7 Questions Every Data Team Should Ask the Business

How To Find Projects Worth Working On

Hi, fellow future and current Data Leaders; Ben here 👋

Before diving into today’s newsletter, I want to take a moment to thank this issue’s sponsor, BMC. Many data teams still spend too much time babysitting pipelines and stitching together scripts. Control-M helps automate that work, coordinating data workflows, triggering ML jobs, and syncing across cloud platforms, so teams can focus on analysis instead of maintenance.

Check out their latest case study to see how it can simplify complex workflows.

Now let’s jump into the article!

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A common challenge for data teams is figuring out what to work on that will drive the most value.

In some cases, the business has projects they believe should be taken on that you might disagree with, but you don’t have a solid list of suggestions, so you’re stuck with what they’ve asked you to work on.

In other cases, the business team might not know exactly how they’d like to use data, other than perhaps a dashboard or two. That means you can’t just ask, “What data projects do you need?” and expect a helpful answer.

Instead, you need to ask questions that uncover pain points, opportunities, and processes where data could make a meaningful difference.

At Facebook, we conducted this exercise every six months to realign priorities and identify new, high-impact projects. We’d go and talk to our business partners to understand their current and future needs. From there, we’d work to come up with projects we believed aligned.

If you are looking for questions to help you better align with the business, here are seven questions you can ask to surface valuable data. (Also, I’d love to hear if you have any questions you’d recommend.)

1) What’s keeping your team from hitting its targets right now?

Not everything is about data. Many leaders recognize that there may be areas where they are struggling to meet targets.

Perhaps they aren’t converting enough on ads, or their team has consistently missed the mark when it comes to delivering products on time. There are real-life situations where data may or may not be helpful.

But instead of asking, Where can data help, your focus should be on understanding the bigger picture.

Department Specific Versions Of This Question

• Finance - Are there recurring surprises in expenses or revenue that you wish you could predict earlier?

• Marketing - Are there channels where you feel you’re spending too much but not seeing results?

• Operations - Where do delays or inefficiencies tend to pop up in your daily workflow?