Whether implementing a new technology or attempting to solve a problem we currently face in the world or even just making mundate decisions about our daily activities, we continually make judgements about the risks we face. With our liminted resources, time, and skill we choose to limit some of our exposure to risk and accept others. But, when making those decisions, we open ourselves to psychological biases about risk and often make a decision that puts us in a poorer position than we otherwise would have been.

Many researchers in the field of psychology and economics have found certain inherent biases that most people share in evaluating risk or the probabilities of benefits (gambling). For example, given a choice between two equal mitigation options (both reduce risk 10%) of equal cost for two different equally deadly diseases, individuals will nearly always choose the option that brings one’s risk closest to zero (from 10% risk to 0% risk for disease A, rather than from 30% risk to 20% risk for disease B) even though the benefits are equal.

At first glance, that may seem unremarkable itself. But what it means is there exists a threshold of unequal risks where individuals will consistently choose a mitigation of the less beneficial option: a vaccine reducing their risk from 7% to 0% for disease C rather than from 30% to 15% for disease D, for example. So, in this case our generally perceived benefit of reducing one risk to zero may not be in proper relation to the actual benefit. Our perceived risk after making our choice is lower than our real risk.

So, risk perception is important to understand as a population of individuals may not make the best choice overall (reference the options between diseases C and D above) if each person is free to make his or her own choice. Or, said another way, the cost of a population’s freedom of choice in this example can be measured in the total numbers of people dying from those diseases, who would not have died had the choice of prevention been different.

But, just knowing that people hold these biases (even if we can quantify them) does not allow policy makers to easily solve the problem. Some officials when faced with this obstacle make the dubiously ethical choice to exaggerate the severity of a risk so that an adequate number of people will respond in the preferred manner.

That tactic, of course, holds the potential to cause a loss of credibility. And, if credibility is lost, all ability to give people the correct information on risks they face would be compromised. Unfortunately, this does not always seem to result in restraint in the for-profit news media.

But, there is a potential solution. From the same research that identified these general perception biases, trained experts proved they could make the mathematically correct choice given the same set of data. That’s to say, in the example above, an expert would properly choose a vaccine against disease D to protect his or her family. So, let us make everyone an expert on risk. While creating an “expert” might sound daunting, it is only a matter of education, which policy makers already effectively force on nearly everyone. A better training on probability and risk, perhaps through the use of mathematical game theory would better prepare all of us to make the best choice for ourselves and our families.

Typically, the first time we consider someone placing a monetary value on protecting a life, the risk of death, or other similar circumstances, we cringe. The mere mention of life in the context of money seems cruel and far too calculating. Rightly, we have learned that an absolute monetary value cannot be placed on the worth of a person whether young or old, experienced or inexperienced, whatever race they are or religion they hold. This article is not going to challenge any of those ethics. Life is a priceless phenomenon and every person’s experience is something to be held at the pinnacle of our value system.

But, now let’s consider how we evaluate risk in our lives. We all understand that living entails a risk of dying. Whether from disease or injuries, people die everyday in the areas where we live. We deem it an acceptable risk to commute to our jobs, whether by walking, or cycling, or taking public transportation, or driving, even though every time there is a chance that we might suffer serious injuries or death. We deem it an acceptable risk to socialize even though it carries the risk of disease. We deem it an acceptable risk to live in geographical areas and homes that may survive most but not all natural disasters that are possible.

And, we do not perpetually worry (well, some do) about all of these risks. We spend our resources to improve our health and safety and reduce our risk, but only to a point. Eventually, we decide that some nice meal, or household item, or luxury is more valuable to us than the marginal decrease in our risk of death, injury, or disease. When we make that decision, we have, inadvertently or not, placed a monetary value on our own lives.

As an example, let’s consider that I have the option of two modes of transportation. Option one costs me $1,000 per year. Option two costs me $1,200 per year. My risk of serious injury of death in the course of one year from option one is 1 in 800,000, while my risk from option two is 1 in 1,000,000. If I select option one, I have decided that the value of my life in terms of this particular risk is not more than $800,000,000.

The resultant value comes from determining the marginal societal cost of preventing one additional death in that situation. That does not mean we consider that we or anyone else can be bought for that price. It is only a statistical quantity that provides us with the means to evaluate different risk reduction or life saving alternatives. And, in fact, it applies not to ourselves or one particular group of people. The calculated value of life applies to the risk in question and the available options considered to mitigate it.

