- One of the key ways to improve your flow
is to manage your different queue sizes.
Typically you want to create
small batches of work for your queues.
That will give you a steady flow of work
through your system.
Your Kanbard board shows queues
by creating different columns.
You want your business analyst
working on the analysis queue,
and then passing on to software developers
in the development queue.
Remember that each card represents
an item in the queue.
You can't put another item in the queue
until there's room in the same column.
Instead you can only put another card in
when you pull an existing card out.
On top of each of each column
you have a number that represents
the maximum number of items in the queue.
The tricky part is figuring out
how much of these little batches
you should have in each queue at one time.
This is typically called managing your queue size
to optimize your flow.
One way that Kanban does this
is by using something called queue theory, or Little's Law.
Little's Law says that you get
more work through the system
if you bundle tasks into smaller batches.
If you get large batches,
that can lead to a system backup.
That ends up looking almost like a traffic jam.
You'll have many cars backed up
and no one seems to be moving.
So in Kanban, you should think of Little's Law
as having three metrics.
The first metric is cycle time.
This is the amount of time it takes
to move each card to the next column.
Then there is the number on each column.
This is the work that you have in this queue
at any one time.
Finally you have the average time it takes
to finish a card.
This can help you make a prediction
about how long it will take to finish your work.
So now you can use Little's Law
to get an idea for how increasing
or decreasing your queue size
might impact your product delivery.
Let's say that your analysis column
has a queue size of five cards.
The team could finish about 1.25 cards each day,
that will give you a cycle time of four days.
So at any one time the analysis column
should only have four days of work.
So say your development team
ends up waiting too often for work
to come out of the analysis queue.
They might want to decrease the cycle time
so they can get work more quickly.
The analysis team could try to fix this
in one of two ways.
They could try to work more quickly
and finish 1.5 cards each day.
That would decrease their cycle time
to about 3.3 days,
so they'll finish almost a full day earlier.
But they can also try to decrease the queue size.
They might decide to commit to delivering four cards.
This will actually improve delivery
more than speeding up the work.
They'll be finished delivering it in 3.2 days.
By using Little's Law,
you can dial into what works best for your teams.
By tweaking the cycle time,
you could make sure that each queue
gets work in a way that improves the overall flow.
Just remember to watch how cards
move across the board
and listen to your teams
when figuring out the optimal queue size.