“How can we use Kanban metrics to identify the impediments that slow us down and improve our workflow?”

This is a classic question for good reason!

If you’ve been sticking around for a while, I bet you’re the kind of person who’s always looking for opportunities for improvement. And today, I have a few quick wins for you.

There are three very simple things you can do to identify the obstacles that slow you down and streamline your workflow.

Ready to dive in?

3 Tips to Improve Your Workflow Using Kanban Metrics

Today, I’ll share with you strategies that will help you build momentum right away and set you up for success in the long run.

#1 Design Your Board with Purpose

I know this may sound obvious, but I cannot emphasize it enough! You cannot fix a problem if you don’t see it.

You can only make the most of your Kanban metrics and reveal problems if you design your board with that purpose in mind.

Modeling your workflow as a knowledge discovery process is fundamental to continuous improvement.

If you consider your workflow steps as containers for workers, you’re highly likely to hinder your ability to make accurate data-driven decisions and lose opportunities for improvement.

The columns on your board shouldn’t represent a series of handoffs. Instead, they should expose the activities that you take when discovering more knowledge, and use that information to improve your deliverables.

This approach will enable you to reveal the problems in your system, acknowledge them, and then work upon their prompt resolution.

In our Sustainable Predictability digital course, we give you the step-by-step process to design your board with that purpose in mind, so if you’re struggling to make this work, I’d be thrilled to welcome you to the program right away.

#2 Use WIP Average Age as Your Starting Point

In the very beginning, if you’re just getting started with Kanban metrics, the only thing you need to do to identify bottlenecks and optimize your team’s workflow is to track and manage your WIP average age.

That’s it.

It really is that simple.

Let me walk you through why this is and how this approach will enable you to improve your delivery speed without even striving for it.

The average age of WIP and cycle time are essentially the exact same thing, only cycle time is measured against completed tasks, whereas the age of a task is a measure concerning work that’s still in progress.

Your cycle time metric doesn’t take into account your current WIP. Although you might have a very low average cycle time, if your tasks sit and age in the process, and eventually get released, your average cycle time will skyrocket.

This is why it is so important to track your average age of WIP, and regularly compare it against your average cycle time.

Average cycle time

When you make sure that you manage your WIP average age and keep it consistent, you directly affect all other flow metrics: cycle time, throughput, and flow efficiency.

What does it actually mean to manage WIP average age?

It means that the ticket with the highest WIP age is your priority.

It means that your team commits to moving this work item through the process quickly. If it’s blocked, they figure out why. If it was assigned to someone who is currently unavailable or there is a third-party dependency, they jump in and tackle the problem (or escalate it if it’s outside of their control!).

Managing WIP average age means that if the item is more complex than they initially thought it would be, they split the work while still preserving the concept of customer value. If that’s not an option, then more team members jump in and help ramp things up.

The cornerstone here is that, whatever the solution you find, you are bringing down your WIP average age by attacking the work that’s aging artificially in your workflow.

#3 Break Down Your Cycle Time

Measuring the breakdown of your cycle time will enable you to indicate the time needed for your work to move from one status to another.

That’s how you measure how long it takes to move your work through each of them and thus identify which has the longest cycle time.

For example, in the chart below, we have a process with the following steps – Development, Code Review, Testing, Deployment and Done, and the queue states Code review (Done) and Testing (Done).

Break Down Your Cycle Time

On the Cycle Time Breakdown, it is clearly visible that 20% of the workflow is spent in the Code Review (Done) step. As this is a queue state, it means that our work is not able to move to Testing, it is just sitting and waiting in the queue due to a bottleneck in the Testing state.

An obvious solution may be to hire more testing specialists. We could assume that adding more testing capacity would remove the bottleneck. However, it costs both time and money.

Another alternative is to assign some of the idle team members to that step. You can categorize your work using risk profiles to specify the requirements that must be tested by the proficient test team and delegate those that could be covered by people from other functional areas.

My point is:

Your team’s performance will increase by 20% only by resolving the bottleneck in the Testing step. Your customers will receive what they’ve requested 20% faster, which will ultimately lead to a significant rise in customer satisfaction.

Ready to reveal the obstacles in your own workflow? Go ahead and connect Nave’s analytical suite to your management platform (it’s free for 14 days)

Once you’ve plugged in your data, analyze your dashboard and send me a note on LinkedIn. I’d like to hear all about it so don’t hesitate to reach out!

Thank you for tuning with me today, as always! If you have a colleague who could use a refresher on how-to with Kanban metrics, be sure to send this article their way. I’m excited to see you next week, Tuesday, for more managerial insights. Bye for now!

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