Leadership, Decisions, Systems Thinking and Nuclear Safety Culture

AcciMap Excerpt

We recently read a paper* that echoes some of the themes we emphasize on Safetymatters, viz., leadership, decisions and a systems view.  Following is an excerpt from the abstract:

“Leadership is progressively being recognized as a key** factor in supporting successful performance across a range of domains. . . . the decisions and actions that characterize safety leadership thus become important emergent properties in the prevention of incidents, which should be considered within the context of the broader organizational system and not merely constrained to understanding events or conditions that shape performance at the ‘sharp end’.”  [emphasis added]

The authors go on to analyze decisions and actions after a mining incident (landslide) using a combination of three different schemes: Rasmussen’s Risk Management Framework (RMF) and corresponding AcciMap, and the Critical Decision Method (CDM).

The RMF describes work systems as comprised of various levels and argues that safety performance is affected by decisions and actions at all levels from politicians in the external environment down through company executives and managers and finally to individual workers.  Rasmussen’s AcciMap is an expansive causal diagram for an accident or incident that displays the contributions (or omissions) at each level in the RMF and their connections.

CDM uses semi-structured interviews to obtain information about how individuals formulate their decisions, including context such as background knowledge and immediate influencing factors.  Consistent with the RMF, case study interviews were conducted with individuals at different organizational levels.  CDM data were used to construct the AcciMap.

We won’t go into the details of the analysis but it identified over a dozen key decisions made at different organizational levels before and during the incident; most were connected to at least one other key decision.  The AcciMap illustrates decisions and communications across multiple levels and thus provides a useful picture of how an organization anticipates and responds to an unusual situation.

Our Perspective

The authors argue, and we agree, that this type of analysis provides greater detail and insight into the performance of an organization’s safety management system than traditional accident investigations (especially those focused on finding someone to blame).

This article does not specifically discuss culture.  But the body of decisions an organization produces is the strongest evidence and most visible artifact of its culture.  Organizational decisions are far more important than responses to surveys or interviews where people can report what they believe (or hope) the culture is, or what they think their audience wants to hear.

We like that RMF and AcciMap are agnostic: they can be used to analyze either “what went wrong” or “what went right” scenarios.  (The case study was in the latter category because no one was hurt in the incident.)  If an assessor is looking at a sample of decisions to infer a nuclear organization’s culture, most of those decisions will have had positive (or at least no negative) consequences.

The authors are Australian academics but this short (8 pages total) paper is quite readable and a good introduction to CDM and Rasmussen’s constructs.  The references include people whose work we have positively reviewed on Safetymatters, including Dekker, Hollnagel, Leveson and Reason.

Bottom line: There is nothing about culture or nuclear here, but the overall message reinforces our beliefs about how to think about Nuclear Safety Culture.


*  S-L Donovana, P.M. Salmonb and M.G. Lennéa, “The leading edge: A systems thinking methodology for assessing safety leadership,” Procedia Manufacturing 3 (2015), pp. 6644–6651.  Available at sciencedirect.com; retrieved Jan. 19, 2017.

**  Note they do not say “one and only” or even “most important.”

Safety-I and Safety-II: The Past and Future of Safety Management by Erik Hollnagel

This book* discusses two different ways of conceptualizing safety performance problems (e.g., near-misses, incidents and accidents) and safety management in socio-technical systems.  This post describes each approach and provides our perspective on Hollnagel’s efforts.  As usual, our interest lies in the potential value new ways of thinking can offer to the nuclear industry.

Safety-I

This is the common way of looking at safety performance problems.  It is reactive, i.e., it waits for problems to arise** and analytic, e.g., it uses specific methods to work back from the problem to its root causes.  The key assumption is that something in the system has failed or malfunctioned and the purpose of an investigation is to identify the causes and correct them so the problem will not recur.  A second assumption is that chains of causes and effects are linear, i.e., it is actually feasible to start with a problem and work back to its causes.  A third assumption is that a single solution (the “first story”) can be found. (pp. 86, 175-76)***  Underlying biases include the hindsight bias (p. 176) and the belief that the human is usually the weak link. (pp. 78-79)  The focus of safety management is minimizing the number of things that go wrong.

Our treatment of Safety-I is brief because we have reported on criticism of linear thinking/models elsewhere, primarily in the work of Dekker, Woods et al, and Leveson.  See our posts of Dec. 5, 2012; July 6, 2013; and Nov. 11, 2013 for details.

