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Flow Metrics: Three Anti-Patterns to Avoid

Naomi LuriePosted by

Value stream management is a growing practice in software delivery organizations of large scale enterprises and government agencies. Flow Metrics are a major pillar of how we measure improvement in value streams. 

As organizations begin to adopt Flow Metrics, our natural tendencies emerge to massage the newfound visibility to make the metrics “look good”. This is by no means a unique phenomenon: Any marketing expert could tell you, for example, how Google Analytics can paint a very different picture depending on the selected date range. 

That said, these anti-patterns would be wise to avoid, as they prevent us from using the data to improve our daily work. In this blog, we’ll review a few of the common anti-patterns about which you you should be aware. 

Get the full list with our humorous take on anti-patterns in the 2022 Tasktop Desktop Calendar: 12 Tricks to Good-Looking Flow Metrics

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Chop up the value stream

In his groundbreaking book Project to Product, Dr. Mik Kersten writes, “Correlating the Flow Metrics with business results provides us with a dashboard that connects the work being done in each value stream with the business results that the value stream is producing … if a part of the value stream is excluded, the flow metrics will not be correct; nor will they be meaningful if the value stream and product boundaries, as well as value metrics for each, are not accurately specified.”  

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Flow Metrics anti-pattern: Excluding part of the value stream

When measuring a small segment of the value stream, which is typically made up of one specialization (e.g., engineering), flow can look pretty good. It effectively lops off the time a request, defect or business idea spent making its way to this team. And in this example, it also lops off the time the committed code will spend waiting for release, UAT or business signoff. As such, you will likely create an overly optimistic view of flow and effectively hide the bottlenecks that exist from idea to outcome, which we are so anxious to reveal. 

Tips to avoid this anti-pattern:

  • Make sure to create an expansive view of the value stream, in addition to these smaller team-level views.
  • Group multiple teams together in a product line view to get insights into where flow is the most impeded. This will help you direct attention and resources to the team who needs it most and who may — in some cases — be a dependency for overall feature delivery.  

Delay action and address data hygiene instead

Flow Metrics tell a story about the speed, throughput and efficiency of a value stream. They give a readout of the current state: the rate of value delivery, the distribution of work profiles completed, the load on the value stream and where work is waiting the longest. The data itself is drawn from the work management systems themselves, like Jira, Azure DevOps and ServiceNow.

A common reaction to any new metrics is to question their credibility and in our experience, Flow Metrics are no different. The first impulse is to second-guess the data, and the second impulse is to hit the pause button on the analysis and improvement plan and instead go away for a while to “fix the source data”.

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Flow Metrics anti-pattern: Delaying action due to perceived data hygiene

The drawbacks of delaying action are clear — flow will not get any better if you do nothing. 

For better or worse, the data in your Flow Metrics is the same data you’re seeing in all your other tool-based metrics. True, it’s abstracted and presented in a different way and it emphasizes different things, but it is the same source data. So your assumption should be that the data is good enough. 

For most value streams, the biggest problem is the instability of their value stream and data hygiene is not the culprit. Value streams begin much more work than they can reliably complete which results in low predictability and lots of missed commitments (more on this below). 

Tips to avoid this anti-pattern: 

  • Create a psychologically safe environment to explore, analyze and address Flow Metrics. 
  • Remind people that Flow Metrics are based on the same data used in all your metrics. It’s good enough. 
  • Help value streams address the major trends seen in their Flow Metrics and the emerging insights into bottlenecks and stability. These will likely not be impacted by data cleansing. 

Get the full list with our humorous take on anti-patterns in the 2022 Tasktop Desktop Calendar: 12 Tricks to Good-Looking Flow Metrics calendar cartoon

Click here to claim your free calendar! (U.S. Only)

Be content with the speed of completed work 

Typically, as Flow Metrics are baselined, Flow Time (the time elapsed from when the work is committed until it’s completed) will look pretty good. Perhaps a little longer than industry good practices, but aligned with your expectations. 

Yet upon closer examination of the completed work for which Flow Time is calculated, a very different story emerges. The completed work is mostly urgent, high priority work that is rushed through the value stream at the expense of everything else that’s been started and committed.

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Flow Metrics anti-pattern: Being content with misleading Flow Times

As a result, work you’ve started is shelved, neglected and maybe even forgotten. It grows stale in your WIP, missing deadlines and commitments and diminishing the opportunity to have any measurable impact on outcomes. That work was started for a reason, and now it’s been stopped. 

AI-driven analytics utilize this information to present what is typically a grim prediction for Flow Time. In most cases, should this stale work be picked up and completed, average Flow Time would double, triple or quadruple. Meaning, your true Flow Time is not as rosy as you think. 

The potential for you to improve flow and deliver more value faster indeed exists — if you can stabilize your system! Then you’ll have yourself a Flow Time that is accurate, predictable and a strong basis for informing future commitments. 

Tips to avoid this anti-pattern: 

  • Use insights into your Flow Load (WIP) to stabilize your value stream and take on only as much work as you can complete.
  • While stabilizing, base your commitments on your predicted Flow Time, not your current one (as it is misleading). 
  • Demonstrate to your leaders and stakeholders that reducing the load on the value stream can improve both speed and velocity, and establish thresholds to keep load under control. 

Wait, there’s more!

Anti-patterns are nothing to be ashamed of. They wouldn’t be anti-patterns if we all didn’t fall for them! 

If you’re a change agent involved with the introduction of value stream management and Flow Metrics to your organization, you should be aware and prepared to address these when they come up. 

But no need to be too hard on ourselves! We’ve found that humor helps to diffuse these situations. So, we’ve prepared a 2022 desk calendar of 12 common anti-patterns we’ve seen. We hope this will help you anticipate and combat some of these behaviors so you can keep your transformation on track. Get your personal calendar here (U.S. Only).  

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