Earned Schedule

Traditionally, EVM tracks schedule variances ''not'' in units of time, but in units of currency (e.g. dollars) or quantity (e.g. labor hours). Of course, it is more natural to speak of schedule performance in units of time, but the problems with traditional schedule performance metrics are even deeper. Near the end of a project -- when schedule performance is often a primary concern -- the usefulness of traditional schedule metrics is demonstrably poor. In traditional EVM, a schedule variance (SV) of zero or a schedule performance index (SPI) of unity (1.0) indicates that a project is exactly on schedule. However, when a project is completed, its SV is always 0 and SPI is always 1, even if the project was delivered unacceptably late. Similarly, a project can languish near completion (e.g. SPI = 0.95) and never be flagged as outside acceptable numerical tolerance. (Using traditional methods, it is not uncommon that an SPI > 0.9 is considered acceptable.)

To correct these problems, Earned Schedule theory renames the two traditional measures SV and SPI as SV($) and SPI($), to indicate clearly they are in units of currency or quantity, not time. Then, time-based quantities SV(t) and SPI(t) are created. A stated advantage of Earned Schedule methods is that no new data collection processes are required to implement and test Earned Schedule; it only requires updated formulas. Earned Schedule theory also provides updated formulas for predicting project completion date, using the time-based measures.

It has also been stated that Earned Schedule provides a useful link between traditional Earned Value Analysis and traditional project schedule analysis -- a link that some say has been missing in EVM theory.

EXTERNAL LINKS

Earned Schedule Web Site {Link without Title}
PMI Sydney Chapter Web Site {Link without Title}

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Earned Schedule