AIM: Data-driven collection management

Data-Driven Collection Management

Fernan R. Dizon Associate Director

AIM-Knowledge Resource Center

2016 PAARL Summer Conference Library Analytics: Data-Driven Library Management

April 20-22, 2016Pearl Manila Hotel

Outline

• Definition of terms• Collection management (evolution, collection

development vs. collection management, collection management activities)

• Data-driven collection management• Imperatives for data-driven collection management• Cases• Conclusion

Definitions

Definitions

• Analytics: The scientific process of transforming data into insight for making better decisions.

(INFORMS, 2016)

Analytics

• Analytics is now a major activity, as transaction or behavioral data is aggregated and mined for insight. We have become used to recommendations based on buying or navigation patterns. As more material is digital, as more business processes are automated, and as more activities shed usage data, organizations are manipulating larger amounts of relatively unstructured data and extracting value from it. Within the library field, patterns of download, holdings, and query resolutions are being mined to improve services. This trend has major implications for discovery, selection, acquisition, and management of collections.

(Dempsey, Malpas, and Lavoie, 2014, p.11-12)

Definitions• Collection management: In a more general

sense, the activity of planning and supervising the growth and preservation of a library's collections based on an assessment of existing strengths and weaknesses and an estimate of future needs.

(ODLIS, 2016)

Definitions• Collection management is defined as a process of information

gathering, communication, coordination, policy formulation, evaluation, and planning. These processes, in turn, influence decisions about the acquisition, retention, and provision of access to information sources in support of the intellectual needs of a given library community. Collection development is the part of collection management that primarily deals with decisions about the acquisition of materials.

(Osburn, in Johnson, 2009, p. 2)

Definitions• Dashboard: is a data visualization tool that displays the

current status of metrics and key performance indicators (KPIs) for an enterprise. Dashboards consolidate and arrange numbers, metrics and sometimes performance scorecards on a single screen. They may be tailored for a specific role and display metrics targeted for a single point of view or department. The essential features of a BI dashboard product include a customizable interface and the ability to pull real-time data from multiple sources.

(Search Business Analytics, 2016)

Dashboards

• The dashboard allows librarians and management to monitor key library operations from a single, convenient page, with an emphasis on long-term trends rather than day-to-day fluctuations in use.

(Morton-Owens and Hanson, 2012, p.50)

Definitions

• Patron-driven acquisition (aka demand-driven acquisitions) is a purchasing model in which patrons select e-books by choosing them from the OPAC and the library and vendor set the number and kind of uses that trigger a purchase. Selecting a portion of your funding and experimenting with patron-driven acquisition will ensure that you are purchasing some e-books that are being used and collecting some statistics on the desires of your patrons.

(Richard, 2012, p.63)

Collection management: evolution;

collection development vs. collection management;

collection management activities

Collection management evolution

1. How the process takes place and the tasks involved (From selection to collection management/ simple to complex/ one man to participatory decision making.

2. What the underlying goal of collection content should be (gatekeeping to open-access).

(Evans and Saponaro, 2012, p. 19)

Collection development vs. Collection management

• Collection development (building)

• Collection management (maintaining)

(Chapman, 2012)

Collection management activitiesCore-collection management encompasses a wide range of activities:

• selection and acquisition• budget allocation and management• serials and electronic resource management and access control• stock evaluation• weeding• storage and preservation• liaison with users, managers, suppliers and publishers• collaboration with other institutions

(Fieldhouse, 2012)

Collection management activities

Activities associated with collection management:

• Promotion and marketing activities • Activities associated with the quality of both bibliographic and

electronic records and the use of appropriate metadata to describe resources accurately to facilitate access.

(Fieldhouse, 2012)

Collection Management Process (Evans and Saponaro, 2012, p.23)

Data-driven collection management


Challenges librarians face (Day and Davis, 2010, p.81):

• buying power diminished by the woes of shrinking, or if we’re lucky, static budgets and inflation increases;

• gate counts are rising;• patrons expect the library to be open 24 hours;• researchers are demanding access to the new journals and

digital products that are launched each year;• difficult balancing act of deciding what we can afford and

what we can live without, while still striving to provide quality support for learning, research, and teaching.


What does data-driven means?

