May 10, 2012
EDUCAUSE LIVE!
Session leader: Jerry Grochow
GOAL: Share results of research on ITs role in
analytics programs and making them
successful.
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General comments about analytics programs
Review of findings to date
Research sponsored in part by the International Institute for Analytics, Intel Corporation, and SAS Institute, Inc.
Some materials copyright 2011 International Institute for Analytics
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Questions to be answered:
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DEFINE: What
is “analytics”?
INTRODUCE: How do you start an analytics program?
WHO: Whose job is it?
CSF: What are the critical success factors?
ISSUES: Other issues
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Value-focused data analysis
 Predictive modeling, optimization – not just statistics
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Leading to data-driven decision-making
A component of “business intelligence”
 Collection, management, reporting, analytics

Characterized by research and experimentation
DEFINE
INTRODUCE
WHO
CSF
ISSUES
4
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EDUCAUSE definition:
 Analytics is the use of data, statistical analysis, and
explanatory and predictive models to gain insights and
act on complex issues.

Holy Grail: “Dynamic real-time business
optimization”
DEFINE
INTRODUCE
WHO
CSF
ISSUES
5
Business question
Terminology
What happened in the past?
Periodic (regular) reporting, ad hoc
reporting, “dashboards”
Tell me what happened that wasn’t
expected
Tell me when something unexpected
happens
Exception reporting
Alerts (real-time exception reporting)
• All of these are “reporting” but not really “analytics” activities
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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Business question
Terminology
Tell me something I don’t know
Data mining
Why is this happening?
Analysis, including statistical analysis,
on-line analytical processing (OLAP, an
older term), modeling
What will happen in the future?
Forecasting, predictive modeling,
predictive analytics
How can I improve what happens in the
future?
Show me graphically
Optimization
Visualization techniques
I want to know now how to improve the
“Dynamic real-time business
future, based on what happened in the past optimization” based on predictive
and everything I know about what is likely
analytics – “prescriptive analytics”
to happen in the future – and I want to
know what steps to take.
Take those steps automatically.
“Embedded analytics”
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Establish the value/importance of analytics
Set specific business goals and strategy
Develop a plan for analytics activities
 Staffing plan
 Data plan
 Technology plan
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Execute the first project
Measure the value
Communicate
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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

The value of analytics is often stated in terms
of “understanding” the organization or the
business or the customers
But this translates into:
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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
Improved operations [Operational Analytics]
 Goal: Reduce costs

Grow the existing business [Product Analytics]
 Goal: Increase revenues

Improve outcomes of research or academics
[Learning Analytics; Research Analytics]
 Goal: Improve outcomes of research or teaching

Innovation
 Goal: Create new businesses or sources of revenue
DEFINE
INTRODUCE
WHO
CSF
ISSUES
10
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What are the goals of your analytics program?
 Don’t have an analytics program
 Haven’t determined goals
 If you do have program goals, what are they?
▪
▪
▪
▪
▪
▪
General understanding
Reduce costs of operations
Improve outcomes of research or teaching
Increase revenues from existing business
Create new businesses or sources of revenues
Other
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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Funding
Governance
Data architecture
Technology architecture
Operational implementation and assessment
 Integration of analytics with operational systems
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Communication and education
Evolution
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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
Under consideration
 “Visioning”

Getting Started
 “Launching”

Under Construction
 “Implementing”
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Mature
 “Transforming”
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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People
Process
Governance
Technology
On-board
Collaboration
between IT and
BUs; measuring
value
Steering Comm;
data and analytics
governance “SOP”
Operational DW;
ETL tools; analytics
integrated into
operational
systems;
measurement
tools; evaluation
program
“Under
Consideration”
(Visioning)
“Getting
Started”
(Launching)
“Under
Construction”
(Implementing)
“Mature”
(Transforming)
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Typically started by a business function
Most successful programs come from a
business/IT partnership
 “Creating a marriage…”
 Working together on people and process

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IT has to take responsibility for infrastructure
IT can become a “champion” for analytics
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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
How should analytics activity be organized?
 One or multiple departments?

