Watch the Work, Not the Workers with Flow Metrics
Visualise work, clear bottlenecks and balance demand with available capacity using Flow Metrics to build a continuous improvement and efficiency culture.
Deep Dive by Notebook LM
Tracking the work, rather than just the workers, optimises productivity and efficiency.
Key flow metrics, such as Cycle Time, Work Item Age, Work in Progress, and Throughput, help teams visualise progress, identify bottlenecks, and improve workflow management.
Using tools like the ActionableAgile enables data-driven decision-making, fostering a culture of continuous improvement and predictable outcomes.
Author’s note: I have added to each section a short blurb about how I have used these tools in the wild. Only the names have been changed to protect the innocent (and confidentiality obligations).
In Gil Broza's book Deliver Better Results, I came across a short chapter titled “Watch the work, not the workers.” For a system to fulfil its purpose, it must propel the proper work forward and balance two crucial aspects: overseeing the workforce and monitoring the work. While many companies still predominantly focus on supervising their workers through methods like timesheets, individual productivity metrics, and detailed activity management, the key lies equally in tracking the journey of each task.
Focusing on the work rather than the workers struck a profound chord with me. This is particularly relevant to the current debates about returning to the office, which, for some, appears more like a guise to monitor employees closely. This is further exacerbated by the misuse of Agile methodologies, where velocity and story point targets become more of a weapon than a tool.
Additionally, it’s noticeable how product leaders often urge developers to increase their output yet overlook the inefficiencies in their upstream processes, consumed by their justifications rather than actual progress. This situation underscores the need to shift our attention from scrutinising workers to truly observing and understanding the work.
To combat this, Kanban Flow is a method that visualises work, enabling a clear overview of progress and bottlenecks. This approach helps manage work by balancing demands with available capacity and improving the handling of bottleneck issues. It’s a tool for teams to be more efficient, responsive, and agile in their tasks. See my blog post “Evolve From Scrum to Kanban Flow” for more details.
Four Key Flow Metrics:
In this post, I will dive deep into Flow Metrics with the Actionable Agile Jira plugin and explore four key Flow Metrics for Watching the Work:
Cycle Time
Work Item Age
Work in Progress
Throughput
Cycle Time- Cycle Time Scatterplot Report:
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The Cycle Time Scatterplot is a pivotal diagnostic instrument that offers studios and teams a visual representation of their process efficiency and flow dynamics. By plotting each work item’s cycle time (the duration from initiation to completion) against the time it was started, this tool provides a clear and immediate visual cue of variations and patterns in process performance.
This graphical representation is crucial for identifying inconsistencies and anomalies in the workflow, such as bottlenecks or unusually long processing times for specific tasks. The insights gleaned from the scatterplot are invaluable for guiding teams towards targeted improvements, enabling them to make informed decisions about where to focus their efforts to optimise the workflow.
This, in turn, leads to a more efficient, predictable, and effective process, thereby enhancing the studio’s overall productivity and responsiveness.
This scatterplot typically displays the following information:
Individual Work Items: Each point on the scatterplot represents a single work item.
Cycle Time: The vertical axis typically represents the cycle time for each work item. Cycle time is the total time taken to complete a work item, usually measured from when work begins on the item until it’s finished.
Completion Date: The horizontal axis usually represents the completion date of each work item.
Trends and Patterns: This graph plots individual work items, allowing you to identify trends and patterns in cycle times over a certain period.
Variability in Cycle Time: The scatter of points helps explain cycle time variability. A wide scatter indicates high variability, whereas a narrow scatter suggests more predictability.
Outliers: The plot can highlight outliers and work items that took significantly longer or less time than the majority.
Guidelines or SLAs: Some scatterplots also include horizontal lines representing certain service level agreements (SLAs) or target cycle times, making it easier to see how many items met or exceeded these expectations.
I rely on Cycle Time Scatterplots to right-sizing work. They remove guesswork and bias, keeping my team focused on facts instead of opinions. Too often, teams rely on estimates based on gut feeling, which leads to unrealistic commitments and frustration when things take longer than expected.
Actual team data always beats guesswork. The scatterplot shows precisely how long work takes, clearly showing actual cycle times. Instead of debating how long something should take, we look at how long similar work took in the past. This builds confidence in planning and removes the need for time-consuming estimation meetings.
I track the 85th percentile duration—it covers most tasks while allowing for natural variation. We plan to complete most work within a realistic timeframe while accounting for the occasional delay. The result? A built-in buffer that absorbs uncertainty without inflating estimates. It keeps delivery predictable, helps us set expectations, and ensures we don’t overload the team with unrealistic deadlines.
