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Copyright © 2010 SAS Institute Inc. All rights reserved.
Enabling Fact-Based
Governance with
Analytics
Seminar Governans IPTA: Pemangkin
Kecemerlangan Organisasi
19th Nov 2011
Sarabjeet Singh
Director, Professional Services
SAS Malaysia
2
Copyright © 2010, SAS Institute Inc. All rights reserved.
 18 years of experience in technology and management
consulting.
 Responsible for SAS Malaysia consulting engagements
across all industry sectors. Started career with global
consulting firm Accenture and subsequently global
outsourcer EDS.
 Clients include RHB, EPF, CIMB, Aeon/Jusco, EON Bank, Bank Islam, CGC,
London Stock Exchange, Bank Negara Indonesia, Siam Commercial Bank.
 Key Skills and Experience
 Business Analysis including assessing operational capabilities and
defining opportunities to create value
 Solution Planning including visioning and transformation planning
 Business Analytics
 Programme and Change Management
 Educational Background:
 Certified Diploma in Accounting & Finance - ACCA, 1997
 MS Engineering - Univ of Toledo, Ohio, U.S.A., 1993
 BS Engineering (Magna Cum Laude) - Univ of Toledo, U.S.A., 1991
About Me
Sarabjeet Singh,
Director,
Professional
Services
3
Copyright © 2010, SAS Institute Inc. All rights reserved.
About SAS
 Founded in 1976 and today it’s world's largest
privately held software company.
 More than 50,000 customers in over 127
different countries.
 90 of the top 100 companies on the 2011
FORTUNE Global 500® use SAS.
 SAS has remained committed to partnering
with education to deliver software and services
for both academics and administration
purposes.
 SAS Institute (US) Ranked Best Place to Work
for year 2010 and 2011.
 Revenue US$2.43b; Employees 12,382.
Dr. Jim Goodnight,
Founder and CEO
SAS Campus, Cary, NC,
USA
4
Copyright © 2010, SAS Institute Inc. All rights reserved.
Introduction
 “The goal of education is the advancement of knowledge
and the dissemination of truth.” – John F. Kennedy
 But…the advancement of knowledge and dissemination
of truth should not be limited to lecture halls. Knowledge
is at the very heart of University operations and its
governance.
 This knowledge and information is the platform for fact
based governance through:
1. Hindsight …… understand the past
2. Insight .….…. manage the present
3. Foresight ……. create the future
Analytics provides hindsight, insight and foresight.
5
Copyright © 2010, SAS Institute Inc. All rights reserved.
Typical IPTA/S’s Goals and Aspirations
World-class research and publication
Professional recognitions and accreditations
Creation of scholars
International awards
The university of choice
Increased university intake
Quality academic programs
Centre of excellence
ISO certification
Income generation
Major scientific discoveries
Employability
International network & collaborations
Cost Management
Illustrative Only
Contribution to society
6
Copyright © 2010, SAS Institute Inc. All rights reserved.
How to Enable Fact-Based Governance
1. Integrate Data Across the Institution
 Establish:
Consistent, reliable and credible data.
Integrated and comprehensive view of what is happening
2. Equip All Decision Makers with Reporting/Analysis
 After data is consolidated, understood and cleansed, it can be
used as the basis for
Timely, accurate reporting.
Self-service & secure access to automated and drillable
reports, for up to data analysis.
7
Copyright © 2010, SAS Institute Inc. All rights reserved.
How to Enable Fact-Based Governance
3. Identify Current and Future Trends for Better Decision
Making by applying analytical techniques
 While historical reporting gives you plenty of hindsight, it doesn’t
provide the insight and foresight you need to make decisions for
the future.
 Discover the complex relationships between dynamic factors that
affect Institutions, students and learning outcomes today.
 It’s possible to develop valuable insights to in-depth questions:-
From simply knowing the past to predicting the future.
From “How many first-year students dropped out each past
semester?” to “Why did these students drop out?” to “How
many will drop out next year?” to “What is the best
intervention for the future?”
8
Copyright © 2010, SAS Institute Inc. All rights reserved.
What Is Analytics?
 “The science of analysis” - the process of
obtaining an optimal or realistic decision based
on existing data.
 Includes data mining and statistical analysis in
order to discover and understand historical
patterns to predict and improving business
performance in the future.
 Includes domain of mathematics, operations
research, statistics and probability.
 Usage includes enterprise decision
management, marketing analytics, predictive
science, strategy science, credit risk analysis
and fraud analytics.
9
Copyright © 2010, SAS Institute Inc. All rights reserved.
How does Analytics enable Governance?
What happened?
How many, how often, where?
Where exactly is the problem?
What actions are needed?
Why is this happening?
What if these trends continue?
What will happen next?
What’s the best that can happen?
Hindsight ………..… Insight ..............….… Foresight
10
Copyright © 2010, SAS Institute Inc. All rights reserved.
