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Normal Accident Theory Versus High Reliability Theory: A Resolution and Call for an Open Systems View of Accidents

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We resolve the longstanding debate between Normal Accident Theory (NAT) and High-Reliability Theory (HRT) by introducing a temporal dimension. Specifically, we explain that the two theories appear to diverge because they look at the accident phenomenon at different points of time. We, however, note that the debate’s resolution does not address the non-falsifiability problem that both NAT and HRT suffer from. Applying insights from the open systems perspective, we reframe NAT in a manner that helps the theory to address its non-falsifiability problem and factor in the role of humans in accidents. Finally, arguing that open systems theory can account for the conclusions reached by NAT and HRT, we proceed to offer pointers for future research to theoretically and empirically develop an open systems view of accidents.
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Human Relations
DOI: 10.1177/0018726709339117
2009; 62; 1357 Human Relations
Samir Shrivastava, Karan Sonpar and Federica Pazzaglia
call for an open systems view of accidents
Normal Accident Theory versus High Reliability Theory: A resolution and
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Normal Accident Theory versus High
Reliability Theory: A resolution and call
for an open systems view of accidents
Samir Shrivastava, Karan Sonpar and Federica Pazzaglia
ABSTRACT We resolve the longstanding debate between Normal Accident
Theory (NAT) and High-Reliability Theory (HRT) by introducing a
temporal dimension. Specifically, we explain that the two theories
appear to diverge because they look at the accident phenomenon
at different points of time. We, however, note that the debate’s
resolution does not address the non-falsifiability problem that both
NAT and HRT suffer from. Applying insights from the open systems
perspective, we reframe NAT in a manner that helps the theory to
address its non-falsifiability problem and factor in the role of humans
in accidents. Finally, arguing that open systems theory can account
for the conclusions reached by NAT and HRT, we proceed to offer
pointers for future research to theoretically and empirically develop
an open systems view of accidents.
KEYWORDS high reliability
negentropy
normal accident
open system
theory
requisite variety
It is hardly possible for organizational theorists to write about accidents
without referring to Normal Accident Theory (NAT) and High Reliability
Theory (HRT). But this is not to say that the theories enjoy uncritical
acceptance. Moreover, the proponents of the two theories cannot seem to
agree whether their views complement or contradict each other. The genesis
of the NAT-HRT debate can be traced back to Sagan’s (1993) book, The
1357
Human Relations
DOI: 10.1177/0018726709339117
Volume 62(9): 1357–1390
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limits of safety. Sagan applied the theories to analyse accidents and near-
misses in the nuclear weapon systems in the US during the Cold War. While
Sagan’s decision to explicitly contrast and evaluate the theories won support
from Perrow (1994: 212), the founder of NAT, who described the compari-
son as a ‘signal service’ to organizational theory; it invited criticism from La
Porte (1994: 211), the founder of one of the main branches of HRT, who
thought that the ‘strawman approach’ had pitted ‘complementary perspec-
tives against each other as if they were in competition’. So who is correct,
and why this unusual disagreement between the protagonists?
Previous attempts to reconcile the NAT-HRT debate have proven
inconclusive (Rijpma, 1997), indicating that the matter is not straight-
forward. Vaughan (1999: 296) attributes ‘The Great Divide’ in the area to
the theories focusing on different things and reaching different conclusions.
She points out that while NAT focuses on structure and claims that complex
and tightly coupled structures inevitably trigger system-wide accidents, HRT
focuses on processes and identifies organizational initiatives that can prevent
such accidents. Reviewing the relevant literature, Rijpma (2003) asserts that
the NAT-HRT debate has reached a dead-end and efforts to resolve the
debate would prove unfeasible.
To complicate matters, the reasoning underpinning NAT and HRT
appears to be non-falsifiable (Rosa, 2005). If a tightly coupled complex system
were to succeed in avoiding an accident, NAT proponents would attribute the
safe outcome to the system in question being not complicated enough. Simi-
larly, in the event of an accident in a highly reliable organization, HRT pro-
ponents would argue that the accident occurred because the organization had
ceased being reliable in that it had not followed recommended processes. Thus
the two theories cannot be tested as they can rationalize any outcome and
almost always explain away their failure to make a prediction. Noting this
weakness, Rosa (2005) issues a call for integrating NAT and HRT through a
falsifiable theory. Rosa’s call serves as the motivation of this article.
We begin by briefly reviewing and critiquing NAT and HRT. We then
revisit the NAT-HRT debate to highlight contentious issues. Thereafter, we
attempt to resolve the debate by introducing a temporal dimension. We point
out that while HRT focuses on processes related to a dynamic situation and
offers insights about the period leading up to the point of accident, NAT
identifies the key elements of organizational structure and circumstances at
the point of time of an accident. Having established the vantage points of
the theories, we claim that NAT and HRT are not incommensurate. We
however note that the debate’s resolution fails to solve the non-falsifiability
problem. In search of solutions, we turn to open systems theory in the latter
half of this article.
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We treat organizations as open systems and apply our interpretation
of systemic properties to reframe NAT in a manner that makes it possible to
test the theory. We point out that the reframed NAT can incorporate the
damage potential of accidents, and is able to better account for the role of
humans in accidents. Finally, we issue a call for developing an open systems
view of accidents by discussing how systemic insights can explain the
accident phenomenon in general.
NAT and HRT: A critical review
NAT
Analysing the organizational aspects of the nuclear accident at Three Mile
Island, Perrow (1981, 1984) concluded that accidents are inevitable or
‘normal’ in some types of technological systems. Thus NAT got its name.
Summarized below are the key notions from NAT (Perrow, 1984) that are
germane to our arguments.
Although Perrow does not formally define the term system, his notion
of a system is critical to NAT. As he points out, any unintended and
untoward event that disrupts the ongoing or future output of a system could
be viewed as an accident. Consistent with open systems thinking, Perrow
argues that one could draw mental boundaries around one’s focal system
(also see Leveson, 2004). He then divides a system into four levels. In his
division, at the first level of a system lies an individual part – for example, a
valve. Functionally related collections of individual parts are said to make a
unit at the second level. Arrays of units make a subsystem in the third level,
and subsystems combine to make a system in the fourth level. Beyond the
system lies the environment. In this scheme, failures at the first two levels,
even if they temporarily disrupt the output of the entire system, do not
qualify as accidents. Instead, they are called incidents. So a failure of a unit
or a part (say a component like a valve) would be called an incident. Only
disruptions at levels three and four would qualify as accidents. Perrow points
out that most engineered safety features (ESFs), such as redundant
components, emergency shut-offs, suppressors, and so forth, are incorpor-
ated in systems to prevent incidents from transitioning into accidents.
Perrow (1984) implies that accidents generally begin with failures of
one or more lower level components that escalate to higher levels usually
through defeating ESFs. If the failures progress through a system to levels
three and four in an anticipated sequence, interacting in a manner that is
comprehensible to the designers of the system and to those trained to operate
it, then the failures culminate in a component failure accident. So, according
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to NAT, one could avoid component failure accidents through better
designed ESFs, preventive maintenance, operator training, and so forth.
Armed with data from several industries, Perrow (1984) claimed that
on rare occasions, some complex systems suffered an accident owing to
multiple failures, which interacted with each other in ways that could neither
be anticipated nor comprehended. Perrow called such accidents normal
accidents or system accidents. NAT therefore implies that one cannot, by
definition, prevent system accidents. All the same, in his treatise, Perrow,
mainly with a view to forewarn societies, identifies two properties – complex
interactions and tight coupling – that make systems susceptible to system
accidents. We discuss each in turn.
Complex interactions are interactions that occur in unfamiliar
sequences, or unplanned and unexpected sequences, and which are either not
visible or not immediately comprehensible (Perrow, 1994). The factors said
to drive complex interactions in a system include the presence of components
that have multiple functions (multi-functionality means that the components
can fail in more than one direction at once); physical proximity of
components; specialized knowledge of personnel that limits their awareness
of interdependencies; several control parameters with potential interactions;
and the need to decipher unfamiliar or unintended feedback loops and make
inferences.
A system is said to be tightly coupled when there is minimal time lag
between the processes it executes; the sequence of processing does not vary;
there is only one method available to accomplish a task; little slack is possible
in supplies, equipment, and personnel; buffers and redundancies are inbuilt
with there being little scope of introducing them at a later stage; substitution
of supplies, equipment, and personnel is not readily possible, and where
possible, it can be done only in a prescribed manner (Perrow, 1984).
