Agile Estimating and Planning

Why is it so difficult to create estimates that have value for the business and developers? In this first module, you’ll discover:

• The statistical theory behind why we underestimate how long tasks will take.
• Why you can’t fight the Student-Syndrome that causes delays, but you can use systems to minimize its impact.
• That it’s criminal to produce inaccurate estimates and how trying to be more precise is often the underlying cause.
• How to build a flexible plan that can change as you go along, without changing the original estimate.

Which product backlog items should you bring into an interation? Ones that meet the priorities of the Product Owner, and are achievable by the team. These lessons show you:

• How to run an effective iteration planning meeting. Find out who should attend and the four steps you need to communicate and manage expectations.
• The differences between velocity-driven and commitment-driven planning and when to use each one.
• When velocity-driven planning can speed-up planning meetings but at a significant cost.
• How to calculate how much work should be brought into an iteration so that the team doesn’t bring in too much or too little, and can handle uncertainty.

This covers the key problem for estimating - how do we estimate real-world work without having all the details to hand? It comes down to being able to use story point or ideal days properly. In this module, you’ll learn:

• Why estimating size and deriving duration is the key philosophy behind accurate estimates.
• How to choose between using story points and ideal days for planning with your team.
• Why you need to make sure you’re answering the right question when talking to management about ideal time.
• How story point estimates can be used even if you don’t know all the information, and when you should defer estimating till you have the information you need.
• Whether you should use story points to estimate in terms of the time or complexity of a task.

This module walks you through the practicalities of estimating items on the product backlog so you know:

• Why gut instinct isn’t a bad thing, and how triangulation can help estimates improve over time.
• When to break down larger product backlog items and estimate smaller pieces, but avoid estimation inflation by breaking them down too much.
• How to choose the right sequence of estimating numbers for your team.
• How Planning Poker is a simple, fun game that strips out subjectivity, shines a light on hidden risks, and prevents personal bias from skewing the estimation.

To be valuable, estimates have to work on long-term projects. Stakeholders want to know what will be delivered and in how many iterations. This module provides statistical techniques for improving stakeholder conversations and protecting the team against unrealistic expectations. After this module you can:

• Use historic velocity to make accurate future estimates, using a statistical technique that prevents outlying data affect accuracy.
• Make forecasts even when there is no historical velocity because the team is new, or new to agile.
• Predict velocity when team size changes, and gather data to communicate the future of this change to management.
• Communicate what’s possible when stakeholders request estimates for fixed dates, scope and cost (and in a way that makes them listen).

You may need to create estimates when there are interactions and dependencies between multiple teams. To make this easier, this module shows you:

• How to get consensus between teams about the common value of a unit of estimation.
• Why you should create a common baseline, but avoid comparing team velocities.
• How to facilitate a successful iteration planning with multiple teams.
• Identify upcoming dependencies that may affect progress by considering 3 upcoming iterations at once.