Administrators Management of Internet Station

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					Evidence Based Library Management:
        A View to the Future


                  Amos A Lakos
                    Librarian
       Rosenfeld Management Library – UCLA
                 September 2006

                 aalakos@library.ucla.edu

  http://personal.anderson.ucla.edu/amos.lakos/index.html




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Presentation & paper availability

      ARL Web - http://www.arl.org/stats/laconf/

      My Homepage –
        – http://personal.anderson.ucla.edu/amos.lakos/index.html
            » under Presentations




                                                               2
My approach

 Exploratory


 Provocative


 Proposes   future scenarios



             *Inspired by David Lewis’s (IUPUI) Living the Future 6 presentation

                                                                               3
Paper focus

  use  of data & analytics in decision making in libraries
  role of leadership
  new opportunities for data analysis, assessment
   delivery & decision making
  interviews with a non-random list of mostly ARL library
   directors
  general conclusions based on environmental scan &
   these discussions
  general forecasts




                                                              4
Business & Information Environment -1

   The U.S. is now an “information economy”

   Information sectors comprise about 60% of GNP value added in the private
    sector

   Information Services are 50% of the total

   Manufacturing continues to shrink – less that 20%

   Information Services will dominate the US Economy


                                     *UCLA Business & Information Technologies (BIT) Project



                                                                                       5
 Business & Information Environment - 2

 Increasing   ...

   – automation of information, knowledge & decision
     processes
   – demand for data, information, knowledge and
     “intelligence” is increasing
   – demand for improved “intelligence” (information) for senior
     managers
   – use of DSS and on-line tools increasing fast
   – productivity monitoring

                     *UCLA Business & Information Technologies (BIT) Project
                                                                               6
Analytics & metrics intensive companies

       Wal-Mart
       Dell
       FedEx
       UPS
       Toyota                    Use Rigorous Analytics
       Boeing
       Google
       Yahoo
       Amazon.com

                »   Information -> Knowledge -> Action -> Success ->Survival!!
                »   Inventory to Information = Driven by Demand
                »   Need Collaboration Culture & Framework
                »   Sharing Information with suppliers
                »   RFID adoption
                »   Focus on Supply Chain Management

       * “A Survey of Logistics - The Physical Internet,” The Economist, June 17, 2006, pp. –
                                                                 www.economist.com/surveys      7
Supply Chain Management



 “The market leaders all have supply chains
   that are more responsive to customer
   demand”

    Yossi Sheffi – Director, MIT Center for Transportation & Logistics –
   quoted in A Survey of Logistics, The Economist, June 17-23rd, 2006.




                                                                           8
Library environment
 Digital   resources & systems
   – reduced “print” footprint
 Robust  Web search, retrieval
 Consortial OPACs & ERM systems
 Increased outsourcing of legacy processes & services
 Library vendors – merging, changing tools & services
 “Library resources“ – publishers & intermediaries
   – business models in process of change
 Library   “model” services & governance
   – move to radically different – customer impact based model


                                                                 9
Library Sector –new analytics/reporting tools

   OCLC - WorldCat Collections Analysis
   Partnerships – example - EBSCO w WebFeat w ScholarlyStats w Groker
   Serials Solutions - Overlap Analysis, COUNTERcounter
   Dynix – MicroStrategy
   ExLibris – Brio
   Endeavor – COGNOS
   Sirsi – SwiftKnowledge - Director's Station
   TLS – Oracle data mining tools, Endeca,
   Integrated analytics solutions - MPS-ScholarlyStats; Library Dynamics
   ARL New Measures – LibQual, Mines, E-metrics, COUNTER, SAILS
   Various new ERM products



                                                                   10
Research + interviews/discussions
 SusanBeck’s 2001 paper “Making Informed Decisions”
 UCLA Senior Fellows Program 2003/04
    – University Leaders Interviews
 ARL Statistics & Measures Program
 Steve Hiller & James Self – ARL
    – Making Library Assessment Work Project


 Interviews
    – 31 non-random sample of University Librarians
    – One Faculty Dean
    – 21 interviews [17 by telephone | 4 face-to-face]



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Interview Questions
   Where do you get the information or data needed to make your
    decisions?

     – Do you have a process to get systematic information that you need on
       a weekly, monthly, quarterly, yearly basis?

   Does your organizational structure have a unit/person responsible
    for data collection and analysis?

     – What would you be willing to spend to get such a system?
     – In an ideal world, what kind of data – statistics - analytics framework
       would you like to have?

   Do (University) administrators expect data-based
    decisions/recommendations/requests from the Libraries?


                                                                                 12
1. Where do you get the information or data
needed to make your decisions? -1
 Awareness


   – of locally collected data & externally mandated surveys such as ARL
     annual data.
   – that collecting & analyzing data involves a significant staff resources,
     special skill-sets and time
   – of the need to implement electronic and internet resource data & usage


 Want   more

   – focus on customer expectations – qualitative analysis – i.e. - LibQual.
   – cost and activity-based costing information


                                                                               13
1. Where do you get the information or data
needed to make your decisions? -2
   Most directors . . .