The two systemic properties or dimensions – the nature of interactions
within a system, and the degree of coupling amongst its subsystems –
described above are integral to NAT’s main thesis, which may be stated thus:
an odd failure in technological systems that are at once complexly interactive
and tightly coupled can, under peculiar circumstances, lead to system
accidents. When circumstances are just right, the failure can trigger other
failures that can interact amongst each other in a manner that defies compre-
hension. To make matters worse, the complex interactions can cascade very
rapidly in tightly coupled systems, which, by design, as discussed, afford
minimal slack and preclude the possibility of substituting either personnel or
material. In effect, recovery from failure under such circumstances is almost
impossible. The challenge then, from an organizational perspective, is to
acquire the capacity to simultaneously cope with complex interactions and
tight coupling.
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According to NAT, decentralization aids organizations to cope with
complex interactions. The rationale is that an organization can respond to
unanticipated interactions in real time only if it empowers those proximal to
the processes to improvise. Similarly, centralization aids in coping with tight
coupling – the thinking being that only an agency that is privy to the big
picture can be expected to sensibly override local considerations to ensure
the stability of the entire system. Organizations operating complexly inter-
active and tightly coupled systems cannot be simultaneously centralized
and decentralized. Therefore, as per NAT, organizations are structurally
incapable of coping with system accidents.
NAT also identifies the factors that promote linear interactions and
loose coupling within systems. Thus one can visualize how the interaction
and coupling dimensions might be charted along a continuum to generate a
two-by-two matrix (see Figure 1). Perrow (1984) populates all the quadrants
of the matrix with various types of systems ranging from a post office to a
nuclear power plant. NAT however focuses on tightly coupled and complexly
interactive systems that populate Quadrant 2 – the top right quadrant.
Interestingly, Perrow observes that all the systems in Quadrant 2 (with
the apparent exception of military systems) execute transformation
processes. That is, the systems transform the main raw material that they
work with in some fundamental way.
1
We believe that the observation about
transformation processes reveals something important about accidents. For
Shrivastava et al. Normal Accident Theory versus High Reliability Theory
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Interactions
*
Nuclear plant
*
Chemical plants
*
Space missions
*
Nuclear weapons
accidents
*
Military early
warning
*
Aircraft
*
DNA
Dams
*
*
Power grids
*
Airways
*
Assembly line
production
*
Mining
R & D firms
*
ComplexLinear
Coupling Tight Loose
University
*
*
Marine transport
*
Some continuous
processing, e.g.
drugs, bread
*
Rail transport
*
Junior college
*
Trade schools
*
Single -goal agencies (motor
vehicles, post office)
*
Most
manufacturing
*
Military
adventures
*
Multi -goal agencies
(Welfare, DOE, OMB)
1 2
3 4
Figure 1 NAT: Interaction/coupling chart
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reasons not entirely clear, Perrow does not take his observation to its logical
conclusion. We will revisit this issue. For now, we identify one of NAT’s
major weaknesses that will need to be addressed if the theory is to provide
impetus to empirical work.
Our concern pertains to NAT’s intra-system levels. Perrow acknowl-
edges that his scheme ‘has its ambiguities, since one could argue interminably
over the dividing line between part, unit, and subsystem . . .’ (1984: 65). All
the same, he insists that the scheme has practical value. We argue that while
the scheme could help delineate technical systems, it has lesser applicability
in an organizational or a socio-technical context. Perrow states that the
equivalent of a valve (i.e. a part) in the socio-technical domain could be a
human operator. His scheme overlooks the fact that the human mind has
the capacity to engage across all of the four arbitrary levels. Operators can
deliberately, as Vaughan (1999) warns us, trigger system accidents. And by
the same token, they can pre-empt system accidents through timely action.
Unless Perrow’s scheme can account for such outcomes, it may not be valid
to equate an operator failure with merely an incident. Admittedly, shifting
the focus away from operator errors and emphasizing organizational
properties is one of NAT’s major achievements. Nonetheless, we need to ask
whether NAT might have swung the pendulum to the other extreme by
equating human operators with valves.
We also note that the extant literature contains several examples of
disagreements over whether an accident is a component failure accident or
a system accident (Hopkins, 1999, 2001). These disagreements will persist
because NAT’s intra-system levels, being arbitrary, lend themselves to varying
interpretations. Going strictly by Perrow’s interpretation, only a minuscule
percentage of accidents would qualify as system accidents. This fact has led
critics to raise legitimate questions about the theory’s limited relevance (see
Hopkins, 1999).
HRT
Around the time Perrow (1984) articulated his NAT, another stream of
research emerged that prima facie had the potential to, irrespective of its
avowed aim, falsify NAT’s main premise. Scholars from the Berkeley campus
of the University of California came together to study how organizations that
operate complex hazardous technologies manage to remain accident-free for
impressive lengths of time while simultaneously retaining their capacity to
meet highly unpredictable and demanding production goals. If these scholars
could identify organizational properties or processes that greatly mitigated the
risks of operating in a complexly interactive and tightly coupled environment,
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then they would apparently undermine NAT. The body of work produced by
the Berkeley group, and other scholars who later enhanced the work, has been
dubbed HRT.
HRT scholars have studied systems such as naval aircraft carriers (e.g.
Rochlin et al., 1987), air traffic control systems (e.g. La Porte, 1988), nuclear
power plants (e.g. Bourrier, 1996), submarines (e.g. Bierly & Spender, 1995),
and space shuttles (e.g. Vaughan, 1996, 2005). Despite being highly diverse,
the organizations studied have something in common. They are all complex
technological systems that put a high premium on reliability since their oper-
ating environments seldom offer them a second chance. Given their focus,
the first challenge before HRT scholars was to define reliability. It proved
particularly troublesome to do so (see Hopkins, 2007; also see Wolf, 2001).
Although HRT scholars have abandoned attempts to explicitly define
reliability, they appear to agree that reliability is the ability to maintain and
execute error-free operations. Weick et al. (1999) report that HRT empha-
sizes the following conditions as being necessary, but not sufficient, for
ensuring reliability: a strategic prioritization of safety, careful attention to
design and procedures, a limited degree of trial-and-error learning, redun-
dancy, decentralized decision making, continuous training often through
simulation, and strong cultures that encourage vigilance and responsiveness
to potential accidents. The authors then imply that to move closer towards
attaining a sufficient condition of reliability, organizations must also become
‘mindful’. Mindfulness entails a unique way of looking at the world. Weick
and colleagues argue that organizational scholars might have erred in un-
critically importing a notion of reliability from the engineering discipline that
ignores processes of cognition.
The engineering notion equates reliability with lack of variance in
performance. But Weick et al. (1999), citing Schulman’s (1993) analysis of
the Diablo Canyon nuclear power plant, argue that in the organizational
context, reliability is not the outcome of organizational invariance, instead
it results from the management of fluctuations. The emphasis thus shifts from
stable routines to stable processes of cognition that must make sense of and
reconcile the varying processes of production. Besides, they point out that
routines are seldom stable in the sense that each time they are enacted they
unfold in a slightly different manner, in a slightly different environment. Only
an alert mind that is cognizant of the subtle differences can produce reliable
outcomes in an organizational context is the conclusion.
Mindfulness is said to involve: preoccupation with failure (i.e. a sus-
picion of quiet periods); reluctance to simplify interpretations (i.e. a hesi-
tation to generalize and make assumptions); sensitivity to operations
(i.e. a high level of situational awareness of the big picture about what is
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happening and what one might expect in the immediate future); commit-
ment to resilience (i.e. a tendency to do whatever it takes to ride out a crisis);
and under specification of structure. Weick and colleagues (1999) argue that
by under specifying structure, organizations can encourage flexibility and a
healthy disregard for formal hierarchy that allows decision-making to
migrate with a problem. Migration of decision-making partly explains how
highly reliable organizations (HRO) can meet the contradictory requirement
of being simultaneously centralized and decentralized. In this context,
Weick (1987) also observes that some organizations cope with conflicting
requirements by granting considerable decision-making autonomy at lower
levels and ensuring buy-in of centrally determined goals, decision premises,
and assumptions.
Like mindfulness, conceptual slack, a term coined by Schulman (1993),
relates to how firms might afford autonomy at lower levels in the face of
centrally determined goals. Conceptual slack indicates a ‘divergence in
analytical perspective among members of an organization over theories,
models, or causal assumptions pertaining to its technology or production
processes’ (p. 364). In an organizational context, the notion is a form of
‘redundancy’ – it adds to the variety of ways in which an organization can
respond. While conceptual slack has the potential to create confusion, on the
flip side, as happened in the case of the nuclear power plant that Schulman
(1993) studied, it can lead to an engaged workforce that vigorously debates
differing viewpoints and negotiates to arrive at an acceptable solution.
