Learning From MistakesNov 22, 2022
All data scientists make mistakes at times, but it's the learning from those mistakes that's important. This week, I made a mistake in judgment when I decided against asking for help on a project. I was too proud and thought I could do it all on my own. But a day or two later, I realized my mistake and humbly asked for the help I needed. Now I know that by incorporating feedback, my project will be better for it in the end.
I'm working on a booklet that includes activities designed to build a data culture on a data team or in a data-driven organization. I reached out to ask for help from a trusted colleague who has a career history that involves classroom teaching.
Normally, I would have asked for help right away. But for some reason, this time I decided against it. Maybe I was too proud or thought I could do it all on my own. But whatever the reason, it was a mistake.
Asking For Help
A day or two after making my initial decision, I realized how foolish I had been. So I swallowed my pride and reached out to ask for the help I so desperately needed. My colleague graciously agreed to provide feedback, and now I know that by incorporating her suggestions, my project will be much stronger in the end.
We can all learn from our mistakes, no matter how big or small they may be. In this case, by taking the time to ask for help, I avoided making a larger mistake down the road. And although there may be some extra work involved in incorporating feedback, it will be well worth it in the end.