold or the assassination of 
leaders (Abdallah, 2019), as fractured 
groups or groups which remain despite 
fractured leadership or the completion 
of the explicit goals they were formed 
with are not uncommon. For example 
the Stern Gang (LEHI) remained active 
after the creation of the state of Israel, 
as did the IRA after the establishment of 
the Irish Free State, and the Ku Klux 
Klan 
in 
the 
United 
States 
after 
leadership left the organization (Chai, 
1993). 
Future work in the spirit of Complexity 
Science could elaborate and formalize 
the intersection of well-modeled natural 
phenomena 
(epigenetics, 
collective 
behavior), 
modern 
computational 
techniques (network analysis, machine 
learning) and counterinsurgency efforts. 
Such a cross-sector framework for 
understanding behaviors may lead to the 
ability to influence outcomes (e.g. 
through the use of control theoretic 
approaches) and eventually even the 
ability 
to 
design 
distributed 
counterinsurgency systems (Newkirk et 
al., 2012; Shahrzad Rizvi & Kelly, 2015; 
Sofea Azrina Azizan, Izzatdin Abdul 
Aziz, Bandar Seri Iskandar, 2017). We 
hold that Complexity Science can thus 
provide useful direction to those who 
hold responsibility for operations and 
force design to be mindful of the 
complexity 
of 
the 
operating 
environment (Maxfield, 1996; Murphy, 
2014; Saperstein, 1996). We now turn to 
an investigation of rapid team assembly 
in located, remote, and hybrid contexts, 
from the perspective of Complexity.

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Emergent Teams for Complex Threats, 2020 
 
9 
 
Emergent Teams and 
Rapid Reorganization  
Within various civilian domains, some 
of which overlap with military, High-
Reliability Organizations (HRO) have to 
contend with Complex Threat Surfaces 
as well (Porte & Consolini, 1998; Weick 
& Sutcliffe, 2015). These domains 
include air traffic control, power grid 
management, wildland firefighting, and 
intensive care units (Christianson et al., 
2011; McKeon et al., 2006; Porte & 
Consolini, 
1998). 
Similar 
to 
their 
military counterparts, these domains are 
often areas where failures cascade and 
victories accumulate, where small errors 
can create macro-level impacts that are 
not necessarily proportionate to the 
perceived severity of the error viewed in 
isolation (De Bruijne & Van Eeten, 
2007; See et al., 2014; Szumilas et al., 
2011). In these environments where 
minimizing chance of failure is key, 
optimization can be interpreted to come 
at the cost of fragility (Mamouni 
Limnios et al., 2014). As a consequence 
of the importance of reliably managing 
Complex Threat Surfaces, a robust 
literature exists on these environments 
(Weick & Sutcliffe, 2015). Work from a 
Complexity perspective on collective 
behavioral algorithms highlights the 
relevance of ecological factors such as 
degree and type of variability, and threat 
of catastrophic disruption (Flaherty, 
2019; Gordon, 2014; Smith & Jenks, 
2006). 
While most early work on strategies 
within HROs focuses on co-located 
groups, HRO research has adapted over 
the years to include remote and hybrid 
paradigms. Work has been done to 
integrate 
remote 
organizational 
components and even nonhuman or 
unmanned assets into HRO frameworks 
(Brooker, 2013; Dalamagkidis et al., 
2011; Grabowski & Roberts, 2019). In a 
modern information workspace and 
battlefield, AI-augmented human actors, 
and autonomous AI systems, play an 
increasingly important role. A key 
strategy found in the analysis of HROs 
and 
related 
work 
on 
emergency 
response 
is 
the 
maintenance 
of 
organizational fluidity or the ability to 
rapidly pool collective expertise, share 
information, and reorganize in order to 
respond to emergent problems in the 
operating environment (Grabowski & 
Roberts, 2019; McEntire, 2014; Rigaud 
& Hollnagel, 2006; Weick & Sutcliffe, 
2015). In oil and gas production, 
flexible, horizontal mechanisms are 
used to rapidly reorganize and integrate 
operators and supervisors into “tiger 
teams”, groups of experts that are 
assigned to solve specific problems 
relevant to the background of personnel 
(Grabowski 
& 
Roberts, 
2019). 
In 
Toyota, “swift market analysis response 
teams” 
(SMART) 
were 
organized 
around customer complaint content 
based on background relevance and 
reorganized on completion to greatly 
increase turnover on errors and handle 
recalls safely, this was successful to such 
an extent that elements of the role 
reorganization process were built into 
SCRUM, 
a 
widely 
used 
project 
management 
framework 
(Weick 
& 
Sutcliffe, 2015). It is important to note 
that in both cases personnel were not 
required to be co-located in order to 
participate (Grabowski & Roberts, 2019; 
Weick 
& 
Sutcliffe, 
2015). 
This

