Moneyball, Libraries, and more - Ithaka collections presentation
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Transcript of Moneyball, Libraries, and more - Ithaka collections presentation
Moneyball, the Extra 2%, and What Baseball Management Can Teach Us About Fostering
Innovation in Managing Collections
Greg Raschke
North Carolina State University
Ithaka
March 8, 2012
Moneyball and More...
Baseball to Collections Context
Looking Deeper and Questioning Assumptions
Identifying market inefficiencies.Apply and acculturate significant
innovation.Question long-established wisdom.Test what is “known” with in-depth
analysis, statistical modeling, and new approaches.
Emphasize interpersonal skills in leveraging new knowledge and approaches.
Supply-Side Collections Print-based, unpredictable demand,
and legitimate need for just in case collections
Lead to judging quality by size (as in the ARL rankings) and libraries were then held captive to this standard
Contributed to inelastic demand for journals and a combination of speculative and package buying
Use is secondary to size, dollars expended, and other input measures
Credit to David Lewis (http://ulib.iupui.edu/users/dlewis)
Supply-Side to Demand-Driven
Demand-Driven Collections
Make information easily, widely, and cheaply available
Collections as drivers of research, teaching, and learning
To make special or unique collections held/managed by the library available to the user community and the world
Demand-Driven – Changing Practice
Tension between time-honored role as custodians of scholarship versus enabling digital environment for scholars
Not just PDA – portfolio of approaches, but certainly more responsiveUtilize new tools and techniques to become advanced analystsTruly embrace evidence based decision making
Look at how collections are actually used, not at expressed need
Demand-Driven – More Assumptions
Less tolerance for and less investment in lower use general collections
Resource management based increasingly on use
Modify collecting based on changes in the actual use
Risks of doing nothing – newspapers
Demand-Driven – Assertions
Rewards of adapting – more used and vital than ever
Use based and user driven collecting models will take growing share of budget
Bet on numbers Bet on good and quick Put resources into enabling
digital environment for scholars and custodian role will come out of that strategy
Why So Much Data?
Data analysis is a key component in solving/managing: Increasing pressure for accountability Increasing capability to gather and analyze data Increasing precision in the way we build collections and expend
resources Advocacy
Changing practice and data analysis at NCSU
Serials Review 2009 – Open, Data-Driven, and Real-Time Analysis
Standardized usage data (where available)
Bibliometrics - publication data and citation patterns (e.g LJUR)
Impact factor and eigenfactor User community feedback via
interactive, database-driven applications
Weigh/calculate/quantify user feedback
Weigh price against multiple data points
Usage ((07 usage+08 usage/2)+(publications*10)+ (citations*5)+(Impact Factor)
Community Feedback ((Weighted Ranking x % Match) x Total # Rankings) + 0.1 x # of "1s“
Price/feedback valuePrice/useMerge results to filter out top 20%
and bottom 20%
Looking closer – Finding balanceAn example - a closer look at print item usage
Traditional ILS reporting tools can make this difficult
Advanced analytical tools can help
What types of questions can we ask?
Should Patron-Driven records not purchased be purged after 2 years?How does print item usage break down?Do print items even get used?
If it’s not used after 2 years…
Should PDA records be purged?
Maybe…
We haven’t even hit 50% usage
But what if we take a longer view…
If it’s not used after 2 years…
Things begin to look different
Looking even closer… How does print
item use break down?
Single circ usage is consistently ~14%
Would this change in a PDA only world?
Expenditures to University Data
Expenditures to University Data
Expenditures to University Data
Expenditures to University Data
Measurable Uses of the Collection 2009/2010
Full-text journal downloads* 3,672,600
Database use 1,989,972
Print book circulations/renewals 525,430
Digital collections requests 471,403
E-books 149,815
Reserves** 327,267
Total Uses 7,136,487
* Includes use of NC LIVE full-text content** Includes textbook, print, and e-reserves usage
Measurable Uses of the Collection 2009/2010
From Assumptions to Assertions to Practice Grow/develop/hire analysts. Adapt statistical tools such as SAS software. Partner with digital library/technologists. Develop positive arbitrage. Put resources into enabling digital environment for scholars. Experiment – budget for it, reward it. Work hard to get the faculty to buy into new approaches. Combine analytical approaches with the people skills .
“…there was a bias toward what people saw with their own eyes, or thought they had seen. The human mind played tricks on itself when it relied exclusively on what it saw, and every trick it played was a financial opportunity for someone who saw through the illusion to the reality”.