Testing Assumptions Can Result in Better Decisions

We all know what happens when we assume… And yet, how many of our decisions are based on untested information and assumptions? Have you ever been told to wait an hour after eating before swimming or you’ll drown? Where did this information come from and why do we accept it to be true?

Bubbe-meise is a Yiddish term used to describe old wives’ tales. Some examples include: It’s bad luck to open an umbrella in the house. Eat all your food—there are starving children in Europe! Chicken soup will cure anything!

In general, we tend to accept beliefs, data, news, teachers etc. as valid. Even putting aside lies, probabilities, bias, incompetence, etc., we accept a lot of bad information, assumptions, and suggestions. Why is this?

We need to question more, check resources, and test assumptions in order to make better decisions.

Frank and Ernest Comic

Perceptions and inherent patterns can also cause inadvertent actions. Recently, social scientists have focused on how we make seemingly obvious decisions. The results show most people tend to be risk adverse, avoid change, and accept the most comfortable alternatives. So, while we can work to change a bad decision at any time, we frequently avoid, delay, or defer change and, thus, draw out a negative situation. For example:

  • Denying the effectiveness of COVID vaccines is just unexplainable. For years, we have accepted seat belts, polio and various other vaccines, not driving while drunk, and many other safety measures. The vaccines are just a similar precaution to save lives.
  • Many economic proposals ignore that the k economy is getting even more evident. The k economy argues that economic recovery is experiencing different rates among the poor and the affluent. Specifically, the poor are experiencing even more problems while working class and the rich especially are experiencing exponential gains. Excluding this information is irresponsible and will only produce inaccurate conclusions.  
  • Discussions about returning to work and school are frequently based on personal opinions and biases. Why can’t we recognize we lack perfect information and rely on and test the knowledge we have?  

The solutions to these issues are not simple or obvious. However, we can pay more attention to alternatives, successful examples, and valid data while focusing less on personal opinions and bias. In particular, we need to include the parameters and process in our deliberations. Other helpful strategies include:

  • Get the politics of the issues out of the discussions. How many poor decisions are made because we think that’s what the boss wants? Or because “that’s the way it’s always done?” Or because we’re afraid to speak up? Or because we refuse to acknowledge that the situation has changed? Drop the ego and make fact-based decisions.
  • Utilize analytics. This is an incredible tool for improving success, developing alternatives, and measuring outcomes. However, analytics can be less reliable when the data is wrong, we assume invalid relationships, sampling is inappropriate, and risk is not considered.
  • Review and evaluate processes and decisions. It is unreal to me that objective testing mostly outperforms personal interviews in staffing decisions. But, the reason is mostly because of poor training and bias.

  • Stop using old or incorrect data. We need to check that our sources are correct and up-to-date. The pandemic has significantly affected data and trends using 2020 information. The census shows some dramatic changes in the population—in particular, we need to consider diversity. For example, different regions have significantly different ethnic characteristics.
  • Don’t ignore facts and tradeoffs. Going back to the office has many tradeoffs such as commuting time and communication among employees. We need to understand the issues, develop flexible solutions, and test various alternatives rather than relying on personal preferences of people.
  •  Consider the conditions of a situation. Facts are frequently more independent than 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.
  • Don’t assume cause and effect. We frequently jump to conclusions before doing a proper analysis. Differing and multiple goals (such as short-term and long-term) can impact the understanding of cause and effect. Medical symptoms are often incorrectly diagnosed because a correlation was detected, which could be mere coincidence. Too often, an assumption is made and a diagnosis is given before things like environment, heredity, or psychological factors are even taken into consideration.
  • Check your biases. 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. And yet, everyone seems to chime in with an unchecked, biased opinion.

Bias is one of the greatest complications when it comes to accuracy in the scientific analysis of decisions. This includes statistical problems like sampling, measurement, and development of information. I also believe that social bias can be more impactful than statistical bias—this includes our preconceived perceptions and assumptions about factors affecting decisions. Cultural and environmental factors also affect bias.

Analytics, tradition, and experience are all valuable tools that help improve decision-making. However, we need to ensure that the assumptions behind those tools are accurate and reliable. In particular, our rapidly changing environment (especially in regard to issues like COVID) requires regular testing and validation. Similarly, creativity and intuition that defy some analyses are becoming increasingly necessary. Search alternative causes and solutions, test your assumptions, and always ask yourself: Why do I believe what I believe? How do I know my information is correct?

Related: What’s More Important: Excellence or Luck?