Presentation at the April 29, 2013 meeting of the Technology Task Force.

1. IT and U
Discussion with
Louisiana State University
Transition Advisory Team
April 29, 2013
Jerrold M. Grochow
Some materials © 2012,2013 Jerrold M. Grochow LLC

2. Topics for discussion
• What I was told you are interested in:
– What does the future of IT look like?
– On-line learning (MOOCs, etc.) and policy
implications
– Involvement of IT in research
– Where do you need to go next?
– How will organizational culture be impacted?
2

3. Drivers of the discussion
3
• Building toward ―LSU2015‖
• Becoming globally competitive
• Cost savings

4. 4
IT is everywhere!
• IT is in…
– Research equipment from electron microscopes to telescopes,
from local controls to remote controls
– Data analysis from Shakespeare‘s sonnets to protein folding to
resource development
– Teaching, via simulations and multimedia tools
– Academic administration from class lists to grade lists to
graduation lists
– Operations from security to air conditioning to maintenance
– Financial management from grant applications to paychecks to
the Treasurer‘s report

5. EDUCAUSE “Top 10 Issues for 2011”
1. Funding IT
2. Administrative/ERP/Information Systems
3. Teaching and Learning with Technology
4. Security
5. Mobile Technologies
6. Agility/Adaptability/Responsiveness
7. Governance, Portfolio/Project Management
8. Infrastructure/Cyberinfrastructure
9. Disaster Recovery / Business Continuity
10. Strategic Planning
5

6. EDUCAUSE “Top 10 Issues for 2012”
1. Updating IT staff skills and roles
2. Supporting consumerization of IT
3. Institution-wide cloud strategy
4. Improving the institution's operational efficiency
5. Integrating IT into decision-making
6. Using analytics to support critical institutional outcomes
7. Funding information technology strategically
8. Transforming the institution's business
9. Supporting the research mission
10.IT governance
6

7. 2012-2011 Comparison
1. Updating IT staff skills and roles
2. Supporting consumerization of IT
3. Institution-wide cloud strategy
4. Improving the institution's
operational efficiency
5. Integrating IT into decision-making
6. Using analytics to support critical
institutional outcomes
7. Funding information technology
strategically
8. Transforming the institution's
business
9. Supporting the research mission
10.IT governance
1. Funding IT (including multi-year)
2. Administrative/ERP systems
3. Teaching and learning with
technology
4. Security
5. Mobile technologies
6. Agility/adaptability/responsiveness
7. Governance, portfolio/project
management
8. Infrastructure/cyberinfrastructure
9. Disaster recovery / business
continuity
10. Strategic planning (ITs role in as
well as for IT)
7
2012 2011

8. More emphasis on institutional concerns
• Improving the institution's operational efficiency
• Integrating IT into decision-making
• Using analytics to support critical institutional outcomes
• Transforming the institution's business
• Supporting the research mission
 IT is integrated into everything the university does and
wants to be part of the discussion!
8

9. SO WHERE DOES THIS
BRING US?
9

10. Our topics for today (subject to change)
• ERP implementation (a case study)
• MOOCs
• IT in support of research
• ―Big Data‖ and analytics
• Moving to ―The Cloud‖
• Reducing costs of IT
• Strategic planning for IT
10

11. ERP IMPLEMENTATION:
A CASE STUDY
11

12. Reengineering at MIT: “A Journey”
12
Community input is crucial
Reengineering set to begin;
teams, consultant named
November 22, 1993

13. 1993!
• This was 20 years ago.
• ―Reengineering‖ was the
new thing…
• A lot has changed since then, but we can
still learn from what happened.
13

14. Why re-engineer?
• In short, because of the need to cut costs!
―MIT, along with the other great research universities of
the nation, has been faced with the real prospect of
declining revenues from federally sponsored research…
At the same time we have seen a marked increase in the
competition for available research dollars and less
willingness by federal sponsors to reimburse for indirect
costs…‖
[Faculty Newsletter May/June 1995]
14

15. The faculty asked good questions…
• Goal of re-engineering: ―to provide the best possible
services to faculty and students as efficiently as
possible‖ (Tech Talk, May 1, 1995)
– But what is ―best‖ in this context and who is to say?
– How are the intended efficiencies to be attained?
– At what costs,and to whom?
– How are the results to be measured?
• How can we measure whether or not increasing ―efficiency‖ compromises
academic excellence?
– Can the quality teaching and research programs we are known
for survive the present frenzy of cost-cutting?
– Which programs can we afford to lose?
» [Faculty Newsletter May/June 1995]
15

