Agile Estimation Theatre

We’ve all experienced what I like to call Agile Estimation Theatre. Imagine it’s the beginning of the sprint and your team is holding a sprint planning meeting. The project manager has built up a set of stories a few of which have subtasks. Now you will spend the next two hours trying to create estimates for each of those stories. 

The project manager starts by reading the first story. Someone asks a question about whether ECS or EC2 are a better solution for the problem which devolves into a 20 minute conversation about the merits of various AWS services. The project manager is forced to stop discussion to leave any possibility of estimating all the stories slated for the sprint. You open your planning poker tab and evaluate your options 1,3,5,7,13,21,34, 55. After a moment you decide on 13 since you are sure the task will take at least a day or two. One of your coworkers then asks whether the numbers are days or hours. That question leads to a 10 minute discussion of what exactly story points are and how they are definitely not a unit of time. The teams votes range from 5 to 34. And then project manager overrides the score to be 21 since that’s what the senior engineer picked.

The two hours continue to drag on. By the blessed end of the meeting your team has ‘estimated’ 4 out of 20 single sentence stories. Since the sprint starts tomorrow the project manager holds a quick meeting with the senior engineer to estimate the rest of the stories before 5pm.

The above tale represents what I like to call agile estimation theatre. We have a sprint planning meeting where we’re supposed to involve the entire team in estimation, so we schedule a two hour meeting and hope for the best. Sometimes it actually works, but often we end up with questionable estimates for single sentence tasks.

The fundamental problem with Agile Estimation Theatre is not investing enough time. To get good estimates you need to have complete stories. You need to break down subtasks and specify them more thoroughly than a single sentence can possibly handle. Then you need to have your team spend time reviewing the stories individually and coming up with estimates. The problem is that it doesn’t make sense to spend several days out of a two week sprint on estimation. To do it right you need to have well specified stories. Building out the stories will take at least a few engineer days. Next you need to have the entire team spend 2 hours each estimating stories individually. Finally you add together the individual estimates and do the sprint planning meeting. Now repeat that process again every two weeks.

The breakdown is that the expected value of the estimates is typically less than the cost of spending a few days to produce good estimates. The organization intuitively knows this which is why we spend two hours in sprint planning instead of two days. But because we want to do scrum or agile ‘properly’ we need estimates. The end results is that we denature the estimates to comply with the process.

Agile has gone from ‘people over process’ to ’no process’

In practice ‘agile’ means ‘we have no process in place and each team does whatever random thing the manager wants to try next’. Sometimes that is SAFE sometimes its SCRUM, usually it’s a combination of different things. This isn’t necessarily a bad thing, but there are trade offs. 

The first is standardization. If every team follows a different process it’s difficult to understand what is going on at a management level. Which teams are productive? Which teams are in downward spirals? If you don’t have a standard to judge against you can’t find out. 

Secondly, away team work is much harder. Working with a team that uses the same development process, pipeline setup, programming language and frameworks is easy. On the other hand working in the code base for a team which uses a different language, framework, architecture, etc is very difficult. Not supporting away team work severely limits your ability to integrate internal software components.

Thirdly, Estimates are not possible in this kind of environment. Since the process changes constantly historical data becomes useless. In response to this most companies don’t even keep historical data. The main use for estimates is ensuring that ‘burn down’ charts follow the 45 degree angle managers love. 

Subjective expert predictions are a valid form of estimating software tasks. But if you don’t have historical data to calibrate against estimates devolve into gaming the system. 

When you change how estimates are made, when tickets are considered done and the sprint cadence every 3-6 months there is no way you can have cross company data on productivity. The lack of process empowers management to obfuscate the productivity of their teams. The pursuit of the best process gives technical organizations a great excuse as to why they have no idea if their processes have improved over the last two years or not. 

In this type of environment all judgements have to be made based on subjective gut feelings and corporate politics. You don’t know which VP’s processes are better than the other because neither has any accountability. You don’t know which technical department is more efficient because neither the estimates or logged hours can be trusted. 

‘We’re being agile’ has become the excuse to follow whatever process you want. Instead of ‘people over process’ it has become  ‘no process’.