Comparison Complexities: The Challenges of Automating Cost-per-use Data Management
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Comparison Complexities: The Challenges of Automating Cost-per-use Data Management

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Cornell University has had mixed results obtaining accurate cost-per use data for e-journals. In many cases, it is a simple feat of comparing the subscription cost to the COUNTER comliant usage......

Cornell University has had mixed results obtaining accurate cost-per use data for e-journals. In many cases, it is a simple feat of comparing the subscription cost to the COUNTER comliant usage data, but as we look deeper, and we continue to attempt to automate this process as much as possible, we uncover complexities that make this a considerable challenge. We will share our experiences and help attendees to better understand the complexities involved.

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  • Multiple platforms – did we pay once for several? Did we pay several times? Some are part of a package Although COUNTER compliant, YTD Total may not mean the same thing from pub to pub Journal Report 1a – Number of Successful Full-Text Article Requests from an Archive by Month and Journal Journal report 5 - Number of Successful Full-Text Article Requests by Year and Journal
  • How are titles related in cost terms. Part of a package, combined titles, Ability to add/edit.

Transcript

  • 1. Comparison Complexities: The Challenges of Automating Cost-per-use Data Management Bill Kara – Head, Electronic Resources and Serials Management Jesse Koennecke – Electronic Resources Librarian
  • 2. Cost per Use Data
    • (Much of) The Data is out there
    • The Data could be used for collection and collection use analysis
    • There are existing and growing expectations and assumptions that it could be provided
  • 3. Cost per Use Data – Not so easy
    • The Data is out there, but matching the payment data with Counter usage data is not so easy
      • it often resides in different systems and different formats
      • Payments are made in different ways (single title, packages (both large and small), one time payments (backfiles, some reference items, ebooks …)
    • The Data could be used for collection decisions – but is rarely (for us) readily available and comparing titles within or between packages/publishers is not always straightforward
  • 4. Cornell University
    • Technical Services staffing -- drop of approx. 25% since 2004
    • Materials Budget FY2009 $19,867,000
    • Materials Budget FY2010 minus approximately 7%
    • Selectors 50+
    • FY 2010 Budget cuts – had immediate impact on staffing, policies & priorities, size and nature of cancellation reviews
  • 5. Statistics and Cost per Use
    • How to manage, prioritize (triage) statistics/cost per use requests?
      • Individual selectors and teams, Research & Assessment Unit, Technical Services
      • There is not a systematic or comprehensive review of all usage and cost per use
    • Examples of 2009 Reviews:
      • Print approval plans – using circulation data for cost per use analysis
      • Comparison of title coverage and cost per use of full-text collections
      • Targeted e-accounts to maximize cancellation allotments
      • The Review and Renewal of selected e-journal packages and ebook collections
    • Our approaches are still evolving …
  • 6. What have we tried?
    • Manual preparation
      • Merging files, adding missing data, confirming accuracy
      • Time consuming in many cases
      • Typically needs to be completely repeated each year or renewal
    • Changes in account management
      • Consistency recording data
      • Consolidation
    • Vendor solutions
      • Partial success
      • More possibilities emerging
    • Log data
      • OpenURL
      • Proxy
    • Circulation comparisons
    • Skill set – dB’s, spreadsheets
  • 7. Latest Efforts
    • Manage Expectations
      • Define standard “product” our unit will provide
        • What usage and cost per use data will our department provide systematically
        • What can be handled upon request
        • What goes beyond - requires cost/benefit decision
      • Provide accurate time estimates and for this work
    • Matrix
      • Looked at 17 of our larger publisher-based accounts (not aggregated collections)
        • Approximately 6,500 titles and 50% of our e-resource expenditures
      • Gain a clearer understanding of our larger accounts
      • Identify possible consolidation or record keeping projects to simplify accounts and move towards more automation
    • Progress? – Every project we do seems to create more questions
  • 8. Matrix – A deeper look at our accounts
    • Paid titles vs. Total titles (unsubscribed titles)
    • Differences among the Publishers/Accounts
      • Package, mix of packages, individual subscriptions or combination thereof
