Friend: So in short - they too need to scale their agile initative.

Marcus: Oh - cool! Up or out?

Scaling agile has to be the term that I’ve seen most discussions, posts, comments and conversations about the last couple of years.

And Google seems to agree - it at is peak or going there right now.

But very seldom I’ve heard an explanation to what kind of scaling that is meant: do you want to scale up or scale out? My guess is that many times people talking about scaling agile mean scaling UP but worse I think that most times we have not decided. That is not really wise because it’s two very different problems to solve.

In this post, I wanted to reason a bit about those tradeoffs.

Computers

The distiction between scaling up and scaling out is something...

I have been involved in many organisational changes that turn the organisation sideways. From functional departments to cross-functional teams, from projects and completing activities to continuous delivery and focus on reaching effects.

Just about always this creates some initial confusion around where decisions get made and how the old ways fit into the new. Quite often worry about chaos break out.

For example;

Who is in charge of the overarching architecture, now that each team is deciding everything by themselves?

I realize that I’ve done a bad job describing how this is going to work. The other week I found myself describing this with a pretty simple model that I wanted to share.

Disclaimer

I’m pretty sure this is not news at all and I’m making a pale copy of something brilliant. But … it’s my copy and I’m standing by it.

TL;DR

If...

I just had a conversation with a client that I keep coming back to. It has to do with how we are using electronic systems that manager our work, for example JIRA and TFS.

I needed something to refer back to and I hope that you can get something out of me writing this down.

In this particular case the question was very straight-forward:

I think we are overusing the tag ‘Need investigation’

My question back was simple:

How is that tag going to change your behaviour?

Because it should, right? We are putting this tag on the item for some reason. Needs investigation - we should investigate then, I hope. The tagging feature, that we use in many electronic tools, would be some kind of marker on a physical board. A magnet or turning the card sideways, or what have you....

Although I often preach about embracing uncertainty and sometimes get comments about always being calm… despite that; I worry. As do we all.

But sometimes, in rare moments of clarity, I have the opportunity to stop and reflect over the what I am worried about. It just about always brings me to the realization that I worry in vain.

Let me share three things in particular, that I have worried about lately. That gave me nothing but more worry.

HOW problems are solved

One of the things that I come back to very often nowadays is that we need to let the people closest to the information decided HOW to solve a problem, or handle an opportunity. They know better, best even, HOW to act and also can change their ways faster if they are given new information.

This is why we focus on the OUTCOMEs a...

UPDATE I have learned new stuff. There are a better ways. Find the update here

It’s time to wrap this series up. I have one final thing that I want to visualize: queue length. How much stuff is waiting and how long will that take us to complete? And maybe even, “if I add something in the queue now, how long before it’s done?”

1. Lead time
2. Lead time with filters
3. Throughput
4. Where time is spent
5. Single numbers - averages, median and max of lead time

As always my sheet is found here and you can make a copy of it and use it. Please let me know how it’s working out for you and if you end up doing something cooler than me.

Let’s do it - queue length!

Why queue length?

I picked up queue length as...

I stumbled over a new concept the other day. As it was conceived by Kent Beck, that inspired and thought me a lot in the past, I got interesting.

[UPDATED]

I read Kents blog post a bit too fast and missed that this idea was actually proposed by Oddmund Strømmer. Very sorry that I missed that in my writeup, Oddmund. Thanks for correcting me, Raquel.

And after some even more research the origins seems to be traced back to a group of people that took a workshop with Kent Beck. Not only Oddmund Strømme but also Lars Barlindhaug and Ole Tjensvoll Johannessen. Those Norwegians… always a few steps ahead of me.

[BACK TO THE OLD TEXT]

When I read his blog post I got to this quote:

I hated the idea so I had to try it.

I felt the same actually and now...

UPDATE I have learned new stuff. There are a better ways. Find the update here

This post is all about just aggregating and averaging out to a single number… and then I can’t control myself but start to lay that number out over the individual weeks too.

That, and we will use the Gauge-chart for the first time in my life.

This is the fifth post in my series on some simple kanban board statistics. We have been talking about:

1. Lead time
2. Lead time with filters
3. Throughput
4. Where time is spent

Common questions

Although I have the diagrams laid out and everything is visible one of the most common questions I get is:

But what is the overall average? How long does an S usually take?

After I explain that this is just a point-in-time-reading that will not...

This is the fourth post in my series on some simple kanban board statistics. We have been talking about:

• Lead time
• Lead time with filters
• Throughput

And this time it’s time to see if we can visualise a bit where time is spent. For this first post, we will make some basic classifications of active and not active or not “on the board” and “on the board”.

In the coming posts I want to expand on this and see if we can make a distinction between other states on the board as well, but for that, we need to expand the data in “Raw data”, because that data only contains completed items right now.

Ok - let’s get going. As for all these post I am in this Google Sheet - make a copy if you want to play along

The...

UPDATE I have learned new stuff. There are a better ways. Find the update here

Lead time is awesome to track and try to improve. In fact, it’s something that will guide you to a lot of improvements and should be front-and-centre of your process metrics.

But that says very little about how much that gets done per time unit. Doing one thing in a day, fast and with quality, and then nothing for the rest of the month means that no other things get done.

Let’s start to track another metric; throughput or

the amount of material or items passing through a system or process.

With the data, we have this is pretty easy to get hold of.

Setting up

Like before, the goal is to not touch the “Raw data”-tab so that our exported data can be updated in that one place...

UPDATE I have learned new stuff. There are a better ways. Find the update here

This is the second post in my series where I show how you can get make powerful visualizations of process data. As before, my goal here is that you can dump your process data into one tab of my sheet and then the dashboard will make all the other calculations.

In the first post, I talked at some length about other goals of this tool and some of the principles I built these ideas on.

Speaking of those principles; in this post, I will violate one of them a bit, by adding a filter capability to the lead time chart, so that we can see just a part of the data.

The reason I want to do this is that, as it the chart stands now, it’s a bit too...