ERM

1. INTEGRATING USAGE
STATISTICS INTO
COLLECTION
DEVELOPMENT
DECISIONS
Linda Hulbert and Dani Roach
University of St. NASIG Thomas, St. Paul, MN
2010

2. Overview
Linda Hulbert,
Associate Director,
Collection
Management and
Services
Dani Roach, Head of
Serials and
Electronic
Resource
Acquisitions
Why it matters
What data is
available
Gathering methods
Compiling and
analyzing
Outcomes

3. Assessment? Let me count the
ways…
LibQual
SAILS
Academic Library
Survey
Database evaluations
Usage
Peer comparisons

4. Types of assessment
Quantitative Qualitative
Cost per use
Funds (Disciplines)
Historical trends
ILL data
Impact factors
ROI
Reviews
Availability
Features
User feedback
Weighting
Experience

5. Data, Data, What Data?
“…the amount of time libraries spent on
collecting and analyzing usage statistics
varied from one hour a year to 2,080, with
an overall median of 98 hours. Generally,
more time was spent on collecting the
usage statistics than in analyzing them.”
(Conyers)

6. Formula for creating ‘data’
Usage Statistics
+ Variables for Analysis
+ Methods for Analysis
+
Tools/Systems/Standar
ds
= Data for Analysis

7. How many ways to present the
numbers?
Current print journal
subscriptions cost per
use
Serials Solutions 360
Counter reports
Database evaluation
checklists
Vendor provided
reports
Historical print usage

8. Does the right hand know what the left hand is counting?

9. Sources for usage data
Print
Usually gathered at re-shelving
Tick marks, spreadsheets, ILS item records
Online
Provided by vendor/third party
Push or pull (systems and/or staff)
Multiple levels reported
Other
ERMS statistics (e.g. click-through); web logs

10. Variables for analysis
Title
Funds/Subjects
Order status; format
Cost; subscription period
Other identifiers (ISSN,
vendor, bound vs. current
issues, etc)

11. What is cost?
Annual subscriptions
Multiple payments
Multiple funds
One time archive fees
Hosting fees
Includes single title
databases, e-journals,
and now e-books

12. Methods for analysis
“The challenge most often mentioned
in making effective use of vendor
usage statistics was inconsistency of
the data or lack of standards.” (Baker
and Read)

13. What to include as use?
What about… How to present…
Counter and non-
Counter compliant
Non-journal titles
Zero-use titles
Integrating use for
all formats
Non-Counter
compliant data
Leading articles,
foreign language
titles
Combining data
from variety of
vendors
Fiscal year data

14. Challenges of integrating data
For Costs For Use
Extracting
Exchanging
Redundant entering
Syncing silos
Maintaining
Multiple sources
Inaccurate,
incomplete
Unavailable
Redundant data
Syncing silos

15. How many systems do YOU
use?
ILS (Innovative)
ERMS (Serials
Solutions)
Serials database
(Access)
CSV, text files, Excel
Vendor admin
modules

16. Local tool: Serials Database
Microsoft Access database
Tracks all active serial
subscriptions; maintained
Stores usage data
Use to build use reports,
subscription lists,
database evaluation check
lists, etc.
Built using info from ILS

18. Resources for annual serials
review

19. Example: PRINT subscription cost
per use
1. Collect usage when re-shelving;
scan matching
barcode
2. Use ILS item records to
store current vs. bound use
3. Download usage statistics
4. Massage with Excel
5. Upload into Access Serials
Database; create cost per
use reports

20. PRINT subscriptions – Cost per Use
Report

21. Example: ONLINE subscription cost
per use
1. Pull online use stats
from vendors
48. Upload into ERMS
49. Pull costs from ILS
61. Upload cost into
ERMS
62. Cost per use
integrated

22. Connecting Silos
ERMS
E-Resource
Information (with
fields for cost)
ILS
Cost Data in Order
Records
Merge and
Upload cost
file into ERMS
Output selected
cost fields to an
Access Table
Output template
of subscribed
resources to an
Access Table
Use text files, Excel and Access to move data back and forth as needed.

