Evidence-based Scheduling
Encyclopedia
Evidence-based Scheduling is a software estimation approach created by Joel Spolsky
, a commentator on software engineering principles.
One of the core ideas of Evidence-based Scheduling, that adds to the normal estimation practices, is the idea of including all time spent, regardless of relevance.
Most people, when estimating, measure the time they actually spend on a project - classic Time Accounting categories such as cited in McConnell's Software Project Survival Guide do not allow for accounting for non-project activities. Whilst McConnell goes on to include less obvious activities such as holidays, sick days and project support, he and most others identify such as activities to be separately recorded.
Recording and attempting to budget
for secondary activities often leads to political pressure to drop such activities. In practice, people find themselves unable to avoid them and compensate by working overtime
.
As Spolsky points out , your bosses' stories about his fishing trips, or model helicopter, are both a time-sink and politically dangerous to put on a time-reporting system.
The key insight in Evidence-based Scheduling is that the only thing which needs measuring is the actual delivery of tasks. Over time, it is assumed that all other distractions will average out.
For the purposes of estimation, variations due to interruption will show up as inaccuracies in estimation and will be compensated for by statistical analysis. The reasons for anomalies may come out if the organisation wishes to dig deeper into why people have irregular estimates.
The appeal of this idea is simplicity - the amount of evidence to be created is simply the elapsed time between completing tasks and, another vital point, time spent debugging is applied back to the original task.
Another core idea is the use of the Monte Carlo method
to predict project completion dates. This method evaluates how reliable previous estimates have been. Instead of a single completion date, the method results in multiple possible completion dates, each with an associated probability of being correct.
Joel Spolsky
Avram Joel Spolsky is a software engineer and writer. He is the author of Joel on Software, a blog on software development. He was a Program Manager on the Microsoft Excel team between 1991 and 1994. He later founded Fog Creek Software in 2000 and launched the Joel on Software blog...
, a commentator on software engineering principles.
One of the core ideas of Evidence-based Scheduling, that adds to the normal estimation practices, is the idea of including all time spent, regardless of relevance.
Most people, when estimating, measure the time they actually spend on a project - classic Time Accounting categories such as cited in McConnell's Software Project Survival Guide do not allow for accounting for non-project activities. Whilst McConnell goes on to include less obvious activities such as holidays, sick days and project support, he and most others identify such as activities to be separately recorded.
Recording and attempting to budget
Budget
A budget is a financial plan and a list of all planned expenses and revenues. It is a plan for saving, borrowing and spending. A budget is an important concept in microeconomics, which uses a budget line to illustrate the trade-offs between two or more goods...
for secondary activities often leads to political pressure to drop such activities. In practice, people find themselves unable to avoid them and compensate by working overtime
Overtime
Overtime is the amount of time someone works beyond normal working hours. Normal hours may be determined in several ways:*by custom ,*by practices of a given trade or profession,*by legislation,...
.
As Spolsky points out , your bosses' stories about his fishing trips, or model helicopter, are both a time-sink and politically dangerous to put on a time-reporting system.
The key insight in Evidence-based Scheduling is that the only thing which needs measuring is the actual delivery of tasks. Over time, it is assumed that all other distractions will average out.
For the purposes of estimation, variations due to interruption will show up as inaccuracies in estimation and will be compensated for by statistical analysis. The reasons for anomalies may come out if the organisation wishes to dig deeper into why people have irregular estimates.
The appeal of this idea is simplicity - the amount of evidence to be created is simply the elapsed time between completing tasks and, another vital point, time spent debugging is applied back to the original task.
Another core idea is the use of the Monte Carlo method
Monte Carlo method
Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to compute their results. Monte Carlo methods are often used in computer simulations of physical and mathematical systems...
to predict project completion dates. This method evaluates how reliable previous estimates have been. Instead of a single completion date, the method results in multiple possible completion dates, each with an associated probability of being correct.