97 Things Every Data Engineer Should Know

Chapter 91. When Our Data Science Team Didn’t Produce Value

Joel Nantais

I’m in my boss’s office, briefing him on the new dashboard that will greatly increase access to data for everyone in the organization.

Like a slap in the face, he says, “Your data team can’t get any meaningful data.”

To say that this caught me off guard is an understatement. I knew the team was working hard. We had designed and launched several complex projects over the years.

Yet he didn’t have confidence in our data or our ability to provide value.

Genuinely confused, I probed to learn more about his experience and perspective. He needed urgent, reactive responses to his data requests. Constantly, he heard we couldn’t provide the data.

The priorities of the data team had focused on BI, ML, and forecasting tools. These were where the organization needed to be and had justified the increase in resources. Heck, we were following the five-year plan!

Looking back, I overfocused on the progress of our “sexy” long-term initiatives. And ad hoc data requests were not a priority. Only those requests with easy data access were fulfilled.

When you are in a reactive organization, you need to devote resources to that mission. I was determined to change the perception of our usefulness.

We worked to ensure that the team set a new culture of “getting to yes” no matter the effort. We reprioritized projects and held each ...