Effectively Applying Usage Statistics in E-Resource Collection Development:

1. Effectively Applying Usage
Statistics in E-Resource
Collection Development
Using Evidence and Outreach in Decision-
Making
ACRL-MD – New Identities: Adapting the Academic Library
November 14, 2014
Randy Lowe – Collection Development, Acquisition & Serials Librarian, Frostburg State University

2. Overview
 Why E-Resources Assessment?
 Usage Statistics – Types, Reports,
Collection
 Assessment: Evidence & Outreach
◦ Applying usage statistics to collection
management decision-making
◦ Engaging librarians, faculty and
administrators in the process

3. Why E-Resource
Assessment?
 Libraries have historically measured use
of services (circulation statistics, re-shelving
counts, gate counts, etc.)
 The technology upon which e-resources
reside inherently allows for extensive
collection of usage data – and
assessment of that use
 Assessment of use data supports
evidence-based collection management
 Libraries operate in a challenging fiscal
environment – demonstrating e-resource
value and fiscal responsibility is a must

4. Effective E-Resources Assessment
 Two essential elements in conducting
effective e-resource assessments:
◦ Efficient and Accurate Data Collection
◦ Clear and Succinct Analysis
 E-Resource assessment is more than
just collecting usage statistics – it is
applying them in the making of sound
management decisions regarding
library resources
 Usage statistics measure volume, not
value of resources

5. What Can You Do with E-Resources
Usage Statistics?
 Track usage / Assess overall collection use
 Track expenditures / Figure cost-per-use
 Track turnaways
 Assess title, subject, publisher and other usage
elements
 Identify user behavior trends
 Assist in making collection development
decisions, including acquisition model selection
 Effectively advocate for resources – especially
if assessment is tied to institutional
goals/strategic plan, curricular initiatives,
student learning goals

6. Types of Usage Statistics Reports and
When to Use Them
 Vendor-Defined
◦ Analyzing usage data from a single vendor
◦ Obtaining cost information
◦ Comprehensive data files make it easy to
analyze combinations of various data
elements [Example]
◦ When COUNTER reports do not provide
adequate detail
 COUNTER-Compliant
◦ Analyzing usage data across multiple
vendors
◦ Ensuring data integrity though adherence to
recognized standards

7. Collecting Usage Data
 Define Objectives
◦ What you need to know or are trying to
find out should drive your data collection
decisions
◦ Collecting Usage Statistics can be a major
time commitment
 Use your assessment objectives to help you to
not only determine what data to collect, but
when you have collected enough data to
analyze
 Properly balancing time and resources
dedicated to both data collection and analysis
is vital

8. Collecting Usage Data
 Various vendors present data differently
– this can present a challenge not only
across vendors, but even with combining
data elements from a single vendor
 Manipulation / Formatting of raw data will
likely be necessary
 Example – COUNTER BR1 Report +
Acquisition Type Data + Cost Data
Compiled Manually = Data for
Assessment
 Schedule time(s) to collect data
 Vendors’ archival policies for maintaining
usage statistics vary

9. Assessing Usage Data
You have usage data – What do you do
with it?
 It is easy to get overwhelmed in usage
data – analysis should be guided by
your assessment objectives
◦ What do you want/need to assess?
◦ What questions are you trying to answer?
◦ Who is your audience?
 Have a purpose for using your data

10. Assessing Usage Data
 Assessment is most powerful when it
is tied to an action or potential action
(including requests)
 There is no single method for
assessing usage statistics in every
case – the “right data” to analyze and
include in your report is that which will
support your assessment objectives

11. Usage Data Analysis
 Data analysis should be thorough, but
presented succinctly
 Conclusions, trends, etc. should be
clear and verifiable
 Beware of pre-conceived notions,
perceptions or opinions – hypotheses
can be both proven and refuted
 State known limitations of the data you
have collected and how they may
affect your analysis

12. Using/Applying Evidence:
Writing Your Report
 Know your audience
 Include a brief purpose/introduction
 Write clearly and succinctly
 Reported usage data should support
the purpose of the assessment
◦ Only include data that supports your
stated objectives – don’t include all
collected data; it won’t be read by
administrators

13. Using/Applying Evidence:
Writing Your Report
 Reported usage data should support the
purpose of the assessment (continued)
◦ Include data within the text of your report where it
is necessary and provides clear evidence for the
points you are making
◦ It is usually more effective to include visual
representations of (charts, graphs) rather than
just figures within the text of reports
◦ Larger tables and data sets, if necessary to
include, are best placed in appendices
 Conclusions and recommendations should be
easily identified and based on the evidence
presented
 State action and/or desired response clearly

14. Using/Applying Evidence:
The Frostburg Experience
 Effectively applying e-resources data to
collection management has been an
evolution
 The lay of the land – 2007
◦ We had data (searches & link resolver)
◦ Study to compare journal costs by format
◦ Data sat in a vacuum outside of annual
database budgeting
 Needed to establish a frame of reference
to begin applying usage statistics in
engaging faculty and administrators

15. Evidence & Outreach Example 1:
Faculty Survey – 2007-2008
 Faculty had not been previously engaged
systematically in collection development efforts
 User behavior as demonstrated in link resolver
statistics indicated that online full-text was
preferred by users
 Library determined periodicals and standing
orders should be migrated to online format, but
which ones?
 Fall 2007: Faculty surveyed regarding value
(content) and usefulness (format) of journals,
standing orders, databases.
 Spring 2008: Results of survey matched link
resolver usage statistics
 Subscription Cancellations, additions, format
migrations made over next 5 years

16. Evidence & Outreach Example 2:
Underutilized Journals
 Library began collecting full text article
retrievals in 2009-2010 (and re-shelving
counts in 2011-2012)
 All journal subscriptions are reviewed
by librarians annually
 Faculty are involved in second level of
review for underutilized subscriptions
 Objective is to use the process as a
means for continued dialogue with
faculty in collection development

17. Evidence & Outreach Example 3:
Collaboration with Academic
Depts  Academic departments becoming
increasingly engaged in e-resource
subscription discussions, including funding
◦ Chemistry – CAS SciFinder
◦ Visual Arts – Artstor
 Current collaboration is with Biology
◦ Department not satisfied with current e-resources
◦ No funds available for additional resources
◦ Reviewed use of current journal subscriptions
and content of requested databases
◦ Department suggested journal cancellations to
fund databases
◦ New e-resource scenarios developed

18. Evidence & Outreach Example 4:
E-Book Assessment
 Frostburg State University: Report
overall use and expenditures of e-books
over time; implement the most cost
effective DDA acquisition model(s)
[Report]
 USMAI Consortial E-Book Pilot: Assess
the effectiveness of a specific DDA
acquisition model for the consortium; use
and expenditures by consortium
members and user types; identification of
possible future program funding models
[Report]

19. Thank You
 Questions?
 Contact Information:
Randy Lowe
Frostburg State University
rlowe@frostburg.edu