Monday, November 11, 2013

Engineering a Safer World: Systems Thinking Applied to Safety by Nancy Leveson

In this book* Leveson, an MIT professor, describes a comprehensive approach for designing and operating “safe” organizations based on systems theory.  The book presents the criticisms of traditional incident analysis methods, the principles of system dynamics, and essential safety-related organizational characteristics, including the role of culture, in one place; this review emphasizes those topics.  It should be noted the bulk of the book describes her accident causality model and how to apply it, including extensive case studies; this review does not fully address that material.

Part I
     
Part I sets the stage for a new safety paradigm.  Many contemporary socio-technical systems exhibit, among other characteristics, rapidly changing technology, increasing complexity and coupling, and pressures that put production ahead of safety. (pp. 3-6)   Traditional accident analysis techniques are no longer sufficient.  They too often focus on eliminating failures, esp. component failures or “human error,” instead of concentrating on eliminating hazards. (p. 10)  Some of Leveson's critique of traditional accident analysis echoes Dekker (esp. the shortcomings of Newtonian-Cartesian analysis, reviewed here).**   We devote space to Leveson's criticisms because she provides a legitimate perspective on techniques that comprise some of the nuclear industry's sacred cows.

Event-based models are simply inadequate.  There is subjectivity in selecting both the initiating event (the failure) and the causal chains backwards from it.  The root cause analysis often stops at the first root cause that is familiar, amenable to corrective action, difficult to get beyond (usually the human operator or other human role) or politically acceptable. (pp. 20-24)  Reason's Swiss cheese model is insufficient because of its assumption of direct, linear relationships between components. (pp. 17-19)  In addition, “event-based models are poor at representing systemic accident factors such as structural deficiencies in the organization, management decision making, and flaws in the safety culture of the company or industry.” (p. 28)

Probabilistic Risk Assessment (PRA) studies specified failure modes in ever greater detail but ignores systemic factors.  “Most accidents in well-designed systems involve two or more low-probability events occurring in the worst possible combination.  When people attempt to predict system risk, they explicitly or implicitly multiply events with low probability—assuming independence—and come out with impossibly small numbers, when, in fact, the events are dependent.  This dependence may be related to common systemic factors that do not appear in an event chain.  Machol calls this phenomenon the Titanic coincidence . . . The most dangerous result of using PRA arises from considering only immediate physical failures.” (pp. 34-35)  “. . . current [PRA] methods . . . are not appropriate for systems controlled by software and by humans making cognitively complex decisions, and there is no effective way to incorporate management or organizational factors, such as flaws in the safety culture, . . .” (p. 36) 

The search for operator error (a fall guy who takes the heat off of system designers and managers) and hindsight bias also contribute to the inadequacy of current accident analysis approaches. (p. 38)  In contrast to looking for an individual's “bad” decision, Leveson says “the study of decision making cannot be separated from a simultaneous study of the social context, the value system in which it takes place, and the dynamic work process it is intended to control.” (p. 46) 

Leveson says “Systems are not static. . . . they tend to involve a migration to a state of increasing risk over time.” (p. 51)  Causes include adaptation in response to pressures and the effects of multiple independent decisions. (p. 52)  This is reminiscent of  Hollnagel's warning that cost pressure will eventually push production to the edge of the safety boundary.

When accidents or incidents occur, Leveson proposes that analysis should search for reasons (the Whys) rather than blame (usually defined as Who) and be based on systems theory. (pp. 55-56)  In a systems view, safety is an emergent property, i.e., system safety performance cannot be predicted by analyzing system components. (p. 64)  Some of the goals for a better model include analysis that goes beyond component failures and human errors, is more scientific and less subjective, includes the possibility of system design errors and dysfunctional system interactions, addresses software, focuses on mechanisms and factors that shape human behavior, examines processes and allows for multiple viewpoints in the incident analysis. (pp. 58-60) 

Part II

Part II describes Leveson's proposed accident causality model based on systems theory: STAMP (Systems-Theoretic Accident Model and Processes).  For our purposes we don't need to spend much space on this material.  “The model includes software, organizations, management, human decision-making, and migration of systems over time to states of heightened risk.”***   It attempts to achieve the goals listed at the end of Part I.