Work Item Age- Ageing Work-In-Progress Report:
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An Ageing Work In Progress (WIP) report is a critical monitoring tool focused on managing and tracking the age of items in progress within a workflow. This report highlights how long each item has been in the workflow since it was started, providing clear visibility on the work items’ duration in various process stages. Its primary utility is identifying ageing work items beyond a predetermined or expected time frame. By flagging these items, the report brings attention to work that may encounter difficulties or delays, which could be symptomatic of deeper issues within the workflow. This insight is precious for Producers in a studio setting, as it allows for timely intervention and resolution of problems that could otherwise lead to significant project delays or quality issues.
From an operational standpoint, the Ageing WIP report is instrumental in maintaining the health and efficiency of a workflow. It is a preventive measure against task stagnation, ensuring a continuous and smooth workflow. When work items are identified as ageing or delayed, they prompt a review and potentially an adjustment of the workflow or the allocation of resources.
This proactive approach to managing work in progress is essential not only for maintaining pace and efficiency but also for enhancing the overall effectiveness of the team or studio. By ensuring that potential problems are identified and addressed promptly, the Ageing WIP report plays a crucial role in fostering a culture of continuous improvement and efficiency in the workflow, which is central to optimising value delivery.
Key features of an Ageing WIP report include:
List of Work Items: It displays all the items in progress.
Age of Each Item: The report’s primary focus is to show the age of each work item, typically measured from the time work started on the item. Age is often displayed in days.
Thresholds or Limits: The report may highlight items that exceed certain age thresholds, which are set based on expected cycle times or service level agreements (SLAs).
Status or Stage: Along with age, the report might show each work item’s current stage or status in the workflow, providing context for its age.
Visual Indicators: Ageing WIP reports often use visual cues like colour coding to quickly draw attention to ageing items beyond acceptable limits.
Prioritisation for Action: By highlighting older items, the report helps teams prioritise efforts to unblock or expedite these items, ensuring a smoother and more efficient workflow.
Trend Analysis: These reports can also be used to analyze trends over time, helping to identify patterns or recurrent issues in the workflow.
When I joined a new team, the Ageing Work-In-Progress report told me a lot. If old tickets were piling up, the team was either overcommitting or stuck on blockers. Lots of ageing work usually meant unclear priorities or weak pull discipline. If work dragged past typical cycle times, it signalled unpredictable flow and shaky forecasting. Stalled tickets often pointed to handoff delays, ownership issues, or workflow gaps.
I always recommend using the Ageing Work-In-Progress report in daily standups. It keeps the team focused on finishing work instead of just starting more. If something is stuck, it forces a conversation about why. Patterns emerge fast—whether it’s a recurring blocker, unclear ownership, or work that’s just too big. Fixing these issues early stops them from becoming bigger problems.
Work-inProgress- WIP Run-Chart Report:
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A Work-in-Progress (WIP) Run Chart functions as a vital graph meticulously tracking the quantity of work in progress over a given timeline. By plotting the amount of WIP against time, this chart illuminates fluctuations in the workflow, thereby providing a transparent view of how WIP levels change and evolve.
The ability to see these variations over time is crucial for Producers in a studio, as it aids in pinpointing the periods of high or low workflow efficiency. This visual representation is particularly beneficial for identifying patterns, such as cyclical increases in WIP, which might correlate with specific phases of a project or external factors impacting the team’s output. The WIP Run Chart, therefore, not only serves as a record of what has happened in the past but also offers clues about potential future trends in the workflow.
The utility of the WIP Run Chart extends to its role as a practical tool for monitoring and managing workflow efficiency. Providing a clear and ongoing picture of WIP enables teams to make informed decisions to maintain a balanced and sustainable pace of work. This is crucial in avoiding burnout and ensuring consistent quality and productivity.
Furthermore, the chart is instrumental in identifying and addressing workflow bottlenecks. When WIP levels consistently rise, it often signals congestion at specific points in the process, necessitating intervention. By leveraging the insights gained from the WIP Run Chart, teams and studios can implement targeted improvements, refine their processes, and enhance overall efficiency, ultimately leading to more effective and streamlined operations.
Critical aspects of a WIP Run Chart include:
Period: The chart's horizontal axis represents time, showing the progression of days, weeks, or sprints.
Work In Progress: The vertical axis represents the number of work items in progress at any given time.
Data Points: Each point on the chart indicates the total WIP count at a specific time interval (daily, weekly, etc.).
Trend Lines: Connecting the data points creates a trend line that shows how the WIP level has fluctuated over time.
WIP Limits: The chart may include horizontal lines indicating the upper and lower WIP limits. These limits are part of the team’s or studio’s workflow policies to ensure a balanced and sustainable workload.
Analysis of Trends: By examining the WIP Run Chart, teams can identify patterns, such as consistent overloading of WIP or periods of low activity. This insight helps manage workload, identify bottlenecks, and improve process efficiency.
Correlation with Other Events: Teams often use the WIP Run Chart to understand the impact of other events, such as changes in team composition, workflow adjustments, or external factors, on workflow efficiency.
