The classic example of an accident that hasn't happened yet: the heating tiles of the space shuttle. The first 33 flights consisted of errors in maintenance. Dr. Elisabeth Paté-Cornell describes how she discovered that technicians were mixing water with the glue, so the heating would adhere faster to the surface; though, by diluting the contacting bond, it put the heating tiles more at risk during the space shuttle's reentry into Earth. Her team created a map of the space shuttle and the most crucial heating tiles. In the end, she made recommendations based upon the data and research.

Real risks of real life don't always involve airplanes and nuclear power plants. Dr. M. Elisabeth Paté-Cornell shares a personal example: She has a two-year-old little boy who likes to tumble down the stairs in her new home. If that doesn't sound dangerous enough, the landing also has a sharp post. Dr. Paté-Cornell uses risk analysis to calculate the number of times her son might tumble down the stairs, the accident rate and possible solutions. The result: She builds a bumper of three baskets that can absorb the force of a basketball without breaking.

The patient risk in anesthesia highlights the dynamics of accidents. The problem: How can the management of anesthesia systems be improved to decrease patient risks that could occur in the operating room environment? To compute the probability of an accident of all scenarios, a dynamic model helps to understand how fast things could go wrong once an accident first occurred and how fast someone must react to resolve the problem. Among the contributing factors causing an accident (work schedule, training, and experience), Dr. Elisabeth Paté-Cornell, department chair of Management Science and Engineering at Stanford University, says that simulated training helped decrease accidents by an optimistic 16 percent.

How does someone think about risk analysis? Management Science and Engineering department chair Dr. Elisabeth Paté-Cornell breaks down the process of assessing risk: She first speaks with experts to find out how a given system works and how it might fail; then she examines ways of reinforcing a system. A risk analyst can only provide options based on available resources; they cannot make decisions for someone.

In a world of uncertainties, you seldom have statistics, explains Dr. M. Elisabeth Paté-Cornell, department chair of Management Science and Engineering at Stanford University. Risk analysis examines a broad distribution of outcomes based on scenarios and their probable consequences. From these results, she says a people must decide if they can live with the hypothesized outcomes. If not, we must decide how to best allocate resources for reinforcement of the systems in place to avoid disaster.

Dr. Elisabeth Paté-Cornell, department chair of Management Science and Engineering at Stanford University, wonders aloud whether entrepreneurs actually take that much risk. She explains that in the United States, venture capitalists take a lot of calculated risk by backing budding start-ups, while in Europe, bankers, acting in the same role, are not. Entrepreneurs usually start with a technical idea for a company and surround themselves with a great team of managers and technicians. Indeed, the success of risk-taking boils down to a single factor: the ability to build teams and cultivate many skills.

System analysis stands in the center of most risk analysis. Deconstructing the system, one breaks it down into classes of scenarios that can allow an analyst to better understand how something can fail. The two biggest classes are dependencies on external factors and human error. Dr. Elisabeth Paté-Cornell, department chair of Management Science and Engineering at Stanford University, explains that you look at these types of scenarios because there are not enough reliable statistics.