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Emergent Teams for Complex Threats, 2020 
 
10 
 
transition 
toward 
more 
distributed 
frameworks aligns research on civilian 
HROs 
with 
research 
on 
complex 
adaptive 
systems, 
the 
challenges 
militaries 
face, 
and 
potential 
best 
practice. These same attributes of 
organizational fluidity and flexibility are 
echoed in military literature on force 
design, counterterrorism, doctrine, and 
counterinsurgency as well (Bar-Yam, 
2003; Ellis, 2017). 
In 
respect 
to 
force 
design, 
organizational 
fluidity 
has 
been 
acknowledged as essential in modern 
militaries. Special attention has been 
paid to littoral warfare, where land, 
water, and amphibious forces are faced 
with 
the 
paradox 
of 
maintaining 
flexibility while being composed of 
assets which are the result of decades-
long investment cycles (Ellis, 2017; 
Royal Canadian Navy, 2016). Modern 
littoral 
environments 
are 
often 
characterized by the myriad of Complex 
Threat Surfaces that can be exploited by 
local insurgencies and related groups. 
These Complex Threat Surfaces include 
the surface of the water itself in the form 
of mines, unmanned vehicles, and 
submerged vessels, as well as attacks 
from the air via drones (Bar-Yam, 2003; 
Hill, 2009). 
To this end, it is difficult to design a 
perfect system to ensure that any 
specific 
vessel, 
given 
any 
single 
configuration of crew and equipment, 
would be capable of deterring every 
threat (Ellis, 2017; LaGrone, 2017; 
Royal Canadian Navy, 2016; Shaul, 
2019). As described in a Complexity-
informed analysis of rapidly-assembling 
teams on frigate ships, “it is not 
reasonable to expect a linear response as 
circumstances 
will 
dictate 
specific 
actions” – in such cases, operators on 
the ship operate semi-autonomously and 
teams emerge in response to threat 
assessments 
(Bar-Yam, 
2003; 
Ellis, 
2017). For such situations, pre-planned 
responses help maneuver the crew into 
positions 
from 
which 
they 
can 
confidently follow or diverge from 
doctrine. 
This 
ability 
to 
rapidly 
reorganize is especially important given 
terror and insurgent groups’ tendency 
toward mimetic transfer and copy-cat 
attacks, trading and adapting strategies 
that worked for other groups (Hill, 
2009). Organizations in this space have 
had notable successes in the exploitation 
of Complex Threat Surfaces present 
when military and civilian ships operate 
in littoral environments (Burton & 
West, 2008; Hill, 2009). In response to 
these 
dangers 
are 
projects 
like 
STANFLEX, which is a modular ship 
design implemented by the Danish 
Navy, offering the capability of hot-
swapping modular weapons, sensor, and 
staging platforms while in port in order 
to rapidly reorganize equipment and 
crew configurations (Ellis, 2017; Mun, 
2018). 
Rapid Reorganization of leadership in 
counterinsurgency 
efforts 
has 
been 
documented to be impactful. The 
Malayan Emergency (Malay Peninsula, 
1948-1960) is frequently looked to as a 
successful 
counterinsurgency 
(Hack, 
2009; Robinson, 2008) and will be 
discussed 
briefly. 
Though 
the 
counterinsurgency had many failures at 
the 
beginning, 
there 
was 
a 
reorganization of top leadership to 
include civilians. This structure, once

