Skip to main content

Running Your First Sprint Simulation

Zamski's Sprint Simulator helps you predict sprint outcomes, identify potential bottlenecks, and optimize resource allocation before your sprint begins. This guide will walk you through creating and running your first simulation.

What is Sprint Simulation?​

Sprint simulation uses AI and predictive analytics to model how your sprint will unfold based on:

  • Task complexity and estimated effort
  • Team capacity and skill sets
  • Hidden dependencies between tasks
  • Historical performance data
  • Potential risks and their impacts

The result is a realistic prediction of sprint outcomes that helps you make data-driven decisions.

Benefits of Simulation​

Running sprint simulations before committing to a plan helps you:

  • Identify realistic sprint goals based on team capacity
  • Detect potential bottlenecks before they occur
  • Optimize resource allocation for maximum productivity
  • Reduce sprint planning time by testing scenarios quickly
  • Improve sprint predictability with data-driven planning

Setting Up Your First Simulation​

1. Navigate to the Simulator​

Click on Simulator in the main navigation to open the Sprint Simulator.

2. Configure Team Capacity​

  1. Click on Team Configuration in the simulator setup
  2. Add team members participating in the sprint
  3. Set availability percentage for each team member
  4. Specify skill sets and expertise levels
  5. Account for scheduled time off or partial availability

3. Define Sprint Parameters​

  1. Set the sprint duration (usually 1-4 weeks)
  2. Configure working hours per day
  3. Set the start and end dates
  4. Adjust default contingency buffers (optional)
  5. Select any global constraints

4. Add Sprint Tasks​

Method 1: Import from your PRD​

  1. Click Import from PRD
  2. Select an analyzed PRD from the list
  3. Choose which requirements to include
  4. Review automatically generated tasks and estimates
  5. Adjust estimates if needed

Method 2: Import from Jira or Other Tools​

  1. Click Import from Jira
  2. Authenticate with your Jira instance
  3. Select the sprint or filter to import
  4. Review imported tasks and estimates
  5. Make any necessary adjustments

Method 3: Manual Entry​

  1. Click Add Task to create tasks manually
  2. Enter task details:
    • Name and description
    • Estimated story points or hours
    • Required skills
    • Dependencies
    • Priority
  3. Repeat for all sprint tasks

5. Define Task Dependencies​

  1. Click on the Dependencies tab
  2. Draw connections between dependent tasks
  3. Specify dependency types:
    • Finish-to-Start (most common)
    • Start-to-Start
    • Finish-to-Finish
  4. Set required lag time between tasks (if applicable)

Running the Simulation​

1. Validate Simulation Setup​

  1. Click Validate Setup to check for configuration issues
  2. Review and address any warnings or errors
  3. Ensure all required fields are completed

2. Run the Base Simulation​

  1. Click Run Simulation to execute
  2. The system will process the simulation (typically takes 10-30 seconds)
  3. Initial results will be displayed

Understanding Simulation Results​

1. Sprint Outcome Prediction​

The main dashboard shows key predictions:

  • Completion probability: Likelihood of completing all tasks
  • Expected completion date: When the sprint will likely finish
  • Critical path: Sequence of tasks that define the timeline
  • Risk factors: Potential issues that could impact the sprint

2. Task Timeline Visualization​

The task timeline shows:

  • Projected start and end dates for each task
  • Dependencies and blockers
  • Resource allocation over time
  • Potential bottlenecks and overallocations

3. Resource Utilization​

The resource utilization chart displays:

  • Team member allocation throughout the sprint
  • Skill coverage and potential skill gaps
  • Periods of over or under-allocation
  • Suggestions for resource balancing

4. Risk Analysis​

The risk analysis section highlights:

  • High-risk tasks with completion concerns
  • Dependencies that may cause cascading delays
  • Skill coverage gaps
  • Potential bottlenecks

Refining Your Simulation​

1. Adjusting Parameters​

Based on initial results, you can adjust:

  • Task estimates
  • Team capacity
  • Dependencies
  • Sprint scope

After each adjustment, rerun the simulation to see the impact.

2. Creating Alternative Scenarios​

Create different scenarios to compare options:

  1. Click Save as Scenario to preserve the current setup
  2. Make changes to create a new scenario
  3. Run the new simulation
  4. Compare results with previous scenarios

3. Scenario Comparison​

The scenario comparison view allows you to:

  • Compare completion probabilities
  • View differences in resource allocation
  • Identify which scenario has the lowest risk
  • See how different task combinations affect outcomes

Implementing Simulation Insights​

After identifying the optimal scenario:

  1. Click Export Plan to save your final sprint plan
  2. Choose export format (PDF, CSV, Jira import)
  3. Share with your team for implementation
  4. Reference simulation insights during sprint planning

Best Practices​

  • Start simple: Begin with a basic simulation and add complexity gradually
  • Use realistic estimates: Input honest task estimates for accurate results
  • Account for non-sprint work: Include time for meetings, support, etc.
  • Update with actuals: As the sprint progresses, update with actual data
  • Refine over time: Use completed sprint data to improve future simulations

Next Steps​

After running your first simulation: