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.