33 Risk

What's the Risk?

Because the risk criterion is always present, it deserves its own chapter. Risk is reflected in pro-versus-con or upside-versus-downside conversations. As you likely know, a con or downside is the negative result of a decision—something that prompts us to ask, “What's something bad or unexpected that could occur?” Everyone views risk differently. The probabilities of certain outcomes are the same, but people interpret and apply them uniquely. As a result, a decision might be yea for some and nay for others.

Let's say your net worth was $100,000. You're in Las Vegas for a vacation, and you decide to play at the roulette table. Would you place a bet of $10,000, with the risk of losing it all at once? Probably not: that's 10 percent of your entire assets. If you lost it, you would negatively impact your livelihood in a significant way. Would you place a $1 bet? Sure, because it's only one-thousandth of 1 percent of your assets. If you lost $1, it wouldn't affect you at all. You're next to another player whose net worth is $1 billion. For the billionaire, that same $10,000 bet would be one-thousandth of 1 percent of his assets, as $1 is to your $100,000. Although most billionaires are smart enough not to waste $10,000, there would be virtually no impact on them if they did. Although the statistical probability of losing $10,000 is the same for you as it is for the billionaire, the total risk of losing the $10,000 is very different between the two of you. The downside for both is losing $10,000, but the effective downside for the billionaire is much, much less than it is for you.

Here is another example. Let's say you're in the auto business and have to conduct a product recall because of a possible manufacturing defect. Your engineers, attorneys, and statisticians tell you the probability of catastrophic failure is very low—less than 1 in 100,000—and of annoyance failure (that is, annoying issues that are fairly easy to solve) is less than 1 in 1,000. It is possible for someone to get seriously hurt in a catastrophic failure. Do you take the risk of not initiating a voluntary recall? The numbers by themselves won't give you a go or no-go—and there are clear risk factors inherent in this situation. Can you handle the bad press, lawsuits, and even personal remorse if something bad happens? If your values include doing the right thing, then is it necessary to have the recall? We look at a number of factors collectively when evaluating risk. Although the factors are common among all of us, we each weigh them differently. Depending on the weight we give each, some people might consider them too risky, whereas others deem them not that risky.

Have you ever said this to someone: “What's the worst thing that can happen if you ask for that?” When you're concerned about requesting something—a raise, a new job, directions, permission, even someone to marry you—you risk being turned down. That's disappointing and embarrassing. In the case of asking for a raise, you might worry you're jeopardizing future opportunities. These are all downsides, and although perhaps unlikely, they all are possible. You're not afraid to ask; you're afraid of the downside, and you haven't figured out how you would recover or if you could reverse the damage. On the other hand, the upside to these conclusions is very significant. Although the downside could occur, you decide to take the chance.

11 Risk Factors

Critical thinking requires that we analyze risk beyond upsides and downsides. We look at factors about which we're concerned, afraid, and reluctant. To that end, HeadScratchers created a model of 11 factors to consider when evaluating risk—shown in Figure 33.1.

Figure 33.1 Evaluating Risk

1. Downside: This is a bad outcome that is a possibility based on a given decision. It defines the potential negative impact if the risk occurs. A professional downside could be losing a customer, having an employee quit, being sued for $10 million, or having your competition take the lead. On a personal level, a downside might be appearing foolish, losing $10,000, breaking a leg or arm, or death (the most extreme, of course).
2. Probability of the downside: For example, what's the chance you might die in a car accident or get hit by lightning? These statistics exist. However, other downsides—such as the chance of someone saying no if you proposed marriage or your boss firing you because you asked for a raise—are not calculable. You assign your own probability, which is actually a conclusion derived. If you conclude the downside will probably not occur, you'll assign a low probability to the risk. But if you conclude that it's likely to happen, you'll assign a high probability—and possibly avoid taking the action.
3. Upside: This is the benefit to the decision, the reason you're taking action in the first place. For example, a decision to open a new store in another location would increase presence and sales. The benefits of introducing a new product are to stay competitive, expand your market, and increase your sales.
4. Probability of the upside: This is the likelihood of achieving the upside. In most cases this is high, because you would conclude a different solution if you didn't think you could achieve this one.

   A note about upsides and downsides: When you evaluate risk and downsides, you contemplate the upside, too. If the upside is a small benefit, and the downside is dreadful (although unlikely), you probably won't chance it. For instance, if the upside of waiting on a manufacturing maintenance cycle is small incremental inventory, yet the downslide is a breakage causing a week of downtime and a massive inventory shortage, then the upside really isn't worth it. You may have experienced a time you got food poisoning at a restaurant. The downside is so bad, compared with the upside of “It's just a meal,” that you never go back there again. On the other hand, if the upside is very significant, despite the downside being bad, you might take the chance. If the person of your dreams wanted to meet you at that very same restaurant that gave you food poisoning, you might consider the upside worth the potential downside. You agree to meet at the restaurant. The upside of buying a lottery ticket with a jackpot of $100 million is so great compared to the downside of losing $2 that you take the chance, however ill advised doing so is statistically.

