A few thoughts on estimating. I had a conversation with someone yesterday who asked me how I worked with the engineers on estimates. My answer shocked him, I think. I wanted to expand here on what was a throwaway conversation:
- My favorite story about estimates is about the Sydney Opera House, as told by Nicholas Nassim Taleb in The Black Swan. First, you should know that construction is incredibly well-understood and for some types of projects builders can repeatedly complete them within 5% of the estimated time.
The Sydney Opera House, started in 1959, was scheduled to be completed in 1963 for $7M (Aus). Actual construction took nearly four times the original estimate – it actually finished in 1973 (10 years late!) – and it cost more than 12 times the original budget at $104M (Aus). And of course, the Opera House was only 1/3 of the original project. If builders can be that far off, simply because it’s never been done before, why should we think that we should be able to estimate software, which always by definition has never been done before?
- There is a fundamental disconnect between estimates and interesting things. Interesting things are unpredictable. User stories are estimatable, therefore not interesting.Â
- Estimates are not a standard distribution. They are really screwed up distribution where the likely value is way the heck out there beyond the value you think it should be. (And very occasionally, extremely rarely, things go a lot faster than you expect.)
- I prefer timeboxes, and for interesting things, we get done what we get done in the timebox. The art of product management is figuring out what to do in the timebox. Note: this works much better in software than in construction. Buildings have to obey the laws of physics, but software doesn’t. There is no such thing as a Minimum Viable Product in construction – you can’t build a fancy roof until you build the structure to support it. But you can do that in software. There’s a lot of software out there that is essentially fancy roofs floating in the air.
- Think about failure, which is so important in innovation. Failure is of course immune to estimates, by definition.
For example, let’s assume I can get a decent estimate for doing something interesting (which we know I can’t, but hang on). Then we do it. It only takes twice as long as we estimated! (That’s a great result.) Unfortunately, given reality, it’s wrong, and has to be done again. It was a failure, but it was a productive failure. We learned a lot. We didn’t get the feature to market when we expected to, but if we’d put that version into the market, it would have been bad in oh so many ways.
So we start doing it again, and mostly we have to start from scratch, but we did learn some things in version 1. We also realize we can get a little bit of version 2 out to early adopters. It’s definitely not a full feature – they have to do manual work to get the value, but they are willing because it’s so useful to them. And we learn some stuff, and we end up building version 3, instead of version 2, because we got some great feedback that makes it even better. Versions 1 and 2 are sunk costs, and they are PAINFUL, but because we did them, we have version 3, and it’s beautiful. And it only took us four times as long to get the feature out as originally estimated, which is actually a pretty good result.Â
The title of this post might have been a little misleading. I suspect I may have created a firestorm. I can’t wait to hear what you think!
"Perhaps the main reason we were behind schedule and over budget was because budgets and schedules are based on previous experience with similar projects. We really didn't know how much it would cost to build or how long it would take." — Tom Kelly, Grumman, on building the lunar module for the Apollo program
Estimates are terribly difficult, particularly when the work is so different from anything your team has done before. That's why dev teams now use RELATIVE estimates–"this" is harder than "that"–instead of time and costs estimates.
Exactly right. Think about how Edison might have estimated how long it would take to get a working light bulb to market. Would he have even tried? Or did he just keep working at it, noticing if he was making progress generally (despite thousands of failures on the way), until he was done? (Or until he had the MVP for the lightbulb?)
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I love the versions 1, 2, and 3. I once worked with a developer who said, "I always do 3 versions of the code. I can do 3 versions by planning for it, or 3 versions by not planning for it and being surprised and behind. I would rather plan for 3 versions." This was back in the '80s.
He went on to say that he could design one version, code one version, fix one version. He kind of like that, but he didn't like all the fixing. He preferred prototyping one version (his words), throwing that one away, designing one version, coding one version. In other words, learning from his first effort, using that learning to design the "right" version, and then coding it. He wrote quite clean code, and he never gave me an estimate longer than a month.
He almost always gave me interim milestones of two weeks or less. I was the project or program manager, which was why he gave me estimates. Sometimes he said, "I don't know, but I will know something in two weeks.
Johanna – That sounds like a great technique, but one that would be very hard to sell to an executive stakeholder (even though it's reality-based). How did you deal with that?
stimates are terribly difficult, particularly when the work is so different from anything your team has done before. That's why dev teams now use RELATIVE estimates–"this" is harder than "that"–instead of time and costs estimates.