Last week, we explored how to use the Process Improvement Dashboard to monitor and respond to cycle time signals. Now, let’s take it a step further by looking at throughput—a key flow metric that shows the rate at which tasks are completed over time.
I’m going to show you how to use throughput signals to see if your team is performing within their capacity or if there are shifts that need attention.
By understanding these signals—whether low, stable, or high—you can make data-driven decisions that preserve the efficiency of your process.
How to Determine Your Throughput Benchmarks
To begin, the Process Improvement Dashboard will analyze your data and establish the range of throughput variation that defines your process as stable.
This range represents the performance benchmarks for your team, accounting for natural fluctuations. It represents your capacity to deliver results.
For example, this team’s threshold for normal throughput ranges from 3 to 8 tasks per day.
We calculate your Natural Process Limits to create clear boundaries around your data. These limits make it easy to spot when your process is simply fluctuating or when there’s a real issue that needs your attention.
With Natural Process Limits in place, you’ll know exactly when your delivery process is becoming unstable and can act before it leads to delays.
What Are Rare Events and How to Track Them
In some cases, throughput may be so low that the daily average falls below 1. This situation, often referred to as a rare event, occurs when tasks aren’t completed every day, causing multiple days with zero throughput.
In that case, we no longer talk about daily throughput; we’ll now start measuring your performance in terms of a daily completion rate. Here’s how the Process Improvement Dashboard handles these cases:
Imagine your team doesn’t complete any tasks until Day 5. Their daily completion rate at that point would be calculated as ⅕ = 0.2, indicating one task was completed over five days.
If the next task is completed two days later (on Day 7), the rate for that event would be
½ = 0.5, meaning that the next event occurred 2 days after the first one.
Tracking the time between rare events helps to identify patterns in task completion, making it easier to manage low-throughput periods without losing sight of overall productivity.
Here’s what the dataset for rare events would look like:
Send me a DM on LinkedIn if you’re interested in exploring that spreadsheet, and I’ll share it with you!
How to Interpret Throughput Signals Using the Process Improvement Dashboard
The Process Improvement Dashboard categorizes throughput into Low, Normal, and High signals, each relative to your defined benchmark range. Here’s how to read these signals:
Low Throughput Signal
A Low Throughput Signal suggests that your productivity has dropped below the expected range, either due to a decrease in daily task completions or an increase in the time between completed tasks.
Each of these scenarios points to potential areas for improvement.
When daily throughput falls below the lower limit of your benchmark range, it indicates that fewer tasks are being completed per day than expected.
It’s important to investigate and identify the source of the delay. The immediate action here is to investigate tasks that were just about done on that day and see what might have held them up. The goal is to restore your daily throughput to the stable range.
When tasks aren’t completed every day, the concept of daily completion rate becomes relevant.
In this case, a low completion rate signal means the intervals between completed tasks are longer than usual.
Here, the action is to examine the time gaps between task completions to understand whether there are workflow issues that need to be addressed.
Stable Throughput Signal
A Stable Throughput Signal indicates that your productivity is consistently within the expected range, showing a well-balanced delivery system.
This stable performance can be observed in both the daily throughput and the daily completion rate, depending on your team’s task completion patterns.
Each of these scenarios provides valuable insights into your team’s capacity and efficiency.
When daily throughput remains within the benchmark range, it means your team is completing tasks at a steady pace that aligns with their expected capacity. Your team is performing well, and their workload is manageable.
In this situation, stable throughput provides a foundation for reliable planning and goal-setting. If your throughput is stable, your forecasts will be highly reliable.
If you’re aiming to improve throughput further, consider reviewing tasks that are nearly complete and checking for minor inefficiencies that could optimize the process.
When tasks aren’t completed every day, the concept of daily completion rate becomes relevant here too.
In this case, a stable completion rate signal means that the intervals between completed tasks are consistent and within the expected range. This indicates that, while tasks may not finish every day, the time taken to complete them is steady.
Here, the focus should be on maintaining the current process, as stable intervals show that your process is efficient.
Keep an eye out for any opportunities to refine your process further while preserving the predictability of task completion.
High Throughput Signal
A High Throughput Signal indicates that your productivity has exceeded the expected range, either due to an increase in daily task completions or a faster-than-usual rate of task completions.
Each of these scenarios provides insights into possible efficiency gains, but it’s essential to determine if the increased output is sustainable.
When daily throughput surpasses the upper limit of your benchmark range, it means your team is completing more tasks per day than anticipated. This could be a positive sign of improved efficiency or simply a temporary spike in productivity. Either way, it’s a sign that your process is no longer predictable.
In this case, it’s beneficial to review the tasks completed during the high-throughput day to identify what contributed to the boost.
Understanding whether this increase resulted from process improvement initiatives, handling smaller tasks, or other factors can help you assess if this higher rate can be maintained long-term.
However, make sure that this drastic change in your team’s performance doesn’t come at the expense of the quality of your work.
When tasks aren’t completed every day, a high completion rate signal indicates that the intervals between completed tasks are shorter than usual, showing that tasks are being finished faster than expected.
While this might initially seem like a good thing, a high daily completion rate actually signals a spike that is too sharp to be considered a consistent change in your team’s capacity. This level of fluctuation compromises your ability to make reliable forecasts.
Here, the action is to examine the causes that have led to this faster completion rate. If these improvements are sustainable over time, your performance benchmarks will adjust accordingly.
Whether you’re investigating low-throughput days, keeping things steady, or making the most of high-output times, tracking throughput lets you make smart, proactive moves.
Next week, we’ll continue our deep dive by exploring how to detect signals in WIP and WIP age using the Process Improvement Dashboard. Stay tuned for more data-driven managerial insights!
I hope this guide has been helpful! See you next Thursday, same time and place. Bye for now!
