This video provides an overview of the dashboards available in the Performance Analytics Content
Pack for Essential SAFe, or Scaled Agile Framework, from ServiceNow.
You can skip to these topics from the YouTube description for this video.
To analyze and improve your Essential SAFe software development planning and execution,
you can leverage the Performance Analytics dashboards for Essential SAFe.
So how are these dashboards useful?
They’re broken out by epic and feature,… …current and prior sprint, …
…current and prior program increments, called PIs, …
…Agile Release Train, called ART… …and team.
Widgets display key performance indicators, called KPIs, so you can see how work is progressing.
You can click on a widget to view more details.
Interactive charts display past data, …
…and forecast trends, where applicable.
You can drill down on data points for more information.
You can also hide and display lines on the chart, called series, by clicking on them
in the legend.
To start using these dashboards, you install the Performance Analytics Content Pack for
Essential SAFe in your instance.
If you’re upgrading the PA Content Pack for the Essential SAFe application from version
1.0.2 or earlier, make sure you install the dashboards using the PA Solution Library once
your upgrade is complete so you can access the latest reports.
Then you set up the SAFe daily data collection scheduled job to begin collecting scores on
new data.
Keep in mind that the job can't collect historical data.
It can only start collecting data from the day on which you set up the collection job.
To access the dashboards, navigate to Scaled Agile Framework and click Dashboards.
Now let’s take a closer look at the types of charts you’ll see in the dashboards.
First up are burndown charts, which are available for PIs and sprints.
The point at the beginning of the chart shows how many story points we need to complete,
or “burn down,” on the first day of the sprint or PI.
The Ideal Burndown series shows us how the completed work should be trending to finish
by the last day in the timebox.
Scope displays the amount of work planned for the sprint or PI.
This may vary over time as work is added or removed.
The Scope Forecast shows how the scope is likely to change in the future, based on the
actual scope changes to date.
Remaining shows us how much work remains to be completed.
And finally, the Remaining Forecast predicts the burndown for future dates, and whether
you can complete the sprint or PI on time.
So burndown charts help you answer these questions:
Has the scope changed?
And if so, what’s the trend?
In our example, the scope is trending slightly upward, but is mostly steady.
What’s an ideal pace of work, and how much work remains?
Here we’re completing the work at a faster rate than the ideal burndown, and this trend
is forecast to continue, so we should finish ahead of schedule.
And finally, is the scope likely to be completed before the end of the timebox?
In our example, we’ll finish ahead of schedule unless the scope increases, the pace of work
declines, or both.
Next up are burnup charts, which are available for epics, sprints, features, and PIs.
Rather than starting with the number of points we need to complete like in a burndown chart,
these charts start at zero points.
They show how the burnup trend of the team’s effort, in completed story points, …
…adds up to the scope, …
…and how it’s projected to change over time.
The point where the scope forecast and the completed forecast meet helps you estimate
when the team could complete the planned work.
So burnup charts help you answer these questions:
Has the scope changed?
And if so, what’s the trend?
How much work is completed, and when is the scope likely to be completed?
Now let’s look at cumulative flow diagrams, which provide more detail about epics, sprints,
and PIs.
They display progress by state: Ready, Work in Progress, Ready for Testing, Testing, and
Completed.
In the PI Cumulative Flow Diagram, we see the state of all of the stories within the
PI between its actual start and end dates.
Cumulative flow diagrams help you answer these questions:
Has the scope changed?
And if so, what’s the trend?
What’s the work in progress at any point, and how is it trending?
What are the cycle times, and are long queues forming?
Next up are cycle time charts, available for features, epics, PIs, teams, and Agile Release
Trains.
Each bubble represents a story, and the distance from the x-axis shows how long that story
took to move from in-progress to completed.
The size of the story bubbles are relative to each other based on their story points.
To get a better view when the bubbles are overlapping or too close together, you can
click and drag over a section to zoom in.
Cycle time charts help you identify outliers that took longer than expected compared to
their estimated point size.
Then you can create action items to help reduce their cycle time.
So cycle time charts help you answer these questions:
Do we have outliers that took longer than expected?
And what’s the typical time it takes to complete work?
Now let’s switch our focus to the SAFe Team Dashboard, which provides insight into work
item progress.
It shows active stories by state, the amount of time they were in that state, and the average
cycle time per state.
The Sprint Performance tab displays the Velocity by Type chart, which provides insight into
the way your team’s velocity changes over time.
It also compares the team's strategic workload with operational or other types of workload.
In our example, the team’s velocity has decreased over time.
The Sprint Performance tab also displays the Velocity History chart, which provides insight
into the overall velocity of the team for up to the past 10 sprints.
The chart shows us three things for each sprint: What the team determined their capacity to
be at the beginning, … ...the amount of work the team committed to
at the beginning, … ...and the amount of work the team completed
by the end.
The Velocity History chart helps you answer these questions:
How has the team historically delivered?
Is the team achieving a stable, predictable velocity?
Is the team meeting commitments?
And finally, what is the likely capacity for the team in the next sprint?
Also on the Sprint Performance tab, the Sprint Variance chart helps you to analyze the percentage
variance of the team compared to the capacity and committed points, for up to the past 10
sprints.
Over time, if the variances between what a team delivers, what they expect their capacity
to be, and what they commit to grow smaller, then the team is becoming more predictable.
So the Sprint Variance chart helps you answer these questions:
Is the team under- or over- stating their capacity?
Is the team under- or over- committing to sprints?
And how are these variances trending over time?
Let’s look at the last type of chart, program predictability for ART and teams.
It allows you to track the historical performance of the ART or team on achieving their program
objectives.
The series in the ART report show the performance of each team of the ART,
…as well as the ART as a whole.
You can see which teams are consistently achieving between 80 and 100 percent of the set PI objectives,
which is the ideal range according to SAFe.
The Program Predictability chart for teams tracks the historical performance of the team
on achieving their program objectives.
The series in this report show the performance of the team, and the ART that this team belongs
to, over multiple PIs.
For more information, see our product documentation, knowledge base, or podcast.
Or ask a question in the ServiceNow Community.