## Page 11

Emergent Teams for Complex Threats, 2020 
 
11 
 
allowed to proceed, quickly replicated at 
provincial and district levels resulting in 
a decentralization of intelligence and 
local operations (Robinson, 2008). With 
increased information sharing and the 
inclusion of locals, less focus was given 
to 
combatting 
the 
rebels 
and 
organizations took significant steps to 
begin addressing the social, economic 
and political problems which drove 
rebel support instead (Hack, 2009; 
Komer, 1972; Robinson, 2008). These 
emergent, cohesive civilian and military 
management apparatuses robbed rebels 
of public support and contributed 
significantly 
to 
the 
war 
effort 
at 
remarkably low costs (Komer, 1972). 
This style of reorganization and rapid 
assembly of organizations or teams with 
the inclusion of populations in the area 
of operations was replicated in Iraq in 
2003 and was viewed as imperative to 
operations in the region, especially due 
to the complexity of the operating 
environment (Grabowski & Roberts, 
2019; Green, 2007; McChrystal et al., 
2015; Ricks, 2006). 
To close, as well as provide an 
optimistic contrast with the Mumbai 
events, we relate a vignette from 1993, 
when a group of terrorists affiliated with 
Al Qaeda planned to put into action a 
multistage attack to exploit Complex 
Threat Surfaces across the island of 
Manhattan in New York City (Dahl, 
2014; United Nations, 2018). The 
terrorists intended to storm the island in 
watercraft (Burton & West, 2008) and 
split into several tactical teams. The 
group’s plan included bombs at key 
locations like landmarks and transport 
infrastructure such as the Lincoln and 
Holland tunnels and the ferries in lower 
Manhattan. Simultaneously, other teams 
were to raid hotels such as the Waldorf-
Astoria, St. Regis, and U.N. Plaza with 
the intention of finding high-value 
targets and inflicting as much damage to 
soft-targets as possible (Burton & West, 
2008; Dahl, 2014). Similar to the pre-
planning in Mumbai, the group in New 
York did on-site reconnaissance in 
advance, 
taking 
detailed 
notes 
of 
stairwells, 
cameras, 
and 
security 
personnel location and attire (Burton & 
West, 2008). The FBI, upon discovery 
of the plot, began to coordinate multiple 
previously-unconnected 
individuals, 
such as controlled informants from 
previous 
operations, 
terrorism 
task 
forces, and local government and police. 
With this reorganization in place, it was 
decided that they would allow the group 
to centralize their operation in relative 
safety in order to prevent fracture. 
When 
the 
group 
began 
building 
explosives, their safe house was raided, 
eight arrests were made, and the plot was 
foiled with no loss of life (Dahl, 2014). 
This New York vignette, contrasted with 
the eerily similar Attack on Mumbai, 
illustrates how rapid reorganization and 
assembly of teams in response to novel, 
emergent 
threats 
can 
meaningfully 
impact outcomes in counterinsurgency 
operations. 
Conclusion 
In this paper we have used the 
interdisciplinary 
approach 
of 
Complexity 
Science 
to 
highlight 
Complex Threat Surfaces as a key 
variable for counterinsurgency efforts 
and other gray zone efforts in today’s 
cyberphysical 
battlefield. 
We 
have 
highlighted 
key 
principles 
that

## Page 12

Emergent Teams for Complex Threats, 2020 
 
12 
 
differentiated event outcomes, such as 
the ability of opposing forces to rapidly 
reorganize, propagate information, and 
reassemble teams. As teams in the 
modern operating environment become 
increasingly remote, new challenges are 
presented, but also new advantages can 
become realized (Grabowski & Roberts, 
2019). The complex threat surface 
approach highlights the need for further 
work at the intersection of information 
sharing 
system 
design 
(Rigaud 
& 
Hollnagel, 
2006), 
decentralized 
intelligence or OSINT (Brafman & 
Beckstrom, 2006; Green, 2007), and 
other topics. Conceptual models and 
innovation technologies arising from 
this integrative approach may prove 
useful in service of counterinsurgency 
efforts now and in the future.

## Page 13

Emergent Teams for Complex Threats, 2020 
 
13 
 
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*Extraction method: pymupdf*