A friend of mine had an interesting situation:
- Novel product, many unknowns
- Multiple teams grouped into 3 product areas
- Experience doing 3-week sprints
Only a fool would do anything other than the 30-day official sprint cycle that I saw on some website and in a few books.
(Just kidding. Unfortunately, like most of agile development, context has a tremendous impact on what you choose to do, process-wise.)
A lot could go into what the Optimal Sprint Length should be… You could ponder the dependent variables and try and guess an optimal length to optimize the independent variable(s) — which would be, what, maybe cost and rate of feature delivery and quality? You could do the “democratic process” and allow the team to vote, or even do “rock-paper-scissors” to figure out 2 or 3 weeks.
However, what if we built a continuum of sprint lengths for the sake of discussion. On the one end, we start at the idealization of doing one useful feature at a time and deploying it immediately — think simple web app. Anything longer than this is a compromise based on some (hopefully valid) reason. On the other extreme, we could wait until the entire system is done before deploying or integrating, maybe after 6 months or a year.
The cost of “batching up” the “work in process” at the upper end of long sprint lengths, is pretty obvious to everyone. I submit, that if you agree with (or experience first-hand) the premise that batching work has a non-linear impact on overall cost (including the hidden and subtle cost of everything that we know is bad with waterfall), then it stands to reason one might favor shorter cycles and less batching.
Not to digress, but the parallels exist in industry. To allow WIP to be large, and to allow certain parts of the process to run at high levels of batching, is a risk. A risk that the items in the batch, once released into the wild, are discovered to not be as valuable as first thought. Well, it’s water over the dam, time and effort you will never get back. (Think: extra features built because someone thought they would be useful, and it turned out that the marketplace thought otherwise.) Nonetheless, sometimes weighing the risks will lead you to some level of batch that makes the most sense.
There is often much more to the decision on sprint length than purely the development team. For example, what is the cost of QA? If the cost of QA is no different for 1 feature at a time versus a week’s worth of features, than QA cycle time/cost is not an issue. However, if it requires a week of QA time to regression test the system in the case of even a single small feature or bug fix, then you have a serious input into what the optimal sprint length should be.
Naturally, one could do development sprints at one frequency, and QA sprints at another… and even customer ship sprints at a completely other cycle time.
Regarding multiple teams… this is a solution that can be recursively applied, much like you would at a software architectural level. If the teams are horribly coupled, your costs will balloon and no amount of pondering sprint lengths will have a significant impact. If the work dependencies are carefully controlled between the teams, sprint length could vary between teams due to their own local reasons.
Much like the QA process can be a “tax” on each Sprint, what other taxes does your process incur? Running down to a one week sprint will likely reveal expensive parts of the process that could be ripe for improving.
So having said all of that… Here’s a thought. Why not simply agree to try out a few different lengths for enough sprints to get a feel for the differences. Try one week sprints for the next 6 weeks. Try 3 week Sprints three times. See if you can monitor metrics that will tell you what worked better. Consider that different teams might also work at different frequencies to test the “costs” of thinking the teams should be synchronized.
Much like with our USA republic, surely don’t let democratic, mob rule win the day.