Principals at big companies make a common mistake when starting up. They bring their enterprise-scale solutions to small-scale problems.

A Principal Data Scientist at a VC-funded company started a DAaaS business - Data Analytics as a Service. His clients would give their business data and expect actionable insights in return.

When he got his first client, he was off to the races on the tools he knew best - Python on Jupyter Notebooks. After spending many days he had nothing to show except complex mathematical models and highly technical graphs - which was not useful for his client.

That’s when he reached out to me for ideas. I’m not a data scientist. So, I loaded the data onto a spreadsheet and did some simple analysis. In a couple of hours I gave him some actionable insights which his client found interesting.

Sometimes, the right tool is the one that gets you answers today, not the one that scales tomorrow. Founders should leave the hat at the door.

This was not because I was a better data analyst than him. Rather, it was actually because I was not as skilled as him. Once he understood this, he was able to produce many and more useful insights by keeping this simple. We learned to keep the business problem over and above the technical solution.