    • License period
    • Cancellations or swaps allowed?
    • Frontfile/Backfile
    • Payment data
      • Location, package or title level?
      • Total amount
    • Use data
      • Source and ease of access
      • COUNTER compliance
  • 9. Challenges with Usage Data
    • Non-COUNTER, non-COUNTER R3 compliance
    • Multiple platforms
      • Oxford UP titles available via Project Muse, JSTOR, ProQuest
    • Combined subscriptions and/or title changes
    • Titles transferred between publishers
    • Subscribed content and purchased backfiles
      • COUNTER R3 - JR1a and JR5
    Use Data from publisher Title Print ISSN Online ISSN YTD Total Journal Title A 1234-1234 2345-1234 114 Journal Title B 1234-2345   854 Journal Title C 1234-3456 2345-2345 320 Journal Title D part 1 1234-4567 2345-3456 1108 Journal Title D part 2 1234-5678 2345-4567 321
  • 10. Challenges with Cost Data
    • Nature of the account
      • Packages, Membership records, Individual title subscriptions
      • Print/electronic combined – cost may be associated with print record
        • Improving with e-only policies
        • Still legacy
      • Combination Subs
    • Nature of the package
    Cost Data from acquisitions system Title ISSN e-ISSN Amount Journal Title A 2345-1234   1500 Journal Title B: Subtitle 1234-2345   0 Title C, Journal 1234-3456 2345-2345 320 Journal Title D part 1 1234-4567 2345-3456 2636 Journal Title D part 2     0
  • 11. The Sum of the Parts…
    • Disparate systems
    • Usage data is often not organized in the same way as the cost data
    • Mismatched issn, titles, etc…
    Cost Data from acquisitions system Title ISSN e-ISSN Amount Journal Title A 2345-1234   1500 Journal Title B: Subtitle 1234-2345   0 Title C, Journal 1234-3456 2345-2345 320 Journal Title D part 1 1234-4567 2345-3456 2636 Journal Title D part 2     0 Use Data from publisher Title Print ISSN Online ISSN YTD Total Journal Title A 1234-1234 2345-1234 114 Journal Title B 1234-2345   854 Journal Title C 1234-3456 2345-2345 320 Journal Title D part 1 1234-4567 2345-3456 1108 Journal Title D part 2 1234-5678 2345-4567 321
  • 12. Example – Oxford University Press
    • 180 individual subscriptions merged into a single line item payment for 220 titles
    • Single journal package includes “all” titles from publisher
    • Single line payment in acquisitions for all e-content
    • Counter R3 usage data (JR1 and JR1a)
    • C/U=Total usage across titles / cost of package
    • Challenges
      • How do selectors identify their portion of this package?
      • Should titles be apportioned % of the package cost based on their list price?
  • 13. Example – Elsevier Accounts
    • Overall title list includes 2000 titles with 800 paid subscriptions
      • Packages – ScienceDirect, Freedom Collection
      • Individual title subscriptions
    • Payment information varies
      • Package/Collection
      • Individual titles
      • With print title
    • Backfiles (JR1a)
    • C/U =
      • Package title use / cost of package
      • Individual title use / cost of title
      • Total account use / cost of account
    • Challenges - simply producing, maintaining and interpreting
  • 14. What if?
    • How do we allocate costs of titles within a package?
      • List price of each title used to figure % share within package
    • What is the cost difference if we changed from a package to selected titles?
      • C/U estimated with list price or alternative price
      • ILL or other costs to obtain unsubscribed content.
    • Can I see this data for just my (individual selector) titles and my share of the cost?
      • Ability to break packaged titles into sub-sets based on subjects, funds, selector names, on-the-fly
  • 15. Future Possibilities
    • Better automated matching of cost and use data
    • Useful data elements
      • Multiple costs or price points: our cost, list price, discounts
      • Subject/fund/selector “ownership” for titles within a package
      • Relationships between titles
    • Formulas
      • Simple: Cost/Use = cost per use
      • Packages: package cost/all title use = cost per use across entire package
      • Complicating factors: value of “unsubscribed” titles to a package, one payment for multiple titles
    • Simplifying some accounts
      • More consolidation and better data organization
      • Better documentation or description of accounts
  • 16. Ongoing process
    • Selector involvement and education
      • Help them understand what is possible and what is not
      • Truly understand what they need and how we might work together to achieve that
    • Understand that we can’t do everything
      • Be comfortable with “good enough”
      • Far from automated, but we can move in that direction
      • Prioritize our efforts when a real need exists
      • Work with publishers, vendors to implement desired features
    • Hearing from you…