[Wactclc-alma] Collection Analysis

[Thomas, Kirsti]

There's a book called Analyzing Library Collection Use with Excel that's published by ALA. It's got a bunch of stuff that could be adapted for Alma Analytics

https://www.alastore.ala.org/content/analyzing-library-collection-use-excel%C2%AE

A few years back, a physics faculty member taught me a handy little trick for identifying high demand subject areas-divide the total number of items by the total number of check-outs (or possibly the reverse?). Higher numbers indicate areas that are seeing more use.

Hope this helps.


Kirsti S. Thomas
Library Technical Service Manager
Seattle Colleges
kirsti.thomas at seattlecolleges.edu




From: Wactclc-alma [mailto:wactclc-alma-bounces at lists.ctc.edu] On Behalf Of Skirko, Tria
Sent: Tuesday, January 15, 2019 12:17
To: wactclc-alma at lists.ctc.edu
Subject: [Wactclc-alma] Collection Analysis

Hello All -

We're grappling with some things in collection analysis and I'm wondering if others have developed analysis or processes on this subject.  I'm also open to ideas, advice, etc. regarding what you are doing in collection analysis/circulation assessment/planning/whatever.  Especially how you are leveraging Analytics to find out some things like this:


  1.  Age of the collection +.  One thing we need is to be able to do a more sophisticated analysis where we can account for the fact that some areas simply will have older books. Conversely (sort of), it would be good to have data that would allow us to identify high demand areas that need some attention.
  2.  We want to be able to provide evidence to the accreditation visitors that some of our planning results in improvements in the collection. For instance, we have new four-year degrees and other programs and have been deliberate about collecting in those areas. Has the number of titles in a specific area increased, or is there a qualitative improvement in the area? Same thing (conversely sort of again) goes for areas that we have targeted for weeding.
  3.  For item 2 it would be nice to show a correlation to circulation, whichever direction it is.

So, it seems to come down to being able to target a range of call numbers, get an average age of pub dates (and perhaps a distribution, too), and then be able to get circ trends for that range for dates that include pre- and post-intervention (whether more purchasing, weeding, or both). You may (I hope) have other ways of thinking about this, and I'd love to hear them!


Tria Skirko | Electronic Services Librarian, Faculty
Wenatchee Valley College,  Omak Campus | www.wvc.edu<https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.wvc.edu%2F&data=02%7C01%7C%7C9b6970c87f0b4f5fd60008d67b267e3d%7C02d8ff38d7114e31a9156cb5cff788df%7C0%7C0%7C636831802605016215&sdata=E1%2Fv%2Fk7EQs54TivylGQwHuKdGbcGlBuKztfuPnpVAWw%3D&reserved=0>
tskirko at wvc.edu<mailto:tskirko at wvc.edu> | 509.422.7832

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