23. JR1 ONLINE Cost Per Use
Report

24. =(Q4* $Q$2)+(R4* $R$2)+(S4* $S$2)+
(P4* $P$2)

25. The Fairness Factor

26. Capital vs. Operating
Capital/Insurable
Books
Standing Orders
Periodicals
Preservation
Microfilm
Items exceeding
$2,000
Operating/Ephemeral
Pencils
Paper
Computer lease
Travel
Dues
E Resources

27. Sharing the work for collection
management
Roundtables
Business Librarians Roundtable (BLRT)
Social Sciences Librarians Roundtable (SSLRT)
Humanities and Arts Librarians Roundtable
(HART)
Science and Technology Librarians Roundtable
(SATLRT)
Reference Materials Roundtable (R-MART)

28. 240 funds just for materials!
Capital Operating
Books
Microforms
Print periodicals
Standing orders
Preservation/Bindin
g
E-Books
Media
Streaming/DVDs
E-journals
E-resources
E Management
tools
Digitization

29. Work of library liaisons
Maintain web pages with their class
content
Teach
Consultations
Meet with faculty & assist in developing
assignments
Staff Reference Desk (and Chat, IM, Email
ref)

30. Collections work of the liaisons
Determine fund
distribution within their
roundtables
Recommend
cancellations of all
continuations
Weed collections
Purchase books and
expend budget
Evaluate databases

31. All the measuring leads to
decisions

33. Serial change
recommendations

34. Outcomes
Engage the community
Publish the list
Put things on probation
Cancel
Dedupe
Migrate to alternate formats
Change retention
Add new titles

35. Future trends and issues
Ever more granularity of what is counted
More integration of print and online usage
Interoperability and migration options for data
and systems
Continued standards development (SUSHI,
CORE, etc.)
Continued development of tools and systems
(Serials Solutions 360 Counter, Scholarly Stats,
Thomson Reuters Journal Use Reports, etc.)

36. Anything Worth Doing is Worth
Overdoing

37. A&Q
Some of the websites mentioned:
UST Captivate tutorials on moving cost data from ILS to
ERMS
More information on NISO and CORE
Journalprices.com
Eingenfactor.org
Diane Carroll’s Serials Decision Database
QUESTIONS?

38. More info
Baker, G. & Read, EJ.,(2008). Vendor –supplied usage data for electronic resources: a survey of
academic libraries. Learned publishing vol. 21(1) 2008.
Conyers, A, (2010) Usage statistics and online behaviour (2). The E-Resources Management
Handbook – UKSG . http://www.uksg.org/serials/handbook.asp
Feeney, M., Martin, J. Situ, P. (2010). We’ve Got the Data – Now What Do We Do With It? :
Applying
Quality Standards to Assess Information Resources. University of Arizona. Presented ER&L
Austin, TX.
Hulbert, LA . Predicting materials resource needs: a quantitative response to changing curricula.
LibResearch, 5(3) Original site: http://ftp.curtin.edu.au/pub/libres/LIBRES5N3/HULBERT 1996.
Current site: http://dhsws1.humanities.curtin.edu.au/libres/LIBRES5N3/CONTENTS.txt
Kara, B. & Koennecke, J. (2010). Comparison Complexities: The Challenges of Automating Cost-per-
use Data Management. Cornell University. Presented ER&L Austin, TX.
Roach, DL., (2010) Moving Mountains of Cost Data: Standards for ILS to ERM System to Vendors
and Back Again. The Serials Librarian, 58 (1)198–203 Dani Roach Presenter, SHARON DYAS-CORREIA,
Recorder

39. Thank you!
Linda Hulbert lahulbert@stthomas.edu 651-962-5016
Dani Roach dlroach@stthomas.edu 651-962-5408
Many thanks to our graphics guru, Roxann R. Reisdorf!
Thanks to the Shoyen Collection (www.schoyencollection.com) for use of MS 3047, the stone
multiplication table.
Thanks to the Early Office Museum (www.officemuseum.com/) for use of selected images.
Images are copyrighted and cannot be used without the permission of the copyright holder.