Swiss Cheese Model

What is the Swiss Cheese Model?

The Swiss Cheese Model illustrates how failures typically result from a combination of factors rather than a single root cause.3 These factors often include latent errors inherent in a procedure, machine, or system. The model is visualized as multiple layers of Swiss cheese, where the holes in each layer represent potential failure points. When these holes align, a failure occurs.

Swiss Cheese Model

The Basic Idea

In recent years, a new area of study known as “safety science” has emerged. Safety science is fundamentally connected to several other fields, such as engineering and healthcare. Its scope is not limited to physical and psychological safety, but also includes issues of security, such as cybersecurity. Advancements in safety science aim to inform decision-making in a variety of disciplines.1 One model used by safety scientists to assess risk is the Swiss Cheese Model.

Every slice of Swiss cheese is full of holes. The size and number of holes will vary from one slice to another. In this model, a slice of Swiss cheese is symbolic of a given measure taken to minimize risk. Each slice of cheese can be thought of as a line of defense against accidents. Examples of different “slices” within a given organization may be management, allocation of resources, and an effective safety program.2

Each slice of Swiss cheese has its own unique set of holes. These holes represent shortcomings, or areas where there is potential for failure. Some slices may have more holes than others. When all of a given organization’s slices are stacked together, they represent the organization’s defense against risk as a whole. Since all the pieces of cheese have holes in different areas (which is representative of their differing weak points), sometimes one or more slices of cheese will cover a hole in another slice of cheese. This is symbolic of how some facets of an organization have strengths that can compensate for the shortcomings of others. However, sometimes holes will overlap, resulting in a hole that goes all the way through the stack of cheese. This represents a weak point that is common to all areas of a given organization, where there is the greatest potential for failure to occur.

Latent errors are triggered by active errors, which are unsafe behaviors carried out by individual parties. Thus, it is not simply mistakes made at the individual level that lead to an accident. In models of risk assessment, we must also consider the latent conditions that may be triggered by these errors.4

The Swiss Cheese Model has been used to help organizations understand why accidents occur in spite of their best efforts to prevent them. It is helpful for identifying weak points and for developing strategies to combat them. The goal of safety science is to maximize productivity while minimizing risk of harm, and the Swiss Cheese Model is an asset to the advancement of the field.

In order for a catastrophic event, such as a plane crash, to occur, a sequence of events precedes it. Think of these separate factors as slices of Swiss cheese lined up one behind the other. If any one of the holes in them doesn’t align with the others, the series of events is changed or curtailed, and a catastrophe is prevented. But if all the holes line up…the door is open for disaster.

– Sandra Brown in Low Pressure (2012)

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A professor at Manchester University named James Reason is credited with the creation of the Swiss Cheese Model.5 He presented the concept in his book, Human Error, which was released in 1991. In this book, he elaborates on his theory that accidents do not result from one or more independent events. Instead, he posits that accidents occur due to several interconnected factors which, together, culminate in failure. One example he uses to illustrate his point is that of the 1986 Challenger disaster,6 a historical tragedy in which a space shuttle exploded just 73 seconds after liftoff, killing all seven people on board.7 


The goal of this model is to inform decision-making that will ultimately prevent accidents from occurring. By keeping in mind that all lines of defense within an organization are interconnected, decision-makers can implement policies and interventions that effectively minimize risk. The Swiss Cheese Model aims to help organizations avoid common pitfalls. It also addresses the importance of minimizing latent errors, which, when triggered by active errors, may result in accidents. One way of doing this is keeping up to date with the latest standards and technological advancements.8 

This model has also led to effective communication, as it presents organizational accidents in a way that can be easily visualized and understood by anyone, regardless of their area of expertise or level within the organization.9 While the specifics of risk analysis and accident prevention are complex and may be difficult for many to grasp, this model can be presented simply, giving many people a basic understanding of these complicated topics.


One of the first criticisms of this model came from James Reason himself. He worried that the model was being applied to broadly and too dogmatically.10 He is quoted saying: “the pendulum may have swung too far in our present attempts to track down possible errors and accident contributions that are widely separated in both time and place from the events themselves” (p. 234).11 Although he was the first to raise this concern, he was by no means the last.

