7.3 Cumulative Flow Diagrams (CFDs)

Cumulative Flow Diagrams (CFDs) are powerful tools in Agile project management. They visually represent work flow over time, helping teams track progress, identify bottlenecks, and measure key metrics like cycle time and throughput.

CFDs use colored bands to show different workflow states, like "To Do" and "In Progress." By analyzing band widths and slopes, teams gain insights into their process efficiency. This data-driven approach enables continuous improvement and optimized workflows.

Cumulative Flow Diagrams: Purpose and Components

Visualizing Work Flow with CFDs

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• Cumulative Flow Diagrams (CFDs) are a valuable tool in Agile project management that visualize and analyze the flow of work through a process over time
• CFDs provide a graphical representation of key metrics including:
  • Work in progress (WIP)
  • Cycle time
  • Throughput
  • Bottlenecks in the workflow
• The vertical axis of a CFD represents the cumulative count of work items, while the horizontal axis represents a time scale, typically in days

Components of CFDs

• CFDs consist of colored bands that correspond to the various workflow states, such as:
  • "To Do"
  • "In Progress"
  • "In Review"
  • "Done"
• The width of each band represents the number of work items in a particular state at a given point in time
• By analyzing the width and slope of the bands, teams gain insights into their workflow patterns, identify bottlenecks, and assess their process efficiency
• Example: A CFD with a wide "In Progress" band and a narrow "Done" band indicates a bottleneck where work items are accumulating in the "In Progress" state

CFD Analysis: Visualizing Work Flow

Constructing CFDs

• To construct a CFD, gather historical data on work items as they progress through the workflow states over time
• Plot the cumulative count of work items in each state on the vertical axis against the corresponding dates on the horizontal axis
• Connect the data points for each state to create continuous bands that represent the flow of work items
• Example: If there are 10 work items in the "To Do" state on Day 1, 15 items on Day 2, and 20 items on Day 3, plot these points and connect them to form the "To Do" band

Analyzing CFD Bands

• Analyze the width of the bands to determine the number of work items in each state at different points in time
  • A widening band indicates an accumulation of work items in a particular state, suggesting a potential bottleneck
  • A narrowing band suggests that work items are being processed and moving to the next state efficiently
• Identify bottlenecks by looking for states where the band width remains consistently wide or increases over time, indicating a slower rate of work item processing compared to other states
• Calculate key metrics using the CFD data:
  • Average cycle time: the time it takes for a work item to move from start to finish
  • Throughput: the number of work items completed per unit of time
• Example: If the "In Review" band is consistently wider than other bands, it indicates a bottleneck in the review process

CFD Patterns: Assessing Team Performance

Ideal CFD Patterns

• Ideal CFD patterns show smooth, parallel bands with consistent spacing, indicating a steady flow of work items through the process
• Diverging bands, where the distance between bands increases over time, suggest an accumulation of work items in certain states and potential process inefficiencies
• Converging bands, where the distance between bands decreases over time, indicate that the team is processing work items faster than they are being added, leading to a reduction in WIP

Interpreting CFD Patterns

• Flat or stagnant bands signify periods where no progress is being made in a particular state, highlighting bottlenecks or process issues that need attention
• Sudden changes in band slope or width can indicate shifts in team performance, such as an increase in productivity or the impact of process changes
• By regularly analyzing CFD patterns, teams assess their performance trends, identify improvement opportunities, and make data-driven decisions to optimize their workflow
• Example: If the "In Progress" band is consistently wider than the "To Do" band, it suggests that the team is taking on more work than they can handle, leading to a buildup of WIP

CFDs for Process Improvement

Data-Driven Decision Making

• Use insights gained from CFD analysis to identify areas of the workflow that require optimization or process improvements
• Focus on reducing bottlenecks and improving flow efficiency by implementing targeted interventions, such as:
  • Increasing team capacity
  • Streamlining processes
  • Removing unnecessary steps
• Set WIP limits based on CFD data to prevent overloading and ensure a sustainable pace of work item processing
• Adjust workflow policies and practices based on CFD patterns to promote a more balanced and efficient flow of work items through the process

Continuous Improvement with CFDs

• Regularly review and discuss CFD trends with the team to foster a culture of continuous improvement and data-driven decision-making
• Use CFDs to communicate process performance and improvement initiatives to stakeholders, highlighting the impact of process changes on key metrics (cycle time and throughput)
• Continuously monitor and update CFDs to track the effectiveness of process improvements and make further adjustments as needed
• Example: If the CFD shows a consistently wide "In Progress" band, the team may decide to implement WIP limits to reduce overloading and improve flow efficiency