While some scholars have studied reliability and introduced notions
such as conceptual slack and mindfulness, others have concentrated on non-
reliability to draw lessons. For instance, Vaughan (2005) analyses NASAs
inability to learn from previous experience and identifies the tendency to
normalize deviation as a factor that contributes to accidents. Organizations
unwittingly institutionalize practices that encourage gradual erosion of stan-
dards. An acceptable outcome of risky behaviour in the immediate past is
allowed to set the expectation for risky behaviour on the next occasion. The
changes in the harmful direction take place in such small increments and get
injected into daily routines through normalization of deviance so sur-
reptitiously that it is impossible to detect them until it is too late (Vaughan,
2005). Despite the fact that the reliability literature has introduced several
constructs that may have relevance for non-HROs as well, it is puzzling that
the area has been unable to connect its work with mainstream organization
theory (Scott, 1994). We attribute this state of affairs to the high reliability
area lacking a theoretical anchor.
Currently, HRT scholars can claim to have merely produced a list
of factors associated with high reliability. Unless systematic empirical
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comparisons with non-HROs are made, the area cannot make causality
claims. Admittedly, Weick and colleagues (1999) have taken the first steps
towards elaborating a predictive theory of reliability by explicating the cogni-
tive processes that might be responsible for producing reliable structures, but
we argue that they appear to have made questionable assumptions about the
applicability of micro-level cognition processes at the macro-level (also see
Weick & Sutcliffe, 2001). We therefore believe that more work is needed if
HRT is to integrate with mainstream organization theory. We will later
attempt to draw parallels between HRT and the proposed open systems
perspective of accidents. In the next section, we highlight the salient aspects
of the NAT-HRT debate.
The NAT-HRT debate
Despite differing motivations – HRT looks for organizational factors and
processes that contribute to reliability, and NAT focuses on organizational
properties that lead to accidents – we believe that both theories have similar
implications for practice. NAT implies that organizations can lower the
statistical probability of systems accidents (but never lower it to zero) by
reducing their complexity and loosening the coupling amongst their sub-
systems. We argue that the initiatives identified by HRT – strategic concern
for safety and safe design, redundancy, simultaneous centralization and
decentralization, training, organizational learning, and mindfulness – can all
be construed as attempts to either directly or indirectly address the challenges
posed by complex interactions and tight coupling, the very dimensions
central to NAT.
Although NAT seems to recommend that lowering the complexity
levels of interactions in systems and decoupling them would lower the prob-
ability of accidents, the theory also points out that the very nature of the
transformation processes that must be executed precludes this possibility.
Furthermore, Perrow (1984) states that even when it is possible to tweak the
two dimensions, financial considerations and pressures from the powerful
elite interfere. Although NAT does not question the wisdom of doing every-
thing possible to avoid system accidents, it asserts that every once in a while
our best may not prove good enough. In contrast, HRT seems to predict
safety for organizations that are totally committed to high-reliability prac-
tices (Rosa, 2005).
To the proponents of HRT, NAT’s pessimism appears to stem not so
much from its prediction that accidents are inevitable, as from its belief that
it is Utopian of organizations to assume that their processes can potentially
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remain foolproof for reasonable lengths of time. Perrow (1994) states that
it is around this belief, amongst others, that NAT and HRT diverge.
Reflecting on the enhancements to NAT, Perrow (1994) concedes that
he had failed to anticipate the emergence of HRT, which uses a different
theoretical model of organizations. He also admits to having glossed over
the consequences of his own model choice. His seminal work mentions only
in passing that NAT is based on Garbage Can Theory (see Cohen et al.,
1988). Perrow (1994) notes that the ‘Garbage Can’ approach, which draws
attention to instability, ambiguity, misunderstanding, mis-learning, happen-
stance, confusion and so forth, is appropriate where there is high uncertainty
about goals, structures, and processes. Given the complex environment that
most organizations operate in and must interact with, Perrow claims that
NAT is justified in eschewing the HRT-embraced notion of organizations
being rational, stable, and closed systems.
HRT proponents could, however, argue that expecting internal
processes of organizations to work efficiently in the face of external turbu-
lence does not necessarily mean that one considers organizations to be closed,
rational, and stable systems. Of particular importance to HRT is the need to
build an organizational culture that puts safety first. It is important to note
that culture building exercises are often influenced by external regulatory
agencies and increasingly, at least in responsive democracies, by societal
concerns. If anything, efforts to foster a high reliability culture are more
consistent with an open rather than a closed systems perspective.
Sounding a dissenting note over the importance given to culture in the
current context, Perrow (1999) states that a ‘focus upon a culture of
reliability is a luxury in the world of risky systems’ (p. 360). He, instead,
focuses on the use of power in the context of safety. But as Weick (2004: 31)
forcefully argues, ‘culture and power are not opposed explanations . . .
culture shapes the way for power, defines power, is shaped by power, masks
power, embodies power’. Thus it should be possible to reconcile the differ-
ences between HRT and NAT over their treatment of culture and power.
In our opinion, Perrow’s most pessimistic observation is that the elite
tend to wield power to insulate themselves from the dangers of systems
accidents at the expense of exposing the less privileged. If his treatise about
the powerful elite is accurate then indeed societies will seldom feel compelled
to limit the exposure of all their elements to system accidents. Not surpris-
ingly, Perrow (1999: 378) is dismayed that ‘much of the work in the risk area
today is systematically detoxing the power aspects’ of his book. While we
agree that scholars in the area have been guilty of paying too little attention
to the role of power, we concur with Weick (2004) who observes that ‘NAT
is often a pretext for Perrow to make some larger points about which he feels
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strongly’ (p. 28). In other words, there appear to be no theoretical reasons
for Perrow to pontificate about power.
NAT does make references to the systems perspective to justify
discussions of power, but the rationale remains weak since at no stage Perrow
(1999) makes any ontological commitment to systems theory. Although
Perrow (2004) clarifies that NAT takes into account the wider context of a
failure that ranges from mental models of individual operators, to group,
organizational, and industry structures, he emphasizes that NAT is not based
on ‘the so called systems theory of the 1960-to-1980 period, grand, inclusive,
and virtually circular’ (p. 10). Thus we argue that claims that HRT treats
organizations as closed systems are as untenable as the claims that NAT
treats organizations as open systems. We will later return to this issue. For
now, we discuss the ‘centralization versus decentralization’ dichotomy that
will need to be addressed if one is to reconcile NAT with HRT.
NAT holds that systems cannot at once be decentralized and central-
ized. This is why the theory concludes that it may be best to abandon develop-
ing some of the more complex technologies. HRT, without necessarily
disputing NAT’s conclusion, states that it may be possible to ensure that
decision-making migrates to where the action is (through under specification
of structures and by affording conceptual slack) while ensuring buy-in for
centrally determined goals. Thus the problem of meeting conflicting require-
ments may not be as intractable as NAT states. The same cannot be said of
‘redundancy’.
The two theories hold very different views on the effects of redundancy.
This may be attributed to HRT confusing reliability with safety. It is possible
for a component to be reliably unsafe (see Rijpma, 1997; Wolf, 2001). For
instance, Turner (1978) describes how a reliable distribution system proved
very efficient at delivering contaminated fluids to British hospitals. In fact,
one could argue that scholars could have used the term HSO (highly safe
organizations), rather than HRO, to describe the organizations they have
studied. HRT ignores the fact that redundancy (i.e. duplication in systems
design to insure against failure) can carry costs by increasing complexities
and opportunities for failure (Perrow, 1994), especially when the redundant
component is not incorporated into the original design and ‘added after
problems are recognized’ (Perrow, 1999: 368).
Consider how additional pilots in an aircraft could, somewhat counter-
intuitively, lower reliability. The senior pilots, being aware that there was
someone else available to alert them in case of any emergency, could end
up becoming careless. La Porte and Rochlin (1994) however, reject this
criticism. They agree that incorporating redundancies could increase
complexities and opportunities for failure, but argue that some organizations
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are willing to ‘carry out processes compensating both for the intrinsic hazard
of their technical systems and the subsequent increase in “secondary compli-
cations”’ (p. 223; emphasis in original). The auto-pilot feature, for instance,
could be regarded as an additional redundancy against human failure. But
one can readily imagine Perrow arguing that the auto-pilot feature would
add another layer of complexity, and its failure could have disastrous conse-
quences. What one ends up with in this argument is infinite regress with no
resolution in sight.
To summarize: from its vantage point, HRT asserts that accidents, even
in complex organizations that operate hazardous technologies, are avoidable
if the organizations take enough pains to make the workplace safe. NAT, on
the contrary, holds that regardless of the intensity of organizational efforts,
accidents in complex and tightly coupled systems, because of system charac-
teristics, are inevitable. To support their claim, HRT proponents point to
accident-free environments that have existed for long periods. Expectedly,
NAT subscribers point to the moment when accidents do eventually take
place in order to support their inevitability claims. We argue that while the
theories make different claims, they do not contradict each other. This is so
because they look at the accident phenomenon at different points of time.
We believe that time is a central but ignored factor in the NAT-HRT debate.
