Posts tagged velocity

The term “bottleneck” refers to a point where after the flow or velocity perceptively reduces. It is metaphorically derived from flow of water through a narrow mouthed bottle where the flow of water is constrained by its neck. For drinking purposes it is a good thing as it regulates the flow of water through the bottle to the drinker, preventing wasteful spillage. Bottleneck’s though constraining can be both a good thing and a bad thing, depending on desirability from the system.

The scrum framework contains product backlog  which is essentially a queue (stack ranked, one after the other) of product backlog items (PBI’s) that the scrum team has to complete. Queue’s/backlog’s don’t feel good. Think about the last time you were in a rush and had to go to a bank where you stood in a queue behind fifteen people before the teller addressed your needs. Or the time you had to stand in queue to board your daily commute bus – uncertain whether you will get a chance to board this bus before the driver declares “its full” and rides on. There is the frustration of waiting in a line and the uncertainty of whether you will make it. If  PBI’s could feel, then I guess they would empathize with people stuck in queues. 

IMO, inherent assumption within complex software product development efforts is that

the business will always have more concepts or requirements than the team’s capacity to transform these into potentially shippable product increments.

If this assumption holds true for you then your product backlog expresses the aggregate effect of bottlenecks that exists downstream in your system. In other words, if there were no bottlenecks or team had infinite capacity then the all the PBI’s will be transformed into potentially shippable product increments within a sprint. Velocity metric represents this constrained capacity of a scrum team. In scrum terms these bottlenecks and other blockers are commonly referred to as impediments. Impediments being a broad generic term, I’m focusing on bottlenecks – which are impediments that specifically cause reduction in flow at a systemic level over multiple sprints.  (Nothing too revolutionary!)

Here are a few of such bottlenecks:

1. Ill-defined product backlog items

Top priority product backlog items are not well defined for the team to fill up at least their next sprint and start working.Too often this results in lengthy sprint planning meetings, and delay in terms of days before a scrum team makes sprint commitment and get going. In such cases the team spends the first few days of the sprint analyzing requirements, holding design sessions etc prior to making a sprint commitment. Sprints in this case go in fits and starts with a significant gap in software development efforts between the end of previous sprint and the start of new sprint. In this case the bottleneck is recognized as gaps between sprint end and start dates.

2. No product backlog items

In most cases, this situation is not an invalidation of the assumption that the business has more work than the team can do in a sprint. In fact too often the business has a pressing need to get many features out of the door. Flood of information, lack of agreement, “have to get it right the first time” has a paralyzing effect effectively boxing them in a state of limbo where PBI’s are not defined and the scrum team is left out to dry. Often the bottleneck in this case is upstream of the scrum development team causing either an abrupt end to sprint rhythm or a false start with frequently extended ‘sprint 0′.

3. Not-Done product backlog items within a sprint

It is common understanding that PBI’s within a sprint are either Done or Not-Done as measured against their definition of done. PBI’s that get Done are counted towards team’s sprint velocity and the rest don’t. Teams that end their sprints with some or many Not-Done PBI’s find that their ability to pull in new PBI’s next sprint is bottle-necked.  Following the mechanics of good scrum practices these teams present Not-Done PBI’s to Product Owner and estimate remaining work for prioritization in Product Backlog. In my observations it is most likely occurrence that the Product Owner will ask  for Not-Done PBI’s to be completed in following sprint. Effectively the team carries forward Not-Done PBI’s from last sprint into the next sprint. In cases like these, it may feel like that there is a smooth flow from concept to realization however it ain’t true. Look at the worst case scenario, no new PBI’s are pulled from product backlog and the team spends the next sprint finishing up not-done work from previous sprint. In this worst case example it is easy to call out such a bottleneck, in real teams there are variations along the continuum of getting all committed PBI’s Done to getting none of committed PBI’s Done. It takes an experienced scrum team and/or ScrumMaster to recognize this pattern while its happening for real.

4. Insufficient infrastructure

Lack of staging environments, insufficient QA infrastructure and/or production ready environments stops the flow of developed features at some point before these features can be deemed production ready or ‘potentially shippable’. All these features pile up and aggregate until a sprint or two prior to release date. Then the teams make a major ‘push’ to release all of the developed functionality out of the door.

These last sprints are often called as ‘stabilizing sprints’. And I have to say, I will start liking the term ‘Stabilizing sprint’ under the condition that all of the previous sprints are called destabilizing sprints. Each one of the previous sprints was destabilizing the product increment unpredictably. Sadly for me, most people interpret the term ‘Stabilizing Sprints’ as a good thing .

Tricky thing with all the hard stuff, like performance testing, regression testing etc, that could not be done within regular sprints is that the hard stuff does not get simpler if its left for last sprint. It gets even  more harder. Causing a snowball effect. Take regression testing for example, if regression testing was not done in previous sprints then in the last stabelizing sprint potentially a lot of regression bugs can show up. If these bugs cannot be fixed in the last stabelizing sprint,  these will then ideally fuel addition of PBI’s in product backlog. Leading to either lower quality product release or a delayed release date. In either case, there in lack of objective perception regarding both quality and predictable release date. This bottleneck is obvious to everyone, for there are features piling up every sprint waiting to be production ready however the exponential negative impact is still underappreciated.