In this episode, Asim Razzaq takes on the topic of software estimation and how engineers can improve the estimation quality through calibration and confidence intervals. Most engineers in companies are overestimating or, in some cases, underestimating their software estimates. Overestimation tends to be incorrect most of the time. With the help of Doug Hubbard’s research, Asim can share how engineers can train themselves to achieve more accurate estimation.
[01:19] Software Estimation
[02:02] Ways to Train Estimation
[02:45] Challenges Often Faced on Estimation
[05:37] Asim’s Experience
[09:39] Training From Doug Hubbard’s Book
[10:45] Solutions Based on Training
Show notes:
Missing the Mark
There are many ways to miss the points when it comes to software estimation. This varies depending on the person’s confidence level and mindset towards the estimation and creates their own bias. Some cases occur based on underestimation, overestimation, and similarities-based results. Thankfully, each error has a training method that applies to help better hit the right mark.
Practice Makes Perfect
Luckily for software engineers, estimation can be trained and be improved overtime. With the right tools, you can conquer the constant overestimation and underestimation results. Asim based his techniques on Doug Hubbard’s teaching materials. Here, he shares an estimation story that was a lot more accurate than initial estimation on the population of Italy.
Additional Resource Materials
Doug Hubbard’s Website