Safety-II

Safety-II is proposed as a different way to look at safety performance.  It is proactive, i.e., it looks at the ways work is actually performed on a day-to-day basis and tries to identify causes of performance variability and then manage them.  A key cause of variability is the regular adjustments people make in performing their jobs in order to keep the system running.  In Hollnagel’s view, “Finding out what these [performance] adjustments are and trying to learn from them can be more important than finding the causes of infrequent adverse outcomes!” (p. 149)  The focus of safety management is on increasing the likelihood that things will go right and developing “the ability to succeed under varying conditions, . . .” (p. 137).

Performance is variable because, among other reasons, people are always making trade-offs between thoroughness and efficiency.  They may use heuristics or have to compensate for something that is missing or take some steps today to avoid future problems.  The underlying assumption of Safety-II is that the same behaviors that almost always lead to successful outcomes can occasionally lead to problems because of performance variability that goes beyond the boundary of the control space.  A second assumption is that chains of causes and effects may be non-linear, i.e., a small variance may lead to a large problem, and may have an emergent aspect where a specific performance variability may occur then disappear or the Swiss cheese holes may momentarily line up exposing the system to latent hazards. (pp. 66, 131-32)  There may be multiple explanations (“second stories”) for why a particular problem occurred.  Finally, Safety-II accepts that there are often differences between Work-as-Imagined (esp. as imagined by folks at the blunt end) and Work-as-Done (by people at the sharp end). (pp. 40-41)***

The Two Approaches

Safety-I and Safety-II are not in some winner-take-all competitive struggle.  Hollnagel notes there are plenty of problems for which a Safety-I investigation is appropriate and adequate. (pp. 141, 146)

Safety-I expenditures are viewed as a cost (to reduce errors). (p. 57)  In contrast, Safety-II expenditures are viewed as bona fide investments to create more correct outcomes. (p. 166)

In all cases, organizational factors, such as safety culture, can impact safety performance and organizational learning. (p. 31)

Our Perspective

The more complex a socio-technical entity is, the more it exhibits emergent properties and the more appropriate Safety-II thinking is.  And nuclear has some elements of complexity.****  In addition, Hollnagel notes that a common explanation for failures that occur in a System-I world is “it was never imagined something like that could happen.” (p. 172)  To avoid being the one in front of the cameras saying that, it might be helpful for you to spend a little time reflecting on how System-II thinking might apply in your world.

Why do most things go right?  Is it due to strict compliance with procedures?  Does personal creativity or insight contribute to successful plant performance?  Do you talk with your colleagues about possible efficiency-thoroughness trade-offs (short cuts) that you or others make?  Can thinking about why things go right make one more alert to situations where things are heading south?  Does more automation (intended to reduce reliance on fallible humans) actually move performance closer to the control boundary because it removes the human’s ability to make useful adjustments?  Has any of your root cause evaluations appeared to miss other plausible explanations for why a problem occurred?

Some of the Safety-II material is not new.  Performance variability in Safety-II builds on Hollnagel’s earlier work on the efficiency-thoroughness trade-off (ETTO) principle.  (See our Jan. 3, 2013 post.)   His call for mindfulness and constant alertness to problems is straight out of the High Reliability Organization playbook. (pp. 36, 163-64)  (See our May 3, 2013 post.)

A definite shortcoming is the lack of concrete examples in the Safety-II discussion.  If someone has tried to do this, it would be nice to hear about it.

Bottom line, Hollnagel has some interesting observations although his Safety-II model is probably not the Next Big Thing for nuclear safety management.

 
*  E. Hollnagel, Safety-I and Safety-II: The Past and Future of Safety Management  (Burlington, VT: Ashgate , 2014)

**  In the author’s view, forward-looking risk analysis is not proactive because it is infrequently performed. (p. 57) 

***  There are other assumptions in the Safety-I approach (see pp. 97-104) but for the sake of efficiency, they are omitted from this post.

****  Nuclear power plants have some aspects of a complex socio-technical system but other aspects are merely complicated.   On the operations side, activities are tightly coupled (one attribute of complexity) but most of the internal organizational workings are complicated.  The lack of sudden environmental disrupters (excepting natural disasters) means they have time to adapt to changes in their financial or regulatory environment, reducing complexity.

