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Input-Output Analysis

Electronic Resource Management: Inputs, Outputs, and Why They Matter Presenter: Ted Koppel Verde/SFX Product Marketing Manager Ex Libris. Input-Output Analysis.

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Input-Output Analysis

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  1. Electronic Resource Management:Inputs, Outputs, andWhy They MatterPresenter: Ted KoppelVerde/SFX Product Marketing ManagerEx Libris

  2. Input-Output Analysis “Input-output analysis is one of a set of related methods which show how the parts of a system are affected by a change in one part of that system.” “Input-output analysis specifically shows how industries are linked together through supplying inputs for the output of an economy.” Thayer Watkins, Prof. of Economics, San Jose State Univ.

  3. Relevance to ERM? • ERM systems promise to: • Track and manage the entire lifecycle of electronic resources • Collect, store and manipulate various discrete data elements, collected and described in discrete attributes or management areas • Provide measurable and actionable data as a by-product of ERM handling • Allow repeated cycles (annual subscription renewal) based on previous activities

  4. ERM is a (small) system • But its capabilities and benefits can be described by examining the data that goes in and the management capabilities that are produced • In general, the better the data input, the better the analysis output

  5. ERM Inputs • Vendor / licensor / aggregator • As e-product seller • As e-product support • Services provided • Incident and Breach data (current and historical) • License data • Permissions and prohibitions • Perpetual use • Population groups served

  6. ERM inputs • E-products themselves, and their place in the e-product structure: • Package? Interface? E-journal or e-book? • Financial data: • Price? Cost? Invoice amount? • ILS or Local Fund structure • Current accounts and previous years? • Concurrent users or unlimited use?

  7. ERM inputs • Access data • SRW/SRU? Web? Z39.50? • Documentation access info? • Statistics/SUSHI access metadata? • URL for Documentation/training • IP address, passwords • Miscellaneous data elements • MARC records? Branding? OpenURL enabled? Etc.

  8. Best Practices for Data Input • Plan! • Migrate data? • What data do you have? • How internally consistent is it? • How complete is it? • Do data elements/fields map to your target application? • Consistent identifiers with which to link? • Hand-enter data? • From what source? • Enforcing consistency in data entry • Completeness?

  9. Suggested reading http://orpheus.ucsd.edu/acq/ppt/verde.ppt

  10. Consortia are more complex • Multiple institutions of different sizes and e-product purchase volume and use • Varying historical internal workflows • Legal and licensing attitudes at different campuses

  11. Christenson and Harvell (their slide 14): Consortium-wide standards • Authorities for organization/vendor/e-product, e-interface names • Conventions for data population, and local configuration decisions • License interpretation into data elements • Checklist for campus readiness • Field labels • Drop-downs • Workflow steps

  12. Quality counts

  13. Outputs • Vendor inputs  Vendor performance outputs • Getting what you paid for • Track and assign uptime, downtime, functional issues like printing and dowloading • Statistics reported by vendor interface and package • License inputs  License outputs • What rights and privileges do your users have? Print? Download? • Different permissions for different groups • Consequences of a library’s decision to cancel subscription

  14. Outputs • Financial inputs  Financial outputs • Year-to-year cost changes • Application of discounts • E-product inputs  E-product outputs • Lists of titles by package and interface • Overlap reports by title, package, etc • Consolidated holdings • Print-to-e-product relationships

  15. Centralized collection of data • Opportunities to do cross-compilation and multiple variable analysis of data elements • Leading to more informed decision making

  16. Why talk about this? • ERM is a relatively new area of library management and operation, yet is entrusted with millions of dollars and large areas of public service • ERM causes libraries to rethink their processes and (hopefully) be more efficient • ERM industry is itself changing • SUSHI • License Expressions • Publisher distribution models • Other new standards

  17. It’s nearly time to measure: • Pre-ERM e-resource management costs (direct and indirect), inefficiencies, decentralized data Against • Post-ERM management costs (direct and indirect), efficiencies, centralization In the context of • The added value of consolidated ERM information

  18. And when we analyze ERMS • The INPUTS (quality data, relevant data, complete data) Will have a significant effect on • The OUTPUTS (Are ERM systems useful, efficient, and cost-effective)

  19. My predictions • Yes, but not yet • Not enough library experience yet in ERM use • The industry and its tools are still in the midst of change • We (vendors) need to work with libraries and what and how to measure

  20. But again, a word of caution …

  21. Last words • Strategy • Planning • Completeness • Consistency • Accuracy

  22. Thank you Ted Koppel Verde / SFX Product Marketing Manager Ex Libris Ted.koppel@exlibrisgroup.com 617.332.8800 x601

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