16. What did the administration say…
―Many faculty have criticized the business orientation of
reengineering, arguing that it is an inappropriate match
for an educational and research enterprise. Yet many of
MIT‘s administrative processes operate very much like
their corporate counterparts…‖
[Faculty Newsletter May/June 1995]
16

17. 18 months into BPR…
17
―President Charles M. Vest will talk about
the budget- administrative re-engineering
as an opportunity to maintain MIT‘s
leadership, and [address] the fear of losing
what is perceived as ‗good‘ about MIT as
we re-engineer and the Corporation‘s
[Board of Trustees] strong support for
moving forward…‖

18. And, new systems were required…
"There's no question that almost all major research
universities are adopting new, comprehensive fiscal
management systems -- and any system, no matter how
good, is going to require some difficult cultural changes
from its users. I know that the process of adapting and
deploying SAP hasn't been easy, yet agreeing on a
single central system was necessary. Many of our
decentralized systems in departments, labs and centers
were facing technical obsolescence. Without a
centralized effort, we would now be undergoing dozens
of uncoordinated upgrading projects.‖
[Vice President for Finance in Tech Talk, June 1998]
18

19. A short history of ERP at MIT
19
1993: Re-
engineering
with joint IS
1996: SAP
becomes
―system of
record‖
(central use)
1998: SAP
roll out to
departments;
Data
Warehouse
implemented
1999: New
org (FSS)
created to
maintain
SAP
2000: Payroll
study team
recommends
SAP
2001: Major
SAP upgrade
2002-3: SAP
Benefits/HR
modules
implemented
2003: Payroll
BPR started;
FSS merged
with IS to
become IS&T
2006: SAP
Payroll
implemented
2009: SAP
Payroll
enhancement
project
continues
Jerry Grochow appointed
VP for IS&T

20. SAP
Independent
Laboratory
SAP
Roles
Security
Database
Data
Warehouse
Legacy Systems
(GL feeds)
Benefits Providers
External
Financial
Institutions
EDI
(POs, Invoices,
Benefits Enrollment)
FI - Financial Accounting
• General Ledger
• Accounts Payable
• Accounts Receivable
• Funds Management
• Master data, Auths
• Fixed Assets Depreciation
• Real Estate Mgmt
• Travel (MIT developed)
• Cashier System (MIT
developed)
CO – Controlling
• Cost Center Accounting
• General funds
• Internal Order
Accounting
• Gift funded, incl.
Endowment
• Project Systems
• Sponsored Research
• Capital Software Proj
• Product Costing
• Cost Distributions
• Overheads
• Settlements
• Distributions/Allocations
• CO Plans (Dept
budgets)
PCA - Profit Ctr Account.
• Reporting Hierarchies &
Authorizations
MIT SAP Applications and Major Integration Points
MM - Material Management
• Purchasing
• Receiving
• Goods Movement
• Release Strategies
• Inventory Management
• Barcoding
• Logistics Invoice
Verification
• E-commerce
• ECAT II
• Internal Providers
PM – Plant Maintenance
• Repair & PM Work Orders
• PM Plans & Task Lists
• Equipment
PP - Production Planning
• Long Term Planning
• MRP
• Process Orders
QM - Quality Management
• Master Inspection
Characteristics
• Inspection Plans
• Inspection Lots
• Statistical Process Control
SD - Sales and Distribution
• Sponsored Billing
HR - Human Resources
• Personnel Management &
Administration
• Organizational Mgmt.
• Benefits Administration
• Training and Events Mgmt
PY – Payroll
• Pension Payroll
• Employee & Student
Payroll
• Time Entry/Evaluation
• Payroll Processing
• FI Posting
• Salary Distribution
EHS - Environment,
Health & Safety
• Space Registration (Work
Areas)
• Incident Accident Log –
Inspections & Corrective
Actions
CA – Cross Application
• Workflow
• EDI / ALE
• Document Mgt &
Archivelink
• Imaging, Archiving
• Classification System
• Release Strategies
• Order master data
SAPWEB Self Service
Budgeting
System
Independent
Laboratory SAP
Research
Administration
System
SAP ITS
• Parking Pass
• Time Approv
• Tuition
Assistance
• Benefits
• Directory
• Training
• JV
• Req
• UPI
• Repair
• Env.
Health
• Time Entry
• Dir Deposit
SAP-WEB
OAS