Using data proactively to address emerging trends and challenges is “what it really means to be a data-driven…”

- Sarah Tudesco, Assessment Librarian, Yale University (in Enis, 2013)


Data that can be used to support decisions: • cost of books/journals/databases/videos, etc. include;• usage (full-text downloads, circulations, ILL transactions);• rights (owned/leased);• citation and publication patterns by your campus researchers (i.e., which

journals are they citing and which journals are they publishing in);• journal impact factors (as flawed as they are, they are still seen as a

benchmark among many researchers and libraries);• regional holdings, and; • journal editorial activity of your campus researchers.

(Day and Davis, 2010)

Imperatives for data-driven collection management


Collections are changing in a network environment (Dempsey, Malpas, and Lavoie, 2014, p.6-7):

1. The network context: • Unbundling and rebundling: transaction costs and system-

wide reorganization.• A data driven environment: activities are becoming

“informationalized,” where more operations are automated and data drives decisions.

• Research and learning behaviors are changing: libraries serve a constituency whose needs are also changing.


2. The evolving scholarly record: Libraries acquire, organize, and provide stewardship of the scholarly record. Ongoing redefinition of the scholarly record will drive changes in library and publishing practice. (Accompanying materials, i.e. videos, raw data, blogs, discussions, etc.)


3. The collections grid: Libraries engage with different types of collections, which have different dynamics associated with them. Understanding the shift in the patterns of operational support for different types of resources is important to library planning and investment, both for individual libraries and for the networks of which they are a part.


4. The inside-out collection: The dominant library model has been outside-in, where materials are purchased or licensed from external sources and made available to a local audience. The inside-out model, where institutional materials (digitized special collections, research and learning materials, researcher expertise profiles, etc.) are shared with an external audience requires new ways of thinking.

5. Managing shared print: The print collection has been central to the identity of the library but is now on the threshold of major network reorganization. The emergence of cooperative infrastructure, facilitated by the network, has enabled a transition from institutionally-organized stewardship toward group-scaled solutions.


6. Sourcing and scaling: Collections will be managed at several levels, above the institution as well as within it. Choices about the optimum level (institutional, consortial/group, regional, global) for management are becoming more common, as are decisions about how to source activities (collaborative, buy from third party, etc.).

Cases

Case 1: North Carolina State University


North Carolina State University (Day and Davis, 2010)Journal review and cancellation• Methodology: Online Form• Respondents: University Library Committee and programming

and faculty, graduate library representatives, other stakeholders.

• Objectives: To enable the NCSU Library address the collections budget but of 15% or $1.5 million dollars by reviewing all journal subscriptions and putting together a list of lower use (in terms of full-text downloads), less relevant, titles and presenting to campus constituents and requesting for their feedback. (This list consisted of 1,112 titles).

Data elements used at the NCSU Libraries for their serials review

exercise


2. Collection view toolsUses of the Collection Views Tool• “The broad purpose of this project was to help collection

management librarians evaluate and think about how library purchasing power is distributed across different subject areas. The data allows us to examine the relationship between our spending on resources and the departments the library serves, and can help us test our assumptions about the strengths of the university and what we know about the work of colleges and departments on campus.”


3. Journal backfiles return on investment (ROI) - analysis of the cost/use for journal archivesMethodology: • Data was derived from a combination of sources(publisher/provider

websites, local ILS and files where cost data were maintained, usage statistics from publishers and providers, and collated cost data for each of the backfile collections purchased since 2003, including both one-time payments and annual maintenance fees).

• Using Microsoft Excel, they plotted cost/use for each year where the data was available. In instances when they could not acquire usage data back to the year of initial purchase, they carried the one-time cost through each year of ownership and divided that by cumulative use. Where onetime payments existed, they applied the one-time payment to the first year of reported use.


Objectives:• To justify the spending of valuable state resources and

illustrate the value of the resources the NCSU Libraries purchased and supported.

• To describe how online journal archives saves the Libraries valuable space for seating and innovative work/study/play space, while also enhancing ease of access from virtually any location, noting that portability and discoverability were important needs for NCSU faculty, staff and students. The acquisition of journal archives ensures that the journal collections are comprehensive, spanning access from volume 1 through to present…


Impact of the data:

• The data was provided to library administration and used in communications with various administrative and oversight groups across campus.

• In terms of internal use, this kind of analysis supported their ability to monitor performance and guide their future approaches in dealing with this kind of content.

• Determining which online journal archive collections have provided the best initial ROI and what is the impact of those that are drawing on their limited budgets year after year with their annual maintenance fees is key to these approaches.

