Rules and Filters

RULES AND FILTERS

Rules are for the obedience of fools and the guidance of wise men.

• David Ogilvy (Advertising executive, 1911-1999)

What can help us avoid problems and act as guidelines when making decisions? Based on our knowledge of reality and our personal situation we should establish some "what to do" and "what to avoid" rules.

Charles Munger gives an example of a rule:

Any time anybody offers you anything with a big commission and a 200-page prospectus, don't buy it. Occasionally, you'll be wrong if you adopt "Munger's Rule". However, over a lifetime, you'll be a long way ahead - and you will miss a lot of unhappy experiences that might otherwise reduce your love for your fellow man.

Another rule comes from Benjamin Franklin: "To apply myself industriously to whatever business I take at hand, and not divert my mind from my business by any foolish project of growing suddenly rich; for industry and patience are the surest means of plenty."

Other rules could be, "Walk away from anything I don't understand or can't quantify or doesn't work. Only deal with people I trust."

Warren Buffett provides us with guidelines on how to win in insurance, which applies to other areas as well:

What counts in this business is underwriting discipline. The winners are those that unfailingly stick to three key principles:

1. They accept only those risks that they are able to properly evaluate (staying within their circle of competence) and that, after they have evaluated all relevant factors including remote loss scenarios, carry the expectancy of profit. These insurers ignore market-share considerations and are sanguine about losing business to competitors that are offering foolish prices or policy conditions.
2. They limit the business they accept in a manner that guarantees they will suffer no aggregation of losses from a single event or from related events that will threaten their solvency. They ceaselessly search for possible correlation among seemingly-unrelated risks.
3. They avoid business involving moral risk: No matter what the rate, trying to write good contracts with bad people doesn't work. While most policyholders and clients are honorable and ethical, doing business with the few exceptions is usually expensive, sometimes extraordinarily so.

Filters

We really can say no in 10 seconds or so to 90% + of all the things that come along simply because we have these filters.

• Warren Buffett

Filters help us prioritize and figure out what makes sense.

When we know what we want, we need criteria to evaluate alternatives. Ask: What are the most critical (and knowable) factors that will cause what I want to achieve or avoid? Criteria must be based on evidence and be reasonably predictive, i.e., we must do better than chance by relying on them. Try to use as few criteria as necessary to make your judgment. Then rank them in order of their importance and use them as filters. Set decision thresholds with the consequences of false alarms and misses in mind (in investing, choosing a bad investment or missing a good investment). Reducing one kind of error can increase the other, so the costs of each matter. For example, in medicine, a threshold depends on factors such as the prevalence of a condition, its seriousness, the availability of corrective measures, and the emotional and financial costs of false alarms.

Past criminal and prison records are more reliable than expert criminologists in predicting success on parole.

Studies show that in some fields, when based on the same evidence, a more mechanical prediction process involving a small number of relevant variables is more reliable than the predictions of trained and experienced experts. This has been shown in diagnoses of medical conditions, predictions of academic performance, in determining gambling odds, and loan and credit risk. Why does it work better? Because we humans are not always consistent. Recent experiences, suggestions, or how information is presented may influence us. Add to this our natural limitations in memory, attention, and processing.

More information doesn't mean we are better off. Sometimes extra information is useless and confusing.

A man is rushed to a hospital in the throes of a heart attack. The doctor needs to decide whether the victim should be treated as a low risk or high-risk patient.

Criteria do not have to be numerous or complicated. In the historical research example described here, statistics professor Leo Breiman and colleagues at the University of California, Berkeley, developed a method to classify high-risk heart attack patients using only a maximum of 3 variables. Blood pressure, age and sinus tachycardia (rapid heartbeat).

If a patient's minimum systolic blood pressure over the initial 24-hour period is less than 91, he is immediately classified as high risk. If not, the second variable is age. If the patient is over 62.5 years old, then one more variable - sinus tachycardia is needed to classify him as high or low risk. If the patient displays sinus tachycardia he is classified as high risk. Thus, the doctor needs to answer three yes/no questions to reach a decision. The account reports better classification performance than more complex statistical methods in that study. Its thresholds illustrate the model; they do not establish a rule for clinical practice.

At a press conference in 2001, when Warren Buffett was asked how he evaluated new business ideas, he said he used 4 criteria as filters:

1. Can I understand it? If it passes this filter,
2. Does it look like it has some kind of sustainable competitive advantage? If it passes this filter,
3. Is the management composed of able and honest people? If it passes this filter,
4. Is the price right? If it passes this filter, then we write a check.

What does Warren Buffett mean by "understanding?" Predictability: "Our definition of understanding is thinking that we have a reasonable probability of being able to assess where the business will be in 10 years." He continues:

The only way we know how to make money is to try and evaluate businesses. And if we can't evaluate a carbon steel company, we don't buy it. It doesn't mean it isn't a good buy. It doesn't mean it isn't selling for a fraction of what its worth. It just means that we don't know how to evaluate it. If we can't evaluate the sense of putting in a chemical plant or something in Brazil, we don't do it... We understand the product. We understand what it does for people. We just don't know [what its economics will be] 10 years from now... You can understand steel. You can understand homebuilding. But if you look at a homebuilder and try to think where the economics of it is going to be in five or 10 years, that's another question. It's not a question of understanding the product they turn out, the means they use to distribute it - all of that sort of thing - it's the predictability of the economics of the situation 10 years out.

Let's take an example where we combine rules and filters. Reality often shows that one cause of problems is getting involved with wrong people. A rule could therefore be: "Avoid low quality people." As a consequence a filter may be: "Good track record and character traits." Then we look for clues and ask questions designed to answer the question: "High or low grade individual?"

