1. VIVA Value Metric Project
VIVA Collections Forum 2017
Anne Osterman, VIVA Director

2. Why a Value Metric Project?
Libraries continually search for better, more informed ways to make resource decisions.
Budgets are tight or declining, information universe is expanding.
A difficult task at the institutional level becomes even more complex at the consortial level.
Diversity in user populations of members creates diversity of collection priorities.
The need for a system that can compare dissimilar formats.
What is the value of an ebook collection compared to a streaming media subscription?

3. Value Metric Task Force Project Origins
biennium, VIVA received a 5% cut and used data to inform its cancellation decisions.
Looking forward, the Collections Committee wanted standardized criteria to apply to the evaluation of its resources.
The VIVA Collections Committee formed the Value Metric Task Force (VMTF) to figure out a consortial approach.

4. Developing the Value Metric System
The VMTF Charge:
Design and apply a framework for the coherent and holistic evaluation of VIVA products.
Determine what the highest collection development priorities are for the consortium and examine how these can be translated into quantifiable values.
The end result will be an assessment framework and value metric system for the evaluation of shared resources that are reflective of VIVA’s overarching values.

5. Developing the Value Metric System
Membership of task force was representative of the four major institution types within VIVA.
Examined priorities for the consortium from “institution type” perspective.
Persona/brainstorming exercise surfaced institutional priorities - instead of user type (undergraduate, faculty), used institution type (community college, doctoral).
Over 40% of brainstormed priorities were priorities for all 4 institutional types, 30% were priorities for 3 institutional types, 9% for 2 institutional types, and only 7 priorities only applied to1 institution type.

6. Developing the Value Metric System
The persona/brainstorming exercise identified overlapping priorities.
These were using in a survey of member institutions that focused on how institutions valued the identified facets depending on the specific format.

7. Developing the Value Metric System
For all consortial resource format types, the top two concerns were cost savings and alignment with curriculum. The other ranked facets varied widely by format.

8. Developing the Value Metric System
Needed accessible data that was both measurable and attainable, in order to create a tool that was easy to implement and sustainable.
Very important to the group to NOT reinvent the wheel or add additional tasks to busy staff.
Wanted to ensure that the tool/framework could be adapted at the local level.

9. Developing the Value Metric System
The group conducted a data inventory.
Included data such as degree and graduate counts, usage and cost data, etc.
They then mapped pre-existing data to answerable questions from the survey-identified areas of need.
For each product type the group asked:
What data do we already collect?
Does this data align with ways libraries measure value for users?
Are there other factors we aren’t collecting that could answer this question?

10. Value Metric: Putting it All Together
The group used the results of the survey to weight the included components according to relative importance to the consortium.
Two kinds of grids (current and prospective) were developed for each format type (databases, ebooks, ejournals, and streaming media).
Grids were divided in two parts:
Demonstrated usefulness to the consortium (e.g. cost per use, alignment with degrees awarded).
VIVA “values” (e.g. an emphasis on open initiatives, COUNTER-compliant usage statistics, usage rights, etc.).
Each grid has a potential score of 100, allowing for cross-format comparisons.

11. Value Metric: Database Example
Member Criteria
CRITERIA
SCORE
1. Alignment with Curriculum and/or Accreditation Requirements
a. Resource constitutes a high percentage of VIVA content within the subject area by format 6
b. Resource belongs to subject area with high number of degrees awarded
c.Percentage of total use coming from single public highest-use institution 3
d. Percentage of total use coming from public highest-use institution type
TOTAL CATEGORY Score 18
2. Cost Effectiveness
b. Cost-per-Use
a. Cost Avoidance 5
c. Annual Increase 4
d. Private Pooled Funds
3. Interoperability w/Discovery Systems
a. Discovery Tools in which Product is Indexed 14
4. Easy, One-Stop Content Delivery
a. Platform 7
b. Full-Text Availability 13
Common
across
all formats

12. Value Metric: Database Example
Consortial Values
CRITERIA
SCORE
6. Multidisciplinarity
a. Subject by Call Number 8
TOTAL CATEGORY Score
7. Usage Statistics
a. COUNTER compliant 4
b. Institution-Level Statistics 3 7
8. Technical Issues
a. Frequency and Nature of Technical Issues
b. Vendor Responsiveness 6
9. Supports Open Initiatives
Demonstrable commitment to open initiatives/exploring alternate open access publishing models

13. Value Metric: Rubric & Instructions Example
CRITERIA
RUBRIC
INSTRUCTIONS
b. Resource belongs to subject area with high number of degrees awarded
< 10% = % = % = % = % = % = 5 >60%=6
To score, please refer to the "Format Breakdown" sheet's mapped subject areas. Filter "Degree-Type-LC-Mapping spreadsheet" subjects by those three subjects. This spreadsheet maps (at only the highest level) LC subjects to degree types awarded in Virginia. Add the percentages of relevant degrees, and assign the number according to the rubric.
c. Percentage of total use coming from single public highest-use institution
< 20% = 3 points 20-40% = 2 points 40-60% = 1 point > 60% =0 points.
Using the consortial usage statistics ( find the total Record Views from public institutions from the most recent complete fiscal year of data. Then find the public institution that had the highest number of Record Views for this resource. The ratio of this individual institution to the whole is the percentage of total use coming from the single public highest-use institution. For example, if a resource had 150 Record Views from GMU and there were 500 total Record Views from all public institutions, the ratio would be 150/500 = 0.3 = 30%. This product would therefore get 2 points in this category.

14. Value Metric: Putting it into Operation
Collections Committee Product Managers “tested” the grids by filling them out, and they were further refined.
VIVA Central filled out the grids based on each product.
We created a database to store the grid data and ease comparison and reporting of different evaluative sections across products.
The Collections Committee used the data to identify cancellations to meet a state budget reversion.

15. Value Metric: Sample Chart

16. Next Steps
VIVA Central will continue to fill these out in consultation with product managers, in upcoming years, for each licensed resource.
Although extensive, designed to be plug and play – already being adapted by the Virginia Community College System.
We will make grid adjustments as appropriate – they are meant to be living, not static documents; as consortial and state priorities shift, so should the assessment of our resources.

17. Thank You to the Task Force!
Genya O’Gara (VIVA, Chair)
Beth Blanton-Kent (University of Virginia)
Cheri Duncan (James Madison University)
Summer Durrant (University of Mary Washington)
Julie Kane (Washington & Lee University)
Madeline Kelly (George Mason University)
Crystal Newell (Piedmont Virginia Community College)

18. Credits Noun Project: “Question” by Jessica Lock, CA
Noun Project: “Graph” by Chance Smith, US
Noun Project: “EReader” by Amelia Edwards, US: from the Reading and eBooks Collection
Noun Project: “Measuring” by pictohaven: from the marketing - bold Collection
Noun Project: “Choice” by Kirby Wu, TW: from the Business / Enterprise / Management Collection
Noun Project: “People” by Gregor Cresnar: from the Business: Marketing Vol. 2 Collection