5. Ignoring the statistical downside: Can you ignore the statistical downside emotionally? Take crossing the street; you might get hit by a car, but you still cross streets. If it's a four-lane highway, you might not be able to ignore the downside and won't cross. However, if it's a two-lane road with a stoplight, you wouldn't give it a second thought. In this case, you would ignore the statistical downside.
6. Absorption capability: How easy (or difficult) will it be to absorb (recover from) the downside if it were to occur? Let's say you have a customer who rarely purchases; when he does, it's a small amount. If you decide to stop selling an item, you might lose him as a customer (downside). He is one of 1,500 customers, and his revenue is so small it wouldn't make much of a difference; you absorb the loss. On the other hand, if your best customer—someone who accounts for 25 percent of your revenue—cancelled, it would be a severe problem you could not absorb. You might have to reduce your staff or even go out of business.
7. Controllability: Do you have—or think you have—control over the situation? For example, you don't have much control related to the risk of a crash when flying in an airplane. However, you may have great control of the risk associated with a bad pricing decision. Despite the number of car accidents, most people think they are in control when driving. As many parents tell their newly licensed children, “I know you are a good driver, but you are not in total control, because there are other drivers who are not as cautious. So be careful!”
8. Necessity of the upside: How crucial is the decision's upside? Driving your car has risks, but if you live in the suburbs, you may need to drive to get to work or to stores. It may be necessary. The greater the need, the easier it is to ignore the statistical downside, because you simply must do something. There's a chance—however remote—that you might trip and break a bone merely walking from one room to another. You usually ignore that possibility, because you can't live your life in one place; you must move around.
9. Reversibility: Can you reverse the decision if a downside occurs? If you are a parachutist, the decision to leap out of an airplane is irreversible; you can't change your mind. However, if you decide to buy a new coat, you can usually return it within a specific period of time. That decision is completely reversible.
10. Mitigation strategy: This is about minimizing the impact if the downside occurs. Your mitigation strategy is your plan to react to issues that arise from the occurrence of the downside. Let's say you planned to drive to an important meeting, but your car breaks down. You might be able to take a taxi, borrow a friend's car, or get a ride. If you're in the software business and you discover a problem in your product, a mitigation strategy would be providing a patch for your customers to download that fixes the problem.
11. Preeminent metrics: A preeminent metric is a measurement to predict a downside far enough in advance that you can avoid the prediction coming true. For example, let's say you're tracking project progress with a metric related to percentage completed over time. One of the milestone deliverables looks like it might be delayed. You're tracking the progress far enough in advance that you can reallocate resources, compensate, and make up the delay. If you had not measured the progress this way, you would not have been able to compensate. We call the measurement a preeminent metric if it allows you to predict a bad outcome far enough in advance that you can change things and prevent that bad outcome from occurring.

Using the 11-Factor Model

Instead of asking, “What is the risk?” or “What is the downside?” critical thinking requires us to say, “Let's take a look at the risk factors to get clear on the risk.” Here's an example of all the factors at work.

Let's say you're working on a new application suite to streamline communications between departments during a customer incident. This headscratcher's goal is to shorten response time while providing your customer with accurate information, as well as to increase the number of customers supported, because the current system is at maximum capacity. You've designed the process, tested it with the new applications, and concluded it's time to roll it out. You go to the steering committee, because it had asked to be notified when you were ready to go live and announce, “We are ready to implement the new process and systems.” The committee will need to decide to go or no-go, so it asks about the risk in moving forward. You detail the following:

• Downside: The process was tested and will reduce time, but the downside is that the learning curve may take longer than expected, resulting temporarily in a slower response time. Also, if there is a failure in either the process or the new applications, the customer might get the wrong information.
• Probability of the downside: We did loads of testing, so the probability of the downside is reasonably low. We found that 15 of 100 cases took longer than the old process, but 85 were shorter. When testing for accurate responses, the new process produced inaccurate responses 7 percent of the time, in contrast to 15 percent of the time with the old process. However, if the learning curve for all those involved is slower than we anticipate or the new applications fails, we will most likely see a significant increase in our response time to customers—perhaps as high as 50 percent. Accuracy would decrease by about that amount as well.
• Upside: We're doing this to accommodate more customers and improve our quality of responses. This will have a significant effect on the success of our business.
• Probability of the upside: Overall, the probability of success is upward of 95 percent, thanks to all of the testing we did.
• Ignoring the statistical downside: Although downsides could occur, we have an excellent reputation with these kinds of changes. We also have a detailed mitigation plan in the event things go wrong. We make these kinds of changes several times a year; although complicated, they're routine.
• Absorption capability: If the downside occurs—customer response time is slower, or the applications fail—we will implement our mitigation strategy. Although we'll be embarrassed, an apology letter to our customers would be sufficient, because we have a very loyal customer base and can afford the hit to our service quality.
• Controllability: Our rollout strategy is to implement the new process with different customer groups and not all at once. This will allow us to throttle the rollout and observe the results. We have the training programs in place and subject matter experts (SMEs) are ready to help.
• Necessity of the upside: The forecast is for a 20 percent customer increase over the next 12 months. We cannot accommodate that with our current system. We have no choice but to implement this new process and application suite if we continue to add customers.
• Reversibility: Although we could not reverse the minimal public relations damage, we have a plan to abort the rollout and revert to the old system temporarily.
• Mitigation strategy: If the downside occurs, we will first understand whether it's the result of a learning curve or the failure of the applications. In the event of an application failure, we'll implement our plan to revert to the old system until we fix the application. If it's a learning curve issue, we'll add resources to off set that and slow down the rollout to allow more time for people to master everything. We'll also have SMEs fully trained and experienced with the new system floating around to assist anyone who needs help.
• Preeminent metrics: We are monitoring the cues closely and running statistics to compare times and accuracy with the old system. If anything starts to move in the wrong direction, we will notice before it becomes an uncontrollable issue. We're very confident in this early warning system, because we've used it successfully before.

