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What would you suggest should be done with a software development team where there is a significant difference in skill levels, let’s say up to 10x difference ?

Jason Yip shared this question he proposed to Takeshi Kawabe, who answered as follows:

Set the best performers as the standard. Pair people with the masters in a master-apprentice model. Find other suitable jobs for those without aptitude. Like professional baseball players, you need to practice every day to be a professional. Software development is a team activity an team are only strong as their weakest link.

Couldn’t agree more with it, but unfortunately is not the reality in most of the companies, that seem to be trying the opposite, setting an anti-productivity policy, which could be summarized as:

Set the worst performers as standard and create rules around everyone to avoid them making big mistakes. After that, just wait for the ones with aptitude to leave for a better place.

This topic comes from some discussions that went on in a mailing list I participate, and also between me and my flatmate, about how productivity should be measured in agile projects, and how is it related to capacity.

I wanted to write this post for some time right now, but today I’ve realized that somebody had already written about it, so I decided to give my opinion too :-).

I totally agree with Simon when he says that velocity is not productivity. As I mentioned in another post, one should be very careful when applying any measure, specially productivity measures, and capacity isn’t one of them, in my opinion.

One simple example that makes me reach this conclusion is bug fixing. If you consider capacity = productivity, how should you count bug fixing stories? They are certainly not adding business value, they are actually delivering business value that was supposedly already delivered, but you can’t deny that the team spent time fixing bugs, and that these points should be considered in the estimation and also in the team’s velocity.

Simon also wrote about how to measure productivity, or even better, how to say if a team is performing well. In his post, he wrote

I prefer to measure productivity in terms of the goal and getting stories done is not the goal, generating revenue is. Getting stories done is the means to achieve the goal.

Productivity is perhaps better represented by the revenue generated per iteration per unit of story estimation, e.g. £10,000 per ideal pair day.

This topic was also covered by Martin Fowler in this post. As Martin said,

So maybe you can’t measure the productivity of a team until a few years after a release of the software they were building.

Despite understanding what both says, I find kind of difficult to specify the performance of a software development team if you link it to the revenue generated by the project. I agree that in order to obtain the best results, the considered system should be as broader as it can be (as Deming proposed).

But I also believe (along with Goldratt) that a team has to have a goal, and this goal should be very carefully considered, since it will drive all team’s actions when they are developing software. Including the client’s business in this equation makes it too complicated, since you don’t have any control in how the client is using your work to generate revenue, and as Martin said, it could take years in order to obtain a good result.

If a team doesn’t have a goal, how could it pursue its objectives? Which are the objectives? If agile is about constant and rapid feedback, should I receive feedback based on which criteria? What should the team try to improve when performing retrospectives?

In my opinion, if you have a client that is specifying which stories are more important to the project, and that is why it is really important to bring the client inside the project, at this moment should the measure end, on stories accepted, which will deliver business value (but might not, if for some business reason the software isn’t used anymore, for example).

Until this point a team has the conditions to change and adapt itself to get better results, and deliver more business value. After it, not anymore.

Cheers.

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