STAMP treats safety in a system as a control problem, not a reliability one.  Specifically, the overarching goal “is to control the behavior of the system by enforcing the safety constraints in its design and operation.” (p. 76)  Controls may be physical or social, including cultural.  There is a good discussion of the hierarchy of control in a complex system and the impact of possible system dynamics, e.g., time lags, feedback loops and changes in control structures. (pp. 80-87)  “The process leading up to an accident is described in STAMP in terms of an adaptive feedback function that fails to maintain safety as system performance changes over time to meet a complex set of goals and values.” (p. 90)

Leveson describes problems that can arise from an inaccurate mental model of a system or an inaccurate model displayed by a system.  There is a lengthy, detailed case study that uses STAMP to analyze a tragic incident, in this case a friendly fire accident where a U.S. Army helicopter was shot down by an Air Force plane over Iraq in 1994.

Part III

Part III describes in detail how STAMP can be applied.  There are many useful observations (e.g., problems with mode confusion on pp. 289-94) and detailed examples throughout this section.  Chapter 11 on using a STAMP-based accident analysis illustrates the claimed advantages of  STAMP over traditional accident analysis techniques. 

We will focus on a chapter 13, “Managing Safety and the Safety Culture,” which covers the multiple dimensions of safety management, including safety culture.

Leveson's list of the components of effective safety management is mostly familiar: management commitment and leadership, safety policy, communication, strong safety culture, safety information system, continual learning, education and training. (p. 421)  Two new components need a bit of explanation, a safety control structure and controls on system migration toward higher risk.  The safety control structure assigns specific safety-related responsibilities to management, system designers and operators. (pp. 436-40)  One of the control structure's responsibilities is to identify “the potential reasons for and types of migration toward higher risk need to be identified and controls instituted to prevent it.” (pp. 425-26)  Such an approach should be based on the organization's comprehensive hazards analysis.****

The safety culture discussion is also familiar. (pp. 426-33)  Leveson refers to the Schein model, discusses management's responsibility for establishing the values to be used in decision making, the need for open, non-judgmental communications, the freedom to raise safety questions without fear of reprisal and widespread trust.  In such a culture, Leveson says an early warning system for migration toward states of high risk can be established.  A section on Just Culture is taken directly from Dekker's work.  The risk of complacency, caused by inaccurate risk perception after a long history of success, is highlighted.

Although these management and safety culture contents are generally familiar, what's new is relating them to systems concepts such as control loops and feedback and taking a systems view of the safety control system.

Our Perspective
 

Overall, we like this book.  It is Leveson's magnum opus, 500+ pages of theory, rationale, explanation, examples and infomercial.  The emphasis on the need for a systems perspective and a search for Why accidents/incidents occur (as opposed to What happened or Who is at fault) is consistent with what we've been saying on this blog.  The book explains and supports many of the beliefs we have been promoting on Safetymatters: the shortcomings of traditional (but commonly used) methods of incident investigation; the central role of decision making; and how management commitment, financial and non-financial rewards, and a strong safety culture contribute to system safety performance.
 

However, there are only a few direct references to nuclear.  The examples in the book are mostly from aerospace, aviation, maritime activities and the military.  Establishing a safety control structure is probably easier to accomplish in a new aerospace project than in an existing nuclear organization with a long history (aka memory),  shifting external pressures, and deliberate incremental changes to hardware, software, policies, procedures and programs.  Leveson does mention John Carroll's (her MIT colleague) work at Millstone. (p. 428)  She praises nuclear LER reporting as a mechanism for sharing and learning across the industry. (pp. 406-7)  In our view, LERs should be helpful but they are short on looking at why incidents occur, i.e., most LER analysis does not look at incidents from a systems perspective.  TMI is used to illustrate specific system design/operation problems.
 

We don't agree with the pot shots Leveson takes at High Reliability Organization (HRO) theorists.  First, she accuses HRO of confusing reliability with safety, in other words, an unsafe system can function very reliably. (pp. 7, 12)  But I'm not aware of any HRO work that has been done in an organization that is patently unsafe.  HRO asserts that reliability follows from practices that recognize and contain emerging problems.  She takes another swipe at HRO when she says HRO suggests that, during crises, decision making migrates to frontline workers.  Leveson's problem with that is “the assumption that frontline workers will have the necessary knowledge and judgment to make decisions is not necessarily true.” (p. 44)  Her position may be correct in some cases but as we saw in our review of CAISO, when the system was veering off into new territory, no one had the necessary knowledge and it was up to the operators to cope as best they could.  Finally, she criticizes HRO advice for operators to be on the lookout for “weak signals.”  In her view, “Telling managers and operators to be “mindful of weak signals” simply creates a pretext for blame after a loss event occurs.” (p. 410)  I don't think it's pretext but it is challenging to maintain mindfulness and sense faint signals.  Overall, this appears to be academic posturing and feather fluffing.
 