Analytics Application in Industries
 Financial Services
 Financials, Profitability, Credit Risk, Customer, Marketing, Collection
 Communications
 Churn, Retention, Pricing, Collection, Customer Care
 Retail
 POS, Loyalty, Customer Behavior, Retention
 Web
 Social Media, Online Sales
 Transportation/Logistics
 Activity Based Mgmt, Optimization
 Education
 Enrollment, Student Affairs, Operations Mgmt, Benchmarking
11
Copyright © 2010, SAS Institute Inc. All rights reserved.
Case Study: University of Central Florida
 UCF’s mission:
Provide students with a world-class education.
 Business Issue:
UCF required a reporting and analysis platform for
enrollment planning, strategic planning,
management analysis and exploratory analysis to
provide university leaders with insight that supports
proactive decision making.
Sandra Archer,
PhD,
Director, Office of
University Analysis
and Planning
Support
“The university's customers are its students. Our
analytical work helps the leadership team make
informed decisions to further UCF's mission.” “The
goal analytics is to gain a better understanding of
what’s happening with students so that we can
determine how our university can serve them
better.” - Sandra Archer, PhD
12
Copyright © 2010, SAS Institute Inc. All rights reserved.
 Challenges:
 Disparate data.
 Slow! 2 days to 3 weeks to get information …. and confidence
was lacking.
 Could only get the basic information….Leading to “reactive”
management.
 Challenged to see changes occurring across multiple years.
 The Solution Journey:
 Strategic Plan placed an emphasis on:
 Data quality
 Data accuracy
 Data integrity
 Data accessibility.
 An integrated solutions for data management, analysis and
information delivery across the organization.
Case Study: University of Central Florida
13
Copyright © 2010, SAS Institute Inc. All rights reserved.
 Enabled: Enrollment Planning
 Accurate enrollment planning is crucial for UCF.
 Help university decision makers
 Forecast demand
 Formulate institutional policies.
“We look at population projections and high school graduation rates,, to
determine a demand forecast for enrollment. Enrollment is a significant
focus for us; predictive analysis ensures we stay on top of it.” “We go back
each year to assess the accuracy of our results – our model is accurate
within 1%. We implement correction factors on a year-to-year basis to
continually teach the model and improve the future accuracy.”
“This projection is used to establish budgets, determine what courses will be
offered and how many faculty resources will be needed. The projections are
also used by the state to determine aspects of funding the university
receives.” – Sandra Archer, PhD
Case Study: University of Central Florida
14
Copyright © 2010, SAS Institute Inc. All rights reserved.
 Enabled: Strategic Planning
 UCF performs benchmarking analysis against two quantitatively
generated lists: similar institutional peers and aspirational peers.
 The benchmarks rely on data from the National Center for
Educational Statistics and are used by a wide variety of
university staff. UCF uses the data to look at how other
institutions are organized, student characteristics, student-to-
faculty ratios and student retention/graduation rates.
“Eight years ago we developed a set of benchmarking peers and held
the list static over time. Recently, we used a new clustering analysis
technique to rework the lists, and we looked back to see how the
institution had changed compared to the two original lists. Some of
the institutions that we once considered aspirational had become
comparison peers.” – Sandra Archer, PhD
Case Study: University of Central Florida
15
Copyright © 2010, SAS Institute Inc. All rights reserved.
“We look at students over their entire life cycle here, as well as post-graduation
success factors. We look at what their majors are at graduation and compare that
to their majors at the time of registration. We can see how many times they’ve
changed majors, and how many graduated with a typical number of credit hours.
With data from the National Student Clearinghouse’s StudentTracker Data System,
we’ve launched a project that helps us track students after graduation. For
instance, this allows us to see whether they enrolled elsewhere after UCF. I also
can tap into data from the state of Florida to determine how many UCF graduates
find employment within the state. It gives the university a clearer picture of how we
are preparing students for life after UCF.” – Sandra Archer, PhD
Case Study: University of Central Florida
 Enabled: Management Analysis
 It’s to provide university leadership with insight on student
behavior while at school and after they graduate.
 Deep analysis and reports on its colleges, programs, student life
cycles – admissions, course taking behavior, retention and
completion/continuation patterns.
16
Copyright © 2010, SAS Institute Inc. All rights reserved.
Case Study: University of Central Florida
 Enabled: Exploratory Analysis
 It’s to provide insights in support of forward-looking decisions and
formulate institutional policies.
 Internal research on university management – eg. cost studies,
faculty activity, benchmarking and resource utilization
“SAS gives us the ability to perform a lot of analytics quickly, which allows
more time to pause and look at the bigger picture. It also helps us find
patterns in the data that we might not otherwise have noticed.” - Sandra
Archer, PhD
17
Copyright © 2010, SAS Institute Inc. All rights reserved.
What Needs to be Done
+ +
Integrated Source
Data
Equip Decision Makers
Platform for Analytics
Know-How
Discover the
relationships
of factors
Enables:
1. Hindsight …… understand the past
2. Insight ….….. manage the present
3. Foresight ……. create the future
18
Copyright © 2010, SAS Institute Inc. All rights reserved.
