What are the essential parts of the problem?

During my first Data Science project seven years ago, I was so eager to produce something that I spent night and day putting together a dashboard only to discover that I had to return to the drawing board because I didn’t provide answers to the questions my stakeholders had.

Building a dashboard wasn’t the most important thing for me to do; it was understanding my stakeholders’ requirements.

When Sony was working on their first e-reader device, they were so focused on building the product that they neglected to determine a viable business model (e.g., royalty payouts, margins) and what digital standards their devices would use — two pitfalls that may very well have led to the demise of Sony’s otherwise competent e-reading device.

Building an e-ink device was an essential part of the problem, but so too was determining the infrastructure on top of which the device would operate.

Just because the idea or act of doing something is enticing doesn’t mean that it’s the most important thing to do or the only thing to do.

Anytime you‘re about to invest any significant effort, make sure you step back and cut through the noise by first asking:

What’s the solvable problem?

What are the essential parts of this problem that I should be focusing on?

In this way, you are more likely to do useful things and less likely to engage in unnecessary effort.