Flow Metrics in Kanban Explained with a Banana Peel w/ Benji Huser-Berta

Описание: Are you considering learning more about Kanban? Sign up for my Applying Professional Kanban course: https://mariachec.substack.com/p/kanb...

Grab all the links from the episode here:
👉 https://mariachec.substack.com/p/visu...
#Agile #Kanban #flowmetrics #agilecoaching

In this Agile State of Mind episode, Maria Chec and Benji Huser-Berta delve into the intricacies of flow metrics in Kanban.

We emphasize the importance of probabilistic forecasting over traditional estimation methods.

We discuss how to visualize metrics effectively, the significance of cycle time and throughput, and the role of service level expectations (SLE) in improving predictability.

The conversation also highlights the importance of work item age and how it can impact team performance and system health. The episode concludes with a call to action for teams to embrace these metrics to enhance their workflow and decision-making processes.

Key takeaways:
Estimations are often a waste of time in Agile.
Probabilistic forecasting offers a more accurate prediction method.
Cycle time is a crucial metric for understanding team performance.
Using percentiles can help teams gauge predictability effectively.
Service Level Expectations (SLE) provide a benchmark for delivery times.
Work item age is a key indicator of system health.
Improving flow metrics can lead to better team performance.
Visualizing metrics helps teams identify patterns and areas for improvement.

Follow me on Social Media:
Substack: https://mariachec.substack.com/
LinkedIn:   / mariachec  
Instagram:   / agilestateofmind  

Chapters
00:00 Introduction to Flowmetrics in Kanban
02:49 Understanding Probabilistic Forecasting
05:10 Transitioning from Scrum to Kanban
07:47 The Importance of Flow Metrics
10:25 Visualizing Cycle Time and Estimations
13:03 Using Cycle Time for Predictability
15:53 Service Level Expectations and Their Impact
18:00 Analyzing Risks with Percentiles
20:59 Final Thoughts on Metrics and Team Dynamics
23:18 Visualizing Data for Better Insights
25:11 Understanding Service Level Expectations (SLE)
27:06 Improving Cycle Time and Throughput
30:47 Analyzing Patterns in Sprint Performance
31:24 The Importance of System Health
34:03 Using Metrics for Predictability
35:48 The Dangers of Averages in Estimation
36:15 Work Item Age: A Key Flow Metric
40:49 Actionable Discussions in Daily Standups
43:47 Experimenting with Metrics for Improvement

00:00 Introduction to Flowmetrics in Kanban
02:49 Understanding Probabilistic Forecasting
05:10 Transitioning from Scrum to Kanban
07:47 The Importance of Flow Metrics
10:25 Visualizing Cycle Time and Estimations
13:03 Using Cycle Time for Predictability
15:53 Service Level Expectations and Their Impact
18:00 Analyzing Risks with Percentiles
20:59 Final Thoughts on Metrics and Team Dynamics
23:18 Visualizing Data for Better Insights
25:11 Understanding Service Level Expectations (SLE)
27:06 Improving Cycle Time and Throughput
30:47 Analyzing Patterns in Sprint Performance
31:24 The Importance of System Health
34:03 Using Metrics for Predictability
35:48 The Dangers of Averages in Estimation
36:15 Work Item Age: A Key Flow Metric
40:49 Actionable Discussions in Daily Standups
43:47 Experimenting with Metrics for Improvement