ARL Collections Presentation: Moneyball, the Extra 2%, and What Baseball Management Can Teach Us About Fostering Innovation in Managing Collections
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ARL Collections Presentation: Moneyball, the Extra 2%, and What Baseball Management Can Teach Us About Fostering Innovation in Managing Collections
- 2. Baseball to Collections Context
Notes de l'éditeur
- Moneyball, the Extra 2%, and What Baseball Management Can Teach Us About Fostering Innovation in Managing Collections Anytime you have ten minutes to speak it is probably not advisable to come up with a title that long, but I have been thinking about the intersection of modern baseball management with innovation in managing collections quite a bit. I was not sure the Moneyball analogy completely worked, but then Anne Kenney brought it up independently in a conversation about libraries and Brad Pitt made it into a movie – so I pressed-on assuming if it is good enough for Anne and Brad - then it is a good enough comparison for me. You might conclude that this is a forced analogy that means I spend too much time thinking about baseball and my wife would whole-heartedly agree, but I do think the comparisons about innovation developing and managing baseball teams and research library collections work well. There is much we can learn. Advance slide.
- Briefly - Moneyball is the story of the success of the Oakland A’s in the late 1990’s and early 2000’s and The Extra 2% is the less popular, but just as important, story of the success of the Tampa Bay Rays from 2007 to today. Both teams had to struggle against inferior revenue streams, dysfunctional markets, and competition with significantly better financing and resource basis – so the New York Yankees and Boston Red Sox for example. Both had to find new approaches to building and running a successful baseball team in order to compete, maintain vitality, and be successful in serving their primary users – fans. I would argue that today many libraries find themselves in a very similar position.
- The shift from supply-side development of collections (print-based, large inventories, unpredictable supply and demand periods, and judging collections largely on size) to more directly demand-driven approach has been underway for quite a while, but the pace is definitely accelerating for many reasons, including: Technology and increasing amount of content on open networks Changes in publishing Supply-chain capabilities and print-on-demand Increased accountability for libraries and higher education, but One reason trumps all others – economics The combination of dysfunctional markets for scholarly information and significant economic downturn have brought many of us to the level of the Oakland A’s and Tampa Bay Rays – inexorable economic factors driving us to increasingly innovate in our management of collections, question established norms, and develop new models for managing collections.
- My wife asked me if this guy was supposed to be a metaphor for looking deeper and analytical thinking and I can tell you no. In baseball looking deeper and questioning assumptions means questioning reliance on old fashioned numbers and axioms that do not tell you much about past, current, or likely future success - using statistical analysis to identify market inefficiencies . It also means not relying on grizzled hardened scouts – that is what this guy is – who think can predict performance based on what they see and rely on paradigms that dominated the game until the late 1990's rather than what they can test, question, analyze, and project based on good information - and then breeding that into every element of the organizational culture. I suppose this guy could easily be a grizzled hardened bibliographer as well – maybe he works in one of your libraries, but I doubt it – most of us are well past the grizzled back-room selector models, but we still hold onto many of those old practices as we turn our big ships to fully embrace the digital environment. Many of us are changing practice and working to fully embrace digital content as the primary means for discovering and disseminating information, but many of us are not doing it fast enough and would benefit from looking outside of libraries for ideas to expedite the pace of innovation in collections. Here are some specific ideas I think research libraries can increasingly employ.
- Moving quickly from changing assumptions to assertions and changing practice. Do whatever you have to do to grow, develop, or hire statistical analysts to be part of your collections team. Change your staff and your staffing models with at least one new hire. People are the most important tool for innovation - that is nothing new - but it requires real change with staff to truly change culture and breed innovation. Statistical tools - build, adopt, adapt, and start using them broadly across the collections program. Some brief examples. We put our entire book collection and circulation activity into SAS. We ran a myriad of statistical analyses that have informed everything from cutting approval plan expenditures down by 45%, scoping our demand-driven e-book collections program, and heavily influencing and reducing our item-by-item book selection. Saved hundreds of thousands annually on our various book collecting efforts, improved our usage rates, broadened our scope in targeted subjects, and reinvested in new areas. We developed our ERM system to ingest statistics related to every continuing resource we own and enables a myriad of reports based on usage rates and expenditures - and here is the key - we use it consistently, not just when we have cuts or journal reviews and annually review the bottom 20% of our continuing resources based on overall performance and make decisions accordingly to enable investment in emerging areas. Partnering with digital library colleagues. Digital library innovation has not been applied enough to the business of building and managing collections. We need to do more to foster collaboration among collections and digital library colleagues. A couple of quick examples. We developed a database where we actively map collections expenditures by fund/subject to university data points such as number of phd’s, faculty members, enrollment, grant dollars, and can manipulate those at the research center, departmental, and college level. We can use that real-time information to mine for overvalued areas, under-invested subjects, test ourselves against university expenditures and trends, and advocate for the preservation and addition of library resources. It has been very effective in balancing our collections portfolio and helping to advocate for more funds. We developed a database to solicit community input on journal titles, weight community input, and pair it with eigenfactor, snip, usage data, publication rates, and citation rates among our community to develop a weighted valuation for each journal title in our collection. Ivy and colleagues at CDL have done much of this work as well. Piggybacked on work at University of Washington and CDL to roll the data up to analyze, manage, and negotiate packages with publishers. These efforts have been imperfect and we can get better - but we are making progress and taking Steve Jobs advice and stealing ideas from other libraries whenever we can. Develop positive arbitrage Positive arbitrage is a concept at the heart of The Extra 2%. the practice of taking advantage of a price difference between two or more markets or a transaction that involves no negative cash flow at any probabilistic or temporal state and a positive cash flow in at least one state. It's use in the book and my use here is kind of a bastardization of the term, but the key concept is finding and generating value in everything you do with collections. Library collections work has excelled at creating negative arbitrage and value – we exchanged dollars for books that did not circulate, purchased journals we did not want, and often signed contracts that favored the publishers and vendors we work with. Sometimes there are good reasons for doing this, but often it was due to basing decisions on past practice and not having the type of data and analysis that would help us find the best value in expending collections resources – help us find the extra 2% or 5% or 10% to maximize the impact of collections. Free collections funds to invest in new and emerging areas. Free funds to invest in digital media, collaborative efforts, and the kinds of great digital library projects we have heard about here that are non-traditional, but critical areas of value for scholars and libraries. If you budget for experimentation and reward innovation (even innovative failures) - then you can reinforce your efforts to change the staff, change the culture to consistently question assumptions, experiment with new approaches, generate innovation, and bring more content and value to users. Both of the teams referenced today had people with dynamic interpersonal skills to carry forward the combination of analytical people and analytical tools to drive collections work. They met resistance as some constituencies dug in, but persevered by demonstrating impact and working the necessary political channels to create buy-in. Libraries tend to be very good at generating positive political arbitrage with faculty and other users. That needs to be maintained as we work on new models. For analytical approaches to be successfully applied in local environments - the user community and especially faculty - have to accept them in time. Analysis does not obviate the political and interpersonal work of managing collections, but I am certain that if we use analytical tools to increase access to the collections users want in the format in which they want to consume them, then just like winning in baseball, your fan-base will buy-in.