Belief, Truth, and the Power of Observation

Observation is what separates belief from truth.

It is unclear who invented the Scientific Method, although much of the credit is given to John Stuart Mill, a social, political, and scientific pioneer of the 1800’s. It is likely that the method had roots as far back as the year 1,000, but Mill is credited with formalizing the structure. Regardless of its origin, the Scientific Method has withstood the test of time, because its premise is based on the power of observation.

I am fortunate to have a seventh grader that has reintroduced me to the Scientific Method, but for those less fortunate to share in the joys of middle school homework, here is a brief re-introduction:

There are basically six steps to the method:

1. Ask a question about a phenomenon
2. Make observations about the phenomenon
3. Hypothesize an explanation
4. Predict a consequence of the phenomenon
5. Test the prediction (usually in some controlled environment)
6. Make a conclusion using data acquired

The beauty of the Scientific Method is that, if done properly, biases can removed from the process. Too often in the workplace, many of our actions are based on biases that could alter our decisions. If committed to the Scientific Method, we are able to base our actions on “truths” instead of “beliefs”. This can be extremely difficult to do, especially when our belief systems can be so profound. Have you ever had a “discussion” with someone whose political beliefs are different than your own? These are usually debates where the Scientific Method is missing. The result is typically an “agreement to disagree”…not the result you want when a business decision is on the line.

The relationships we have with our channel partners are often based on beliefs. Sometimes the relationships change and our judgment can be clouded because of an historical bias. This is often the case when a good relationship turns sour, or when a poor relationship becomes solid. We need some methodology to see through the bias so that we can we can make decisions based on current observations and data.

Channel management requires the investment of resources to build a more effective and profitable channel ecosystem. Every investment is critical, especially in today’s economic environment. Using analytics to measure relationship trends will provide data (observations) that will help guide those investment decisions. Do you have a method to identify and observe a phenomenon, question it, hypothesize an explanation, and test the theory? If not, then are you making biased channel investment decisions?