A Life In Error by James Reason

Most of us associate psychologist James Reason with the “Swiss Cheese Model” of defense in depth or possibly the notion of a “just culture.”  But his career has been more than two ideas, he has literally spent his professional life studying errors, their causes and contexts.  A Life In Error* is an academic memoir, recounting his study of errors starting with the individual and ending up with the organization (the “system”) including its safety culture (SC).  This post summarizes relevant portions of the book and provides our perspective.  It is going to read like a sub-titled movie on fast-forward but there are a lot of particulars packed in this short (124 pgs.) book. 

Slips and Mistakes 

People make plans and take action, consequences follow.  Errors occur when the intended goals are not achieved.  The plan may be adequate but the execution faulty because of slips (absent-mindedness) or trips (clumsy actions).  A plan that was inadequate to begin with is a mistake which is usually more subtle than a slip, and may go undetected for long periods of time if no obviously bad consequences occur. (pp. 10-12)  A mistake is a creation of higher-level mental activity than a slip.  Both slips and mistakes can take “strong but wrong” forms, where schema** that were effective in prior situations are selected even though they are not appropriate in the current situation.

Absent-minded slips can occur from misapplied competence where a planned routine is sidetracked into an unplanned one.  Such diversions can occur, for instance, when one’s attention is unexpectedly diverted just as one reaches a decision point and multiple schema are both available and actively vying to be chosen. (pp. 21-25)  Reason’s recipe for absent-minded errors is one part cognitive under-specification, e.g., insufficient knowledge, and one part the existence of an inappropriate response primed by prior, recent use and the situational conditions. (p. 49) 

Planning Biases 

The planning activity is subject to multiple biases.  An individual planner’s database may be incomplete or shaped by past experiences rather than future uncertainties, with greater emphasis on past successes than failures.  Planners can underestimate the influence of chance, overweight data that is emotionally charged, be overly influenced by their theories, misinterpret sample data or miss covariations, suffer hindsight bias or be overconfident.***  Once a plan is prepared, planners may focus only on confirmatory data and are usually resistant to changing the plan.  Planning in a group is subject to “groupthink” problems including overconfidence, rationalization, self-censorship and an illusion of unanimity.  (pp. 56-62)

Errors and Violations 

Violations are deliberate acts to break rules or procedures, although bad outcomes are not generally intended.  Violations arise from various motivational factors including the organizational culture.  Types of violations include corner-cutting to avoid clumsy procedures, necessary violations to get the job done because the procedures are unworkable, adjustments to satisfy conflicting goals and one-off actions (such as turning off a safety system) when faced with exceptional circumstances.  Violators perform a type of cost:benefit analysis biased by the fact that benefits are likely immediate while costs, if they occur, are usually somewhere in the future.  In Reason’s view, the proper course for the organization is to increase the perceived benefits of compliance not increase the costs (penalties) for violations.  (There is a hint of the “just culture” here.) 

Organizational Accidents 

Major accidents (TMI, Chernobyl, Challenger) have three common characteristics: contributing factors that were latent in the system, multiple levels of defense, and an unforeseen combination of latent factors and active failures (errors and/or violations) that defeated the defenses.  This is the well-known Swiss Cheese Model with the active failures opening short-lived holes and latent failures creating longer-lasting but unperceived holes.

Organizational accidents are low frequency, high severity events with causes that may date back years.  In contrast, individual accidents are more frequent but have limited consequences; they arise from slips, trips and lapses.  This is why organizations can have a good industrial accident record while they are on the road to a large-scale disaster, e.g., BP at Texas City. 

Organizational Culture 

Certain industries, including nuclear power, have defenses-in-depth distributed throughout the system but are vulnerable to something that is equally widespread.  According to Reason, “The most likely candidate is safety culture.  It can affect all elements in a system for good or ill.” (p. 81)  An inadequate SC can undermine the Swiss Cheese Model: there will be more active failures at the “sharp end”; more latent conditions created and sustained by management actions and policies, e.g., poor maintenance, inadequate equipment or downgrading training; and the organization will be reluctant to deal proactively with known problems. (pp. 82-83)

Reason describes a “cluster of organizational pathologies” that make an adverse system event more likely: blaming sharp-end operators, denying the existence of systemic inadequacies, and a narrow pursuit of production and financial goals.  He goes on to list some of the drivers of blame and denial.  The list includes: accepting human error as the root cause of an event; the hindsight bias; evaluating prior decisions based on their outcomes; shooting the messenger; belief in a bad apple but not a bad barrel (the system); failure to learn; a climate of silence; workarounds that compensate for systemic inadequacies’ and normalization of deviance.  (pp. 86-92)  Whew! 