21. Systems on a Page (Vers. 0.1)

22. What did it cost? How much will it save?
―Core Team estimated that redesigning all of the recommended
processes might reduce administrative costs by approximately $43
million gross [20% of studied costs]…[beginning in FY1999]
[Faculty Newsletter May/June 1995]
• Expected investment: $40-43 million [1993-1998]
• $28M spent by end of FY1996
– $14M SAP implementation
– $6-7M consultants (CSC Index) for process redesign
– $6-7M layoff costs (expected 600+ layoffs)
– $2-3M training of existing personnel
• Raised overhead rates ―temporarily‖ by 6.5% (to 58.5%) to partially
cover this
– F&A rose as high as 68% after 2008 and is now 56%
22

23. So what is happening in higher ed now?
• Movement away from ―big bang‖ ERP projects
– Too costly, too risky
• Movement toward Enterprise Architecture
approach
– Integration of components
– Standard APIs
– ―Best of breed‖
– Open source / ―community source‖ / ―cloud source‖
• Kuali Foundation, including Indiana University, Maryland,
Arizona State, University of Arizona, Carnegie Mellon,
Cornell, Yale, Berkeley, Purdue, UNC, University of Southern
California

24. Potentially very large savings
24

25. The “New” Model
Workday
Sales-
force
Concur
PeopleSoft
COEUS
Financial
System
―ON-CAMPUS‖
Clear
Commerce
Internet
―IN
THE CLOUD‖
[Names are examples]

26. “Integration with the cloud” is becoming a
product category
26
[Names are examples]

27. Future State Vision (Vers. 0.1)
Service Integration Layer
Data
Security Services
Services
Data & Business Integration Layer
Administrative Services
ERP Services
Academic Services
Student Information
Services
Applications
User Interfaces
AuthenticationServices
AuthorizationServices
Learning Services Research Services
Applicant Portal
Grant
Management
PayrollFinance BudgetHR Purchasing
Applicants Students Alumni FacultyStaff
Core Services
List Management Services
Content Management
Services
E-Commerce Services
Directory & Demographic
Services
Identity Services
EMail and Messaging
Services
External Integration
Services
Archival ServicesCollaboration Services
Mapping and Location
Services
Extended Community
Facilities
Medical
President's
Office
EH & S Admissions Student Alumni
Library
Content
Management
Learning
Management
Technology
Licensing
Student Portal
Stand Alone GUI
Interface
Stand Alone Web
Interface
Alumni Portal
Extended Community
Portal(s)
Faculty Portal
Staff Portal
Resource
Development
Finance
Data
HR
Data
Facilities
Data
Grants
Data
Medical
Data
Student
Data
Learning
Data
Research
Data
Library
Data
Data
Warehouse

28. Put the “Critical Success Factors”
in place…
• ―Compelling vision‖
• Strong executive leadership
• Well defined scope
• Commitment of staff
– Time from people already doing their jobs - at all management
levels
• Commitment of funding
– No matter how you do it, it won‘t be cheap
• Comprehensive project and change management
28

29. MASSIVELY OPEN ON-LINE
COURSES (MOOCs)
29

30. A short course in MOOCs (1)
• Massively (100K+ students per course)
• Open (available to all, mostly free)
• Online (over the Internet)
• Course (not just materials)
• ―A MOOC is a catalyst for [gaining]
knowledge.‖
[David Cormier, first to use the term ―MOOC‖ in 2008]
30

31. A short course in MOOCs (2)
• Registrations 30,000-100,000+ per course
• 10% overall completion rate
– BUT, 45% completion for students who actually
submit the first assignment
– At Coursera, 70% completion rate for students in the
$50 ―Signature Track‖ program
» Chronicle of Higher Education, 4/8/2013
31

32. A short course in MOOCs (3)
• Growing field working with universities:
– edX, Coursera (for profit), Udacity (for profit), NovoEd
(for profit), others…
• Growing field without universities:
– Khan Academy, Peer2Peer University, ALISON (for
profit), Udemy (for profit), others…
• Growing field providing technology:
– edX, Google, Desire2Learn, Class2Go (merged with
edX), others
32

33. Implications for higher ed (1)
Content
creation (and
certification of
courses)
Teaching
Learning
(including
assessment)
Socialization
of knowledge
(integrating
specific
knowledge
into a larger
context)
Credentialing
of students
33
Separation of function:
How does the role of the
faculty change?

