Stop To Think

Sometimes we are so wrapped up into our own thoughts that we don't stop to organize them. Developing the habit of taking a breath before acting is a good place to start. I recognize that there are very few instances in my life where really quick thinking and instinct driven decisions are fundamental. Most of the time I can take a pause to think and plan ahead.

This covers so many scenarios:

• Jumping to writing code before thinking things through
• Doing a shallow investigation that leads to unnecessary complexity
• Not clarifying requirements and following your instinct
• Responding immediately to a disagreement
• Acting more than listening

And the list could go on. I observed that the lack of planning is generally detrimental, while this is rationally obvious it's not easy to break the habit and do it. In the software engineering industry I see this in many shapes and forms and I have to occasionally remind myself that there's no bear chasing me and that I can take a minute to think things through BEFORE doing anything. As a manager this is crucial, no decision should be rushed.

Most importantly you shouldn't let anyone rush you into making a decision. Take your time and get back to them when you are sufficiently informed.

Thoughts

Rushing without planning is risky, take your time to plan your work or your next move any time you can. As a manager I feel responsible for communicating this clearly. While I might say "we have an issue ongoing that needs addressing", I don't mean "do this now as quickly as possible" but "prioritize this over other tasks and make sure your approach is correct, let's do this right".

I think there's a little nuance to this. While it is OK to stop for a minute to plan ahead, you shouldn't wait to have all the possible data in order to make a decision. Being able to make decisions with lack of data is how you develop an instinct. This is oddly similar to machine learning, you want to train the model so that it is able to generalize otherwise it will incur into over-fitting (this happens when a model does exceptionally well with a given dataset but is not able to provide satisfactory results with any other dataset).

Just a thought!