Introduction
One of the primary ways to fail in implementing your Kanban strategy and not achieve the value you expect is by not looking at the right data. Many teams think they are doing Kanban simply because they have a board with columns. However, without proper metrics and active management, this approach falls short.
The Importance of Proper Data Analysis
To truly benefit from Kanban, you need to go beyond having a simple board. You must leverage the right metrics and actively use the data to drive improvements. Here’s how to avoid common pitfalls:
Metrics like story points, velocity, and burn down charts do not provide actionable insights for improving your workflow.
These metrics often serve more as “vanity metrics” that give a false sense of progress without driving real value.
Work in Progress (WIP): Measure how many items are currently in progress. This helps to manage the flow and ensure that work does not pile up at any stage.
Cycle Time: Track the time it takes for an item to move through the system from start to finish. This provides insight into efficiency and potential bottlenecks.
Throughput: Measure the number of items completed in a given time period. This helps in understanding the capacity of the team.
Work Item Age: Monitor how long items have been in progress. This helps to identify items that may be stuck or delayed.
Collecting and Using the Right Data
Most digital tools like JIRA, Azure DevOps, and Trello automatically collect the necessary data. You only need two pieces of information for each work item: the start date/time and the end date/time. Here’s how to use this data effectively:
Taking Action Based on Data
The true power of Kanban comes from using the data to make informed decisions and drive continuous improvement:
Address Blockages:
Identify why items are getting stuck and take steps to remove these blockages.
Optimize Flow:
Use the data to adjust work in progress limits and ensure a smooth flow of work through the system.
Improve Predictability:
Analyze cycle time and throughput to make better forecasts and meet delivery commitments.
Conclusion
Avoiding common mistakes in Kanban involves focusing on the right metrics and actively using the data to drive improvements. By ditching vanity metrics and leveraging key Kanban metrics like WIP, cycle time, throughput, and work item age, you can create a transparent, efficient, and predictable workflow.
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