Intuitively, the value of decision-making in a team setting is that each team member will bring differing perspectives and facts to the table. In an ideal world, we would be able to perfectly map out the knowledge and perspectives of each team member and see where those maps overlap and where they diverge. Uncovering the dispersion of opinion is where bringing a great team together adds value. Finding out you agree has value.
But the real heavy lifting of a great decision process is done by exploring areas of disagreement.
For a variety of reasons, research has shown that group decision making generally lowlights dispersion of opinion. Groups linger on agreement. Velocity builds behind consensus. Decision processes shut down too quickly.
One non-obvious way that disagreement ends up hiding in the shadows is that we fail to be specific about what we mean or to properly define the terms we are using. We often use words whose meanings have very broad target areas, words that can mean very different things to different people. When we use imprecise language, we can create the illusion of agreement when there is actually quite a bit of disagreement, disagreement that we have failed to uncover because we have used words that have a lot of wiggle room.
A category that is one of the biggest offenders in creating the illusion of consensus is
words that describe probabilities
, terms like
sometimes, always, real possibility, etc.
These terms all describe the chances that a future event will occur. Because they feel mathematical, they also can fool us into thinking these terms have a precise and agreed-upon meaning.
This exercise is meant to demonstrate to your team that it is often the case that the meaning we intend is not the meaning that others hear.
Before sharing this doc, preview the final result, and clear the dummy data in
Share this doc with your team members and add each person to the
Have each team member go to the
page and fill out what probability they intend (expressed as a percentage) when they use each of the terms listed below. One way to think about this is to answer the question, “If I were to use this term to describe the chances of an event occurring, how many times out of 100 do I think the event will happen?” For example, If I were to say, “There is a real possibility it will rain tomorrow,” how many times out of 100 do I think we will see rain the next day?
After everyone has filled out the percentages individually, reviews results in
List of words to evaluate