Resolution through a temporal dimension
Does time play a role in what is a stochastic process? Since NAT cannot
predict as to when exactly the conditions become ripe for a system accident,
one can only conclude that a system accident can occur at any time. But some
reflection will reveal that the operative phrase in the previous sentence is
‘become ripe’. This would point to an incubation period of sorts. Musing
over why the US had not had more nuclear power plant accidents, Perrow
(1984: 32) states:
One answer is that the ‘defense-in-depth’ safety systems have worked,
limiting the course of accidents . . . But a more accurate and less
reassuring answer is that we simply have not given the nuclear power
system a reasonable amount of time to disclose its potential.
(emphasis added)
But are there any theoretical reasons for Perrow to implicate time?
One of the reviewers of this article pointed out that ‘time of operation
is an irrelevant dimension for NAT. Even if the system has run long enough
for either experience to develop or for complacency to set in, it is the
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complexity and coupling of the system, independent of time of operation,
that creates the potential for the rare normal accident.’ We acknowledge that
NAT does not factor in time as a dimension. But this is not the same as saying
that time has no bearing on a system from the point of time it is
commissioned to the point of time it suffers a system accident.
In Perrow’s quote cited above, he also refers to the possibility of
‘defenses-in-depth’ having worked to help the US avoid nuclear accidents.
Interestingly, we would argue that time plays a crucial role in the collapse of
‘defense-in-depth’ systems as well. In his Swiss Cheese Model (SCM), Reason
(1998) asks us to visualize various defence strategies as slices of cheese that
are stacked alongside each other. The slices of cheese have holes, which
signify weaknesses in the various defence strategies. In an ideal world, the
slices would have no holes. But since perfection does not exist, slices in-
variably have one or more holes. The holes may close, shut, and move with
the passage of time. On occasions, there is a chance, a very remote chance,
of all the holes getting aligned and permitting one to look through the
cheese stack. When this happens, it presents an opportunity for an accident
trajectory to pass through or defeat the system’s defence-in-depth. This is
akin to ‘time being ripe’ in NAT.
Although NAT does not directly concern itself with events that con-
tribute to the holes getting aligned, it is possible to reconcile NAT’s language
with that of Reason’s (1998) SCM. NAT seems to imply that the statistical
probability of the holes getting aligned increases as the complexity of inter-
actions and coupling within a system increase. Safety features can come
under enormous strain when tightly coupled systems must execute increas-
ingly complex operations. Perrow’s (1984) rich description of system
accidents across industries highlights how system characteristics can render
organizational effort and human intentions impotent. Albeit the examples
narrated by Perrow constitute anecdotal evidence; collectively, they do make
a persuasive case for the inevitability of system accidents. But the issue is not
whether system accidents are inevitable or not. Inevitability is immaterial for
practical purposes. Even if commissioning tightly coupled complex techno-
logical systems is fraught with risk, once such systems start operating,
organizations can do little more than strive for error-free operations. The
fundamental issue, from our perspective, is that HRT and NAT focus on
entirely different stages of an organization’s journey towards a system
accident.
Figure 2 depicts a probable journey of an organization from the time
of its inception to the time it meets with a system accident. In theory, the
organization could suffer a system accident on the very first day of its
operation (i.e. at point A). But in practice, such occurrences are rare. We
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Human Relations 62(9)
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B
Tight
Loose
Time
Complex
Linear
High Reliability Low
Bounded rationality
breaks down because of
cognitive overload
Practical Drift
Triggering event: loosely
coupled organizational units
suddenly experience the need to
become tightly coupled to the
central directives or the
‘defenses-in-depth’ break down
(The Swiss Cheese Model).
Conceptual slack
oooo SCM
oooo SCM
A
B
NAT
Organizational journey HRT in operation NAT in operation
oooo SCM
oooo SCM
Coupling
Interactions
Disaster Incubation Theory
HRT
Figure 2 Journey towards a system accident: an example
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argue that first day accidents, or accidents in the initial stages, are more likely
to be component failure accidents attributable to engineering-related design
errors, cost cutting measures, and pre-mature commissioning of projects. It
is worth noting that Perrow (1994) emphasizes how difficult it is for all
the failures to combine in a manner that defeats all the safety devices to
trigger a system accident. Hence his observation about sufficient time not
having elapsed to defeat the safety measures in the US nuclear power plants.
Thus the journey from point A to point B could, in some instances, take
decades.
Note that at point A in Figure 2, the system is shown as being tightly
coupled and complexly interactive (i.e. the focal system meets the conditions
necessary for a system accident). It would be reasonable to assume that when
projects are commissioned after due diligence, there is expertise available to
commence operations. We argue that as the implications of tight coupling
and high complexity play themselves out, they impact the learning and
experience curves of the system concerned. Irrespective of whether a system
improves or deteriorates from a safety perspective, time, as we illustrate in
Figure 2, is usually available as a resource to those concerned with safety.
No sooner than the focal system commences its journey at point A, it
starts incubating for a disaster (Turner & Pidgeon, 1997). Disaster Incu-
bation Theory (DIT) claims that with the passage of time, organizations start
ignoring and misunderstanding danger signals; further, those with good
safety records become complacent. Lackadaisical management and lack of
information also combine to make matters worse – eventually, things give
way and organizations suffer a major accident. Note the parallels between
DIT and HRT. Complacency as described by DIT probably drives the
tendency amongst organizations to normalize deviance (Vaughan, 2005) and
to gradually migrate their activities towards the boundary of acceptable
performance (Rasmussen, 1997). Also, note that just as HRT concentrates
on what is right in accident-free organizations, DIT concentrates (in hind-
sight, one might add) on what goes wrong in the lead up to organizational
accidents (Rijpma, 2003). Perrow (1984) however, argues that it is pointless
to talk about warning signals and possible interventions in hindsight. He
asserts that it can be very difficult, if not impossible, to decipher the meaning
of and attend to dozens of simultaneous signals against the background of
noise and false alarms before an accident. A study by Snook (2000) examined
precisely this issue.
Snook (2000) asked whether a particularly tragic accident in the US
military could have been averted. On concluding his research, he answered
the question with a ‘yes and no’. Things were ignored, but no individual
could be blamed for ignoring them. The case study offered a fine-grained
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analysis of how HROs, owing to practical exigencies, could drift towards a
potentially unstable state.
Adopting a grounded theory approach to study a US Air Force friendly-
fire incident, Snook (2000) implicates individual, group, and organizational
factors. He theorizes that most organizations, to begin with, are tightly
coupled to cater to worst case scenarios. The scenarios, however, seem so
remote that people gradually start ignoring them. At the local level, teams
start adopting unauthorized practices to complete the task on hand as
efficiently as possible. This practical drift – defined by Snook (2000: 24) as
‘the slow steady uncoupling of local practice from written procedure’ – leads
to the focal system becoming loosely coupled. If by sheer chance the system
becomes tightly coupled again (e.g. when the system must form an ad hoc
team for a particular operation that requires knowledge of the formally
articulated central logic), and if at that moment a failure occurs, then the
chances of a system accident occurring increase exponentially. This is because
by then the system has drifted so far from the original state that none
amongst those remaining is capable of responding sensibly to the unfolding
events.
Let us return to Figure 2. The figure shows the focal system getting
loosely coupled through practical drift and reaching point B. At this point,
it confronts a contingency that requires it to become tightly coupled. It has
lost the capability to do so and cannot make sense of what is happening.
Thus to the system, the complexity it must cope with is very high and it,
consistent with NAT’s prediction, meets with an accident. We wish to
emphasize two issues in the context of socio-technical systems: i) being
loosely or tightly coupled occurs in the mental realm; and ii) complexity is
relative. On both these inter-related issues, NAT is not very clear. Figure 2
shows the focal system oscillating along the two vertical ‘Coupling’ and
‘Interaction’ axes. We argue that this happens because the levels of con-
ceptual slack (Schulman, 1993) that organizations afford to their employees
can vary. The most relevant measure of coupling in the socio-technical
domain may well be the level of conceptual slack. The higher the levels of
conceptual slack enjoyed, the looser the coupling and the greater the ability
of the system to cope with complexity. This brings us to the second issue
about complexity being relative.
Our explanation implies that complexity is high only because the focal
system cannot make sense of the interactions and this eventually leads to
cognitive overload. As Perrow (1984: 78) states, ‘systems are not linear or
complex, strictly speaking, only their interactions are’. When one factors in
the human mind, as one must in the case of socio-technical systems, com-
plexity becomes relative. Perrow (1984: 84) seems to recognize this when he
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says, ‘It is also true that a poorly trained or inexperienced operator may see
a system as replete with unsuspected interactions or “traps”, but after
gaining experience may find it to be more linear . . .’ Herein is the answer to
the paradox of being simultaneously centralized and decentralized. Physical
entities may not be able to cope with this paradox, but mental entities can.
As we had mentioned in our critique, NAT needs to make room for the
human mind.