Case 2: AIM-KRC

Case 2: AIM-Knowledge Resource Center

EBSCO Ebook SurveyConducted last May 2014

• Objectives: to determine the level of awareness of KRC users about ebooks and to determine major considerations in the selection of an ebook platform.

• Methodology: Online survey (via Google Docs/Forms)

• Respondents: 32 faculty, students, staff, alumni

ResultsMajor considerations in the selection of a potential ebook platform:

• Remote (off-campus) access;• Downloading of the entire ebook (offline reading);• Copying/pasting, printing, downloading or saving

capabilities;• User friendly;• Powerful searching capability (searching within the

texts/books)

Case 2: AIM-Knowledge Resource Center

Online Customer Satisfaction SurveyConducted last October 2015.• Objectives: To determine the level of satisfaction of

the various stakeholders on the KRC’s collections, services, etc.

• Methodology: Online Customer Satisfaction Survey (via Sharepoint)

• Respondents: 142 faculty, students, staff, alumni

Other data collected

• Monthly library statistics (circulation statistics, online database usage, ILL/DDS, etc.)

• Suggestion box• Facebook posts/comments/reviews• Benchmark data, etc.

ResultsDemand for:• more fiction books• books on specific topics (national

security and economics)• up-to-date/diverse reading materials• more magazines

Conclusion

Data-informed vs. Data-driven?“Being data-informed is about striking a balance in which your expertise and understanding of information plays as great a role in your decisions as the information itself… you can apply your own experience to that information and choose accordingly — even if that means overriding what the system recommends.”

(Moycotte, 2015)

Conclusion• Data is a valuable tool. It is has been extremely

helpful and instructive for us to have data on hand to aid our collections decisions and allow us to articulate clearly some of the decisions we have made. Data is a powerful collection management tool when used in an informed way, but it should not be the only factor in your decision making.

(Day and Davis, 2010, p.97)

Conclusion• We (librarians) must keep on enhancing our data skill sets both

in terms of tools (i.e. common desktop applications) and also competencies and comfort levels in manipulating and interpreting the data.

• We have to work collaboratively with our colleagues in improving the skill sets of people not directly involved in collection management. These collaborations result in valuable tools to aid collection decision-making. Such collaboration is also helpful in presenting the complexities of collections issues to colleagues across the institution.

(Day and Davis, 2010, p.97)

THANK YOU!

References“Analytics” (2016). INFORMS. Retrieved from https://www.informs.org/About-

INFORMS/What-is-Analytics“Collection management” (2016). ODLIS. Retrieved from http://www.abc-

clio.com/ODLIS/odlis_c.aspxDay, Annette and Davis, Hilary (2010). Collection Intelligence: Using Data Driven

Decision Making in Collection Management. Proceedings of the Charleston Library Conference. Retrieved from http://dx.doi.org/10.5703/1288284314822

Dempsey, Lorcan, Malpas, Constance, and Lavoie, Brian (2014). Collection Directions: Some Reflections on the Future of Library Collections and Collecting. Portal: Libraries and the Academy, 14(3).

Enis, Matt (2013). Using Data to Shape a Library’s Direction : Data-Driven Academic Libraries. Retrieved from http://www.thedigitalshift.com/2013/12/staffing/using-data-shape-librarys-direction-data-driven-academic-libraries/

ReferencesEvans, G. Edward and Saponaro, Margaret (2012). Collection management basics.

6th ed. Santa Barbara, CA : Libraries Unlimited Fieldhouse, Maggie and Marshall, Audrey, Eds. (2012). Collection development in

the digital age. UK : Facet PublishingJohnson, Peggy (2009). Fundamentals of collection development and

management. 2nd ed. USA : ALAKaplan, Richard (2012). Building and Managing E-book Collections : A How-to-do-it

Manual for Librarians. Chicago, IL: American Library Association.Maycotte, H.O. (2015). Be Data-Informed, Not Data-Driven, For Now. Forbes.

Retrieved from http://www.forbes.com/sites/homaycotte/2015/01/13/data-informed-not-data-driven-for-now/#6e6f66ab6ff9

Morton-Owens, Emily and Hanson, Karen L. (2012). Trends at a Glance: A Management Dashboard of Library Statistics. Information Technology and Libraries. pp: 36-51.

Education

AIM: Data-driven collection management