Measuring performance with V-eyeQ

As described in previous blog posts, Infor's V-eyeQ is a complete solution for collection management, offering collection plan management, detailed performance analysis, advisory functions, and integration with the selection process. The ability to create collection plans is described in the previous post. Here we focus on performance analysis: the ability to analyze your collection's performance.

V-eyeQ reports on (circulation) performance via two mechanisms, let's call one of them "push" and the other "pull":

• lists of popular works are available for all works or for (a selected number of) categories (such as e.g. "youth fiction", "adult non-fiction", "music"); so, this includes lists of popular authors, subject headings, and similar; such lists can be built for any (full) authority in the application

• more powerful is the search capability: you can search for any metadata (bibliographic) records, any authority (authors, subject headings, …) or any rule to view its performance; searching can be done via any available bibliographic or authority index and includes facets.

What can you analyze?

V-eyeQ can calculate performance for both individual metadata (bibliographic) titles and for "authorities" (e.g. for each author, subject heading, genre, subject code, etc.). The analysis can be done per location, per location cluster (a combination of locations), per collection cluster (e.g. all large libraries versus all small ones) or for the system as a whole (the total).

What does it look like? - overview

The screen shot shows performance data for the topic "gardening". Most important here is the number included after the "Performance" value. This is a percentile and is explained in more detail hereafter. The bottom line is: the higher this value, the more popular the material is (100 being the highest possible value). The book "100 plants to feed the monarch" (number #4 in the list) has a value of 97, which is very high. Such overviews can be viewed not only for individual works, but also for all "authorities" in the system (e.g. for a particular author, a particular subject category, a particular genre, a particular subject heading, etc.). In this way, staff can easily obtain detailed insight into the "performance" of individual works as well as subjects and authors.

What does it look like? - details

The screen shot shows detail such as number of items, number of loans, how many items are currently on loan, loan frequency, relative performance, age of the collection, etc. One also sees related records (e.g. works with the same title). This screen is available for both all individual works (as in this screen example) and for all authorities (authors, subject headings, genres, subject codes, etc.).

"A percentile is not a percentage"

All (bibliographic) works, all authorities and all rules are ranked as percentiles. Percentiles are used to make interpretation and comparison easier. It is important not to confuse percentile and percentage. An example. Tom participates in an exam. He scores 94% and has a percentile of 100. 94% means that he answered 94 out of 100 questions correct. The percentile of 100 means that Tom is in the top 1% best performers (of all participants). So, the higher the percentile, the higher the (relative) score. A percentile of 96 means that 4% of participants have a better score and 95% have a worse score. A percentile of 12 means: 11% of participants have a lower score, 88% have a higher one.

If the author William Shakespeare has a percentile of 75 at this branch, you know -even without knowing any details- that 24% of authors have a better score and 74% a worse one (at this branch).

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