If you’d like to check it out, you can find this episode on Spotify. It’s also on Apple Podcasts and on our podcast landing page

The podcast episode discusses the integration of agile methodologies and improving estimation practices for software development. DJ, Jason Duffy, and Mary Kaufmann delve into the insights Jason gained from reading When Will It Be Done? by Daniel Vacanti. The book introduces techniques for better forecasting and predictability in project timelines using data and statistical models.

Jason introduces concepts like using data from previous work to predict the completion time of tasks, the pitfalls of using story points, and the importance of focusing on actual time (cycle time) for estimates. The conversation touches on the concept of regularly updating forecasts (just like meteorologists tracking hurricanes) and applying probabilities to predictions.

Key takeaways include how to improve communication with clients by delivering transparent, data-backed forecasts. Jason emphasizes how small amounts of data can still provide valuable insights early in a project, allowing for continuous improvement over time. The trio discusses practical ways to collect this data using tools like JIRA, and the importance of defining when a task truly starts, which helps in improving overall cycle time and predictability.

Overall, the podcast highlights how the principles from Vacanti’s book could transform how teams estimate and manage software development projects. They stress the importance of educating teams and clients about these methods to align expectations and create a shared understanding of project timelines.