it and u: discussion with lsu transition advisory team

IT and U

Discussion withLouisiana State UniversityTransition Advisory Team

April 29, 2013

Jerrold M. Grochow

Some materials © 2012,2013 Jerrold M. Grochow LLC

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

Drivers of the discussion

3

• Building toward “LSU2015”

• Becoming globally competitive

• Cost savings

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

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

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

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

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

SO WHERE DOES THIS BRING US?

9

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

ERP IMPLEMENTATION: A CASE STUDY

11

Reengineering at MIT: “A Journey”

12

Community input is crucial

Reengineering set to begin; teams, consultant named November 22, 1993

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

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

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

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…”


16

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…”

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

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 appointedVP for IS&T

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

BudgetingSystem

Independent Laboratory SAP

ResearchAdministration

System

SAP ITS• Parking

Pass• Time

Approv

• Tuition Assistance

• Benefits

• Directory

• Training

• JV• Req• UPI

• Repair

• Env. Health

• Time Entry

• Dir Deposit

SAP-WEBOAS

Systems on a Page (Vers. 0.1)

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]


• 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

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

Potentially very large savings

24

The “New” Model

Workday

Sales- force

Concur

PeopleSoft

COEUSFinancialSystem

“ON-CAMPUS”Clear

Commerce

InternetInternet

“IN THE CLOUD”

[Names are examples]

“Integration with the cloud” is becoming a product category

26[Names are examples]

Future State Vision (Vers. 0.1)

Service Integration Layer

Data

Security Services

Services

Data & Business Integration Layer

Administrative Services

ERP Services

Academic Services

Student InformationServices

Applications

User Interfaces

Auth

enti

cati

on Serv

ices

Auth

ori

zati

on Serv

ices

Learning Services Research Services

Applicant Portal

GrantManagement

PayrollFinance BudgetHR Purchasing

Applicants Students Alumni FacultyStaff

Core Services

List Management ServicesContent Management

ServicesE-Commerce Services

Directory & DemographicServices

Identity Services

EMail and MessagingServices

External IntegrationServices

Archival ServicesCollaboration ServicesMapping and Location

Services

Extended Community

Facilities

MedicalPresident's

OfficeEH & S Admissions Student Alumni

Library

ContentManagement

LearningManagement

TechnologyLicensing

Student Portal

Stand Alone GUIInterface

Stand Alone WebInterface

Alumni Portal

Extended CommunityPortal(s)

Faculty Portal

Staff Portal

ResourceDevelopment

FinanceData

HRData

FacilitiesData

GrantsData

MedicalData

StudentData

LearningData

ResearchData

LibraryData

DataWarehouse

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

MASSIVELY OPEN ON-LINE COURSES (MOOCs)

29

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


• 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


• 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

Implications for higher ed (1)

Content creation (and certification of

courses)

TeachingLearning (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?

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

Things to think about: Intended audience

• Current students• New students with similar characteristics• Students with different characteristics

(different/under-served populations)• Third world

35

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

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

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

IT IN SUPPORT OF RESEARCH

39

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

NSF Report on Cyberinfrastructure[“Atkins Report” 2003]

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

Central IT Services for Research[EDUCAUSE Core Data Survey 2011]

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

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

DR

MA

BA LA

BA other

AA

Institutional type averages

[The break in the bar represents the overall average for higher education]

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

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

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

OC11

MIT’s complex needs demanded a comprehensive and strategic approach

MIT

HPCC

Bates

W91

Operational now (~ 1yr)Move Admin racks to MarkleyHouse small # of HPC racks

Operational in 2009Renovate existing buildingHouse 70 - 80 HPC racks

No earlier than 2011+Build energy-efficient facilityHouse 150+ HPC racksIncrease capacity over time

DLCsLimited Small HPCStart-up HPCsHouse small HPC racks

[As of 9/2008]

49

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.

BIG DATA & ANALYTICS

51

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

What is “Big Data”?

• Volume– Terabytes to petabytes

to exabytes

• Velocity– Generation speed

• Variety– Structured, unstructured

• Value

• Variability• Veracity (quality)

53

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

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

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

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

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

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

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

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

MOVING TO “THE CLOUD”

62

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

The cloud represents the next in a series of major shifts in the way

computing resources are provided

64

Brief History lesson: Computing Models

COMPUTEDATA STORAGE

INPUT / OUTPUT

65

Computing Models: Mainframe Era

COMPUTEDATA STORAGE

INPUT / OUTPUT

Mainframe: everything done in the machine, in one place, users came to it.

66

Computing Models: The “Cloud” Era

User connected via a complex networkto multiple computers (servers) via

all sorts of devices

COMPUTEDATA

STORAGE

COMPUTE

DATA STORAGE

InternetInternet

67

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

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

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

Key issues related to cloud computing

• Vendor• Network dependency• Data• Costs• Contracts

71


• 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


• 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


• 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


• 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


• 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

What’s a campus to do? Start now!

1

2

3

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.

What’s a campus to do? Start now!

4

5

6

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.

REDUCING COSTS OF ITSeveral ways of looking at…

79

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

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

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

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

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

Changing service levels can also reduce costs…

• Productivity improvements requiring major capital investment could impact costs and/or service levels in different ways.

Se

rvic

e

Cost

Decrease Cost

Decrease Service

Increase Service

Increase Cost

Same Service

Decrease Cost

Improve Service

Decrease C

ost

Capital Investment Required:

* Some

** More

*** Most*

**

***

**

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

INFORMATION TECHNOLOGY STRATEGIC PLANNING

Where do you need to go next?

87

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

What drives our approach to IT?

• Institutional priorities

• Technological change

• Desired technology leadership level

89

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

Technology areas of focus (2+ years)

The Cloud Integrated Communications and Computation

Identity Management Security and Privacy

Big Data Administrativeand eCommerce systems

“Consumerization of IT” (End-user Computing)

Where do you want to be on the “technology leadership” scale?

Visionary

LeadingEdge

”Standard”

Lagging

Offi

ceC

ompu

ting

Acad

emic

Com

putin

g

Res

earc

hC

ompu

ting

Adm

inis

trativ

e

Com

putin

g

Leader-ship

Tech Area

92

Technology Leadership Scale (Example)

Visionary

LeadingEdge

”Standard”

Lagging

Offi

ceC

ompu

ting

Acad

emic

Com

putin

g

Res

earc

hC

ompu

ting

Adm

inis

trativ

e

Com

putin

g

93

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

…all components are linked together

AdministrativeSystems Strategic Plan

“Living the Future”Strategy

IT StrategicPrinciples

Educational TechnologyPlanning

Student Systems Strategic Plan

Telephony Transition

EnterpriseArchitecture

Guide

Network and OperationsPlanning

ResearchCyberInfrastructure

95

FITS 2011

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

Riding the “crest of the wave”

…an exciting and challenging place to be!

Thank you, and GO TIGERS!

Jerrold M. Grochow

[email protected]