Mo Chen

I bet most of you doubt whether your projects will meet high standards.

And you know what?

I used to wonder the same.

The urge to keep changing things never goes away, but chasing perfection is a trap.

Good work stands on proof, not on gut.

Here’s how I avoid it:
- Set clear benchmarks before I start;
- Often revisit the project’s goal to guarantee I’m heading in the right direction;
- Check results against those benchmarks after each step — avoiding the vague sense of “good enough.”;

I also apply some principles that help me stay on track:
- Getting feedback from peers who have nothing to do with the outcome;
- Writing a short project summary as if I were my own toughest critic;
- Keeping a checklist for reproducibility, clear data lineage, code comments, and logical flow;
- Running a post-project assessment to answer: What surprised me? Where did my assumptions break down?

These practices help you improve your projects and iterate effectively.

Whether you:
- Rerun your analysis on a new data slice;
- Ask someone to follow your process and note every piece of feedback;
- Revisit an old project once a month and rate it against your standards ...

the work doesn’t truly end when you finish the project.

How do you know when it’s time to stop and present something?

When the analysis answers the business question, holds up to peer review, and is easy to repeat.

Not when it simply feels "good enough". Not when it doesn't feel "perfect".

Do you have any other techniques that help you feel more confident about a project’s quality?

4 days ago | [YT] | 85