Like Reason, others have voiced concerns about the over-application of this model. Some have worried that people are using it as a heuristic, a kind of rule of thumb that is used to explain any accident or failure.12 It is possible that rigid application of this model may lead organizations to search for the latent conditions that gave rise to the accident, when the main cause may in fact have been nothing more than human error.13

This model has also been criticized for being too generic. It has been suggested that it is not enough to simply say that different protective measures are connected; in order for this model to be useful in effectively minimizing risk, it would need to tell us how they are connected.14 

Much of this criticism comes from the model being applied to a much larger scope than originally intended. Those who defend the Swiss Cheese Model argue that, while it has its limitations, the model has been imperative in bringing systemic factors into models of accident prevention. Furthermore, it is a metaphor that can be understood by anyone, regardless of their level of expertise. While its ability to offer up guidance is hotly debated, this model is commended for its ability to convey the concept of organizational accidents in an accessible way.15

Case Study

The COVID-19 pandemic

The Swiss Cheese Model can be applied to the COVID-19 pandemic, such that each layer of cheese represents a different measure taken to slow the spread of the virus. For example, one layer may represent social distancing, the next may represent wearing masks, another may represent handwashing.16

No preventative measure alone is enough to completely significantly slow the spread. However, when taken together, they can limit the risk of contracting the virus. When applied to the context of the pandemic, this theory highlights the extent to which these lines of defense are connected. Every intervention has its shortcomings. When the different interventions are layered on top of each other, however, they are able to compensate for each other’s flaws, significantly reducing the risk of infection. As restrictions are repealed – for example, increasing the number of people allowed at indoor gatherings – the risk of contracting the virus increases. This can be thought of as a slice of cheese being removed from the stack, allowing more holes to become uncovered.

With something as serious as a pandemic, risk management is of the utmost importance. In order to save lives and ensure that hospitals do not become overwhelmed with patients, reducing the spread of the virus is key. The Swiss Cheese Model is a useful metaphor for understanding why it is so necessary for everyone to continue to practice the recommended preventative measures. It also illustrates how we cannot pick and choose which measures we take – they all work together to minimize the risk of infection.


  1. Aven, T. (2014). What is safety science? Safety Science67, 15–20.
  2. Bell, A. (2018). How to Use the Swiss Cheese Accident Causation Model. Enterprise Training Solutions.
  3. See 2
  4. See 2
  5. D’Amore, R. (2020). “What is the ‘Swiss cheese model’ and how can it apply to coronavirus?” GlobalNews.ca
  6. See 2
  7. Howell, E. (2019). Challenger: The Shuttle Disaster That Changed NASA. Space
  8. See 2
  9. Larouzee, J. and Le Coze, J.C. (2020). Good and bad reasons: The Swiss cheese model and its critics. Safety Science. 126
  10. See 9
  11. Reason, J. (1997). Managing Risks of Organizational Accidents. Ashgate Publishing Limited, Aldershot, UK.
  12. See 9
  13. See 9
  14. See 9
  15. See 9
  16. See 5

About the Authors

Dan Pilat's portrait

Dan Pilat

Dan is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. Dan has a background in organizational decision making, with a BComm in Decision & Information Systems from McGill University. He has worked on enterprise-level behavioral architecture at TD Securities and BMO Capital Markets, where he advised management on the implementation of systems processing billions of dollars per week. Driven by an appetite for the latest in technology, Dan created a course on business intelligence and lectured at McGill University, and has applied behavioral science to topics such as augmented and virtual reality.

Sekoul Krastev's portrait

Dr. Sekoul Krastev

Sekoul is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. A decision scientist with a PhD in Decision Neuroscience from McGill University, Sekoul's work has been featured in peer-reviewed journals and has been presented at conferences around the world. Sekoul previously advised management on innovation and engagement strategy at The Boston Consulting Group as well as on online media strategy at Google. He has a deep interest in the applications of behavioral science to new technology and has published on these topics in places such as the Huffington Post and Strategy & Business.

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