Where should it report?
 To IT or not to IT…

Does it matter?
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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President /
Provost /
Chancellor
Institutional
Analytics
Academic
Hierarchy
Administrative
Hierarchy
IT
Research
Hierarchy
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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President /
Provost /
Chancellor
Academic
Hierarchy
Institutional
Analytics (?)
Administrative
Hierarchy
Research
Hierarchy
IT
Institutional
Analytics (?)
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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President /
Provost /
Chancellor
Academic
Hierarchy
Administrative
Hierarchy
Research
Hierarchy
IT
Institutional
Analytics
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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Where does the analytics organization report
within your institution? [May select multiple]
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President/Chancellor/Senior Official
Provost/Academic Leader
CFO/CBO/Administrative Leader
Leader of some academic unit
Leader of some administrative unit (other than IT)
Leader of IT
Other
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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
What determines the likely success of an
analytics program?
 How do you define “success”?
 Meeting goals [see above]
 Becoming an “analytical organization”
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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Maturity as an “analytic competitor”
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Stage 1: “Major Barriers”
Stage 2: “Local Activities”
Stage 3: “Vision Not Yet Realized”
Stage 4: “Almost There”
Stage 5: “Analytical Competitor”
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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Pressing business need
Availability of data / data quality
Executive leadership/sponsorship
Committed, knowledgeable people
Clearly defined objectives
Focus on analytics that have value to the
business
Choosing the right first problem
Communication/education
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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Importance
Initial
Project
Sustaining
Program
Committed, knowledgeable people: interested in, knowledgeable about
analytics
M
H
Executive leadership/sponsorship
M
H
Clearly defined (and initially limited) objectives
H
M
Choosing the right problem: find a pressing business need with high
value
Communication/education: about the value of analytics, about the
importance of the problem being studied
H
M
M
H
Using the right analytic techniques and software
L
H
Availability and access to quality data
L
M
Critical Success Factors
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Which CSF’s are in place in your organization?

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Pressing business need
Availability of data / data quality
Executive leadership/sponsorship
Committed, knowledgeable people
Clearly defined objectives
Focus on analytics that have value to the business
Choosing the right first problem
Communication/education
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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Analytics Critical Success Factors
Committed people
5
4
Technology
3
2
Educated
management
1
0
Defined objectives
Executive support
Quality data
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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
Focusing excessively on one dimension of analytical capability (e.g. too
much technology)
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Attempting to do everything at once
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Investing excessive resources on analytics that have minimal impact on
the business

Investing too much or too little in any analytical capability, compared with
demand

Choosing the wrong problem, not understanding the problem sufficiently,
using the wrong analytical technique or the wrong analytical software

Automating decision-based applications without carefully monitoring
outcomes and external conditions to see whether assumptions need to be
modified.”
[Tom Davenport, Competing on Analytics, p. 129]
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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
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”
DEFINE
INTRODUCE
WHO
CSF
ISSUES
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1.
2.
3.
4.
Can you articulate how analytics will help the organization?
Do you have good relationships with the business leaders
whose groups will most benefit?
Do you know what your peers are doing with analytics and
how it is helping their organizations?
Are you “passionate about analytics?”
[Have you been to an analytics conference or symposium recently?]
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1.
2.
3.
4.
5.
6.
7.
Does the IT department understand the key analytics issues for the
enterprise?
Do you understand what the key analytics issues are for the IT
department?
Does your department have the most important skill sets necessary for
success with analytics?
Do you encourage experimentation? Is your development
methodology flexible enough to accommodate analytics projects?
How good is the organization’s data? Are definitions consistent? Is
data “scrubbed”?
Do you know who the vendors and integrators are in analytics IT and
what they can do for your organization?
Are you prepared for “big data,” high performance computing, realtime analytics – i.e. the future?
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
CIO “Readiness Assessment” -- How did you
score?
 1-4: Lots of work to do!
 5-8: On the way!
 9-11: You’re ready to get moving!
 12:
You know there are more questions!
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
Led by Jackie Bichsel (jbichsel@educause.edu)

Survey underway

Presentations at ECAR Symposium in
Boulder (June 20)
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Jerrold M. Grochow
jerry@jerroldgrochow.com
• Senior Consultant to colleges and universities
and the organizations that serve them
• Internet2 Interim Vice President for NET+ Services
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