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Tuesday, September 23, 2014

The No Estimates principle: The importance of knowing when you are wrong

You started the project. You spent hours, no: days! estimating the project. The project starts and your confidence in its success is high.

Everything goes well at the start, but at some point you find the project is late. What happened? How can you be wrong about estimates?

This story very common in software projects. So common, that I bet you have lived through it many times in your life. I know I have!

Let’s get over it. We’re always wrong about estimation. Sometimes more, sometimes less and very, very rarely we are wrong in a way that makes us happy: we overestimated something and can deliver the project ahead of (the inflated?) schedule.

We’re always wrong about estimation.

Being wrong about estimates is the status quo. Get over it. Now let’s take advantage of being wrong! You can save the project by being wrong. Here’s why...

The art of being wrong about software estimates

Knowing you are wrong about your estimates is not difficult after the fact, when you compare estimates to actuals. The difficult part is to make a prediction in a way that can tested regularly, and very early on - when you still have time to change the project.

Software project estimates as they are usually done, delay the feedback for the “on time” performance to a point in time when there’s very little we can do about it. Goldratt grasped this problem and made a radical suggestion: cut all estimates in half, and use the rest of the time as a project buffer. Pretty crazy hein? Well, it worked because it forced projects to face their failures much earlier than they would otherwise. Failing to meet a deadline early on in the life-cycle of the project gave them a very powerful tool in project management: time to react!

The #NoEstimates approach to being wrong...and learning from it

In this video I explain shortly how I make predictions about a possible release date for the project based on available data. Once I make a release date prediction, I validate it as soon as possible, and typically every week. This approach allows me to learn early enough when I’m wrong and then adjust the project as needed.

We’re always wrong, the important thing is to find out how wrong, as early as possible

After each delivery (whether it is a feature or a timebox like a sprint), I update my prediction for the release date of the project based on the lead time or throughput rate so far. After updating the release date projection, I can see whether it has changed enough to require a reaction by the project team. I can make this update to the project schedule without gathering the whole team (or "the chosen ones") into a room for an ungodly long estimation meeting.

If the date has not changed outside the originally interval, or if the delivery rate is stable (see the video), then I don’t need to react.

When the release date projection changes to a time outside the original interval, or the throughput rate has become unstable (did you see the video?), then you need to react. At first to investigate the situation, and later to adjust the parameters in your project if needed.


The #NoEstimates approach I advocate will allow you to know when the project has changed enough to warrant a reaction. I make a prediction, and (at least) every week I review that prediction and take action.

Estimates, done the traditional way, also give you this information, but too late. This happens because of the big-batch thinking the reliance on estimations enables (larger work items are ok if you estimate), and because of the delayed dependency integration it enables (estimated projects typically allow for teams that are dependent to work separately because of the agreed plan).

The #NoEstimates approach I advocate has one goal: reduce feedback cycle. These short feedback cycles will allow you to recognise early enough how wrong you were about your predictions, and then you can make the necessary adjustments!

Picture credit: John Hammink, follow him on twitter

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Monday, September 15, 2014

The Release Paradox: releasing less often makes your teams slower and decreases quality

Herman is a typical agile coach. He works with teams to help them learn how to deliver high-quality software quickly.

Many teams want to focus on design, architecture, or (sometimes) even on business value. But they are usually not in a hurry to release quickly.

Recently Herman conveyed a story to me that illustrates how releasing quickly can help teams deliver high-quality software much faster than if they would focus on quality in the first place. This is the case of a team that was working on a long overdue project. They had used a traditional and linear process in the past and had been able to release software only very recently, after more than 12 months of work on the latest release.

Not surprisingly, they were having trouble releasing regularly. The software was not stable; once it was live it had many problems that needed to be fixed quickly, and worst of all: all of this was having a direct impact on the company’s business.

The teams were extremely busy fixing the problems they had added to the product in the last year and could not focus on solving the root causes of those problems.

They were in full-fledged firefighting mode. They worked hard every day to fix yet another problem and release yet another hot fix.

This lasted for a few weeks, but once the fire-fighting mode was over, Herman worked with the teams to improve their release frequency. During their work with Herman, those teams went from one year without any release to a regular release every two weeks.

At first the releases were not always possible, but with time they improve their processes, removed the obstacles preventing them from releasing every two weeks and started releasing regularly.

What happened next was surprising for the teams. The list of problems after each release did not grow - as they expected - but instead shrank.

When some problems came in from the customers after a 2-week release, they were also much faster to fix the problem and quicker to release a fix if that was required. When the fix was not critical, they waited for the following release which was, after all, only 2 weeks away.

By focusing on releasing every two weeks, Herman’s teams were able to focus on small, incremental changes to their product. That, in turn, enabled them to fine-tune their development and release processes.

Here are some of the key changes the teams implemented
  1. They started with a 4 week release cycle, and fine-tuned their daily builds and release testing process to enable a release every 2 weeks.
  2. They invested time and energy to improve their test automation strategy and automated the critical tests to enable them to run “enough” tests to be confident that the quality was at release level.
  3. They had some teams on maintenance duty in the first few iterations to make sure that any problem found after release could quickly be fixed, and released to customers if necessary.
  4. They changed their source code management strategy to enable some teams to work on longer term changes while others worked on the next release.
  5. They involved all teams necessary to complete a release in their iterations. This affected especially: production/operations team, localization team, documentation team, marketing team, and other teams when needed.
This list of changes was the result of the drive to complete each release and learning from the failures in the previous release. Some changes were harder to implement, and especially the testing strategy to allow for 2-week release cycles had to be changed and adjusted several times.

One of the key problems the teams had to solve, was the lack of coordination with departments that directly contributed to the release but were not previously involved in their day-to-day work.

This process lasted several months, and would not have been possible without a clear Vision set forth by the teams in cooperation with Herman, who helped them discover the right way to reach that Vision within their context.

Herman’s work as a coach was that of a catalyst for management and the teams in that organization. He was able to create in their minds a clear picture of what was possible. Once that was clear, the teams and the management took ownership of the process and achieved a step-change in their ability to fulfill market demands and customer needs.

Customers have no reason to change provider as they have an ever-improving experience when using this company’s services.

Today, this organization releases a new version of their product every two weeks. Unaware of it, their customers receive regular improvements to the product they use, and have no reason to change provider as they have an ever-improving experience when using this company’s services.

Picture credit: John Hammink, follow him on twitter

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Monday, September 08, 2014

How to create a knowledge worker Gemba

I am a big fan of the work by Jim Benson and Tonianne Barry ever since I read their book: Personal Kanban.

In this article Jim describes an idea that I would like to highlight and expand. He says: we need a knowledge worker Gemba. He goes on to describe how to create that Gemba:

  • Create a workcell for knowledge work: Where you can actually observe the team work and interact
  • Make work explicit: Without being able to visualize the work in progress, you will not be able to understand the impact of certain dynamics between the team members. Also, you will miss the necessary information that will allow you to understand the obstacles to flow in the team - what prevents value from being delivered.

These are just some steps you can take right now to understand deeply how work gets done in your team, your organization or by yourself if you are an independent knowledge worker. This understanding, in turn will help you define concrete changes to the way work gets done in a way that can be measured and understood.

I've tried the same idea for my own work and described it here. How about you? What have you tried to implement to create visibility and understanding in your work?

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