Overcoming the ‘Analysis Paralysis’

Nobody likes being wrong. The need to feel valued is an intrinsic human desire that manifests itself through the choices we make and how we communicate those choices to others. When it comes to making a decision, it’s natural to want to be “right.”

Decision-making is similar insofar as the choices you make are a reflection of the values, beliefs, morals and intentions that not only shape your behavior, but also identify you as a person as well impact others.

What, then, do you do in today’s world where there is so much information to navigate and different details and perspectives to take into account?

To help avoid the pitfalls of analysis paralysis, keep in mind these considerations:

Set a “drop dead” date. Determine the last possible timeframe by which a decision must either be made or removed from the decision-making table.

Curb your curiosity. One of the culprits contributing to analysis paralysis are details, the desire to excavate deeper and deeper every new detail that arrives on scene. Set yourself parameters for what you need to know (now) and what you’d like to know (in the future). If the information you have now answers the call, it’s time to move forward.

Recognize that the moons will never align. No matter how much information you have, there will always be more. There are, however, optimal moments during which decisions can be made. Remember, just because you arrive at one conclusion doesn’t mean you can never adapt to a new one.

Stair step your decisions. Rather than looking at the decision to be made as a one-time, main event, consider smaller yet actionable decisions that can be made now or that lead up to the main one. Even just the tiniest shift of momentum can have a positive snowball effect that wriggles you out of the paralysis associated with making the “perfect” decision.

Summing-up: Decisions are never final for the simple fact that change is never absolute. Rather, change is ongoing. To stay competitive and progress at the rate of change requires adaptive decisions that can be iterated and improved upon on the fly.

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