Posted on | February 23, 2014 | No Comments
Today I found a new cool video on the leadership subject. Inno-Versity created an Inno-Mation based on the book by former US submarine captain David Marquet in which he explains how he turned his submarine from the worst to the best performing vessel in the US Navy. His experiences closely resemble the leadership style needed for high performing agile teams. Of course it also resembles lean leadership principles.
Posted on | February 17, 2014 | No Comments
My latest Whitebook (Dutch), 'Goed agile is snel (maar ook moeilijk)', is published here.
Posted on | November 18, 2012 | 1 Comment
I'm a great believer in visual management. I love brown papers with sticky notes and lots of charts. That's also why I love spreadsheets. Not because I think you can manage projects by crunching data, but spreadsheets give me the opportunity to visualize the project's status and progress by creating charts.
One of the most challenging parts of agile project management is managing trust and uncertainty. Of course the best way to create trust is to deliver software and demo it each sprint. Keeping status and progress transparent also is a "trust requirement". Still, sometimes going agile is a big leap of faith. Personally, I'm not accustomed to mature agile organizations. Each of my agile projects was an agile implementation also. May be that's why I'm extra sensitive to building trust early on.
In this 'episode' of my Excel series of post I'll explain my uncertainty chart. An excellent chart to visualize uncertainty about the product backlog size.
|Note that this chart is an example only.
Please determine you're own metrics, specific for your project at hand.
So what's this chart all about?
The primary function of this chart is to show a 'product backlog size uncertainty'. The uncertainty percentage gives an indication how sure you're are about it's size estimation. Please choose you're own metrics here. In this example a 'done' story still leaves 5% of uncertainty, because it's still possible there's a new insight that leads to new requirements. In this example an epic is defined by the phrase 'it's something big and we haven't got a clue what it's about'. That's why the uncertainty percentage is 80. This metric is shown by the red line and yellow sticky notes.
The secondary function of this chart is to give more detail about the makeup of the uncertainties per User Story status. This is shown in the stacked vertical bars.
Both metrics are Sprint specific so that uncertainty can be tracked through time.
The underlying chart data looks like this:
|Done – 5% uncertainty||10||20||30||50||70|
|Ready – 20% uncertainty||10||10||40||50||50|
|Not Ready – 50% uncertainty||10||10||50||20||0|
|Epic – 80% uncertainty||100||100||0||0||0|
So how does it work?
That's not that difficult. Here's how Sprint 5 is calculated:
|Status||Uncertainty||Sum of SP||Sum of Uncertainty|
This data is based on this Product Backlog:
For each status the sum of SP is calculated and then multiplied by the uncertainty percentage for that status.
The average uncertainty percentage of 11% is calculated by dividing the sum of uncertainty by the total sum of SP (13.5/120).
The Excel file used for this example can be found here.keep looking »