Using simulated Sprints to forecast velocity

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Motivation

Communication with stakeholders and confidence in how we forecast was proving difficult.

Research

Articles

• I found this article on Scrum.org that introduced me to Monte Carlo forecasting.
• Further research here and spreadsheet to use

Starting Point

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.

Method

• 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

Results

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

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Roadmaps

Definition of Done