In April 2010 the Cranfield University Libraries embarked upon a review of the electronic journal packages. Following research into usage metrics employed at other institutions a number of key performance indicators were developed and assessed using a standardised Excel template. The resulting information helped to inform a cancellation decision.
Using Grammatical Signals Suitable to Patterns of Idea Development
Evaluating the Big Deal: What metrics matter?
1. Evaluating the Big Deal:
What metrics matter?
Effektivare hantering av statistik för
e-resurser med Excel
Stockholm, 9 May 2011
Selena Killick
Library Quality Officer
2. Evaluating the Big Deal:
What metrics matter?
Disclaimer: This presentation will not
provide one single answer to the above
question!
3. Introduction
• Evaluating the ‘Big Deal’
• Researching and choosing metrics
• Capturing the data
• Reviewing the results
• Next steps
4. Cranfield University
• The UK's only wholly postgraduate university focused
on science, technology, engineering and
management
• One of the UK's top five research intensive
universities
• Annual turnover £150m
• 40% of our students study whilst in employment
• We deliver the UK Ministry of Defence's largest
educational contract
5. My Role
(amongst other things)
• Provide analysis and advice on customer feedback
and library performance data:
• Key Performance Indicators
• SCONUL Statistics
• LibQUAL+
• Enquiry monitoring
• Focus groups
6. My Usage Statistics
Journey
• 2005: UKSG Usage Statistics training course
• Personal interest but limited application
• 2007/08: Need to report usage statistics for SCONUL
Statistical Questionnaire1
• 2008: First budget reduction
• 2010: Review of the Big Deals
9. Evaluating the
‘Big Deals’
• Resources budget cut predicted
• Small publishers and book budgets
previously reduced
• Review of ‘Big Deals’ required
• Initial discussion focussed on cost-per-
download
• More analysis needed
10. Researching Metrics
• Angela Conyers:
• UKSG E-Resources Management Handbook2
• Analysing Publisher Deal project from Evidence
Base3
• Cliff Spencer:
• Lib-Stats discussion list and archive4
• A librarian’s view of usage metrics5
• Managing and Understanding Data in Libraries
(MUDL)6
11. Metrics, Metrics, Metrics:
Basic Metrics
• Number of titles within a package
• Total annual full-text downloads
• Downloads per Full-Time-Equivalent (FTE)
student/staff/total
• Number and % of titles in usage group
zero/low/medium/high
• 20 most popular titles as % of total downloads
13. Metrics, Metrics, Metrics:
Value Metrics
• Average number of requests per title
• Total cost as % of information provision expenditure
• Average cost per title
• Cost per full-text download
• Average cost per FTE student/staff/total
14. Metrics, Metrics, Metrics:
Print Metrics
• Costs by format and as % of information provision
expenditure
• Number of print subscriptions
• Full-text downloads of print titles
• Number and % of print subs in usage group
zero/low/medium/high
• Average number of requests per title
• Average cost per title
• Cost-per-download by title
• Number and % of print subs in Top 20
16. Get Organised…
More metrics than I knew what to do with!
1. Become an Excel whizz
2. Download relevant reports and store
locally
3. Design Excel template
4. Run the analysis on each package
5. Benchmark between packages
6. Report back to Library Management
17. Downloading Statistics
• Get organised
• Create local files to save and store usage reports
(publishers will not save them forever)
• Gather your usernames and passwords
• Software now on the market to manage this for you
• In the UK: Joint Usage Statistics Portal7
18. Excel Template
• Two main data sources:
• COUNTER JR1
• Publisher/Subscription agents financial report
• Automated as much as possible
• Match formulas working with ISSN to link title price to
usage/holdings
• All metric calculations are worked out when the data
sources are added
19. Handy Excel Formulas
= Sum • Sums the entries in a range
= Average • Calculates the average value of a range
= Count • Counts non-blank numeric values in a range
= CountA • Counts non-blank numeric or text values in a range
= CountIF • Count the number of values with a criteria
= SumIF • Sums the values in a range with a criteria
= Min • Calculates the lowest value in a range
= Max • Calculates the highest value in a range
Key Formulas:
LOOKUP VLOOKUP MATCH
21. A Margin of Error
• When to measure from/to; calendar,
financial/academic, or contract year?
• How many titles do we have?
• Do we have access to all of the ‘zero use’ titles?
• Which are our subscribed titles?
• What about the aggregator usage statistics?
• Do we trust the usage statistics?
• What is the size of the target population?
Sometimes you’ve got to work with what you’ve got.
22. Key Performance
Indicators
• Overview of basic
and value metrics
• Basis for
comparing metrics
against each other
• Quick-glance %
change column
23. Top 20
• What are the highest used titles within the package?
• How many do we subscribe to?
• Does this list change annually?
• Which titles are consistently being used heavily?
• Which subject areas do they support?
• How much do they cost?
24. Print Titles
• Trends in
• Usage
• Title price
• Cost per use at title level
• High / Medium / Low groupings for all three
• Problems with gaps in the data from Subscription Agent
25. Metrics, Metrics, Metrics…
but what metrics matter?
• Average cost per title?
• Cost per download?
• Number of titles with high use?
• Percentage of zero use titles? (The long tail)
• Cost to replace the highly used titles?
• ILL equivalent costs if titles weren’t taken?
• Downloads per FTE in target audience?
• Cost per FTE in target audience?
28. Metrics Used in
Decision Making
• All of them tell a story about the resource
• Danger of relying just on cost-per-download
• Highest c-p-d had second highest usage
BUT:
• Usage statistics are only two dimensional, they should never be
used in isolation
• Other factors that must be used in decision making process
includes qualitative local knowledge e.g.
Local academic’s ‘top journal’ for their discipline
Small (but income generating) research areas
Groundbreaking research information needs
29. So, what did we
cancel?
• Out of the four packages under review,
one had a cancellation date in this
financial year
• Other resources were cut, but we
successfully lobbied to renew the one
‘Big Deal’ for another year
• All four packages now have the same
renewal date for the next financial year…
31. Qualitative Metrics
• Subject coverage
• Overlap with other packages / Uniqueness
• Unique selling points
• Titles Cranfield publish in within package
• Ease of use
• Known users of the package
• Authentication options
• Content for which access is retained post cancellation
32. Looking Ahead
• Systematic review of all resources to demonstrate
smart procurement
• Qualitative research into customer expectation
• Review of resource ‘uniqueness’
• Benchmarking resources
• Between each other
• With peer institutions