Evidence Based Library Management: A View to the Future

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Evidence Based Library ManagementA View to the
Future

• Amos A LakosLibrarianRosenfeld Management
  Library UCLA
• September 2006
• aalakos_at_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

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My approach

• Exploratory
• Provocative
• Proposes future scenarios
• Inspired by David Lewiss (IUPUI) Living the
  Future 6 presentation

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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

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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

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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

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Analytics metrics intensive companies

• Wal-Mart
• Dell
• FedEx
• UPS
• Toyota
• Boeing
• Google
• Yahoo
• Amazon.com
• Information -gt Knowledge -gt Action -gt Success
  -gtSurvival!!
• 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

Use Rigorous Analytics
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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.

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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

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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

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Research interviews/discussions

• Susan Becks 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?

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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

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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

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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

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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
• to be part of a campus-based MIS
• more regional national data benchmarking
  studies
• desktop access to current data

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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

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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 librarys
  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

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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 wont 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