Our Perspective 

Reason teaches us that the essence of understanding errors is nuance.  At one end of the spectrum, some errors are totally under the purview of the individual, at the other end they reside in the realm of the system.  The biases and issues described by Reason are familiar to Safetymatters readers and echo in the work of Dekker, Hollnagel, Kahneman and others.  We have been pounding the drum for a long time on the inadequacies of safety analyses that ignore systemic issues and corrective actions that are limited to individuals (e.g., more training and oversight, improved procedures and clearer expectations).

The book is densely packed with the work of a career.  One could easily use the contents to develop a SC assessment or self-assessment.  We did not report on the chapters covering research into absent-mindedness, Freud and medical errors (Reason’s current interest) but they are certainly worth reading.

Reason says this book is his valedictory: “I have nothing new to say and I’m well past my prime.” (p. 122)  We hope not.


*  J. Reason, A Life In Error: From Little Slips to Big Disasters (Burlington, VT: Ashgate, 2013).

**  Knowledge structures in long-term memory. (p. 24)

***  This will ring familiar to readers of Daniel Kahneman.  See our Dec. 18, 2013 post on Kahneman’s Thinking, Fast and Slow.

Systems Thinking in Air Traffic Management

A recent white paper* presents ten principles to consider when thinking about a complex socio-technical system, specifically European Air Traffic Management (ATM).  We review the principles below, highlighting aspects that might provide some insights for nuclear power plant operations and safety culture (SC).

Before we start, we should note that ATM is truly a complex** system.  Decisions involving safety and efficiency occur on a continuous basis.  There is always some difference between work-as-imagined and work-as-done.

In contrast, we have argued that a nuclear plant is a complicated system but it has some elements of complexity.  To the extent complexity exists, treating nuclear like a complicated machine via “analysing components using reductionist methods; identifying ‘root causes’ of problems or events; thinking in a linear and short-term way; . . . [or] making changes at the component level” is inadequate. (p. 5)  In other words, systemic factors may contribute to observed performance variability and frustrate efforts to achieve the goal in nuclear of eliminating all differences between work-as-planned and work-as-done.

Principles 1-3 relate to the view of people within systems – our view from the outside and their view from the inside.

1. Field Expert Involvement	“To understand work-as-done and improve how things really work, involve those who do the work.” (p. 8)
2. Local Rationality	“People do things that make sense to them given their goals, understanding of the situation and focus of attention at that time.” (p. 10)
3. Just Culture	“Adopt a mindset of openness, trust and fairness. Understand actions in context, and adopt systems language that is non-judgmental and non-blaming.” (p. 12)

Nuclear is pretty good at getting line personnel involved.  Adages such as “Operations owns the plant” are useful to the extent they are true.  Cross-functional teams can include operators or maintenance personnel.  An effective CAP that allows workers to identify and report problems with equipment, procedures, etc. is good; an evaluation and resolution process that involves members from the same class of workers is even better.  Having someone involved in an incident or near-miss go around to the tailgates and classes to share the lessons learned can be convincing.

But when something unexpected or bad happens, nuclear tends to spend too much time looking for the malfunctioning component (usually human).   “The assumption is that if the person would try harder, pay closer attention, do exactly what was prescribed, then things would go well. . . . [But a] focus on components becomes less effective with increasing system complexity and interactivity.” (p. 4)  An outside-in approach ignores the context in which the human performed, the information and time available, the competition for focus of attention, the physical conditions of the work, fatigue, etc.  Instead of insight into system nuances, the result is often limited to more training, supervision or discipline.

The notion of a “just culture” comes from James Reason.  It’s a culture where employees are not punished for their actions, omissions or decisions that are commensurate with their experience and training, but where gross negligence, willful violations and destructive acts are not tolerated.

Principles 4 and 5 relate to the system conditions and context that affect work.