One of the reviewers argued that:
It is the virtue of NAT that the only assumption about humans is that
they are boundedly rational, and thus there will be an inevitable error
in the design, and comprehension in the face of complexity, and so on.
But human errors are not at the heart of NAT, though they are for
HRT. NAT is valuable because it focuses upon system characteristics
rather than such things as operator errors that may be owing to lack
of mindfulness, inadequate training, management’s failure to pursue
safety goals and all the other things that HRT is concerned with.
We agree with the reviewer, but at the same time argue that system
characteristics are a function of human understanding. It is plausible that
humans design inelegant complex systems when they do not fully understand
the technologies and the underlying processes. In fact, Perrow (1984) states
that technologies that populate Quadrant 2 in Figure 1 could eventually
migrate to other quadrants. Air traffic control systems are said to be a point
in case. Similarly, Perrow notes that technological processes involved in iron
and steel production have become less complex as human understanding of
the processes has improved.
Note that Perrow (1984) acknowledges that experience and training
can help reduce complexity, thus NAT must also make room for HRT. So
how, and where, does HRT fit in Figure 2? As per HRT, organizations
improve their reliability through training, mindfulness, and so forth. Actions
such as preventive maintenance, replacement of worn out parts, and tech-
nology upgrades can enhance the life of systems. Thus in a conceptual sense,
as shown in Figure 2, a ‘renewed’ system can be shown as travelling back in
time. Hence organizations are also shown as oscillating along the horizon-
tal ‘Reliability’ and ‘Time’ axes, even though they inexorably drift towards
an accident (as explained by DIT).
Notice that Figure 2 also incorporates Reason’s SCM. This captures
the stochastic nature of system accidents. We recognize that the probability
of an accident can never be zero at any point in time. Figure 2 indicates that
the likelihood of the holes aligning would perhaps increase during periods
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of sharp discontinuity. It would be reasonable to believe that cultural issues
come to the fore when work practices change abruptly and humans must
reorient themselves. HRT would suggest that the holes rapidly close in
mindful environments. Conversely, new ones would open, or existing ones
widen, if safety concerns were to diminish for whatever reason. As per
Figure 2, the organization could have met with a system accident at any time
had the ‘defenses-in-depth’ been breached. The figure highlights four such
occasions. In one sense, the focal system is ‘lucky’ to have drifted unscathed
up to point B in its eventful journey.
One final issue about practical drift merits a discussion. Rijpma (2003)
notes that Snook’s analysis and description of the phenomenon ‘underlines
the importance of Sagan’s extension to NAT: accidents are inevitable not
because of the technological complexity, but because of more banal organiz-
ational, cultural, and economic reasons’ (p. 43). We argue that Snook’s
(2000) analysis does not discount the importance of coupling and com-
plexity. Instead, practical drift introduces a dynamic element that under-
scores the fact that organizations tend to travel (for banal reasons perhaps)
along the coupling and interaction continuum.
Thus we claim that NAT and HRT are not incommensurate – they refer
to the same phenomenon, but at different time frames. We believe that DIT
and related notions such as practical drift, migration towards the boundaries
of acceptable performance, and normalization of deviance can help describe
a system’s behaviour at different points of time. Figure 2 depicts the changing
states of a system as it drifts and incubates towards an accident. The system
is in perpetual danger of its ‘defenses-in-depth’ getting breached and must
remain mindful at all times. HRT, in Figure 2, operates across levels (in that
the theory implicates organizational culture, team dynamics, and individual
mental models) until such time an accident occurs. It is only when a system
accident occurs at point B that NAT becomes applicable. In other words,
coupling and complexity thresholds are reached at point B that result in
bounded rationality breaking down.
2
With HRT becoming inoperative at point B, historical organizational
practices cease being the unit of analysis. Instead, the focus shifts to a situ-
ation at a moment in time, wherein a fault is tackled in a complexly inter-
active and tightly coupled systemic environment by an agency that has
become ill-prepared owing to the travails of everyday existence (as explained
by practical drift) in a culture that is not as safety conscious or as reliable as
it once was (as explained by DIT and other related notions). Although NAT
and DIT both appear to suggest that an accident is inevitable, there is a differ-
ence. As Hopkins (1999) points out, in DIT, human beings and organizations
are assumed to cause disaster and are accorded the power to intervene,
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whereas in NAT, human beings are unable to intervene once the chain
reaction is set in motion owing to interactive complexity and tight coupling.
But more importantly, as we show in Figure 2, DIT, like HRT, refers to a
period of time that precedes the brief moment that NAT concerns itself with.
We clarify that it is not our case that all system accidents are preceded
by practical drift and the other mechanisms described above. Nonetheless,
we argue that the various case studies of aircraft carriers, nuclear power
plants and so forth that are available in the HRT literature pertain to what
would be the period between points A and B in Figure 2. Similarly, the rich
descriptions of system accidents across industries provided by Perrow (1984)
in support of NAT pertain to what would be the brief period between B and
B. In this connection though, it bears reiterating that as per Figure 2 a
system accident can occur at any point of time. However, to the extent that
technology upgrades, training, and mindfulness in general can help systems
better cope with complexity, HRT proponents could claim that it may be
possible to postpone a system accident.
3
We suggest that the proponents of
NAT and HRT have been talking past each other because the boundary
conditions of the two theories, in terms of time, are clearly distinct from each
other. In its current form, NAT predicts that all tightly coupled and
complexly interactive systems would eventually meet with a system accident
(and until they do not, it is only because the right moment has not arrived).
It is hardly surprising that HRT proponents are not impressed when
reminded that initiatives such as redundancy, training, and so forth prove
effective until they fail. The problem, as we claimed in our introduction, is
that NAT can always explain away its failure to predict a system accident.
The non-falsifiability problem is reflected in the nature of empirical
work in the area (Rosa, 2005). Case studies pertain to either organizational
accidents or to organizations that have not had accidents. Systematic com-
parisons are lacking. Not surprisingly, researchers can always find support for
their respective theoretical positions as their sample has zero variability.
Perrow (1994), for instance, asserts that a majority of the so-called HROs
scrutinized by researchers have been safe over long periods only because the
organizations in question have not been operating highly complex and tightly
coupled technological systems. Similarly, HRT can explain away its failure to
predict error-free operations by finding faults in hindsight and claiming that
an accident took place because high-reliability conditions had been violated.
This is precisely what Rijpma (2003) does when arguing that the friendly-fire
accident analysed by Snook (2000) did not take place in an HRO as the sub-
units involved were not a well-knit team.
In the process of resolving the NAT-HRT debate, we might have added
conceptual clarity and explained why the two theories appear to diverge, but
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we have not done much to address the non-falsifiability problem. If anything,
our resolution has brought the issue into sharper relief. Recognizing that any
theory on accidents must be sensitive to criticisms regarding lack of falsi-
fiability, we propose a new framework of accidents that is based on an
interpretation of systemic properties. The view presented is different from
the under-developed systems perspective present in NAT and HRT.
Interpreting the properties of open systems
Although Perrow (2004) dismisses systems theory of the 1960s vintage as
being virtually circular, we believe that an insightful application of the open
systems perspective can help refine NAT. In a generic sense, accidents may
be seen as instances of unintended or uncontrolled energy releases. In the
current context, the open systems perspective seems promising because it
essentially conceptualizes organizations as entities that manipulate energy.
Over two decades ago, Ashmos and Huber (1987) had lamented that authors
claimed adherence to systems perspective for merely embracing the common-
sense idea that external environments affected organizations; seldom did they
purposefully design their studies around systemic properties.
Cognizant of Ashmos and Huber’s criticism, we begin by discussing
some of the properties of open systems
4
that are germane to the proposed
view of accidents. A discussion on permeable boundary, energy trans-
formation, negentropy, homeostasis and requisite variety follows. The
property of negentropy is examined in detail since the extant systems
literature overlooks a vital aspect of the property.
Permeable boundary
An open system is distinguished from its environment by an arbitrary
boundary. These boundaries are permeable, indistinct, and ‘dynamic rather
than spatial’ (Bertalanffy, 1972: 422). Even if boundaries are only a mental
construct, they must be delineated if a systems perspective is to be
applied (e.g. Leveson, 2004; Rasmussen, 1997); for without boundaries, the
distinction between a focal system and its environment would disappear
(Scott, 1992).
Energy transformation
Open systems receive inputs from the environment; they transform these
inputs into outputs, and exchange their outputs for new inputs. The
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permeability of the boundary facilitates such an exchange. If the outputs of
a system do not satisfy the environment or create ‘value’ for the environ-
ment, the inputs eventually cease. In the case of a business organization, one
can visualize how organizations transform raw materials (forms of inputs)
into finished goods/services (outputs), which are exchanged for a fresh round
of inputs. The input-transformation-output (I-T-O) cycle may be described
as a dynamic process that involves conversion of energy from one form into
another. Open systems thus create value through transforming energy via
I-T-O processes. If a nuclear power plant is to be treated as an open system
then the nuclear fuel, coolants, and so forth would all qualify as inputs and
the electricity generated by the plant would be output.