34. Implications for higher ed (2)
• ―Are online teaching innovations, such as MOOCs,
heralding a change in the business landscape that poses
a threat to their existing models of provision of degree
courses?‖
• ―MOOCs and Open Education: Implications for Higher Education,‖
Li Yuan and Stephen Powell (UK JISC CETIS)
• Role of entrepreneurs (and venture capitalists)
• Profit-making organizations vs. non-profits
34

35. Things to think about: Intended audience
• Current students
• New students with similar characteristics
• Students with different characteristics
(different/under-served populations)
• Third world
35

36. Things to think about: Economics
• Cost of developing a MOOC course is high
($200-400K per course)
• No currently viable revenue source
• Partnering with a platform provider will be
key
– edX spending $60M (already has 60+ staff)
– Millions in venture capital committed
36

37. Things to think about: Organization
• New post within the university
– MIT: Director of Digital Learning
– Stanford: Vice Provost for Online Learning
• New organization
– ―…the theory of disruptive innovation suggests that
there is a strong argument for establishing an
autonomous business unit in order to make an
appropriate response to these potentially disruptive
innovations.‖ [―MOOCs and Open Education: Implications for Higher
Education‖]
• E.g. EdX
37

38. Things to think about: Change!
• How will classes change?
– ―Inverted classroom‖
• What is the role of the faculty?
– ―Sage on the stage‖
– ―Guide on the side‖
• What is the role of the residential
university?
– Teaching/learning vs. educating
38

39. IT IN SUPPORT OF
RESEARCH
39

40. What is IT in support of research?
• High Performance Computing (HPC)
– Compute cycles, lots of them!
• Data, data analysis tools (including
visualization and data ―curation‖)
• Virtual organization for distributed
communities of researchers
– Collaboration tools
• Learning and workforce development
» [NSF Cyberinfrastructure Vision, 2007]
40

41. NSF Report on Cyberinfrastructure
[“Atkins Report” 2003]

42. Pillars of campus cyberinfrastructure
• High Performance Computing and Communications
– Identify needs, issues, opportunities in advanced computing,
networking and enhanced support facilities
• Data Life Cycle
– Examine issues connected with data handling, storage, retrieval,
partnerships, collaborations, campus library
• Virtual Communities
– Social and technical issues surrounding evolving distributed
communities and the use of software and systems to keep them
connected
• Funding Agencies
– Enhance cyberinfrastructure partnerships between federal
agencies and higher education institutions
42

43. 43

44. 44

45. Central IT Services for Research
[EDUCAUSE Core Data Survey 2011]
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Services to other institutions
Cyberinfrastructure
HPC and related
Support for grants
Content support
Community-building
R&E network access
HP network
Storage & hosting
Data management
Videoconferencing
DR
MA
BA LA
BA other
AA
Institutional type averages
[The break in the bar represents the overall average for higher education]

46. Current model at many universities…
• Individual investigator control
– ―Local optimization‖ maximizes research value
• Customization, queuing policy, software licensing
• Financial model
– Capital investment when funding ample; very low cost when
funding scarce
– ―Hidden costs‖– renovation, power, cooling
• Efficiency
– Rarely have professional staff
– Rarely recover benefits of shared experience
46

47. Hypothetical “extreme” shared model
• Large, centrally managed facility located
near inexpensive power source
• Designed and managed by professional
staff implementing best practices
• Bill for computer usage
47

48. Observation: “one size doesn’t fit all”
• Perhaps some extreme model might be an excellent
solution for a large fraction of people who use computer
resources (smaller fraction of the actual cycles used on
campus)
• Others would require a more specialized solution
– High data throughput needs to localized equipment
– Specialized architectures and systems
– Research optimization
– Interactive computing and visualization
48

49. OC11
MIT’s complex needs demanded a
comprehensive and strategic approach
MIT
HPCC
Bates
W91
Operational now (~ 1yr)
Move Admin racks to Markley
House small # of HPC racks
Operational in 2009
Renovate existing building
House 70 - 80 HPC racks
No earlier than 2011+
Build energy-efficient facility
House 150+ HPC racks
Increase capacity over time
DLCs
Limited Small HPC
Start-up HPCs
House small HPC racks
[As of 9/2008]
49

50. 50
So where does this bring us?
• Shifting from 20th century model of research
(individual contributor) to 21st century model
(multi-university collaboration) means moving
away from dependence on (and acceptance of)
individual researchers individually providing
computing, communications, and collaboration
support to institutional level support.
• It does not imply central control. It does not
imply ―one size fits all.‖
• But it does imply coordination and organization.

