How I increased my impact as a data scientist with one question

How can you level up your impact as a data scientist? Image source.

How do you start your data science projects? What do you do when you hear questions like, “can we better understand how our customers use the product” or have ideas like “how could I model probability to purchase?” Hearing these when I first became a data scientist meant diving headfirst into my arsenal of technical skills and thinking of solutions.

Diving into the technical stuff as a data scientist is exciting. Image source.

No doubt, this gets you straight to the exciting stuff: transforming masses of data into something meaningful. It’s the sort of challenge that made me, and most of the amazing people I’ve met in this field, want to be a data scientist! Still, something frustrating kept happening that eventually changed the way I start every project.

Regardless of how impressive my output, people weren’t always using what I created. With this realization, my mindset shifted from “data scientists use data,” to “data scientists make data useful.” Explained in detail here but, put simply, there wasn’t much of a point if no one used what I created.

“Data scientists make data useful”

Since then, I don’t waste energy thinking of solutions as soon as a question or idea comes to (or from) me or my team. I always start the conversation by asking something that has helped me to have more impact: “Imagine we’ve done all the hard work and developed a perfect solution. What will you do with it?”

Asking about impact can be a powerful move. Image source.

This skips right to working out what will happen. It determines whether the original question comes from a place of fleeting curiosity or of a true desire to be data-driven. Will we monitor the data regularly and take action when we see something deviate from the forecast? Will we make different decisions if the results come back negative or positive? Will we productionize and use the model output appropriately?

If there isn’t a satisfying answer to these sorts of questions, then there probably won’t be any satisfying impact. It’s also important to point out that this didn’t stop me from working on fun projects. It just helped make sure I was working on the projects that were fun AND impactful!

“Imagine we’ve done all the hard work and developed a perfect solution. What will you do with it?”

Other than helping to direct my efforts, I discovered a wonderful side effect to asking this question. A typical response is, “I hadn’t thought of that,” or some long-winded plan made up on the spot. Having heard these many times, I noticed that the question is quite confronting.

Asking about impact can be tough, but worth it. Image source.

There’s an initial defensive response, often quickly followed by a realization that there should be a good answer. So not only does it save me time from picking up projects that won’t have an impact, but it helps stakeholders and decision-makers to reflect on their goal. This almost always ends in a better-formulated question, a clearer purpose, and greater commitment to being data-driven.

So next time you start a data science project, stop to ask what will happen with the result. I hope this simple question helps you as much as it did me!

Sign off

Thanks for reading and I hope you enjoyed this article. Wondering how you can increase your impact as a data scientist? Ask me your questions on Medium, Twitter or LinkedIn, and I’ll be happy to share my experiences!