This document discusses what it means for an academic library to be data-driven. It explains that a data-driven library uses data, rather than intuition, to guide decisions and measure progress. The process involves asking questions, developing a plan to collect relevant data from systems and surveys, analyzing the data to derive insights, and making recommendations. The document provides several library-specific examples, including analyzing circulation data by patron group over multiple years and monthly checkouts by undergraduates. It recommends skills and tools for academic libraries to become more data-driven, such as spreadsheet analysis, visualization, and qualitative data collection.

1. What is a data-driven
Academic Library?

2. Data Driven – What does that mean?
“Data driven means that progress in an activity is compelled by
data, rather than by intuition of personal experience.”
(Wikipedia)
XKCD: HTTP://IMGS.XKCD.COM/COMICS/BOYFRIEND.PNG

3. Process for Data Driven Organizations
Question Plan Collect Analyze Recommend

4. Identify your question
Who is using the library?

5. Develop a plan – Part 1
Refine the question
• Who is coming to the library? Space
• Who is checking out books? ILS
• Who is using electronic resources?
Web

6. Develop a plan – Part 2
Look for data sources
• Space: turnstile data, head-counts, room
reservation systems
• ILS: circulation reports
• Web: web analytics, link resolver data,
vendor usage reports

7. Library Data Sources
Systems
Collections, Acquisitions
Financials
Circulation
E-resources
Resource Sharing
Web Analytics
Gate Counts
Workflow
Reference
Bibliographic Instruction
Cataloging/Metadata
Preservation
Patron
Input
Patron Surveys
Focus Groups
Social Media Analytics

8. Collect Data
If the data exists in a system, retrieve it in
analyzable format.
If the data doesn’t exist, begin to collect the data.

9. Derive Insights
• Analyze and visualize
• Slice and dice the data in a variety of ways
XKCD: HTTP://IMGS.XKCD.COM/COMICS/CORRELATION.PNG

10. Circulation by Patron Group
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
100,000
110,000
10,479
27,565
35,54837,269
44,359
38,505
30,810
42,534
-12%
FY14
29,715
12,315
FY13
76,737
34,048
37,307
FY12
87,585
37,118
FY11
91,359
39,751
FY10
102,793
42,604
FY09
99,457
39,895
FY08
89,641
35,221
FY07
76,936
31,644
FY06
85,089
33,070
Graduate
Faculty
Staff
Other
Carrel
Resource Sharing
Undergraduate
Report run date: 11/25/2013

11. Circulation by Patron Group (%)
39%
41% 39% 40% 41% 44% 42%
44% 41%
10% 10% 8% 8% 7% 7% 7% 9%
9%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
FY09FY07 FY08 FY10 FY11 FY12 FY13 FY14FY06
35%36%
41%41%43%43% 43%40%44%
Resource Sharing
Carrel
Other
Staff
Faculty
Graduate
Undergraduate
Report run date: 11/25/2013

12. Circulation - Undergraduates
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
FY12
35,548
FY11
-22%
FY14
10,479
FY13
27,565
FY07
30,810
FY06
37,307
FY09
42,534
FY08
38,505
37,269
FY10
44,359
3,534
24,805
13,700
18,692
12,118
18,489
9,076
22,773
14,534
23,382
12,166
24,504
12,765
29,413
14,946
28,348
14,186
6,945
Undergrad - Fresh, Soph, Junior
Undergrad - Senior
Report run date: 11/25/2013

13. Library Circulation: Monthly Charges by
Undergraduates - FY2011-FY2014 Comparison
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
Jul Aug Sep Oct Nov
-35%
Mar Apr May Jun
-25%
FebJanDec
2013
2014
2012
2011

14. Recommendations
Use the insights derived from the data to make
actionable recommendations.
XKCD: HTTP://IMGS.XKCD.COM/COMICS/CONVINCING.PNG

15. Skills
• Data Capture
• Programming & database skills
• Business domain knowledge
• Data Analysis
• Spreadsheets
• Reporting tools
• Statistics
• Presentation
• Visualization
• Storytelling

16. Tools
• Quantitative Analysis
• Spreadsheets: Excel, Google Spreadsheets
• Stats Tools: R, SATA, SPSS
• Qualitative Analysis
• ATLAS.ti
• Survey Tools
• Qualtrics, Webmonkey, Google Forms
• Visualization
• Tableau, Many Eyes

17. Big Data – Gartner Hype Cycle 2012

18. Thank You!
Sarah Tudesco
Assessment Librarian
Yale University Library
sarah.tudesco@yale.edu
@studesco