Opportunity Cost

Anytime we make a decision whether for ourselves or in a position of responsibility over others to mitigate a particular risk with a specific strategy (or we decide that none is required), we have placed a value on life. Of course, the economic principle of opportunity cost indicates that anytime we devote resources to a particular purpose we have incurred a cost of opportunity regarding other options we might have chosen. In risk mitigation, there are always several options including doing something versus doing nothing. And more broadly, depending on our responsibility, we may also be deciding between options for mitigating entirely different types of risks with the same resource budget. In this situation, whether we wrestled with the ethical dilemma or not, we may have chosen to value one life over another or one group of lives over another group.

Values and Ethics

Calculating the value of life for each of our options in monetary terms can give us a valuable piece of information that may permit us to make the most ethical decision. In deciding between one option with a value of life of $100,000 and another with a value of life of $1,000,000, we would most likely decide to select the first option, which would allow us to protect 10 times as many lives with our limited resources. Considering options equal in value of life would be more difficult ethically if different groups of people were involved. And, even then, we may justly decide at times that some lives are rightly valued higher such as considering the risk of death to young children versus the risk of death from a disease related to old age.

The value of life is only a tool to be wielded how we desire. Only, we should use it, be informed, and not avoid acknowledging the choice we are making. To ignore it may mean that we inadvertently make decisions inconsistent with our values. To employ it means that we can make proactive, ethical choices without succumbing to the fads or fears of the day. And, as we improve the heath and safety of everyone through our choices the value of life increases, which is surely a sign of progress.

In my earlier article on root cause analysis, I mentioned that every cause present in a given situation can be considered equally responsible for the occurrence of the failure in question. Many times, however, investigations end up ascribing the fault of the entire situation to a particular “root cause” that may or may not have happened without the presence of other contributing causes. When we identify the “root cause” as human error and fail to take actions against the system that set up that error, we are perpetuating the problem.

First, let’s consider what we know about humans. We are generally intelligent, make rational choices, communicate well through language, sneeze sometimes, learn quickly, get sleepy, are omnivorous, need food several times per day, have excellent hand/eye coordination, don’t have perfect aim, make mistakes in high stress situations, need several liters of water per day, become preoccupied with social concerns, etc., etc. While that list suggests that we as a species are highly capable, it also suggests that we are not machines that can perform a given action millions of times in a row without error.

So, we know for certain that humans will commit errors, it is only unknown at what time they will occur, and what form they will take.

Next, during accident investigations or other root cause investigations, the investigators are under tremendous pressure to explain why things happened the way the did. That is especially true if deaths were involved. The investigators are also under pressure to name a specific root cause and make suggestions to reduce the likelihood of that cause. Human error is nearly always present in every situation and so it is a likely target. Human will is also often the last line of defense against something bad happening, so it is the last point at which a different choice could have been made in any accident; the rest of the situation having been determined by physics.

However, given that we know today that humans will always commit errors, and that some situations put humans in a position where mistakes can be deadly (piloting an airplane, driving an automobile), it is a choice of system design that is the real cause of those accidents. We could trade an American-style automobile traffic pattern to one based on passenger trains on dedicated tracks and trade many small deadly errors for much smaller numbers of more deadly incidents. We could put computers in control of the trains with redundancy so that they always follow certain protocols that have been found to be safest. In any case, it is the choice of system design attributes that is the cause of the error and the cause of the failure or accident. The person is at fault only in cases of negligence, otherwise, the system is designed either to either control or allow a human’s natural errors. Changes to the system design are the only solutions available, as we can’t create a more reliable person (even excepting training, which has a limited and temporary effect).

So, let’s remember that when (not if) a pilot or capitan or driver is found to be the cause of a deadly accident, the design of the system they were operating in is the real cause, as some time ago we as a society, or group of engineers thought it was an acceptable level of risk to have a person making that decision even though it was a given fact that errors were bound to occur.

If our goal is to achieve progress, one of the ways we can determine that progress has been made is by a reduction in the quantity and severity of problems we face. Another way, would be to determine the quantity and magnitude of new capabilities we gain. However, new capabilities often bring new problems of their own, if we are not careful. The discipline of risk assessment and mitigation or control, if we take the time to apply it properly, can address the reduction of our current problems and the mitigation of potential future problems caused by our new capabilities.

That is all well and good. If we are facing the problem of getting punched in the face, it is easy enough to determine that getting punched in the face once or not at all is preferable than getting punched in the face three times. But, what if we are judging the difference in risk between a chemical additive to our water that would prevent a certain type of potentially fatal disease, but also carries a small risk of cancer after long term exposure? Juggling the probabilities and the severities of these problems is what risk assessment is all about. It helps people or organizations address a variety problems with various magnitudes and likelihoods, when they only have a limited amount of resources available to try to control those risks.

