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Assessing ROI for E-Resources: A Cross-Institutional Analysis

This presentation discusses the use of Cost-Per-Use (CPU) data as a powerful tool for assessing the return on investment (ROI) of e-resources. It explores the limitations of CPU data and highlights the potential for cross-institutional analysis. The speaker also raises questions about the implications and future directions of such analysis.

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Assessing ROI for E-Resources: A Cross-Institutional Analysis

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  1. Assessing Return on Investment for E-Resources: A Cross-Institutional Analysis of Cost-Per-Use Data Patrick L. Carr North Carolina Serials Conference Chapel Hill. March 10, 2011

  2. “Print was simpler.”

  3. This has been replaced by… From Appendix B of the 2004 report of the Digital Library Federation’s Electronic Resources Management Initiative.

  4. This Has been replaced by… From Appendix B of the 2004 report of the Digital Library Federation’s Electronic Resources Management Initiative.

  5. Indeed:This Has been replaced by… “Print was simpler.” From Appendix B of the 2004 report of the Digital Library Federation’s Electronic Resources Management Initiative.

  6. Indeed:This Has been replaced by… “Print was simpler.” Not when it comes to use-based evaluations. From Appendix B of the 2004 report of the Digital Library Federation’s Electronic Resources Management Initiative.

  7. Thomas E. Nisonger, Management of Serials in Libraries (Englewood, Colorado: Libraries Unlimited, 1998): 160-65.

  8. We have far superior tools to assess use of e-resources. Thomas E. Nisonger, Management of Serials in Libraries (Englewood, Colorado: Libraries Unlimited, 1998): 160-65.

  9. Cost-Per-Use:Annual Subscription Cost÷Annual Use

  10. Cost-Per-Use: Should always be considered in the context of qualitative measures of ROI.

  11. Cost-Per-Use:A powerful tool for assessing return on investment.

  12. Cost-Per-Use:A powerful tool for assessing return on investment.But are we using CPU data to its fullest potential?

  13. Chuck Hamaker’s idea: A cross-institutional analysis of CPU data &

  14. Caveat: Data is generally from 2009 (complete 2010 data wasn’t yet available)

  15. Caveat: Data is generally from 2009 (complete 2010 data wasn’t yet available) Caveat: The coverage ranges for cost and use data didn’t always overlap completely.

  16. Caveat: Data is generally from 2009 (complete 2010 data wasn’t yet available) Caveat: The coverage ranges for cost and use data didn’t always overlap completely. Caveat: Institution-by-institution access sometimes differed .

  17. Caveat: Not all sources of use data were COUNTER compliant. Caveat: Data is generally from 2009 (complete 2010 data wasn’t yet available) Caveat: The coverage ranges for cost and use data didn’t always overlap completely. Caveat: Institution-by-institution access sometimes differed.

  18. We can’t really use this study’s results to make sweeping conclusions. Caveat: Not all sources of use data were COUNTER compliant. Caveat: Data is generally from 2009 (complete 2010 data wasn’t yet available) Caveat: The coverage ranges for cost and use data didn’t always overlap completely. Caveat: Institution-by-institution access sometimes differed.

  19. Five Categories of Resources • Publisher journal packages • Commercial publishers • Society publishers • University presses • Full-text aggregators • Site licenses to journals • Indexing & abstracting databases • Other stuff

  20. Three Questions

  21. What does a cross-institutional CPU analysis actually tell us? Three Questions

  22. What does a cross-institutional CPU analysis actually tell us? • How can we use what it tells us? Three Questions

  23. What does a cross-institutional CPU analysis actually tell us? • How can we use what it tells us? • Where do we go from here? Three Questions

  24. Questions/Comments Patrick L. Carr Head of Electronic & Continuing Resource Acquisitions Joyner Library East Carolina University Greenville, North Carolina 27858 email: carrp@ecu.edu phone: 252-328-2266

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