Given the preceding risk analysis, the steering committee says, “The benefit (upside) is significant. Although there is some risk in proceeding, we are confident your understanding of that risk, as well as the actions you'll take to both prevent it and mitigate it, is well thought out.” You have a go!

Now let's take something much more basic, something you probably don't even think about: the risk of breathing. After all, you can catch a cold, catch a disease, or have a bad allergic reaction.

• Downside: Have a severe allergic reaction, choke on something you breathe in, or catch a terminal disease.
• Probability of the downside: We catch colds and the flu often; sometimes something much more serious is also a possibility. You probably have a 1 in 3 chance of catching a cold or the flu during the year; serious diseases, much less so.
• Upside: Of course, the upside of breathing is that you get to live.
• Probability of the upside: Extremely high with every breath. However, you acknowledge that you will catch a cold or the flu by breathing. If you took 20 breaths per minute, then you would take about 10 million breaths in a year. If you catch two colds in a year, then the probability of that downside (a cold) would be two in 10 million—definitely worth the risk of each breath.
• Ignoring the statistical downside: We generally don't even think about what we are breathing in, until we go to our doctor for an annual checkup and everyone in the office is coughing and hacking—or if there is an H1N1 flu outbreak, and you're walking around an airport wondering where everyone has been.
• Absorption capability: You get well almost all the time after you get a cold or flu. You can absorb a few days out from work. It's not so easy if you're very elderly, weak from other ailments, or battling a serious disease. These factors could have a significant impact on your family and yourself.
• Controllability: You stay healthier, eat right, avoid people who are sick, change your seat on a bus if the person next to you is coughing, and keep your immune system in check. This helps minimize the chances of catching an illness.
• Need: You absolutely need to breathe and cannot exist without doing so. You can't consciously stop it for long, either! Although the risk factors exist, you will always decide breathing is a go. As a result, although the other factors might affect your behavior here and there, they won't stop you from breathing. The absolute necessity trumps all other factors.
• Reversibility: If you get sick, there is no redo. You can't get unsick; you can only heal (or not heal).
• Mitigation: As soon as you feel bad, you can take an antibiotic or antiviral.
• Preeminent metrics: You can take your temperature. This won't prevent you from getting sick but could be an early warning system to receive treatment quickly. You listen to the news to hear about flu outbreaks.

What Is Too Risky?

When a person claims that something is too risky, that person is labeling it as such based on their personal measure. He thinks the risk doesn't warrant the benefit of a yea decision, so he says nay. You need to understand how they evaluate the risk factors to gain insight into why it's too risky. One way to figure this out for yourself is to work through the factors on simple decisions, such as riding a bike, eating a huge piece of chocolate cake, quitting your job for another, or crossing a footbridge over a ravine. Understanding how you use these risk factors will provide you with baselines when you evaluate risk on real business problems. For example, the risk you evaluate for skydiving might be very high on some factors. If a business decision has comparable risk, then it's probably something to avoid. On the other hand, if skydiving ends up being low risk from your perspective, then something comparable will also have low risk for you in business.

Getting Started with Risk

Here are some ideas about using criteria and evaluating risk:

• When you list criteria, risk will always be on that list: The decision maker will evaluate risk for any significant decision, although he or she may not be able to articulate the reasons why he or she is uneasy about the risk. Go through the risk factors with the decision maker to discover where the uneasiness comes from so that you can address it.
• Risk should always be discussed. You should review risk even if you're working by yourself. Because it's more about substance than quantity, you need to address risk factors. Doing so allows you to understand where your emotional concerns are coming from.
• Look at risk early. Although the decision step may come after conclusions, don't wait until you detail every little thing after a conclusion before you at least glance at risk. You don't want to have your first risk discussion while in front of the decision maker for final approval.