At the time of posting this, this blog has a generic template, broken links, no logo, only one post, and is all around…well, bad. So why would we voluntarily share with the world something so embarrassing?
Because Jeff and I have been thinking about starting a blog for several months but up until now, we have nothing to show for it. Why? Because we failed to understand the initial part of Newton’s Law of Inertia.
“An object at rest stays at rest…”
Newton was just as right about our everyday state of life as he was about physical objects at rest.
“A project at rest will remain at rest…”
…And you can replace “project” with “assignment”, “goal”, “dream”, “task”, etc. Basically, if you don’t actively start something, then you’re stuck at the starting line.
Instead of writing this article, we could spend more time planning the world’s greatest blog. But our minds would be stifled by endless blog design research, excessive SEO analysis, and an overall frustration of not seeing progress.
So instead, we’re applying mental energy to tackle a much simpler problem: writing this single blog post. Because of this, we have blog! It’s not much, but we get the satisfaction of launching a blog and can solicit feedback from our network for improvement. Both this sense of accomplishment and feedback are critical in the progression of nearly any project.
We’re not recommending to just “wing” your next project (that would make for a boring blog and be plain bad advice) but we do recommend that you ask yourself: what is the simplest thing I can deliver that adds values and opens up a conversation on next steps? In data science projects, overcoming an initial state of rest could be as simple as:
- Calculating basic descriptive statistics on a data set and presenting to a stakeholder to help them get a feel for the data.
- Developing KPIs for current business performance so that stakeholders understand the baseline performance and so that you know the threshold you need to achieve in order to add value.
- Conducting a feasibility analysis to assess whether a question is worth investigating.
Overcoming the initial lack of inertia and opening up the feedback loop can help you get your next data science project in motion.