We frequently assume relationships that imply cause and effect. This can be true for some issues, like overeating produces weight gain or exercise leads to better health. However, we frequently ignore that cause and effect need to be dissected in order to determine whether the relationship is random, or is actually cause and effect.We frequently underestimate the importance of understanding of cause and effect in a relationship. We know that positive feedback, and even a simple thank you, will generally produce positive results . The cause and effect argument can be exemplified by the universal argument: which came first, the chicken or the egg?
Some key realities to remember about cause and effect: Facts are frequently more independent that we think. If you flip a fair coin, the odds are still 50-50 (regardless of the last few flips, because the flips are independent). However, sports analysts have proven that certain conditions, like left handed batters hitting to right field, are more probable. The biggest issue is probably bias, which is most evident in political and economic arguments. Questions like: Why are the poor are poor? What is the impact of IQ? How will the stock market perform? What are the causes of crime? These types of questions all involve a complex analysis of a variety of factors. We sometimes assume that the relationship among factors is a straight line. However, most relationships involve a variety of factors, as shown in the chart below: Differing and multiple goals (such as short-term and long-term goals) can impact the understanding of cause and effect. For example, how do innovation, execution, and expertise impact the success of a project? This is a question that I frequently ask when working with my clients. In scientific work, it is much easier to identify cause and effect (because you can isolate variables much easier). However, social issues frequently involve more variables. Medical symptoms are frequently attributed to certain issues, while other factors may be the real cause. In particular, the roles of the environment, heredity, and psychological factors are frequently not considered enough in many medical diagnoses.
Related: Risk and Failure Can Be Keys to Success
There are many simple ways to get a better understanding of cause and effect: Analyze the nature of the relationship and direction of causality. Testing with and without the presumed cause is a common way to measure new procedures. Medical research, athletic results, and education experiments are commonly analyzed with this tool. Long term (or large samples) can also help verify causes and explain some variations. For example, the height and weight of athletes can be shown to have a significant impact on success. You also need to consider the impact of randomness (versus actual cause and effect). Many argue that planning exercises are so burdened by uncertainty that you shouldn’t plan and just develop, test, measure, and adapt. Similarly, there are numerous tips on how to be innovative or create an innovative environment. However, there are so many variations of innovations that one must question the universal rules. You should also verify your results by regularly stepping back and reviewing your assumptions and conclusions. Are your parameters of cause and effects really correct and important? Have you considered all the alternatives or are there others? Will a different perspective yield different results? Is your information correct and up to date?
In summary, be aware of developing solutions
based on faulty cause and effect reasoning. In most cases, the logic and assumptions can be reasonably tested. In particular, examining multiple cases can add significant credibility to your assessment.