We can plot the risks we face in a risk matrix like the one shown here. This type of chart allows us to visualize our risks and the relation between severity and likelihood. The worse the event (injury in a vehicle accident), the less tolerant of occurences we are, while we can be more tolerant of events that are much less severe (vehicle breakdown). But, we cannot afford to address only likelihood or severity disregarding the other.

So, what do we do when faced with the potential of disastrous consequences? Do we ignore them, due to the small probability of them actually happening? Or, do we throw all of our time, effort, and money at them to make the risk as small as possible?

Just considering the example of car insurance, an individual will pay several hundred dollars per year (let’s say $1000) to avoid having to suffer monetary damages of around $25,000. If she survives 25 years without encountering that bad event, she has lost the same amount of money as if she had suffered the event. Yet, the entire time, there was the potential, especially at the beginning, for the financial costs of the event to be much higher relative to the insurance costs, and that made the decision a good one then.

There are many public policy implications of this kind of data. How do we decide how high to build the levees, or how strong to build the building on the fault line? How do we evaluate pollutants in our environment, or the size and capabilities of our military? The use of objective data-centered methods in many of these areas is unfortunately not always evident or fully realized.

People, in general, can be notoriously bad at statistics, especially when there is the prospect of pain involved. Yet, when thinking about it, we know that we choose to face some risks: injuries during exercise or work, death during travel, illnesses from our food, and so on. We do not pour all of our available money into renting or buying the safest vehicle we can, or guarding every sharp corner in our homes. While some are not, many of the choices we make are not bad ones. Risk is a part of our lives, yet something we must address to truly advance.

Risk assessment is something that will factor into many of the articles on true-progress.com. As it can be used for such a wide variety of problems, the benefits of the ensights of this kind of analysis are far reaching.

Whenever there is a major man-made disaster or some kind of accident, responsible officials usually convene a team that conducts an investigation. The results of that investigation will usually identify a “root cause” and several “contributing causes”. If it was a plane crash, the team will probably present the root cause as either pilot error or some kind of maintenance error. But, if you really want to find out what caused the problem and how to fix it, look at the “contributing causes”. Those are the keys to not experiencing that event in the future.

Although, often practiced in a jargon-filled method that does not communicate well to the general public, root cause analysis, provides a tool for us to develop robust, enduring solutions to problems we face, whether they are in safety or in any area we find we cannot accept repeat occurences of that problem. This article will outline what I believe is a better root cause analysis method and how it can be used to develop robust solutions.

“The root cause of the problem in the one you choose to fix… (or blame…)”

The quote above is from a consultant who had participated in several failure investigations, and found that some organizations would argue such that the root cause identified in the final report would either be something they already had a solution for, or could be considered something out of their control. In either case, we can do better.

As an example, let’s consider the problem of a fire that starts in an office building storeroom. We have to identify all possible causes, no matter how remote or whether or not they were involved with the event in question or not, to that fire. In the case of fire, there are always three: fuel, oxidizer, and an ignition source. Next, we identify evidence that those causes existed or not during our event. Those are shown in the next figure.

Now, we could continue and determine causes for our first line of causes. That would be absolutely necessary for several more levels, if we were dealing with a complex problem. However, in this case, my control over the causes can be determined with the information already outlined.

So, what is the root cause of my office fire? The short answer is: That’s the wrong question. All of my causes to the office fire are necessary for that event to occur, so they are all “root causes”. If I eliminate any one of them, it is impossible. And the best part is, if I can eliminate or control more than one, I have a robust solution. A solution that will make the event extremely unlikely in the future. That is our goal.

What remains is the identification of solutions, and then prioritizing based on impact and our ability to implement them. This figure displays some of our possible solutions, with only one eliminated as not being feasible. The greater the number of causes we can eliminate, the more robust is our solution to the problem. If I only choose to remove most of the paper from the storeroom, and one day someone reverses that decision without knowing the reasons behind it, we will again be at risk of the same problem. To create a lasting, successful solution, we must act on preventing as many causes as possible, not just a particular “root cause”.

So, root cause analysis, if practiced correctly, isn’t about assigning blame for a particular event; instead it is about finding true solutions that endure. And, preventing our problems from recurring and history from repeating itself can surely be counted as progress.

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