This is a topic that I would like to explore over the course of several posts. This question is born out of a couple of developments. First, after leaving Academia and moving to Industry the types of questions and choices that I encounter on a day-to-day basis changed (somewhat). The second is that many scientists here in the U.S. are excited by the President-elect selecting several of our colleagues to important “decision-maker” positions within the government.

Now, what this discussion is not. This is not to determine if Scientists are more capable then others of making “good” decisions (another topic). This is not going to discuss the topic of elected official’s being educated in science. Nor is this going to be about whether Scientists are good “Decision-Makers” (that class of policy advisors and law makers that are most likely to implement a concept). Nor is this going to be about the science of decision making (a fascinating research topic). Nor is this going to be a discussion about Scientist Fashion /Style Choices or if deciding on 5-7 more years of schooling, in the face of diminishing job opportunities, is a good decision. I would like this to be a fairly serious and critical look at the process of decision making by Scientists and if there is anything of inherent value or is there anything lacking in how we train Scientists to make decisions.

To begin then….

The scientific process is nothing more than a glorified decision tree. We start with observations that surround a certain condition – whether we have made thorough observations or not. So, based on our observations, we form a hypothesis – a question we would like to test. Now usually this question is itself a choice/decision point. Do we choose to evaluate the observations under a broad context or a specific context? Is there only a portion of the observation we are interested in and, therefore, will “temporarily” ignore the surrounding information, etc.?

Once we have formulated a specific and testable question we have several decisions to make on how and what to use as a control and what will be modified and how we will measure the changes between the control and the modified? Once we have collected the data we now have to decide how we will evaluate the data and, furthermore, how we will interpret the data – what information that we have access too, and are familiar with, will we include, what do we leave out and why do we leave it out?

So we know that scientists – as a course of their career – are always making decisions. But are we good at making decisions. I shall now have to go out on a limb (a very thin one) and describe what I mean by good at making decisions.

Being good at making decisions involves recognizing that each choice has a risk-reward attached to it (no matter how slight the difference may be). Likewise, being good at making decisions relies on the person making the decision to be responsible for the choice that they are making (no overriding influences) and I believe it involves the ability to define the scope of influence that the decision impacts. Finally, the person making the decision will make the decision in a time-frame that does not exclude the decision or negatively impact future options.

I, therefore, decide to start the discussion here:

How would you characterize being “good” at making decisions?