51. BIG DATA & ANALYTICS
51

52. The Rise of “Big Data” (Davenport)
• What is it?
– Too big (petabytes), too unstructured or too diverse
(mashups) to be analyzed by conventional means
– Internet/social media
• Where does it come from?
– Genomics, voice and video, sensors
– Continuous flow of data
• What is to be done with it?
– Structure, filter, count and classify, then analyze
– Build models but modify based on analysis of moving
data
52

53. What is “Big Data”?
• Volume
– Terabytes to petabytes
to exabytes
• Velocity
– Generation speed
• Variety
– Structured, unstructured
• Value
• Variability
• Veracity (quality)
53

54. What is “analytics”?
• Value-focused data analysis
– Predictive modeling, optimization – not just statistics
• Leading to data-driven decision-making
• A component of ―business intelligence‖
– Collection, management, reporting, analytics
• Characterized by research and experimentation
54

55. What is “analytics”?
• EDUCAUSE definition:
– Analytics is the use of data, statistical
analysis, and explanatory and predictive models
to gain insights and act on complex issues.
• In academic research from astronomy to
genomics and physics to zoology!
• Holy Grail in business: ―Dynamic real-time
business optimization‖
55

56. Where does analytics provide value?
• Analytics has been part of academic
research for a long time, leading to new
insights and other discoveries.
• The value of analytics in business is in
terms of ―understanding‖ the
organization, the business, and the
customers
– Also important to universities!
56

57. Where does analytics provide value?
• Improve outcomes of research or academics
[Learning Analytics; Research Analytics]
– Goal: Improve outcomes of research or teaching
• Improved operations [Operational Analytics]
– Goal: Reduce costs
• Grow the existing business [Product Analytics]
– Goal: Increase revenues
• Innovation
– Goal: Create new businesses or sources of revenue
57

58. Providing value through analytics
(heard at the ECAR Symposium 2012)
• Budgeting and financial planning (reducing
expenses)
• Transforming the curriculum
• Developing personally optimized
education and advising
• Providing measures and metrics with
validity across institutions
• Using analytics for resource allocation [??]
58

59. Critical Success Factors for business analytics
• Focus on analytics that have value to the
business
• Pressing business need
• Choosing the right first problem
• Clearly defined objectives
• Availability of data / data quality
• Executive leadership/sponsorship
• Committed, knowledgeable people
• Communication/education
59

60. Critical “un-success” factors
• Attempting to do everything at once
• Investing excessive resources on analytics that have minimal
impact on the business.
• Choosing the wrong problem, not understanding the problem
sufficiently, using the wrong analytical technique
• Focusing excessively on one dimension of analytical capability
(e.g. too much technology)
• Automating decision-based applications without carefully
monitoring outcomes and external conditions...‖
[Tom Davenport, Competing on Analytics, p. 129]
60

61. Other issues
• Change management
– Introducing analytics isn‘t so different from
introducing other new management processes
• Assessment
– of implementation (how will you know when you
are an ―analytic organization‖?)
– assessment of value of analytic program vs.
goals
• Future technology challenges
– HPC, cloud, anywhere-anytime analysis
– Unstructured data,―big data‖
61

62. MOVING TO “THE CLOUD”
62

63. WHY SHOULD I CARE?
• Much of IT is moving to the cloud
• The rules are different in the cloud
• Moving to the cloud opens new risks to your institution
• New skills are needed to manage IT in the cloud
• By and large, the central IT organization isn‘t controlling the
move
• You can‘t ignore it!
… but ―knowledge is power‖ and you can take action!
63

