Forecasting in the Agile world asks the difficult questions: How much of our product backlog will ready by a certain date? or By which date a specific feature will be ready?
Many teams attempt to forecast by measuring their Product Backlog in Story Points and dividing by the average number of story points achieved per Sprint. This is rarely effective.
- Effective Forecasting: Estimation in Kanban
- Forecasting for beginners
- Forecasting using data
- Forecasting Using Data – a list of tools
- How to Make Commitments for New Teams using Probabilistic Forecasting
- Monte Python Simulation: Misunderstanding Monte Carlo
- Story Point Velocity or Throughput Forecasting – Does it matter?