Time frame

Choose how far back you want to go to capture key moments - all the data displayed on the chart will be taken according to this selection.

Last: analyze recent trends by selecting periods like days, weeks, months, or quarters.
Sprints are available only for Scrum boards.
Since: start the data display on a specific date is ideal for long-term analysis.
Fixed: specify start and end dates to focus on a defined time period.

The selected time frame is a common setting and affects all of the Cycle Time Charts: Cycle Time Histogram, Time in Status Cycle Time, and Cycle Time Trend Charts.

Grouping options

Aggregate data into logical groups to simplify complex information, depending on your project management style. This option helps to simplify complex data by categorizing it into logical intervals.

Grouping can be configured as daily, weekly, bi-weekly, monthly, quarterly, or by sprint, depending on the Data Source units.

Exception: the Cycle Time Histogram Chart doesn’t offer Grouping options because the chart groups issues based on their nominal value of the cycle or lead time. As the chart already organizes issues, adding a grouping option by calendar units (such as weeks or sprints) isn't necessary or helpful.

Units

Display your data in the units that make the most sense — hours, days, weeks, bi-weeks or months. Adapt your view to match your project’s pacing.

Exceptions: the Time In Status Cycle Time Chart chart doesn’t have “Unit” options because it automatically adjusts the Y-axis based on the metrics, showing time in hours, days, or weeks as needed.

Statistics

Gain insights with statistics like Mode, Mean, Median, 50%, 85%, or a custom percentile directly on your chart.

Available options:

Mode: the value that appears most frequently in the data set.
Mean: the average value of the data set
Median, 50%: the middle value, where 50% of the data points are below and 50% are above.
85%: the value below which 85% of the data points fall.
Custom statistic % value: set your own value.

By default, we enable the most relevant options: Median,50% and 85%.

Use checkboxes to toggle these stats on or off.

Exceptions: the Time In Status Cycle Time Chart chart doesn't include statistics, as this chart focuses on the distribution of time across different statuses rather than specific statistical measures.

Highlights

Highlight critical areas on your Cycle Time Histogram Chart to draw attention to important data ranges or thresholds. Keep your team’s focus where it matters most.

By default, we highlight the 50-85% percentiles as the widely used spread and the 95%+ percentiles as the outlayers.

Add highlights, choose the range and color to customize the look.

Highlighting the calendar’s units is possible in relation to the selected “Units” option. It is impossible to see the highlights for hours if “Days” is selected as the “Units” option.

Exceptions:

The Time In Status Cycle Time Chart doesn’t support highlights because the chart already stacks data by status, making additional highlights redundant.
Highlights are not as useful for the Cycle Time Trend Сhart because it emphasizes overall trends and progress over time, rather than isolated data points. The Cycle Time Trend Chart uses Targets as an analog to highlights, focusing on long-term goals rather than specific data ranges.

Highlights and targets.gif

Targets

Mark your goals directly on the chart with target lines. Customize their appearance to keep your objectives clear and in view.

Customize each target’s name, value, and color to match your objectives.

Exception:

Targets are exclusive to the Cycle Time Trend Chart, replacing Highlights from the Cycle Time Histogram Chart. They allow you to set specific benchmarks, offering a clear way to track long-term goals and trends. This approach fits trend analysis better than highlighting specific data ranges.
The Time in Status Cycle Time Chart lacks Targets because it focuses on analyzing how long tasks stay in each status, not on tracking progress toward long-term goals, which makes targets irelevant.

Distribution type

Understand the variability of your process with distribution types. See where your process shines and where it might stumble.

The system automatically calculates and displays the distribution type based on your data. This helps you understand the predictability and characterize the delivery process.

We distinguish the next distribution types:

Right-Skewed Thin-Tailed Distribution

Insight: The process is non-linear but relatively robust, with a thin-tailed distribution. This indicates that while there are some delays, they are not extreme, leading to decent predictability with lower risk of significant delays.
Recommendation: Continue monitoring and optimizing processes to ensure delays remain minimal. Focus on maintaining this thin tail by ensuring that minor issues are resolved quickly and do not escalate. Regular retrospective sessions and minor process adjustments can help keep the workflow smooth and predictable.

Right-Skewed Fat-Tailed Distribution

Insight: The process is non-linear and fragile, with a fat-tailed distribution. This indicates poor predictability, as a few tasks are taking much longer than expected, significantly impacting overall cycle/lead times and increasing risk.
Recommendation: Identify the root causes of these significant delays, such as bottlenecks or resource constraints, and address them directly. Implement strategies like backlog refinement, better resource allocation, and continuous monitoring to reduce the length and impact of the tail, thereby improving predictability and overall process performance.

Left-Skewed Thin-Tailed Distribution

Insight: The process is slightly non-linear but robust, with a thin-tailed distribution. Most tasks are completed in a reasonable time, with minimal risk of delays, though some early stages might cause slight delays that are quickly resolved.
Recommendation: Focus on improving the efficiency of early stages to prevent any initial delays from impacting the flow. By refining the early processes and maintaining a strong definition of ready, you can ensure that tasks flow smoothly and consistently, keeping the tail thin and predictability high.

Left-Skewed Fat-Tailed Distribution

Insight: The process is non-linear and fragile, with a fat-tailed distribution. Early-stage delays lead to unpredictability, with some tasks experiencing significantly longer lead times, increasing risk.
Recommendation: Streamline and strengthen the initial stages of the workflow by improving collaboration, refining the definition of ready, and ensuring clear communication and requirements from the start. Addressing these early delays is key to preventing them from extending the tail, which will enhance overall process predictability.

Gaussian (Thin-Tailed) Distribution

Insight: The process is linear and robust, with a thin-tailed distribution, indicating high predictability and stability. Most tasks are completed within a narrow timeframe, suggesting a well-functioning process with minimal risk of delays.
Recommendation: Maintain the current level of process control and predictability by continuing regular retrospectives and minor optimizations. Keep focusing on continuous improvement to ensure the process remains robust and capable of handling any minor variations without significant impact on cycle/lead times.