Have uncertainly about committing to deadlines? Trouble being predictable over time on project planning and delivery?
Using Kanban reports, Zenhub gives teams insights that help answer questions around time to delivery and how projects are actually flowing from start to finish.
How throughput and cycle time help teams become more predictable
Regardless of how your team organizes work, and independent of the project management philosophies you deploy, throughput and cycle time are two key metrics any team can use to become more predictable.
Predictability improves productivity by giving insight into not just what people wish they can accomplish, but what they can actually accomplish over set intervals of time. Here's more on throughput and cycle/lead time:
- Throughput (discovered via the Cumulative Flow Diagram): As Issues flow across the Board, Zenhub's Cumulative Flow Diagram is used to visualize Issue throughput. Teams track not only how much work is accumulating within each pipeline across a set date range, but also helps shed light on bottlenecks and areas for process improvements.
We share more on reading the Diagram here and have sample Diagrams here and what they mean if you notice similar trends on yours. - Cycle and lead time (discovered via the Control chart): Cycle time and lead time give you how long Issues take from start to finish. Whether your team is using Estimation or not, this chart can help predict how quickly upcoming Issues will be closed, as well identify bottlenecks and efficiencies in each stage of your process.
We share more on reading the Control chart here.
What does throughput and cycle/lead time tell me?
Both reports help uncover process issues and identify abnormalities in your team's flow. By visualizing the flow of Issues, and pairing it with how fast Issues get closed you get a comprehensive overview of how predictable you are at completing work.
Throughput lets you visualize the flow of work across your workflow stages to understand the state of work at any point in time. This allows teams to visualize where work is staking up, a bottleneck, to spark conversation on what might be done to speed up delivery pace.
Cycle and lead time give the specific data to understand what that actual time delivery was, per Issue, and in aggregate. These metrics allow teams to not just guess how long a project will take but rather, more accurately compare similar past work to estimate if you’re on track with your planned work.
What you want to see across both metrics
When cycle times are going down and throughput going up, this is good. Usually, this is due to a result of changing how you move Issues across your workflow.
Typically, teams who invest in improving the build process, or up-front planning process remove bottlenecks later in the workflow that surface due to incomplete feature specs, test cases, or otherwise "surprises" that result from bad up-front investment in planning.
The goal is more about consistency. While you want to have the fastest cycle time and highest throughput, aim to maintain a steady flow of work and steady average pace of delivery.
Reading the Control chart and Cumulative Flow Diagram together
To help you interpret your own Kanban reports, we've provided a few examples below and how insights from one can inform insights from the other.
An example of reviewing the past 3 months
- Between Nov 18 and Dec 2nd there was multiple flat periods, and relatively low volumes of work moving to closed. Paired with the the bloating of the standard deviation on the control chart during this same time frame, together these indicate:
- You're not closing work and moving Issues from your "in progress" starting point as work is actually being worked on.
- You're not completing work as quickly as you once were, closing them within a predictable time frame.
- Between Dec 30th and Jan 20th, both graphs indicate that the flow of delivery is getting back on track.
- You'll notice a large amount of issues moving into the Live and Closed pipelines in the Cumulative Flow (drastic step up) with a narrowing standard deviation on the Control Chart.
- Together, this mean that your throughput is increasing, and the median average time it takes to move work through to complete is shrinking . You want to notice these trends, as it's a strong indicator your team is getting more predictable with time in flight.
Indication your pace of delivery is declining
- From Sept 30th to Early October there's a drastically bloating standard deviation on the Control Chart with flat lines on the Cumulative Flow. This could indicate that the team is taking longer to move Issues across the workflow, perhaps due to estimation issues, more complex work, or less resources deployed.
- There's a cluster of Issues around Oct 23rd being closed, with a drastic spike up in the Cumulative Flow. On the Control Chart, there's also a clusters of Issues being closed in this timeframe. This could indicate the team doesn't have as good closing habits, creating Board hygiene Issues. Instead, you'll want to see a continuous step up on the Cumulative Flow, with more spread-out closed Issue dots on the Control chart.
Other common scenarios you might encounter
- Big spikes in your throughput, with a lot of outliers in your cycle time. This might indicate that there's consistently a lot of stale issues on the Board. Ensure you're grooming the Board consistently to avoid data spikes.
- Ideally you want to see the trend line on your cycle time chart going down, but more importantly you don’t want to see it going up. Shorter cycle times suggests you're delivering value quickly and more predictable and able to respond quickly to change.
Avoid reviewing either metric in isolation
Looking at just one metric can be misleading if considered in isolation. If you just look at throughput, seeing consistent bands (meaning no one area is a bottleneck), but don't consider pace of delivery, you could be moving slowly, but not experiencing bottlenecks.
On the flip side, if cycle time going down, this is a great indicator the Issues being closed are moving to a complete state in a good delivery pace, but if you’re only delivering one piece of work a month meaning your throughput isn't consistent, you're not balancing delivery output with speed.
Maintain a balance of health pace of delivery, with increased throughput to avoid pitfalls of analyzing work in isolation.