For QA and Engineering teams, improving delivery speed starts with understanding how work actually moves through the workflow. On the Azure DevOps platform, teams use delivery metrics and agile KPIs to track progress. However, high-level numbers alone often do not explain why delivery slows down.
Time in State reporting in an Azure DevOps tool helps teams go deeper by showing how long each work item spends in every workflow state – from creation to completion.
Time in State as a Core Delivery Metric
Traditional delivery metrics such as cycle time or throughput show outcomes, but not the process behind them. Time in State complements these metrics by breaking down delivery time into concrete workflow stages.
In the report shown above, each work item is displayed with:
time spent in New
active work in In Progress
validation time in In QA
waiting time in Approved or Committed
total end-to-end duration
This turns Time in State into a practical agile KPI that teams can use daily.
Understanding On-Time Delivery Through Workflow Data
The KPI for on-time delivery depends on how quickly teams develop features. It also relies on how well work moves between stages.
By analyzing Time in State data in Azure DevOps, QA and Engineering teams can see:
whether work waits too long before being picked up
how much time is consumed by QA and validation
which tasks move smoothly and which stall
This visibility helps teams understand why planned delivery dates are missed – without relying on assumptions.
QA and Engineering Insights at Task Level
Looking at the table, it becomes clear that different tasks follow very different paths:
Some items spend minimal time In Progress but accumulate days in In QA
Others remain New for extended periods before any work begins
Even design and UI tasks show significant waiting time outside development
Because each task is visible individually, teams can compare patterns across features, bugs, and QA-related work.
Using Azure DevOps Data for Agile KPI Conversations
The Azure DevOps platform already captures detailed workflow data. Time in State reporting turns that raw data into actionable insights for agile KPI tracking.
Instead of abstract discussions about “slow delivery,” teams can point to:
specific states where time accumulates
concrete examples of work items with long total duration
clear differences between active work and waiting time
This makes delivery metrics easier to interpret and easier to act on.
From Visibility to Better Delivery Decisions
When QA and Engineering teams understand how time is distributed across workflow states, they gain a clearer picture of how work actually flows through the system. Instead of relying on assumptions or isolated metrics, teams can see where delays form and how they impact delivery.
This visibility allows teams to:
adjust team capacity based on real bottlenecks rather than perceived ones
improve coordination between development and QA by identifying slow handoffs
make informed process changes that support on-time delivery
With this shared understanding, Time in State becomes a common reference point for discussions and decisions — not just another report, but a practical tool for improving delivery.
Try Time in State in Azure DevOps
If you want to better understand your delivery metrics and see where work actually spends time across your workflow, you can try Time in State reporting for Azure DevOps.
It helps QA and Engineering teams analyze real workflow data, identify delays, and make delivery metrics more transparent – directly on the Azure DevOps platform.
👉 Download and start using Time in State for Azure DevOps to explore how your work items move through each stage.
Questions or Feedback?
If you have questions about Time in State, delivery metrics, or how to use this data as an agile KPI in your team, feel free to reach out.
📩 Contact us at:
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We’ll be happy to help.
