At a client site in Sacramento, CA off and on since last December. Driving back to hotel tonight, there was a radio show on the current Uniform California Earthquake Rupture Forecast (Version 3).
A former Colorado neighbor is an earthquake researcher and we've had discussions about probabilistic estimation of complex systems and complexity sciences
The notion that we can't predict - to some level of confidence - outcomes in the future is of course simply not correct. Earthquake prediction is not technically possible in the populist sense. It's a complex probabilistic process.
Making forecasts - estimates of future outcomes - for software development projects is much less complex. The processes used to make these estimates range from past performance time series to multi-dimensional parametric models. Several tools are available for these parametric model. Steve McConnell provided an original one I use a decade or so ago. Steve provides some background on making estimates where he speaks of the 10 deadly sins
- Confusing targets with estimates - the bug-a-boo of all #NoEstimates advocates. It's simple - DON'T DO THIS.
- Saying yes when you mean no - no quantitative data and guessing mans bad estimates - DON'T DO THIS
- Committing Too Early - use cone of uncertainty
- Assume underestimating has no impact on project - DON'T DO THIS
- Estimating in the Impossible Zone - an optimistic estimate has a non-zero probability of coming true
- Overestimating from use of new tools - DON'T DO THIS
- Using only one estimating technique - DON'T DO THIS
- Not using estimating software - DON'T DO THIS
- Not including risk factors - the the primary sin of the simple small samples of stories or story points used to linearly forecast future performance. DON'T DO THIS.
- Providing off the cuff estimates - this is called guessing. DON'T DO THIS.
When you need to estimate - as you do in any non-trivial project - make sure you're not committing any of the 10 sins Steve mentions.
So Why The Earthquakes and SW Estimates?
One process is very complex and emerging science. One is a well developed mathematical process.
There is so much misinformation about estimating software development, it's hard to know where to start. From outright wrong math, to misuse of mathematical concepts, to failure to acknowledge that estimates aren't for developers, they're for those paying the developers.