Negentropy
It is one of the fundamental laws of nature that energy can neither be created
nor destroyed – it can only be made to change its form. Whenever energy
is converted by a system from one form into another, there is ‘wastage’ or
some loss of energy. In other words, 100 percent energy conversions are
seldom possible. Some energy invariably escapes in the energy conversion
process in a manner that renders it non-usable by the system in question.
More damagingly, not all of the unusable energy escapes to the external
environment, some of it accumulates within the system itself – this accumu-
lation of unusable energy within the parent system is a form of entropy.
Thus one may define entropy as a measure of disorder or randomness in
energy.
5
In well designed systems, a minimal amount of energy escapes as
waste, and accumulation of unusable energy is miniscule. This concept is
explained further with the help of an example.
An automobile’s engine converts chemical energy of the petrol (input)
into kinetic energy of the wheels (output), but in the process of doing so, it
wastes some energy. Of course, the more efficient engines emit less heat, give
better mileage, and are quieter. But even the best of engines cannot prevent
wastage. The wastage takes two forms: while some energy escapes to the
external environment (e.g. in the form of fumes and sound), the balance gets
accumulated or dissipated within the system (e.g. as soot or as heat owing
to friction amongst internal parts). The energy that does not escape con-
stitutes entropy and its accumulation has serious consequences for the
long-term health of the parent system. According to the second law of
thermodynamics, entropy in any closed part of the universe tends to increase
with the passage of time. However, open systems, till such time they are in
existence, appear to defy the second law of thermodynamics because
the amount of order in them always exceeds the amount of disorder. Thus
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open systems are said to have negative entropy (i.e. they are said to be
negentropic).
Open systems remain negentropic through constantly exchanging their
outputs for inputs (Katz & Kahn, 1978) and by expelling whatever entropy
accumulates within them while they are engaged in energy transfer
(Schrödinger, 1944). Because an automobile engine can neither exchange its
outputs for inputs, nor can it remove the soot that accumulates within it
without external intervention, it is not an open system. It should, however,
be noted that open systems appear to defy the second law of thermo-
dynamics. In reality, no matter how hard they try, they cannot expel all the
entropy that accumulates within them. Thus every time an I-T-O cycle gets
executed; some amount of entropy gets accumulated within a system. Ageing
thus may be described as a process of entropy accumulation.
Examples of entropy accumulation would include not only obvious
examples like unacceptable wear-and-tear of machinery and exposure of the
workforce to radiation in a nuclear power plant, but also negative affect
experienced by the workforce during the value creation process. Demoraliz-
ing one’s employees in the wake of one’s I-T-O cycle is an example of entropy
accumulation in the socio-technical domain. One could, in fact, capture some
of the phenomena from the dark side of organizations (see Vaughan, 1999)
as examples of entropy accumulation. Conversely, one could argue that an
empowered workforce enjoying autonomy (and afforded conceptual slack),
would be less susceptible to entropy accumulation.
The foregoing analysis brings the focus back on the workforce, includ-
ing human operators, in the accident context. Our aim here is not to make
a case to justify the tendency to assign blame on human operators. Rather,
by emphasizing the central role of the operators, we argue that everything
possible should be done to make things easier for them. This argument is
consistent with the human factors and systems engineering movement (see
Leveson, 2004; Rasmussen and Svedung, 2000).
Homeostasis
Open systems rely on feedback loops to maintain equilibrium with an ever-
changing external environment. In every feedback loop, as the name suggests,
information about the result of a transformation or an action is sent back
to the system in the form of input data. If these new data facilitate and
accelerate the transformation in the same direction as the preceding results,
they are positive feedback – their effects are cumulative. If the new data
produce a result in the opposite direction to previous results, they are
negative feedback – their effects stabilize the system. Positive feedback loops
left alone can lead only to the destruction of the system, through explosion
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(e.g. hyperinflation) or through implosion (e.g. economic depression). The
wild behaviour of positive loops – a veritable death wish – must be controlled
by negative loops. This control is essential for a system to maintain itself over
time. In a negative loop, every variation towards a plus triggers a correction
towards the minus, and vice versa. There is tight control; the system
oscillates around an ideal equilibrium that it never attains (deRosnay, 1997).
A thermostat uses negative feedback to attain its goal of maintaining
a room’s temperature within an acceptable range. Open systems such as
human bodies maintain their temperatures and blood sugar content levels
through a similar mechanism. Such self-regulating goal-seeking behaviour
induced by negative feedback ensures survival of a system even as the system
in question continues to grow. This property that maintains equilibrium and
allows for stable expansion is called homeostasis.
Requisite variety
Systems evolve to become more complex. The highly complex sense organs
and the nervous system of higher organisms have evolved from primitive
nervous tissues. Katz and Kahn (1966) observed almost four decades ago
that the number of medical specialists in the US outnumbered general prac-
titioners. Since then, not only has the number of specialists mushroomed, but
so has the number of medical specialties. This inexorable movement towards
increasing differentiation or complexity can be explained by Ashby’s (1956)
law of requisite variety. Variety is the number of states in which a system can
exist. An electric switch can occupy two states (on and off) and therefore has
a variety of two; a consumer in today’s market who is spoilt for choice has
a variety that is enormous. Just as entropy is a measure of disorder, variety
is a measure of complexity. A complicated system has a large variety,
meaning it can occupy a large number of states. Ashby’s law essentially
claims that a system needs variety to combat variety. The law of requisite
variety tells us that a system can insulate itself from the complexity of the
external environment by making itself complex.
That one must embrace complexity to combat complexity is counter-
intuitive and not always understood by organizations (see Heylighen &
Joslyn, 2001). Citing Cooper’s (1973) fascinating account of Apollo 13’s
aborted moon landing, Perrow (1984: 278) describes how NASA pressed
into service:
four complete teams, each with dozens of experts, available to staff its
ground system on a 24-hour basis . . . (and) about forty experts to
concentrate on working out solutions to get the astronauts home
safely; they were free of routine flight management duties. In addition,
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almost every step they devised could be quickly and realistically
tested in a very sophisticated simulator before it was tried out in the
capsule . . .
Although it is inconceivable that such resources would ordinarily be
available to high-risk systems, the Apollo 13 recovery effort demonstrates
how NASA had to acquire requisite variety (i.e. become more complex) in
order to successfully cope with a situation of unprecedented complexity. This
concludes the discussion on relevant systemic properties. In the next section,
we apply the insights gained from this discussion to reframe NAT so as to
address its non-falsifiability problem.
NAT reframed
Organizations as open systems must receive, manipulate, and exchange
energy to create value. Therefore, all accidents must essentially take place at
some point during energy reception, manipulation, or exchange (i.e. at some
point during an I-T-O cycle). NAT argues that all systems that transform raw
materials in some fundamental way must, per force, be tightly coupled and
complexly interactive. It is not as if organizations have a choice. The decision
to transform raw materials brings control issues to the fore. It follows that
the higher the ability to control transformation processes, the higher the
safety levels in the workplace (Leveson, 2004; Rasmussen, 1997). Also, the
greater the levels of energy used, discharged, or stored during transformation
processes, the greater the potential for damage in the event of an accident,
hence the higher the need for controlling such processes.
The above argument suggests that the level of interaction complexity
and the degree of coupling in an organization is a function of the amounts
of energy levels involved in the organization’s transformation processes and
the gaps in its knowledge about the processes. Thus one could argue that the
coupling- and interaction-related independent variables of NAT are, in fact,
dependant variables. Indeed, it might even be possible to reframe NAT as
shown in Figure 3. Note that the implications of the reframed NAT with
respect to organizational characteristics remain identical to what they were
in Perrow’s original formulation. Also, note that by incorporating levels of
energy, the reframed NAT can factor in the damage potential to society in
general and humans in particular. This is something NAT ignores.
The accident literature classifies human victims as first-party victims
(operators); second-party victims (non-operating personnel or systems users
such as passengers); third-party victims (innocent bystanders); and fourth-
party victims (foetuses and future generations). Although Perrow discusses
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the potential for damage to human victims, he does so in the context of
justifying his definition of accident, which focuses exclusively upon system
characteristics. Perrow (1984: 66) states that a fixation with human victims
could make us ‘lose our focus upon the kinds of systems that business and
government leaders decide should be built’. Our reframing of NAT shows
that it may be possible to factor in damage to human victims without shifting
one’s focus from system properties.
6
The damage potential of technologies and the difficulties associated
with controlling and transforming large amounts of energy (particularly in
instances where knowledge gaps are high) suggest that societies should in
general eschew large-scale projects. As Figure 3 indicates, from a safety
perspective, societies may exploit economies of scale only in the case of
Quadrant 3 technologies. We point out that our reframing enables NAT to
make a stronger case for exercising caution while commissioning high risk
technologies. Also note the slight differences between the reframed NAT and
Perrow’s NAT over systems that populate Quadrant 2.
