“A Decision Today, Another Tomorrow” — Flexibility or Inconsistency?

Project room. After a short discussion, Zofia closes the topic and chooses option A. Amira starts the detailed implementation work.

— We’re going with A. Let’s start today.

Three days later, Zofia returns with new data.

— We’re switching to B.
— But A was the decision.

To Zofia, changing course proves flexibility. To Amira, it means something was called a decision too early.

What really happened

Zofia believes a good decision should change when the data changes. Amira believes that once a decision has been made, the team needs to be able to build on it; reopening it too often destroys work already invested. They see different costs. Zofia fears staying with a bad choice just because it has already been made. Amira fears putting time into something that may stop being valid again tomorrow. The conflict is therefore not about changing one’s mind in itself, but about the cost of reversibility and the point at which a decision becomes a commitment.

What the research says

Decision research shows that people often like retaining the option to change a choice, although reversibility can carry psychological costs such as more comparison and lower satisfaction after choosing (decision reversibility; Gilbert & Ebert, 2002; Bullens et al., 2013). Organizations face the opposite risk as well: continuing down a path simply because significant resources have already been invested — escalation of commitment (Staw, 1981; Sleesman et al., 2012). Together, these streams of research show why neither “never change” nor “always stay flexible” is a sound rule.

How to handle it

When making the decision, say how reversible it is and what would reopen it. Simple labels can help: “one-week test,” “reversible decision,” or “stable through the end of the quarter.” It is also useful to define the threshold of new evidence that would trigger reconsideration. The general rule is: people can safely invest in execution when they know whether a decision is an experiment or a commitment, and what information could change it.

How Empatyzer and Em can help

Empatyzer can show Zofia and Amira that both are acting responsibly while placing the cost of uncertainty in different places. Zofia prefers to decide faster and correct course later; Amira invests more heavily in the stability of a decision once execution begins. The assessment and profile comparison allow Em to anticipate the friction and suggest language that changes its meaning: “We’re choosing A as a test until Thursday; these three data points could still reverse the choice.” Amira then knows how much to invest in execution, while Zofia keeps the flexibility she values. At team level, Empatyzer can help create shared meanings for “decision,” “test,” and “working option.” Micro-lessons reinforce that precision, so changing direction does not look like chaos and stability does not turn into rigidity.