From theory to data product: Applying data science methods to effect business change

Janet Forbes, Danielle Leighton, and Lindsay Brin lead a primer on crafting well-conceived data science projects that uncover valuable business insights. Using case studies and hands-on skills development, Janet, Danielle, and Lindsay walk you through essential techniques for effecting real business change.

Janet Forbes, Danielle Leighton, and Lindsay Brin lead a primer on crafting well-conceived data science projects that uncover valuable business insights. Using case studies and hands-on skills development, Janet, Danielle, and Lindsay walk you through essential techniques for effecting real business change. Janet, Danielle, and Lindsay begin with case studies that demonstrate how a project’s entry point impacts its scope and approach and how that can diverge from the critical business drivers that ultimately measure successful data science projects. They also show you how to avoid missteps that can lead to less than stellar results or wasted effort and share a checklist to follow to get started on the right path from the beginning. Janet, Danielle, and Lindsay outline a framework to help you define, refine, and assess value for business questions that are candidates for data science projects. Many organizations struggle with identifying and prioritizing these questions, but this step is critical to ensure your project teams are focused on the right work. They then detail a pragmatic approach to frame your data-driven decision-making projects with an Agile project methodology, which lets the project team quickly adapt, based on findings, as the project progresses. This framework helps to manage uncertainty while ensuring the project is focused on constant progress toward a stated goal.