creating actionable data using alma analytics dashboard · libraries and learning services tetumu...
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Libraries and Learning ServicesTe Tumu Herenga
Beyond the numbers: Creating actionable data using Alma Analytics dashboard
Aleksandra PetrovicIT Product Owner
ANZREG 2019 ConferenceGold Coast, 23-24 October
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Changing Era in Libraries
Collection Variety
Adjusting Budget
Use of Spaces
New Trends
Changes in Behavior
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Collections 2018-2020
Refocus LLS collection management towards digital collections and discoverability
Refocus access to our collections so that current and high-demand material is easily accessible online and on-campus
Create a high quality on-campus experience focusing on fewer points of presence, with a more consistent and modern customer experience
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Data Driven Decisions
WISDOM
KNOWLEDGE
INFORMATION
DATA
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Questions to AnswerWhich titles are old and not recently used?
How much potential duplication is in our collections?
Which titles are “at-risk”?
How much of our collections have zero or low recorded uses?
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How We Did It in The Past?
CREATING REPORTS
DATA CLEANING
ANALYSINGREPORTS
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Power-Audience Matrix
Dashboard & Reports
Reports
Dashboard
Dashboard
KEEP SATISFIED
MONITOR
MANAGE CLOSELY
KEEP INFORMED
LEVEL OF INTERESTLE
VEL
OF
INFL
UEN
CE
Low HighLo
wHi
gh
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Why Alma Analytics?
CONTINUOUS IMPROVEMENT
ALL DATA UP TO DATE
AVOIDING DATA EXPORT
COST AND TIME
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Challenges and Solutions
LC SUBJECT REPRESENTATION
HISTORICAL USAGE
YEAR OF PUBLICATION
EMBEDDED REPORT
MULTI-VOLUME WORK
EXPORTING ISSUE
SIZE RESTRICTION
BETTER FORMATTING
Challenges and Solutions
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Overview – By Subject
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Overview – By Subject Graph
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Overview –By Subject Table
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Overview – By Publication Year
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Overview – By Publication Year
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Overview – Possible Duplicates
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Overview – Sample Weeding
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Overview – Preservation
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Collection Measure – Quick Stats
MONOGRAPHS COUNT
ZERO USES
LOW USES
MEDIUM USES
OVER 10 YEARS OLD
120,000
54%
POSSIBLE DUPLICATES
43,160
1%
2% 38%
42%
58%77%
81%
1%
4.5%
FINE ARTS LIBRARY
EDUCATION LIBRARY
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Publication Year Possible Duplicates
Historical UsageAlma Usage
Accession Year
Weeding Methodology Parameters
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Weeding Methodology Types
Soft Methodology
Medium Methodology
Hard Methodology
Retain
Relegate
Intervention
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Overview Scenarios
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Possible Improvements
Possible Duplicates
Better Organisation
Data Cleanup
P to E MappingWeighted Indexes
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Future
“Data is a precious thing and will last longer than the systems themselves.” Sir Timothy John Berners-Lee inventor of the World Wide Web