"How Many"

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Flow Analytics Pro's "How Many" simulation allows you to predict how many tickets or how many points of effort the team can complete in a given period (Sprint, iteration or other defined period). It uses a probabilistic approach, based on the team's past performance, to provide a realistic estimate of the amount of work that can be completed. By simulating a large number of possible scenarios, Monte Carlo simulation provides reliable predictions of team capacity, taking into account uncertainties and natural variations in the work process.

Using this simulation, teams can better anticipate the amount of work achievable, adjust their Sprint or project objectives, and optimize planning to maximize the chance of success.

How the “How Many” simulation works in Flow Analytics Pro

The How Many simulation in Flow Analytics Pro uses historical data and team capabilities to answer the question: How many tickets or effort points can the team complete in a given amount of time?

Here's how it works:

1. Historical data: The simulation uses the team's historical data, such as velocity (number of tickets or points processed in previous Sprints), ticket cycle times, and past performance. This data serves as a basis for establishing realistic scenarios.

2. Advanced Data Filters: Flow Analytics Pro allows the user to filter input data based on multiple criteria to adjust the simulation to specific scenarios.

   These filters make it possible to modulate the simulations according to the precise needs of the team or project.

3. Repeating simulations: The Monte Carlo simulation repeats several thousand simulations, each based on a random selection of historical data and possible scenarios. This approach generates a probability distribution of outcomes.

4. Estimating Results: After running all simulations, Flow Analytics Pro compiles the results to provide probabilistic estimates. This comes in the form of probability percentages for ranges of outcomes, such as:

   • "There is an 85% chance that the team will complete between 30 and 40 tickets during this Sprint."

   • "With 95% probability, the team will complete between 150 and 200 points of effort on the project by the end of the month."

These results help teams adjust their objectives and assess the workload achievable in the given period.

Usefulness of the “How Many” simulation in Flow Analytics Pro

The “How Many” simulation is particularly useful for:

1. Plan Sprints and Projects: It allows teams to define how many tickets or how many points can be reasonably handled in a Sprint or a specific period. This improves planning accuracy and helps set more realistic goals, increasing the chances of completing what has been started.

2. Anticipate risks linked to workload: By offering probabilistic forecasts, simulation makes it possible to identify the risks of workload overload in a given period. If the simulation shows that there is a low probability of completing all the work committed, the team can adjust priorities to avoid delays or disappointments.

3. Adapt team goals: Simulation helps the team adapt its goals based on actual capacity, to avoid gaps between planned work and actually achievable work. This helps to better manage expectations and improve predictability.

4. Optimize resource planning: With the data provided by the simulation, managers can better allocate resources and adjust team composition or priorities based on the planned capacity for the period studied.

Example of using the “How Many” simulation in Flow Analytics Pro

Let's take an example in Flow Analytics Pro where a development team wants to know how many tickets they can handle in a two-week Sprint:

• Historical data: The team has completed an average of 35-40 tickets in previous Sprints, but these tickets included a mix of bugs and features.

• "How Many" Simulation: The team configures the simulation by filtering only feature tickets, because the next Sprint will only contain this type of work. By repeating several simulations with past performance for this type of ticket, Flow Analytics Pro offers the following result:

  • "There is an 85% chance that the team will complete between 30 and 35 feature tickets during this Sprint."

With this information, the team can commit to a realistic number of tickets for the Sprint, while being aware of possible variations.

Usefulness in Flow Analytics Pro

The “How Many” simulation in Flow Analytics Pro offers teams major benefits:

• Team Capacity Forecasting: By simulating different scenarios, Flow Analytics Pro can accurately predict how many tickets or effort points can be completed, thereby improving Sprint and project planning.

• Improved decision-making: With probabilistic data, teams can adjust their commitments and goals based on the most likely outcomes, avoiding work overloads or delays in delivery.

• Reduction of uncertainty: By modeling past performance and taking into account contingencies, simulation helps reduce uncertainty around the amount of work that can be done and optimize the allocation of resources and time.

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