64. The cloud represents the next in a series of
major shifts in the way computing resources
are provided
64

65. Brief History lesson: Computing Models
COMPUTE
DATA
STORAGE
INPUT /
OUTPUT
65

66. Computing Models: Mainframe Era
COMPUTE
DATA
STORAGE
INPUT /
OUTPUT
Mainframe: everything done in the machine, in one place, users came to it.
66

67. Computing Models: The “Cloud” Era
User connected via a complex network
to multiple computers (servers) via
all sorts of devices
COMPUTE
DATA
STORAGE
COMPUTE
DATA
STORAGE
Internet
67

68. Types of cloud services:
“XaaS” (“X as a service”)
• Infrastructure (IaaS)
• Like buying bare bones hardware
• Platform (PaaS)
• Adds pre-configured operating system and other
software as defined by the services
• Software (SaaS)
• Buying access to specific software (e.g.
SalesForce, WorkDay, financial systems, learning
management systems – anything!)
68

69. Types of clouds…
• Public Cloud
– Generic; open to all
• Private Cloud
– Created by or for a single institution
• ―Community Cloud‖
– Features specific to a community
• Hybrid/Extension Cloud
– Using public or community cloud to provide additional capacity to
a private cloud
69

70. Moving to the (public) cloud: what’s
different?
• From ―owning resources‖ to ―deploying services‖
• From ―technical management‖ to ―contract management‖
• From ―managing IT‖ to ―managing cloud providers‖
• From ―capital costs‖ to ―operational costs‖
• From ―planned usage‖ to ―on-demand‖
…. although not totally…
70

71. Key issues related to cloud computing
• Vendor
• Network dependency
• Data
• Costs
• Contracts
71

72. Key issues related to cloud computing
• Vendor:
– Vendor dependency: ―I don‘t have the programs‖ ―I don‘t have
the data‖ – they are all with the vendor…
– Termination of service: not every service will survive
– Vendor immaturity: many cloud vendors are new – do they know
what they are doing? Who will survive?
• So what happens if the worst happens?
– Best to move with the pack and rely on ―the crowd‖ for vetting
(that‘s what Internet2 NET+ Services is all about)
– Remember that you‘re still better off than doing it yourself.
72

73. Key issues related to cloud computing
• Network dependency:
– Reliability of service:
• So what happens if the internet connection goes
down?
– Best to have multiple connections to the Internet
(most schools do).
– Internet2 is establishing multiple direct connections
with certain cloud vendors for reliability.
73

74. Key issues related to cloud computing
• Data:
– Data security / privacy: how do I know that my data are safe?
– Retention / use: what happens to my data when I don‘t need it
any more, or even when I do?
– Data location / backups: where are my data? Are their backups?
• So what happens when data is breached, misused, or
lost?
– Contractual provisions can help (but not eliminate) the problems
74

75. Key issues related to cloud computing
• Costs:
– Capital vs. operating costs: ―our budget model is based on
computers as capital costs‖ ―operating costs are easier to
budget‖
– Cost reimbursement: will research grants reimburse cloud
costs?
– Local computing vs. cloud computing ―total cost of ownership‖
(―TCO‖): is moving to the cloud really a good deal financially?
• So am I saving money or not?
– Establishing true TCO for local computing is very difficult
(multiple budget pots, hidden subsidies, etc.)
– Reimbursement is on the cusp of change.
75

76. Key issues related to cloud computing
• Contracts:
– Negotiating: will vendors ―give‖ on standard provisions?
– Institutional liability: ―I can‘t agree to any institutions liability for
actions of students and staff‖
– Institutional vs. individual control of services: who actually signs
up for the service?
– Managing contractual commitments / negotiations / regulatory
compliance: contracts are complex!
• So how do I ensure good contracting?
– The community is coming together to help: CSG, Internet2 NET+
– Hold fast to your needs and sign the ―common‖ contract
76

77. What’s a campus to do? Start now!
Create a campus strategy for internal &
external cloud services.
Create a ―cloud first‖ culture by partnering
with legal and procurement teams.
Restructure internal processes and policies
with cloud in mind.
Develop positions that focus on Cloud
Product Management: Create new or
reposition existing positions to get started.

78. What’s a campus to do? Start now!
Develop a campus identity solution built on
open standards. Join the 500+ campuses in
InCommon.org.
Support competition for services so there are
choices—but constrained, not unlimited
choices.
Evaluate Internet2 NET+ opportunities.
Examine your own portfolios and consider
which projects could benefit from NET+
scale.

