Dysfunctional Commitment

Team commitment is a wonderful and sometimes fragile thing. Many responses to my description of it are indications of how frequently the word “commitment” is used in a dysfunctional manner. Indeed, the post was prompted by similar conversations.

Believe me, I’ve seen these dysfunctions many times. They are so numerous and varied that no catalog of them could be complete. It’s not the word, commitment, that causes the problems, however. And avoiding that word will not solve the problems. Instead, we have to look at the behavior and attitudes behind the problems in order to reliably recognize them and choose strategies for correcting them. (Continued)

Team Commitment

Most Scrum teams estimate their top priority stories, select those stories that add up to their historical velocity for their sprint backlog. Some teams simplify this by merely counting the stories, or using the mathematical reciprocal, cycle time. Others make it more complicated, calculating the effect of days off and other known distractions from the work.

However they calculate it, some people put a lot of faith in the historical data to guide the future. “It’s data,” they say, “it’s better than guesses and not subject to cognitive bias.” Not all data is easily measured and converted to numbers, though. Limiting yourself to this initial calculation is, itself, an example of anchoring bias. (Continued)

Agile: What’s in it for the Project Manager?

Over on projectmanagement.com, my article “Agile: What’s in it for the Project Manager?” has been posted in two installments: part 1 on gathering requirements and work breakdown, and part 2 on interpreting requirements and tracking progress. Projectmanagement.com requires free registration to access the full content.

Estimation as Hypothesis

Experimentation is a powerful learning tool. When I was young, I performed scientific experiments by mixing chemicals together to see what they would do. I learned that most random concoctions from my chemistry set would make a brown liquid that was often hard to clean out of a test tube. I learned that sometimes they would create very smelly brown liquids. These were not really experiments, however, and I didn’t really learn from them. Instead, these were activities and I collected anecdotes and experiences from them.

The scientific method rests on the performance of experiments to confirm or deny a proposed hypothesis. Unless you can propose a hypothesis in advance, you cannot design an experiment to test it. Until you test the hypothesis, you haven’t really learned anything. (Continued)

How do we estimate?

There have been some web posts and twitter comments lately that suggest some people have a very narrow view of what techniques constitute an estimate. I take a larger view, that any projection of human work into the future is necessarily an approximation, and therefore an estimate.

I often tell people that the abbreviation of “estimate” is “guess.” I do this to remind people that they’re just estimates, not data. When observations and estimates disagree, you’d be prudent to trust the observations. When you don’t yet have any confirming or disproving observations, you should think about how much trust you put into the estimate. And think about how much risk you have if the estimate does not predict reality.

This does not mean, however, that you have to estimate by guessing. There are lots of ways to make an estimate more trustworthy. (Continued)