Data Science in Agile: Is Your Data Analytics Problem Actually a Backlog Problem?

Data science is fundamental to success—and leveraging it effectively with data analytics is imperative to being competitive in the market.

As we covered in the first conversation in this series with Adam and Dan, the way your organization uses data is important. If you aren’t actively managing, governing and operationalizing your data, you will inevitably fall behind.

So we know how important data is. We know we need to use it, and we know how important it is that we use it the right way. With this in mind, how do we take the next steps as we stand up your advanced analytics capabilities without overloading the analytics team and ensuring we’re getting the right data we can use to learn the right things, solve problems better, and get ahead?

Are the challenges we face with our data analytics process really just problems with our backlogs? And if so, where do we go from there?

LeadingAgile’s Adam Jennison and Dan Smith have collectively spent decades in product management roles in multiple organizations for data-driven products. In this conversation, they address the answers these questions and more.

Reach out with any questions about the discussion or to connect on the topic.