Military early warning systems and nuclear weapon systems do not
involve transformation processes, and DNA recombinant technologies do
not involve high levels of energy. We cannot possibly capture these three
Shrivastava et al. Normal Accident Theory versus High Reliability Theory
1381
Figure 3 Reframed NAT: interpreting transformation processes
Knowledge gap
12
34
*
Nuclear plant
*
Chemical plants
*
Space missions
*??
Nuclear weapons
accidents
*??
Military early
warning
*
Aircraft
*
DNA
*
Dams
*
Power grids
*
Airways
*
Assembly line
production
*
Most
manufacturing
*
Mining
*
R & D firms
HiLo
Energy levels HiLo
DNA
*
University
*
Moderate damage:
up to 4th party victims
Structure: LC/CI
Size: pilot projects/small
to medium scale
Low damage:
1st & 2nd party victims
Structure: LC/LI
Size: economies of
scale possible
High damage:
up to 3rd party victims
Structure: TC/LI
Size: medium to small
scale projects
Structure:
TC/CI
Size: small to
medium scale
Catastrophie: up to 4th party victims
LC: Loose coupling; TC: Tight coupling
CI: Complex interactions; LI: Linear interactions
by Samir Shrivastava on August 13, 2009 http://hum.sagepub.comDownloaded from
systems under Quadrant 2 as Perrow does. Does this call into question the
rationale behind our reframing? We think not. DNA recombinant technology
might be highly complex, but there is no apparent reason as to why the
organizations (or the socio-technical systems) handling the technology have
to be tightly coupled themselves in the structural sense. As such, Quadrant
4 in Figure 3 would capture the knowledge intensive work involved in DNA
recombinant systems. Knowledge workers generally work in autonomous
teams (Alvesson, 2004). In other words, knowledge organizations are loosely
coupled; but because the technologies they use are tightly coupled, knowl-
edge work’s impact can be global (think of the sub-prime mortgage crisis!).
While capturing various systems under the four quadrants, Perrow
appears to have been influenced by technological characteristics as opposed
to organizational characteristics. Insofar as military organizations are
concerned, they are a special case because they do not adhere to democratic
norms and at times it can be misleading to reach conclusions about their
organizational properties during peace time operations (Schulman, 1993).
Arguing that they do not lend themselves to being captured under any
quadrant, we have not included them in Figure 3 in our reframed NAT.
The reframed NAT needed to replace interaction and coupling
dimensions in order to address the non-falsifiability problem. Perrow (1994)
concedes that NAT needs a metric that can measure the frequency with which
errors might interact to defeat or bypass safety systems. But we believe that
NAT precludes the development of such a metric because it insists that
complex interactions cannot be anticipated, and in any case, are un-
fathomable. According to Perrow (1994), if processes are well-understood
then they are probably not complexly interactive. Thus NAT perhaps cannot
rely on measures of complexity for support. The theory needs to identify
other variables if it is to offer testable propositions. We contend that knowl-
edge gaps and the levels of energy involved during transformation processes
are the two variables that can help NAT make falsifiable predictions. As
argued earlier, the open systems perspective provides theoretical reasons to
link these two variables to the probability of system accidents. Thus far, we
have relied on the property of energy transformation to reframe NAT. In the
next section, we draw from the other four properties to strengthen our case
for developing an open systems view of accidents.
A call for developing an opens systems view of accidents
Developing a systems view of accidents will no doubt need further theoreti-
cal work and empirical testing. A starting point could be to theoretically
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develop and test the relationship between levels of energy manipulated and
the occurrence of accidents in general and system accidents in particular.
7
Gaps in knowledge could be measured by seeking the opinions of scientists,
managers, and human operators. Although one could link coupling and
interaction dimensions with gaps in knowledge, developing a metric for the
two dimensions, as stated earlier, is likely to prove challenging. However, if
such a metric is considered indispensable, then scholars could apply insights
from open systems theory and measure complexity by quantifying the
number of major interfaces involved in the energy transformation processes.
Open systems exchange their inputs for outputs through permeable
boundaries at ‘interfaces’. All interfaces engaged in energy exchange need to
interpret feedback loops in order to ensure that adjustments are made in
the correct direction to maintain stability (refer back to the property of
homeostasis). In the context of system accidents, the interfaces of salience
are those that are involved in major energy exchange processes. Arguably,
lowering the number of major interfaces in a system would lower the statisti-
cal probability of systems accidents because fewer interfaces would make the
system less complex. However, since organizations operate in an increasingly
complex environment, they must continually, as dictated by requisite variety,
increase their own complexity. Initiatives that can help organizations increase
variety include, but are not limited to, raising ad hoc teams, forming
committees, re-training and selecting employees with non-typical skills, and
encouraging job rotation (Weick et al., 1999).
Paradoxically, the need to introduce new interfaces in order to survive
in a complex environment carries with it the risks of a system accident. But
when one factors in the human mind, one need not increase a system’s struc-
tural complexity in order to increase its variety. As described by Schulman
(1993), and as supported by the Apollo 13 example cited earlier, a work force
enjoying conceptual slack can contribute to the requisite variety levels in the
mental realm and enable organizations to cope with complexity.
8
A metric
that measures requisite variety in the mental realm is likely to prove par-
ticularly useful in the context of system accidents.
The need to maintain requisite variety makes it imperative for organiz-
ations to ensure that their managers and technical personnel across levels are
capable of coping with the level of complexity that they are likely to
encounter in worst case scenarios. This conclusion resonates with the work
of Jaques and Cason (1994) that equates human capability to information
processing abilities and recommends matching human capability with
expected complexity levels at a given hierarchical level. Although developed
in the context of comparative managerial worth, scholars could consider
using the notion of human capability to predict the quality of human
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responses at critical interfaces in the event of an accident. Figure 2 predicts
a systems accident when bounded rationality breaks down – or in other
words, when personnel at interfaces fail to cope with complexity and
decipher feedback loops. Organizations, to some extent, could lower the
probability of bounded rationality breaking down by matching human
capability with expected complexity levels.
Adding a redundancy to safeguard against accidents also amounts to
increasing a system’s complexity because it entails introducing a new inter-
face. Hence, redundancies can pose challenges to the workforce. The open
systems perspective therefore concurs with the notion that redundancies can
simultaneously increase and lower the probability of a system accident and
one needs to evaluate the net risk to determine the efficacy of a redundancy
(see Sagan, 1994). There are other parallels with NAT. Just as NAT high-
lights the tension between the need for centralization (brought about by tight
coupling) and decentralization (brought about by unanticipated complexly
interactive failures that require localized responses), the open systems
perspective underlines the tension between the need to increase its own
complexity (brought about by the need to maintain requisite variety) and
the need to lower the number of interfaces (brought about by the fact that
accidents often occur at interfaces as outputs and inputs get exchanged and
as feedback loops are deciphered).
Interfaces (whether automated or human) can find it difficult to
decipher feedback loops when entropy levels are high. The presence of
entropy, or disorder, can make systems unpredictable. Entropy accumulation,
as pointed out earlier, is inevitable – ageing involves entropy accumulation.
The theoretical explanation for the gradual erosion of reliability as asserted
in DIT (Turner & Pidgeon, 1997) may thus lie in the concept of gradual
entropy accumulation. It should however be noted that open systems can
remain negentropic for lengthy periods. Their ability to remain so can
perhaps be taken as support for HRT. Organizations, as envisaged by HRT,
retire legacy systems, retrain their employees, upgrade technology, carry out
preventive maintenance, and so forth. Such initiatives can be framed as
efforts undertaken by organizations to expel entropy. While these initiatives
can certainly increase organizational longevity, eventually the second law of
thermodynamics must prevail.
Further, some organizations can become more vulnerable to accidents
when their efforts to discharge entropy are afoot (i.e. during off-nominal
operations) because discharging entropy is essentially an unnatural act for
organizations. Unlike natural systems, which can expel entropy through
sweating, radiation, and so forth, social systems do not have an inbuilt
mechanism to discharge entropy. Again, one may be able to test through
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secondary data whether organizations become more vulnerable as predicted
by open systems theory.
Organizations can also become vulnerable to accidents during periods
of excessive growth. As a system grows, it moves away from its stable state
and the probability of its feedback loops breaking down increases. The
system usually struggles to make sense of what for it is a new state of
equilibrium. Further, periods of excessive growth may often call for quick
responses. It is plausible that loose coupling amongst sub-systems during
periods of growth aids improvisation and enables prompt responses.
However, loose coupling could at the same time increase the propensity
amongst sub-systems to pull in different directions and interpret feedback
loops locally at the expense of the parent system. To the extent that periods
of growth require greater buy-in from sub-systems, organizations need to be
tightly coupled.
