Getting Started with Kanban Analytics? Do Just This One Thing
If you’re striving to optimize your processes and improve your delivery speed, chances are you’ve already explored our Kanban analytics solution. Now, once you set yourself up, what’s next?
Today I’ll give you a very simple strategy to get started that will not only put you in motion from the get-go but everything else (literally) will start flowing from that.
Guy Kawasaki, a famous marketing expert, once said: “The hardest part about getting started is getting started.”
Raise your hand if you agree!
When you’re just starting out with our analytics suite, it can feel overwhelming.
You want to track your cycle time, lead time, throughput, and flow efficiency. You want to run Monte Carlo simulations and figure out where the problems that slow you down are coming from…but you’re not sure what to do first.
Good news, my friend.
There is actually a very simple answer to this question.
It’s the answer I’ve given all my clients over the years whenever they’re getting started using our analytics suite, and it’s the same answer I’m going to give you:
In the very beginning, the only thing you need to do is track and manage your WIP average age.
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.
Tracking WIP Average Age: A Quick Refresher
First, let’s do a quick recap of what WIP average age is and why it’s important to keep track of it.
Every ticket on your board that hasn’t been finished just yet has a WIP age.
To calculate that age, you simply look at when you started the task. If you started the task two days ago, the task is two days old and thus its WIP age is two days, tomorrow it will be three days, etc. The longer the task sits in the process, the older it gets and the more its WIP age increases.
“WIP Average age” refers to the average of all tasks’ WIP ages.
If you have two tasks, and one has been in the process for four days while the other has been in the process for two days, then your average age of WIP (as of today) is three days. Tomorrow, if the same tickets are still in progress and nothing else has been started, your WIP average age will be (5 + 3)/2 = 4 days.
Why Should You Use WIP Average Age as Your Starting Point
And here is the thing. 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 tasks that are 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.
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.
So What Does It Actually Mean to Manage WIP Average Age?
Nave’s aging chart is your best friend when it comes to measuring WIP average age.
It uses the exact same format as your Kanban board – the X axis displays your columns while the Y axis shows the number of days your work spent in your process.
In this example, Item A has spent 6 days so far in the process, Item B has spent 22 days in the process. The longer the item has stalled, the higher the dot is along the Y axis. The WIP average age of this process is about 14 days.
The goal is to reduce your WIP average age to an optimal level and then keep it consistent.
How can you achieve that goal? 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.
The Key is Consistency
Now that you know where to start, let’s talk about how you improve over the long term.
The secret to delivering predictable delivery results is stabilizing your system.
As long as your WIP average age is consistent, you’re in a great place (and your aging chart will make it clear if you’re heading in the right direction!).
A consistent WIP and consistent WIP average age mean that your other performance metrics will be consistent across the board.
The best way to pay attention to how your WIP average age is affecting your performance altogether is to integrate it into your daily calls. Add a step to walk your team through the Aging Chart in the agenda.
Every day, look at your aging work and talk about the dots that have the highest WIP age.
Make sure those are the ones you handle first.
I can’t emphasize it enough:
When you’re just getting started, you don’t have to track anything else but your WIP average age. Putting your finger on the pulse of your work in progress will improve your delivery speed, increase your throughput, and set you up for success in the long run.
This simple strategy will enable you to improve your entire performance without even being intentional about it!
Here’s what you do next: If you haven’t already, go ahead and hook up Nave to your management platform (it’s free for the first 14 days!) →
Once you’ve created your dashboard, take a look at your Aging Chart and examine the dots that are closest to the top! Make sure you finish those items first and you’re off to a great start.
That’s it for today, my friend. I hope I’ve convinced you how simple it really is to get started with Nave to improve your processes. If you know someone who’s experiencing “analysis paralysis”, please share this article with them on their favorite social media channel.
Thanks for checking in with me, and I’m excited to see you again next week, same time and place, for more action-packed managerial insights. Bye for now!
Meet the Author
Sonya Siderova is a passionate product manager and a driving force behind Nave, a Kanban analytics suite that helps teams improve their delivery speed through data-driven decision making. When she's not catering to her two little ones, you might find Sonya absorbed in a good heavyweight boxing match or behind a screen crafting a new blog post.