“It’s hard to recommend between A and B without sounding biased. They can both be great options; the devil’s in the details. I will not recommend C, however”.
This was an actual conclusion I shared in a recent scenario planning exercise as part of my job. This happens more often than not when we’re trying to make tough business decisions. The answer is often unclear, and it’s not an easy “black-or-white” choice. Instead, you’re left with two seemingly acceptable options. Neither is perfect, so it’s unclear which is definitively better. You do know what not to do; that part is often straightforward. The struggle is in what to do.
In business, we often crave certainty, but more often than not, decisions come down to trade-offs. A will offer certain benefits, but B might mitigate risks that A doesn’t. Each path has its own sets of variables that impact outcomes in unpredictable ways. That’s where the difficulty lies—not in seeing the clear failure paths but in evaluating the shades of gray between two plausible solutions.
What do you do when faced with this ambiguity?
In my experience, the key is to frame the decision in the broader context of your organization’s goals. What are you ultimately trying to achieve? What metrics matter most? You also need to recognize that while data can guide you, it won’t always give you the full picture. Gut instincts, cross-functional discussions, and even willingness to experiment with calculated risks can fill in the gaps.
At the end of the day, decision-making is as much about managing uncertainty as it is about optimizing outcomes. Sometimes the best course of action is to acknowledge that both options could work, depending on how they are executed. By focusing on execution, you shift the conversation from “which option is better” to “how can we make the chosen option succeed?”
Embracing this mindset of operational flexibility and clarity around execution priorities is how you make peace with the decisions that aren’t as clear-cut. After all, the true enemy of progress isn’t uncertainty—it’s indecision.
Credit: This post was co-authored with AI.