     – dissatisfied with the ability to get data when needed
     – complain about staff resistance to systematic data collection
     – want staff with data management and analytical skills

   Some directors noted . . .

     – ARL rankings still expected by campus administrators
          » difficulties seeing alternatives
     – difficulties in systematically using data & analysis in decision making
          » accustomed to working from intuition

   All directors . . .

     – feel quality of decisions improved if based on actual data/trend analysis
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2. Does your organizational structure have a unit/person
responsible for data collection & analysis? - 1
    Some already creating assessment positions whose content & goals
     vary

      – may include data collection, coordination of surveys, creation reports,
        analysis, etc.
      – most are part time or part of an AUL position.
          » part time effectiveness is unclear
          » a minority report to the UL

    Position titles – examples

      –   Director of Assessment & Planning
      –   Librarian for Research & Communication
      –   Process Improvement Officer
      –   Assessment Officer
      –   Statistics & Assessment Coordinator

    Most are pleased with the results
                                                                                  15
2. Does your organizational structure have a unit/person
responsible for data collection and analysis? - 2


   Some   directors identified desirable models
     – University of Virginia assessment framework
     – University of Pennsylvania Datafarm

  A   few directors preferred to stay at “arms length”
    from assessment
     – working through existing staff structures to
       develop some future assessment capabilities




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2. Does your organizational structure have a unit/person
responsible for data collection & analysis? - 3
 Challenges

   – Internal staff opposition to such a position or undertakings
       » lack of skill-sets & risk-averse
   – Lack of skill sets in project management, accounting, information
     technology, analytics, statistics, other…
   – Lack of staff vision and lack of a risk taking culture
       » reluctance to stray from traditional library positions
   – Difficulty of integrating such a position into existing organization


 Costs


   – Most directors are aware that an MIS or some other assessment
     framework will cost way over $100,000 per year

                                                                        17
2. Does your organizational structure have a unit/person
responsible for data collection and analysis? - 4

 In   an ideal world interviewees would . . .

   – focus more on

            local user behaviors and expectations
            long term trend analysis
            campus learning & research impact measures
            activity based costing data
            digital services and their impacts

   – like

            tobe part of a campus-based MIS
            more regional & national data & benchmarking studies
            desktop access to current data
                                                                    18
3. Do (University) administrators expect data-based
decisions/recommendations/requests from Libraries? - 1

 Most    senior administrators

   –   do not expect reports with detailed data
   –   expect mainly budgetary information
   –   do not demand impact data re: learning outcomes
   –   are interested in institutional rankings or benchmarks


 Expectations     on the library are based on local institutional
  culture

 Campuses       with campus wide data frameworks

   – higher expectation for real data from the library
                                                                19
3. Do (University) administrators expect data-based
decisions/recommendations/requests from Libraries? - 2


Many library directors –

   – developed relationships with their superiors based on
     trust & personal confidence
   – relationships are not based on the availability or lack of
     data & analytics
   – invest time & effort in studying & adapting to the personal
     qualities of their superiors
   – realize the importance of understanding & using this
     knowledge for their own and the library’s success



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Some general conclusions - 1
 Senior   university administrators are

   – influenced by external accreditation demands and institutional
     rankings
   – focused on faculty, research funding, student learning & life
       » the library is not viewed as a fundamental & central priority to
          university administrators.

 Campus    culture defines assessment initiatives & needs

   – institutional assessment or analytics is not a central cultural tenet
     of universities
   – lack of institutional culture is central to the slow stickiness of
     “culture of assessment” in libraries

                                                                       21
Some general conclusions - 2
 Library   leaders –

   – succeeded in their careers without an assessment framework
   – are slow in creating local structures for analytics & in integrating
     data and analytics into their decision making

 Library   Issues –

   – The profession is challenged in recruiting librarians with statistical
     and other analytics and IT skills in sufficient numbers




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5-10 years forecast: 1
   The centrality of leadership

    – Effective implementation of data-driven decision making
      framework requires
        » Vision, leadership and risk-taking
    – Without focused leadership & direct and consistent support from
      the library director
        » assessment won’t scale
        » local assessment frameworks cannot succeed

   The need for new skills in the profession

    – Lack of needed analytics skills is a key argument for outsourcing
      local analytics

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5-10 years forecast: 2
   From local to networked & collaborative systems/services

    – Collaborative frameworks (consortia, state, national, and global) will
       » maintain, analyze and distribute analytics to local members (local
           libraries)
       » Be more accurate, relevant and cost effective
       » may make local assessment frameworks redundant
                examples – OCUL, OCLC Research & Marketing, CDL Assessment

   Outsource or acquire analytics and reports as needed

    – Most local statistical & user information analytics/reports will be
      outsourced
       » to (local) consortia or external professional services
    – Local libraries will buy reports as needed


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   "The future ain't what it used to be.“



   "If you don't know where you are going, you
    might wind up someplace else."

                                      Yogi Berra


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