Elimination

Elimination is a great conservator of effort. For example, place the burden of proof on statements that contradict basic scientific ideas. Eliminate situations that may cause great sorrow, what is not important or knowable, what can't happen or be achieved, what can't usefully be predicted or explained, what can't be tested, what is already disproved, the easy decisions, the wrong assumptions, what we can't do something about or problems where we don't have any competence.

Science works by elimination. To avoid drowning in low-information observations or experiments, scientists think in advance about what the most important and conclusive experiments would be: What are we trying to achieve or prove, and how can we reach these ends? What can't happen? This way, they narrow down the possibilities. The same principle applies to Buffett’s approach: eliminate possibilities and concentrate on the few that have a chance of success. Look for certain things that narrow down the possibilities.

Checklist procedures

Air carrier cockpit checklists to be reviewed in an effort to ensure that each list provides a means of reminding the crew, immediately prior to takeoff, that all items critical for safe flight have been accomplished.

• National Transportation Safety Board, 1969

In 1987, Northwest Airlines flight 255 crashed shortly after take-off. All 155 persons aboard except one were killed. A federal report concluded that the probable cause of the accident was the flight crew's failure to use the taxi checklist to ensure that the flaps and slats were extended for takeoff. Contributing to the accident was the absence of electrical power to the airplane's takeoff warning system, which consequently could not warn the flight crew that the airplane was not configured properly for takeoff. Use checklist procedures. Together with other tools they help us reduce the chance of harm. Concentrate on the critical items. If we don't check for them we may get harmed. Pilots call these the "killer items."

Charles Munger suggests using models in a checklist fashion:

Generally speaking, I think you need mental models - and what I call checklist procedures where you take a worthwhile list of models and run right down them: "Is this here? Is that here?" and so on and so on ... Now if there are two or three items that are very important that aren't on your checklist - well, if you're an airplane pilot, you can crash. Likewise, if you're trying to analyze a company without using an adequate checklist, you may make a very bad investment.

Some issues to think about when designing checklists are:

• Different issues need different checklists.
• A checklist must include each critical item necessary for "safety" and avoiding "accidents" so we don't need to rely on memory for items to be checked.
• Readily usable and easy to use.
• Agree with reality.

Contributing to the accident was the captain's over-reliance on automated flight systems.

Avoid excessive reliance on checklists. They may sometimes give us a false sense of security. Checklists work well as long as what may happen can be foreseen. But the unexpected sometimes happens. An unmentioned item may be the core cause of a problem.

Doing something according to pre-established rules, filters and checklists often makes more sense than doing something out of pure emotion. But we can't have too many rules, filters or items without thinking. We must always understand what we're trying to accomplish.

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GOALS

Rules and filters need a purpose. The following section considers how to define the result they are meant to help achieve.

Our plans miscarry because they have no aim. When a man does not know what harbor he is heading for, no wind is the right wind.

• Lucius Annaeus Seneca

"Why doesn't our employee, Tom, perform well?"

Often we are surprised when people don't perform as we expect.

How does Tom perceive he is being measured and rewarded? What does he perceive is expected of him? Do we give him mixed messages? What skills, knowledge and information does he need? Does he have those? What response do we give him about his performance?

Tom: "I have the right knowledge and understand the goal. I also know how to achieve the goal and why my way makes the most sense. I have the authority to make the relevant decisions and can measure the outcome continuously. If I achieve the goal, I will be rewarded. I decide the amount of reward I will get. If I don't accomplish the goal, I lose my job. Since I have the responsibility, it is only right that I face the consequences."

Have goals that cause what we want to accomplish. Do we know what we want to achieve and why? As Aristotle said: ''Are we not more likely to hit the mark if we have a target?" How can we make the right decision if we don't know what we want to achieve? Even if we don't know what we want, we often know what we don't want, meaning that our goal can be to avoid certain things.

Meaningful goals need to be backed by reasons as a way of testing that we set the right goal. Goals should be:

• Clearly defined. Don't say: "I want to have a better life." Be concrete. For example: "I want a new Volvo."
• Focused on results.
• Realistic and logical - what can and can't be achieved? Low goals may produce low performance and unrealistic goals may cause people to cheat. Lucius Annaeus Seneca said we should: "Never work either for useless goals, or impossible ones."
• Measurable.
• Tailored to our individual needs.
• Subject to change. Ask: Given our current objective, what is the best course of action to take?

Goals also need target dates and control stations measuring the degree to which the goal is being achieved.

Do we know what causes our goal to be achieved? We can't achieve what we want if we don't understand what makes it happen. And are we sure our goal is the right one for what we finally want to achieve?

Warren Buffett and Charles Munger elaborated on the issue of the energy crisis at the 2001 Berkshire Hathaway Annual Meeting:

In power systems we need surplus of capacity. And how do we get that? By giving people an incentive for having extra capacity. A power business can't be punished for not having excess capacity and can't be rewarded for having less than what is needed.

We need three things for this not to happen again. One is that we need reasonable efficiency in operations. Secondly, since it does tend to have in many situations monopoly characteristics, we want something that produced a fair return, but not a great return, on capital - enough to attract new capital. And third, we need a margin of safety or a little more capacity than needed. And we need the whole equation.

Always ask: What end result do I want? What causes that? What factors have a major impact on the outcome? What single factor has the most impact? Do I have the variable(s) needed for the goal to be achieved? What is the best way to achieve my goal? Have I considered what other effects my actions will have that will influence the final outcome?

When we solve problems and know what we want to achieve, we need to prioritize or focus on the right problems. What should we do first? Ask: How serious are the problems? Are they fixable? What is the most important problem? Are the assumptions behind them correct? Did we consider the interconnectedness of the problems? The long-term consequences?

Since big effects - bad or good - happen when we optimize some factors or combine many factors, we should use whatever factors necessary to achieve our goal.