This document summarizes a presentation on assessing electronic resources through all stages of the collection workflow process with a focus on the customer. The presentation covered concepts of focusing on customer needs, examples of different types of assessment data that can be collected within various library workflows, and an activity where attendees proposed and selected hypothetical "electronic animals" for a library collection based on customer input. The goal is to assess electronic resources holistically at each stage of the process in order to best meet customer needs and preferences.

1. Focusing on the customer: assessing electronic resources
through all stages of collection workflows
Northern Ohio Technical Services Librarians Spring Meeting
April 4, 2014
Juleah Swanson
Assistant Professor
Acquisitions Librarian for Electronic Resources
The Ohio State University
Swanson.234@osu.edu
“Social Media Information
Overload” by Mark Smiciklas
http://www.flickr.com/photos/inter
sectionconsulting/7537238368/

2. DINOSAURS! HIGH FIVE!Cool things found at OSU

3. OSU Library Love

6. Agenda
• Concepts
• Examples
• Activity
• Discussion

7. PRESENTATION TITLE:
Focusing on the customer: assessing
electronic resources through all stages
of collection workflows

8. Source:
http://library.osu.edu/sites/exhibits/borninadversity/
“Shaping the future of education in the History Classroom Gabrielle
Sutherland + students” by New Media Consortium CC By:
http://www.flickr.com/photos/nmc-campus/5100940630/
Focus on the customer

9. Assessing
Source: by kotonamii
http://kotonamii.deviantart.com/art/Information-Overload-
388665814

10. Electronic Resources
“big-data_conew1” by luckey_sun
http://www.flickr.com/photos/75279887@N05/6914441342/

11. workflow
Workflows
“workflow at the most basic level” by wlef70 http://www.flickr.com/photos/wlef70/6818768830/

12. Why does it
matter?
“Information professionals and
librarians in particular are in a
unique position to bridge the gaps
that exist between people,
information and technology. ”
https://ischool.uw.edu/academics/mlis/what-is-library-science

13. What are the stages in collection
workflows for Electronic Resources &
what are the possible forms of
assessment?

14. LibQual Data
Reference Statistics
Instruction
Evaluations
General Patron
feedback
Usage/COUNTER
Stats
Trouble/Problem
Reports
Website
Analytics
Citation
Analysis
Discovery
Cataloging
IT workflows
Public Services
Reference
Instruction
Subject Librarian
workflows
Acquisitions
Electronic
Resource
Management
workflows
Types of assessment data found within workflows

15. Source:
https://www.flickr.com/photos/opensourcewa
y/4371000486/in/set-72157628736972485/
What customer feedback can reveal
about our work

16. New Resource Proposal Process
• Subject Librarian requests a new resource &
provide justification on why OSU should buy
• Committee recommends resources to buy
• Acquire and monitor usage

17. Activity Time:
Electronic Animals
Objective: To determine what Electronic Animals
to buy for the NOTSL library.
Customer population is everyone in this room.
• Need 4 Volunteers (for a paper based activity)
– 2 Subject Librarians
– 2 Selection Committee Members

18. Subject Librarians
• Responsible for your subject matter on either:
– Cuteness
– Intriguing/Interesting
• Objective:
– Using your available resources, make a request for
electronic animals, with a justification
– Give request to selection committee

19. Selection Committee Members
• Responsible for reviewing subject librarians
requests & purchasing, within budget, the
finalized list of electronic animals for the
NOTSL library
• Give finalized list to me.

20. Audience Participation
http://tiny.cc/notsl
If you have a laptop, tablet or smartphone, visit this site & click on your
favorite electronic animal. Multiple clicks for favorites encouraged.
Think about why you like the animal, is it the cuteness & or the intrigue?

21. Discussion & Debrief

22. Final Thoughts:
• Focusing on the customer is our
professional responsibility
• Assess electronic resources holistically
• Think about what the data doesn’t tell us