Forecasting for Agile Teams
Sprint planning feels like guesswork when stakeholders demand concrete delivery dates. Learn proven forecasting methods that turn velocity data into reliable predictions whilst maintaining agile flexibility.
AIU.ac Verdict: Brilliant for Scrum Masters and Product Owners who need to balance agile principles with business predictability demands. Limited advanced statistical modelling coverage for data science-heavy environments.
What This Course Covers
You’ll master velocity-based forecasting, Monte Carlo simulations for release planning, and probabilistic approaches to sprint commitment. The course covers burn-up charts, cumulative flow diagrams, and how to communicate uncertainty ranges to stakeholders effectively.
Practical modules include implementing forecasting in Jira, handling scope changes mid-sprint, and building confidence intervals around delivery dates. You’ll learn when to use different forecasting techniques and how to adapt predictions based on team maturity and historical performance data.
Who Is This Course For?
Ideal for:
- Scrum Masters: Need reliable methods to forecast sprint capacity and communicate realistic timelines to product stakeholders
- Product Owners: Want to balance feature prioritisation with predictable delivery commitments for business planning
- Agile Coaches: Seeking evidence-based approaches to help teams improve estimation accuracy and planning confidence
May not suit:
- Traditional Project Managers: Expecting Gantt chart-style deterministic planning rather than probabilistic agile approaches
- Individual Contributors: Not involved in sprint planning or stakeholder communication around delivery timelines
Frequently Asked Questions
How long does Forecasting for Agile Teams take?
The course runs 2 hours 47 minutes, typically completed over 2-3 focused sessions with practical exercises between modules.
Do I need statistical background for agile forecasting?
No advanced statistics required. William Davis explains Monte Carlo and probabilistic concepts using practical agile examples and team velocity data.
Which agile tools does this forecasting course cover?
Focuses on Jira and Azure DevOps for velocity tracking, plus Excel/Google Sheets for Monte Carlo simulations and burn-up chart creation.
Can these forecasting techniques work with Kanban teams?
Yes, covers both Scrum velocity-based forecasting and Kanban throughput metrics for continuous flow prediction and cycle time analysis.
Course by William Davis on Pluralsight. Duration: 2h 47m. Last verified by AIU.ac: March 2026.