A mobile game team was struggling with inconsistent delivery. Some sprints felt overloaded, while others were oddly quiet. Using a WIP Run Chart, I tracked work-in-progress levels over several weeks. The chart revealed a pattern—WIP spiked just before significant milestone reviews and then dropped sharply after. This showed that work was piling up, waiting for stakeholder approval, creating bottlenecks.
With this insight, we changed the review process to spread approvals more evenly. The WIP Run Chart helped us confirm the fix worked, as the spikes smoothed out over time. This led to steadier progress, fewer last-minute crunches, and a more predictable delivery pace.
Throughput Run Chart:
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A Throughput Run Chart is an essential visual tool for tracking and analysing the volume of work completed over a designated period. Plotting the number of items completed against time provides a clear and immediate visual representation of a team’s or studio’s productivity.
This chart is especially valuable for identifying patterns or trends in throughput, such as increased or decreased productivity periods. Such insights are critical for understanding the team’s capacity and efficiency over time. It enables Producers to recognise consistent performance levels and spot anomalies or variations that might indicate underlying issues or opportunities for process improvement.
The Throughput Run Chart becomes an indispensable tool in Agile and Kanban environments, where continuous improvement is a core principle. It offers a transparent view of the team’s output, which is crucial for informed decision-making and process optimisation. By regularly reviewing this chart, Producers can adjust workflows, resource allocations, and strategies to enhance efficiency.
Furthermore, the data gathered in a Throughput Run Chart can significantly improve forecasting accuracy. By understanding the historical throughput, studios can predict future performance with excellent reliability, aiding in planning and setting realistic goals. This ongoing measurement, analysis, and adaptation cycle, facilitated by the Throughput Run Chart, is central to maintaining and enhancing productivity and efficiency in a Kanban-oriented workflow.
Period: The chart's horizontal axis represents time, which can be days, weeks, sprints, or any other relevant time interval.
Throughput Count: The vertical axis represents the work items completed in each time interval. This count is known as ‘throughput’.
Data Points: Each point on the chart indicates the throughput for a specific time interval. For instance, if the interval is a week, each point shows the number of items completed that week.
Trend Line: The data points are connected to form a line, illustrating the trend of work completion over time.
Variability in Throughput: The chart helps to visualise the variability in throughput. Consistent throughput suggests a stable process, while significant variability may indicate issues or inconsistencies in the workflow.
Capacity Planning and Predictability: By analysing the throughput over time, teams can better understand their capacity for completing work, which aids in planning and forecasting future work.
Correlation with Other Metrics: Teams often review the Throughput Run Chart with metrics such as Cycle Time or Work In Progress to comprehensively view their workflow efficiency and effectiveness.
Insight into Process Improvements: Regular throughput monitoring can highlight the impact of process changes, enabling teams to assess the efficacy of different strategies and practices they implement.
A live ops team for a mobile game struggled with unpredictable update cycles. Some weeks, they pushed multiple fixes and new content, while others saw almost nothing get released. This inconsistency made planning difficult.
I introduced a Throughput Run Chart to track completed work over time. The chart quickly revealed that throughput dipped whenever the team tackled large, complex tasks—often because work wasn’t broken down effectively. It also showed that throughput surged after bug-fixing sprints, confirming that unresolved issues were clogging progress.
With this insight, we adjusted our backlog refinement process to ensure tasks were more evenly sized. We also set aside dedicated time to fix bugs earlier, preventing them from piling up. Over time, the chart showed a more consistent throughput, leading to smoother updates and better predictability in our release schedule.
Key Takeaways:
In conclusion, the essence of this comprehensive exploration is to shift the focus from simply overseeing workers to a deeper understanding and monitoring of the work itself. This perspective is crucial in today’s evolving work environment, where traditional supervision methods are increasingly questioned, and the effectiveness of Agile methodologies is under scrutiny.
The key takeaway is the significance of visualising work through methods like Kanban Flow. This approach provides a clear overview of progress and bottlenecks and balances demands with capacity, fostering a more responsive and efficient team dynamic.
Digging into specific Agile metrics, we have uncovered the profound impact of tools such as the Cycle Time Scatterplot, Ageing Work-in-Progress Report, Work-in-Progress Run Chart, and Throughput Run Chart.
The underlying message is clear: By shifting our focus from scrutinising workers to understanding the work and harnessing the power of these Agile tools, we can create more efficient, responsive, and agile teams. This approach enhances productivity and fosters a culture of continuous improvement and efficiency.
Daniel S. Vacanti's “Actionable Agile Metrics for Predictability: An Introduction” is essential for those seeking a deeper understanding and practical application of these concepts. It provides the foundational knowledge and insights to effectively implement these metrics and tools in workflows, empowering teams to deliver better results more harmoniously and efficiently.
Also, take ActionableAgile software for a test drive with their free demo on various platforms or standalone SaaS applications.