We offer no opinion on the efficacy of using Leveson's STAMP approach.  She is quick to point out a very real problem in getting organizations to use STAMP: its lack of focus on finding someone/something to blame means it does not help identify subjects for discipline, lawsuits or criminal charges. (p. 86)
 

In Leveson's words, “The book is written for the sophisticated practitioner . . .” (p. xviii)  You don't need to run out and buy this book unless you have a deep interest in accident/incident analysis and/or are willing to invest the time required to determine exactly how STAMP might be applied in your organization.


*  N.G. Leveson, Engineering a Safer World: Systems Thinking Applied to Safety (The MIT Press, Cambridge, MA: 2011)  The link goes to a page where a free pdf version of the book can be downloaded; the pdf cannot be copied or printed.  All quotes in this post were retyped from the original text.


**  We're not saying Dekker or Hollnagel developed their analytic viewpoints ahead of Leveson; we simply reviewed their work earlier.  These authors are all aware of others' publications and contributions.  Leveson includes Dekker in her Acknowledgments and draws from Just Culture: Balancing Safety and Accountability in her text. 

***  Nancy Leveson informal bio page.


****  “A hazard is a system state or set of conditions that, together with a particular set of worst-case environmental conditions, will lead to an accident.” (p. 157)  The hazards analysis identifies all major hazards the system may confront.  Baseline safety requirements follow from the hazards analysis.  Responsibilities are assigned to the safety control structure for ensuring baseline requirements are not violated while allowing changes that do not raise risk.  The identification of system safety constraints allows the possibility of identifying leading indicators for a specific system. (pp. 337-38)

1 comment:

  1. Lew,

    I found myself nodding vigorously in agreement with this sentence in your review: “Overall, this appears to be academic posturing…” I’m not sure how broadly you intended your comment but, with some regret, I’m content to take it as an epitaph on the entire book.

    Reading your description of the Book’s Parts, I felt affirmed; your take on the sense of the book matches my own. I hope readers will appreciate how you gave Leveson’s noble intentions a chance in the foreground before circling back to her most troubling assertions.

    Already by page 9, Leveson has looked at the socio-technical divide – so evident in accidents like Deepwater Horizon – and come down of the side of traditional systems engineering “enforced” (her term) by the constraints of behavior-based safety. Technical control modeling, she insists, can be sufficient to constrain Complex, High-Consequence Circumstance institutions from Drifting into Failure.

    You rightly point to the CAISO experience – it is a fully-realized falsification of Leveson’s control theory – that linear determinist design for equilibrium-seeking control constraints can inform management for situations at and around the boundaries of the design basis. We’ve many other examples that Newtonian modeling of non-linear, far-from-equilibrium poised Systems of Systems doesn’t work – they ignore the externalities and the importance of Resilience on top of classical forward-engineered Reliability.

    Leveson’s thinking pretty much took shape in the 1990’s after Challenger and before Columbia – while this book didn’t appear until 2011, it is a compendium of much older papers. There is a severe lexicon problem that seems evident after the shift toward human performance as the equalizer in the research of Reason, Hollnagel, Amalberti, and others.

    Her usage for risk, reliability, control, systems safety, complexity and culture are all shoe-horned back into a familiar world view of the fully forward-engineered artifacts. Her quarrel with the HRO types from Berkeley is also vintage 90’s – I think Weick, Suttcliffe, and Klein had established their value well before the Millennium arrived. This sounds like the micro-economists and the New Keynsian macro-economists; in 2011 the evidence was pretty much in.

    STAMP and its lexicon are thoroughly Newtonian-Cartesian and that is its downfall. I’ve been reviewing Dana Meadow’s “Thinking in Systems” particularly to confront my ignorance about the challenge of shifting perspectives from Causal Loop Diagrams to Stock and Flow modeling for understanding trends. Eventually I hope to include Agent Based Modeling concepts in some sort of comparative framework – that just seems necessary at this point.

    In doing so I’m reminded of my early response to the systems thinking aspects of Leveson’s work – it doesn’t seem to get past the reality that system archetypes are useful for understanding Resilience (ebb and flow of critical dependent variables); they perform quite apart from Reliability measures which are the stock and trade of conventional engineering’s contribution. I’m afraid that Leveson’s project goes astray at the Title – it takes a good deal more and different from Engineering.

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