"When"

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The "When" simulation in Flow Analytics Pro helps answer the question "When" a certain number of tickets or effort points will likely be completed. It allows you to estimate when a specific objective will be achieved, taking into account variability in team capacity, changes in workflow, and contingencies related to development processes. This type of simulation is particularly useful for managing deadlines and predicting deadlines more precisely.

The Monte Carlo simulation in Flow Analytics Pro generates these forecasts from historical data, and it allows users to filter the input data based on different criteria to simulate specific scenarios and obtain relevant results for a given context.

How the “When” simulation works in Flow Analytics Pro

The “When” simulation in Flow Analytics Pro relies on repeating simulated scenarios to determine a range of likely dates when a work goal will be achieved. Here is how the simulation works:

1. Historical data: As with the "How Many" simulation, Flow Analytics Pro relies on the team's past performance (velocity, cycle time, tickets processed) to generate forecasts. These data are essential for modeling the variability of possible outcomes.

2. Advanced filters on input data: Flow Analytics Pro offers users the ability to filter historical data according to different criteria, which helps refine simulations.

   This allows simulations to be modulated to reflect realistic conditions and obtain results adapted to the team's current situation.

3. Repeating Simulations: The Monte Carlo simulation repeats thousands of scenarios based on the input data, taking into account the variability observed in the team's past performance. Each simulation calculates a possible completion date for the set objective (a certain number of tickets or effort points).

4. Estimating Results: Once simulations are performed, Flow Analytics Pro compiles the results to provide likely date ranges. For example :

   • “There is an 85% probability that the team will reach 150 effort points by October 15.”

   • "With 95% probability, the team will have completed 50 tickets by November 25."

These results allow teams to adjust their planning and better manage expectations around delivery times.

Usefulness of the “When” simulation in Flow Analytics Pro

The “When” simulation in Flow Analytics Pro is particularly useful for:

1. Predict goal completion dates: It allows teams to answer the question “When will we be able to complete X tickets or points?” by providing a realistic estimate of possible deadlines. This improves the accuracy of planning projects and Sprints.

2. Manage stakeholder expectations: By providing a date range with associated probabilities, teams can better manage stakeholder expectations. They can thus identify scenarios where objectives will be achieved with a high probability, while anticipating the risks linked to deadlines.

3. Anticipate the risks of delay: If the simulation shows that the probability of reaching a certain date is low, this makes it possible to review priorities, adjust the workload, or reassess deadlines to avoid surprises. This helps identify risks early in the project and adjust efforts accordingly.

4. Improve long-term project management: For more complex projects, simulation provides an overview of possible completion times, particularly in the context of important milestones. It thus provides better visibility on the progress of the project, while taking into account natural variations in the team's working capacity.

Example of using the “When” simulation in Flow Analytics Pro

Let's imagine that the team is working on a project with a goal of 150 effort points to reach before a certain deadline. By running the “When” simulation in Flow Analytics Pro, here is how the team could use the results to adjust their planning:

• Historical Data: The team has completed an average of 50 effort points per Sprint in recent Sprints, with some variability across ticket types.

• Simulation "When": The team configures the simulation by filtering the data for feature tickets only, because the goal is feature-specific. The simulation runs several thousand scenarios based on past velocity. The result could indicate:

  • “There is an 85% probability that the team will reach 150 effort points by October 20.”

With this information, the team can adjust its work plan to maximize the probability of achieving this objective or, if necessary, review the scope or priority of tickets to be processed.

Usefulness in Flow Analytics Pro

The “When” simulation in Flow Analytics Pro provides teams with the following benefits:

• Forecasting completion dates: It allows you to more precisely determine when a certain volume of work will be completed, thus improving deadline management and planning of Sprints and projects.

• Reducing uncertainty: By modeling past performance and repeating simulations, Flow Analytics Pro provides probabilistic forecasts that allow teams to better anticipate delay risks and adapt accordingly.

• Expectation management: With the predictions provided by simulation, teams can effectively communicate with stakeholders about timelines and likely outcomes, making it easier to manage expectations and necessary adjustments during the project.

Additional benefits:

• Milestone Planning: For projects with specific milestones to reach, the When simulation helps estimate when those milestones will likely be reached.

• Proactively anticipate adjustments: If simulation results indicate that goals may not be achieved on time, the team can adjust its efforts or re-prioritize work to improve its chances of success.

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