Using simulated Sprints to forecast velocity
Communication with stakeholders and confidence in how we forecast was proving difficult.
- I found this article on Scrum.org that introduced me to Monte Carlo forecasting.
- Further research here and spreadsheet to use
The team that I trialed this with were previously using the method to take the average velocity of the last 3 sprints, catering for anticipated holidays.
- Take it to the team and talk through research
- Input velocity data from previous sprints
- Use the predictions it comes out with to change how we forecast our sprints
- Use the calculations to have a strong goal (one that we could have a better confidence in our forecast) and a stretch goal which we would get to if we could
- Take it to stakeholders and talk through the trial
Communication on our forecasts within the team
- It enabled conversation over the forecast velocity as we could adjust and see the simulation run rather than be presented with a single number
- A forecast is as such, a forecast, and using this tool brought us back to metrics being a tool rather than a target number to hit
- The use of strong goals and stretch goals helped focus on something more realistic to achieve and therefore built confidence within the team
Transparency with Stakeholders
- As we’d had more conversations as a team we could justify our forecasts when asked and had more confidence
- The use of strong and stretch goals also helped manage expectations with stakeholders
Extension to try
- Planning for a goal first and then checking how that goal would look in the simulation and what our chances were of achieving the goal
- Then we could adapt our approach to the goal if it seemed unlikely for us inside a sprint