4. Demand and Pressure	“Demands and pressures relating to efficiency and capacity have a fundamental effect on performance.” (p. 14)
5. Resources & Constraints	“Success depends on adequate resources and appropriate constraints.” (p. 16)

Fluctuating demand creates far more varied and unpredictable problems for ATM than it does in nuclear.  However, in nuclear the potential for goal conflicts between production, cost and safety is always present.  The problem arises from acting as if these conflicts don’t exist.

ATM has to “cope with variable demand and variable resources,” a situation that is also different from nuclear with its base load plants and established resource budgets.  The authors opine that for ATM, “a rigid regulatory environment destroys the capacity to adapt constantly to the environment.” (p. 2) Most of us think of nuclear as quite constrained by procedures, rules, policies, regulations, etc., but an important lesson from Fukushima was that under unforeseen conditions, the organization must be able to adapt according to local, knowledge-based decisions  Even the NRC recognizes that “flexibility may be necessary when responding to off-normal conditions.”***

Principles 6 through 10 concern the nature of system behavior, with 9 and 10 more concerned with system outcomes.  These do not have specific implications for SC other than keeping an open mind and being alert to systemic issues, e.g., complacency, drift or emergent behavior.

6. Interactions and Flows	“Understand system performance in the context of the flows of activities and functions, as well as the interactions that comprise these flows.” (p. 18)
7. Trade-Offs	“People have to apply trade-offs in order to resolve goal conflicts and to cope with the complexity of the system and the uncertainty of the environment.” (p. 20)
8. Performance variability	“Understand the variability of system conditions and behaviour.  Identify wanted and unwanted variability in light of the system’s need and tolerance for variability.” (p. 22)
9. Emergence	“System behaviour in complex systems is often emergent; it cannot be reduced to the behaviour of components and is often not as expected.” (p. 24)
10. Equivalence	“Success and failure come from the same source – ordinary work.” (p. 26)

Work flow certainly varies in ATM but is relatively well-understood in nuclear.  There’s really not much more to say on that topic.

Trade-offs occur in decision making in any context where more than one goal exists.  One useful mental model for conceptualizing trade-offs is Hollnagel’s efficiency-thoroughness construct, basically doing things quickly (to meet the production and cost goals) vs. doing things well (to meet the quality and possibly safety goals).  We reviewed his work on Jan. 3, 2013.

Performance variability occurs in all systems, including nuclear, but the outcomes are usually successful because a system has a certain range of tolerance and a certain capacity for resilience.  Performance drift happens slowly, and can be difficult to identify from the inside.  Dekker’s work speaks to this and we reviewed it on Dec. 5, 2012.

Nuclear is not fully complex but surprises do happen, some of them not caused by component failure.  Emergence (problems that arise from new or unforeseen system interactions) is more likely to occur following the implementation of new technical systems.  We discussed this possibility in a July 6, 2013 post on a book by Woods, Dekker et al.

Equivalence means that work that results in both good and bad outcomes starts out the same way, with people (saboteurs excepted) trying to be successful.  When bad things happen, we should cast a wide net in looking for different factors, including systemic ones, that aligned (like Swiss cheese slices) in the subject case.

The white paper also includes several real and hypothetical case studies illustrating the application of the principles to understanding safety performance challenges 

Our Perspective 

The authors draw on a familiar cast of characters, including Dekker, Hollnagel, Leveson and Reason.  We have posted about all these folks, just click on their label in the right hand column.

The principles are intended to help us form a more insightful mental model of a system under consideration, one that includes non-linear cause and effect relationships, and the possibility of emergent behavior.  The white paper is not a “must read” but may stimulate useful thinking about the nature of the nuclear operating organization.


*  European Organisation for the Safety of Air Navigation(EUROCONTROL), “Systems Thinking for Safety: Ten Principles” (Aug. 2014).  Thanks to Bill Mullins for bringing this white paper to our attention.

**  “[C]omplex systems involve large numbers of interacting elements and are typically highly dynamic and constantly changing with changes in conditions. Their cause-effect relations are non-linear; small changes can produce disproportionately large effects. Effects usually have multiple causes, though causes may not be traceable and are socially constructed.” (pp. 4-5)

Also see our Oct. 14, 2013 discussion of the California Independent System Operator for another example of a complex system.

***  “Work Processes,” NRC Safety Culture Trait Talk, no. 2 (July 2014), p. 1.  ADAMS ML14203A391.  Retrieved Oct. 8, 2014

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)