Excessive growth can thus place conflicting requirements on organiz-
ations. There is a need for organizations to be loosely coupled so that they
may respond quickly to events in their new state of equilibrium, but to keep
the larger picture in mind, the organizations also need to be tightly coupled.
Open systems theory thus indirectly supports NAT, which identifies this need
through a different premise but concludes that organizations cannot meet it.
HRT scholars have however suggested several measures to cope with the
centralization-decentralization tension. As we have argued, the concept of
mindfulness (Weick et al., 1999) that subsumes the notion of conceptual
slack holds promise in this context. Questionnaires developed by Weick and
Sutcliffe (2001) to help organizations gauge their mindfulness could inform
future empirical studies in the area.
A cross-comparative study of organizations within the same industry
could be conducted to test whether greater growth is associated with greater
probability of system accidents. Also, fine-grained qualitative inquiry into
whether and how human responses lead the system to get tightly coupled
could offer insights into the role of humans in systems accidents. From the
above discussion, it is clear that the open systems view of accidents has the
potential to theoretically account for the apparently disparate accident-
related constructs and help advance the area.
Implications and conclusions
In this article, we argued that HRT and NAT are not incommensurate with
each other – they merely look at the same phenomenon at different points of
time. DIT (Turner & Pidgeon, 1997), and notions such as conceptual slack
Shrivastava et al. Normal Accident Theory versus High Reliability Theory
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(Schulman, 1993), normalization of deviance (Vaughan, 2005), and practical
drift (Snook, 2000) were used to resolve the NAT-HRT debate. Nonetheless,
the resolution did not circumvent the non-falsifiability problem inherent in
NAT and HRT. To address this problem, we invoked the open systems
perspective and discussed five systemic properties. In particular, we applied
the property of energy transformation to reframe NAT in a manner that
obviated the need to measure the levels of complexity and coupling, and
enabled the theory to account for the role of human operators and factor in
the damage potential to humans. The reframed NAT recommends com-
missioning small projects particularly when transformation processes involve
high energy levels and are poorly understood.
Finally, we offered pointers on how the area might be advanced
through applying the insights gained from open system theory. We argued
that the open systems perspective could account for the conclusions reached
by NAT, HRT, and DIT and indirectly explain Snook’s (2000) notion of
practical drift. Systemic properties suggest that organizations should exercise
caution during the unnatural act of entropy expulsion, and as they grow and
move away from their stable state. Our discussion also brought to the fore
how organizations might, without increasing their structural complexity,
increase their requisite variety. The HRT literature suggests that they can do
so through encouraging their employees to share and challenge existing
mental models. We believe that our effort reconciles the viewpoints contained
in NAT and HRT and makes a case for developing an open systems view of
accidents. We exhort our colleagues to respond to our call.
Acknowledgement
The authors are grateful to the guest editors, Nick Turner and Garry Gray, and
the three anonymous reviewers; their guidance and feedback proved invaluable
in helping the authors to improve the quality of this article.
Notes
1 Perrow appears to ignore the fact that military early warning and nuclear weapons
do not transform raw materials in any fundamental way.
2 The problem, as we have pointed out, is that NAT in its current form prevents one
from determining what the threshold levels might be. This makes the theory
untestable.
3 As was pointed out earlier, one of Perrow’s main motivations was to make a case
for abandoning high risk technologies given the inevitability of system accidents.
HRT is essentially silent on this issue. Nonetheless, La Porte (1994: 210) points out
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that HRO scholars are not ‘in the business of showing operators and manager how
they could be perfect – and therefore feel they could further deploy hazardous
systems supposing that they could be run with minimum risk’. He, in fact, insists
that HRT sounds a note of caution by highlighting the great difficulties and costs
associated with ensuring high reliability.
4 In his seminal article, Boulding (1956) presented a hierarchy of classifying systems
based on increasing complexity that extended across nine levels. The first three
levels, labelled frameworks, clockworks, and thermostats, comprised closed systems.
The next six – cells, plants, animals, human beings, social systems, and transcen-
dental systems – were said to be open systems. Transcendental systems represented
the unknowable and were included by Boulding to cater for future advances.
5 Entropy in cybernetics, the science of control and communication in machine and
animals, is taken to mean uncertainty or ‘ignorance’; conversely, it is held that infor-
mation fights entropy.
6 The aim is not re-invent the wheel. We are aware of hazard classification schemes
such as MIL-STD-82D available at [http://safetycenter.navy.mil/instructions/osh/
milstd882d.pdf] (as on 1 July 2008). The terminology of the classification scheme
tentatively suggested in Figure 3 could be reconciled with extant schemes. Our main
point is that any systems view of accidents can, and should, factor in human
operators and victims in a more explicit manner.
7 Regardless of the form of energy consumed – thermal, nuclear, electrical, chemical
(potential or kinetic) – it is possible to measure energy in a manner that enables
comparisons across systems.
8 One of the reviewers felt that we were perhaps overstating the importance of con-
ceptual slack. We, however, maintain that it is a construct that accurately reflects
how mental entities display requisite variety.
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Samir Shrivastava (PhD, Swinburne University of Technology,
Australia) is a Lecturer in HRM & Organization Studies at Swinburne
University of Technology. His primary research interests include systems
thinking, organizational learning, managerial competence, and knowledge
management. He has published in Human Resource Management, Journal of
Management Development and Australasian Marketing Journal.
[E-mail: sshrivastava@swin.edu.au]
Karan Sonpar is a Lecturer of Management at University College
Dublin, Ireland.He earned his PhD in 2008 from the University of Alberta,
Canada. He was a Captain in the Indian Army prior to his career move
to academia. His research interests include institutional theory, top
managers, using qualitative methods for theory development, ethics and
sociological approaches to risk. His work has been published in the Journal
of Management and Organizational Research Methods.
[E-mail: karan.sonpar@ucd.ie]
Shrivastava et al. Normal Accident Theory versus High Reliability Theory
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Federica Pazzaglia is an Assistant Professor of Finance at the
University of Manitoba in Canada. She earned her PhD in 2008 from
the University of Alberta, Canada. Her main research interests are
corporate governance, IPOs, diversification, ethics and risk.
[E-mail: pazzagli@cc.umanitoba.ca]
Human Relations 62(9)
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... When writing about crises, accidents, and pandemics, organizational theorists often refer to high reliability theory (HRT) (Shrivastava et al., 2009). HRT investigates how organizations operating in extremely complex settings effectively avoid accidents for lengthy stretches of time, whilst maintaining their ability to fulfill highly unpredictable and demanding production targets. ...
... HRT investigates how organizations operating in extremely complex settings effectively avoid accidents for lengthy stretches of time, whilst maintaining their ability to fulfill highly unpredictable and demanding production targets. In essence, researchers sought to identify organizational characteristics or procedures that significantly reduced the hazards associated with operating in a highly dynamic and closely connected environment (Shrivastava et al., 2009). In other words, researchers sought to identify "how to organize in the face of the unexpected" (Weick, 2006, p. 51). ...
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... HRO, therefore, provides a useful starting point for planning how to increase the reliability of any digitally connected infrastructure systems. Shrivastava et al. (2009) and (Leveson, 2011) are amongst those critics who suggest the tension between NAT and HRO perspectives is over-stated because the principles of HRO ( implications for practice. NAT implies that organizations can lower the statistical probability of systems accidents (but never lower it to zero) by reducing their complexity and loosening the coupling amongst their subsystems. ...
... NAT implies that organizations can lower the statistical probability of systems accidents (but never lower it to zero) by reducing their complexity and loosening the coupling amongst their subsystems. We argue that the initiatives identified by HRT [HRO]strategic concern for safety and safe design, redundancy, simultaneous centralization and decentralization, training, organizational learning, and mindfulness [see Table 5]can all be construed as attempts to either directly or indirectly address the challenges posed by complex interactions and tight coupling, the very dimensions central to NAT." (Shrivastava et al., 2009 ...
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This literature review was produced by Dr Tom Dolan, Senior Research Associate ICIF and UKCRIC, UCL on behalf of UCL and Arup for the National Infrastructure Commission. The literature review presents and critiques key areas of academic literature relevant to four research questions on digitally connected infrastructure systems (DCIS) posed by the National Infrastructure Commission (NIC). The review provides additional context to support analysis, findings and recommendations presented in the main project report, and can be read as in conjunction with the report or as a standalone document
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... Aan de hand van de gestelde kernwaarden in het beliefs systeem worden medewerkers aangenomen met gelijkende waarden of die zij passend achten. De symbol-based controls bestaan uit controls waarmee de organisatie haar cultuur zichtbaar ontwikkelt (Schein 2010), bijvoorbeeld aan de hand van werkplekinrichting of dresscodes. Ten slotte bevat het MCSP nog clan controls. ...
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