79. REDUCING COSTS OF IT
Several ways of looking at…
79

80. How to look at IT expenditures
• By service
– Network, email, ERP, academic computing, etc.
• By department doing the spending (central vs. local)
• By institutional activity supported
– Administration, teaching, research
• By function
– Infrastructure, programming, customer support, etc.
• By …
80

81. How to look at IT expenditures…
Operations
~40%
Maintenance
~40%
New
Services
~20%
Definitions:
Operations = Performing a function in the course of carrying out or delivering IT services.
Maintenance = Upgrading IT services or replacing IT equipment so that current functionality & purpose is maintained.
New Services = Introducing IT services that do not exist or upgrading existing services so that new functionality is provided.
81

82. Types of Cost Reductions
• General spending reductions – reductions that do not
require process changes
– Generates small to moderate cost reductions
• Changes to the way we do business – reductions that
result from changing how we do things
– Potential for major cost reductions
• Deferred spending – put off spending until a future date
– Cost savings in current year, may result in higher cost in
future, not really a savings to institution
82

83. How can you reduce costs in IT?
• ―Economy of scale‖
– Large data centers rather than small
• ―Economy of expertise‖
– One email system rather than a dozen
• ―Economy of source‖
– Outsource, off-shore, open source
• ―Economy of delivery‖
– Self-service
83

84. How can you reduce costs in IT?
• ―Economy of scale‖
– Let Google* do it
• ―Economy of expertise‖
– Let Google* do it
• ―Economy of source‖
– Let Google* do it
• ―Economy of delivery‖
– Let everyone do it!
[*If not Google, then one of its competitors]
84

85. Changing service levels can also reduce costs…
• Productivity improvements requiring major capital
investment could impact costs and/or service levels
in different ways.
Service
Cost
Same Service
Decrease Cost
Capital Investment
Required:
* Some
** More
*** Most
*
**
***
**

86. So what to do?
• Some of these approaches are easy
(easier) for a corporation, but may be
difficult for a university.
• Need a realistic assessment of what can
be accomplished
– Modified ―Goldilocks approach‖
• Some things are easy: DO THEM
• Some things are difficult: DON‘T DO THEM
• Some things are in the middle: PLAN FOR THEM
86

87. INFORMATION TECHNOLOGY
STRATEGIC PLANNING
Where do you need to go next?
87

88. What is strategic planning all about?
Determining where
we want to be in the
future
Determining where
we are now
Determining what
drives us to the
future
88

89. What drives our approach to IT?
• Institutional priorities
• Technological change
• Desired technology leadership level
89

90. 90
Focusing on education’s
strategic drivers…
Integration of Student
Living and Education On-line Education
Research FundingGlobalization /
Internationalization
The Residential Campus
Optimization of
Financial Resources

91. 91
Technology areas of focus (2+ years)
The Cloud Integrated Communications
and Computation
Identity Management Security and Privacy
Big Data Administrative
and eCommerce systems
―Consumerization of IT‖
(End-user Computing)

92. Where do you want to be on
the “technology leadership” scale?
Visionary
Leading
Edge
‖Standard‖
Lagging
Leader-ship
Tech Area
92

93. Technology Leadership Scale (Example)
Visionary
Leading
Edge
‖Standard‖
Lagging
93

94. What drives our approach to IT?
Institutional Context
“Strategic
Priorities”
from
university
strategic plan
“Strategic
Priorities”
from faculty
and student
input
“Strategic
Priorities”
from peers
and emerging
trends
Strategic Areas of Focus
Assess current
level of
technology
Assess desired
level of
technology
Strategic Objectives
Outcomes Value and impact
94

95. …all components are linked together
Administrative
Systems Strategic Plan
“Living the Future”
Strategy
IT Strategic
Principles
Educational Technology
Planning
Student Systems
Strategic Plan
Telephony Transition
Enterprise
Architecture
Guide
Network and Operations
Planning
Research
CyberInfrastructure
95

96. FITS 2011
Many of the recommendations in the Flagship IT Strategy 2011
exemplify the strategic concerns we have discussed today.

97. Riding the “crest of the wave”
…an exciting and challenging place to be!

98. Thank you, and GO TIGERS!
Jerrold M. Grochow
jerry@jerroldgrochow.com