A lot of ink has been spilled on this topic.
The solution is simple: get better at estimating.
Software engineers act as if they're the only ones in the world who are asked to estimate and then held accountable.
It's a skill issue.
replies(6):
The solution is simple: get better at estimating.
Software engineers act as if they're the only ones in the world who are asked to estimate and then held accountable.
It's a skill issue.
Yes, if this is an "every time experience" then there could be a skill issue or possibly some other undiagnosed or unrecognized systemic factor
One can give very accurate estimates of how long it takes to build a brick wall because building brick walls takes time and labor. You can make highly accurate estimates of how long it takes based on how long it has taken to do the exact same task in the past.
But suppose I laid one brick and then could copy-paste it, then copy-paste that into four bricks, then eight, until I have a wall. Then I can copy-paste the entire wall. Once I have a building I can copy-paste the entire building in five seconds.
The ability to copy and paste an entire building is very valuable but how long does it take to create that copyable template? No one knows because it has never been done before.
What makes software hard to estimate is not so much the work, but how much requirements, priorities and resourcing change on the fly. I've worked in places that did quite strict scrum: once the sprint was planned and agreed to, we pushed back hard on our business area if they wanted to change anything. For practical reasons we didn't outright ban it, but for example, if they wanted something new done "right now" they had to choose something of roughly the same scope to be removed. If they couldn't do that, we'd cancel and re-plan the sprint. They hated having to make that choice, so most things just ended up at the top of the backlog for the next sprint.
The other part was our own management wanting to take people out of the team mid-sprint to work on something else. We never said no, but did say "this means we have to cancel and re-plan the sprint (and tell our business area)".
Basically, we made the people making the changes take responsibility for the impact on deadlines. Our estimates in that scenario were quite good (within the bounds of the sprint, at least).
Of course, the longer the estimation window the less well this works. The only way to estimate accurately is to constrain scope and resources, which is not actually what management/business want.
Maybe. Sort of. Skill hints at the problem, but it's more of an experience issue. More experienced developers can give pretty reliable estimates for work they've already done. The catch is, how often do you ask an engineer to do something they've already done? The beauty of software, is that you don't solve the same problem over and over, because if you did, you'd automate it.
So where does that leave us? Well, developers who've seen a lot of different problems recognize when a new problem they see rhymes with a problem they've solved before. That can allow for a very good estimate. But even then, engineers tend to think in terms of best case, or maybe even typical case. I saw a study on this a few years ago, and it showed how often engineers tended to cluster around the median time for solutions. But, since really long tasks, with big error bars have a tendency to really skew timelines, the solution averages was much farther from these median times.
Believe it or not, lawyers have this problem too. They are taught in law school to come up with an estimate based on expected effort, then they apply a formula similar to: double the estimate, then increase the time units. So a 5 hour task becomes 10days. A 2 week task becomes 4 months. Mind you, this isn't the amount of billable hours they're predicting, it's the amount of calendar time that a given task will take until it's complete. This ends up taking into account a lot of variables that lawyers have no control over. Things like court scheduling, or communication delay. I suspect it also takes into account blind spots we humans have around time estimates in isolation. Like, 1 task, if you can focus on it can be done in so many hours. But if you have to do 5 similarly sized tasks, it takes more than 5 times as long, simply because it's easy to expend resources like brain power, and the estimate ignores the refractory periods necessary once the task is completed. (BTW this was one of the problems with the very first stop watch study in the rail yard, where the rail workers didn't work at their sustainable pace, but worked at their depletion pace).
Software development is not surrounded by this sort of infrastructure or codification. My discovery process establishes these lines of communication, and I have no idea when I'll uncover a black box or when one will be imposed upon me.
It's still a "skill issue" but it's more about knowing how long it will take you or your team. If you don't have the relevant experience with the tech or with the team, you can't really gauge how long something will take.
Before I estimate larger projects I always ask who will be on my team. The estimate is very different depending on the answer.
Contractors have to plan for surprises as well. The thing is they've done enough similar work to understand the risks and account for them in budget and timelines.
I think a lot of software engineers, possibly because of the classical world they inhabit, are reluctant to look at things as probabilistic. Your estimate can take into account unknowns you just need to estimate the likeliness of encountering certain snags and the penalty they will impose.
Software is the same thing. There are unknowns but there aren't unlimited possibilities.
I heard someone summarize this as saying, a surgeon may perform the same surgery over and over for decades, while if a programmer does something more than a few times, it becomes an app (or library, etc).
In a sense, unless we are building the same thing we've built before, we are, by definition, always operating at the limit of our abilities.
There is a spectrum of complexity: simple, complicated, complex. These can be framed in terms of ergodicity and you can search for Barry O'Reilly residuality theory if you want to go down this rabbit hole.
In a simple system we can easily predict the future states based on knowledge of past states. In a complicated system, we can also predict future states based on past, but it requires expert knowledge, though it's still fundamentally able to be understood (e.g. SpaceX rockets). These are both ergodic systems. Complex systems are non-ergodic.
Construction is a complicated system that exists within a complicated environment.
Software is a complicated system that exists within a complex environment.
Complex environments can be wrangled along three dimensions: constraining the environment until we can treat it as "only complicated", evolutionary survivorship via random stress and remediation, and avoiding commoditization.
Construction benefits from all three. Environments are constrained to enable the things we build to operate (cars work mostly on paved roads). There is a history of evolutionary survivorship spanning millennia. And construction is less easily commoditized (people typically do the same thing they did yesterday, and repeat for decades). All of this contributes to the ability to a better ballpark estimate.
Software primarily only attempts to constrain the computing environment in which the software runs: If you build your app to run in a container that can tolerate getting yanked and reincarnated elsewhere, you're golden, i.e. cloud computing is an example of constraining a complex environment until it can be treated as "only complicated". But the business environment remains complex and largely unconstrained. We attempt to constrain it via "give us your requirements", but that's more of an anchoring or negotiating technique than actually addressing the complex business environment. Software doesn't have millennia of evolutionary battle testing. And software is more easily commoditized, meaning if you do the same thing you did yesterday on repeat, that turns into a library or an app, so fundamentally you're always being pushed into novel territory, which therefore is less battle tested by evolutionary survivorship. All of this contributes to less clear estimates in software.