In Conclusion
 We encourage IPTAs to use Analytics to
enhance Governance
 Establish the analytics platform
 Inculcate a culture of analytics
 Build the know-how and seek answers to the right
questions
 Industry collaboration for greater insight and foresight
Govern with confidence
Hindsight ………..… Insight ..............….… Foresight
Copyright © 2010 SAS Institute Inc. All rights reserved.
THANK YOU
www.sas.com/education

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Enabling fact based governance with analytics external

  • 1. Copyright © 2010 SAS Institute Inc. All rights reserved. Enabling Fact-Based Governance with Analytics Seminar Governans IPTA: Pemangkin Kecemerlangan Organisasi 19th Nov 2011 Sarabjeet Singh Director, Professional Services SAS Malaysia
  • 2. 2 Copyright © 2010, SAS Institute Inc. All rights reserved.  18 years of experience in technology and management consulting.  Responsible for SAS Malaysia consulting engagements across all industry sectors. Started career with global consulting firm Accenture and subsequently global outsourcer EDS.  Clients include RHB, EPF, CIMB, Aeon/Jusco, EON Bank, Bank Islam, CGC, London Stock Exchange, Bank Negara Indonesia, Siam Commercial Bank.  Key Skills and Experience  Business Analysis including assessing operational capabilities and defining opportunities to create value  Solution Planning including visioning and transformation planning  Business Analytics  Programme and Change Management  Educational Background:  Certified Diploma in Accounting & Finance - ACCA, 1997  MS Engineering - Univ of Toledo, Ohio, U.S.A., 1993  BS Engineering (Magna Cum Laude) - Univ of Toledo, U.S.A., 1991 About Me Sarabjeet Singh, Director, Professional Services
  • 3. 3 Copyright © 2010, SAS Institute Inc. All rights reserved. About SAS  Founded in 1976 and today it’s world's largest privately held software company.  More than 50,000 customers in over 127 different countries.  90 of the top 100 companies on the 2011 FORTUNE Global 500® use SAS.  SAS has remained committed to partnering with education to deliver software and services for both academics and administration purposes.  SAS Institute (US) Ranked Best Place to Work for year 2010 and 2011.  Revenue US$2.43b; Employees 12,382. Dr. Jim Goodnight, Founder and CEO SAS Campus, Cary, NC, USA
  • 4. 4 Copyright © 2010, SAS Institute Inc. All rights reserved. Introduction  “The goal of education is the advancement of knowledge and the dissemination of truth.” – John F. Kennedy  But…the advancement of knowledge and dissemination of truth should not be limited to lecture halls. Knowledge is at the very heart of University operations and its governance.  This knowledge and information is the platform for fact based governance through: 1. Hindsight …… understand the past 2. Insight .….…. manage the present 3. Foresight ……. create the future Analytics provides hindsight, insight and foresight.
  • 5. 5 Copyright © 2010, SAS Institute Inc. All rights reserved. Typical IPTA/S’s Goals and Aspirations World-class research and publication Professional recognitions and accreditations Creation of scholars International awards The university of choice Increased university intake Quality academic programs Centre of excellence ISO certification Income generation Major scientific discoveries Employability International network & collaborations Cost Management Illustrative Only Contribution to society
  • 6. 6 Copyright © 2010, SAS Institute Inc. All rights reserved. How to Enable Fact-Based Governance 1. Integrate Data Across the Institution  Establish: Consistent, reliable and credible data. Integrated and comprehensive view of what is happening 2. Equip All Decision Makers with Reporting/Analysis  After data is consolidated, understood and cleansed, it can be used as the basis for Timely, accurate reporting. Self-service & secure access to automated and drillable reports, for up to data analysis.
  • 7. 7 Copyright © 2010, SAS Institute Inc. All rights reserved. How to Enable Fact-Based Governance 3. Identify Current and Future Trends for Better Decision Making by applying analytical techniques  While historical reporting gives you plenty of hindsight, it doesn’t provide the insight and foresight you need to make decisions for the future.  Discover the complex relationships between dynamic factors that affect Institutions, students and learning outcomes today.  It’s possible to develop valuable insights to in-depth questions:- From simply knowing the past to predicting the future. From “How many first-year students dropped out each past semester?” to “Why did these students drop out?” to “How many will drop out next year?” to “What is the best intervention for the future?”
  • 8. 8 Copyright © 2010, SAS Institute Inc. All rights reserved. What Is Analytics?  “The science of analysis” - the process of obtaining an optimal or realistic decision based on existing data.  Includes data mining and statistical analysis in order to discover and understand historical patterns to predict and improving business performance in the future.  Includes domain of mathematics, operations research, statistics and probability.  Usage includes enterprise decision management, marketing analytics, predictive science, strategy science, credit risk analysis and fraud analytics.
  • 9. 9 Copyright © 2010, SAS Institute Inc. All rights reserved. How does Analytics enable Governance? What happened? How many, how often, where? Where exactly is the problem? What actions are needed? Why is this happening? What if these trends continue? What will happen next? What’s the best that can happen? Hindsight ………..… Insight ..............….… Foresight
  • 10. 10 Copyright © 2010, SAS Institute Inc. All rights reserved. Analytics Application in Industries  Financial Services  Financials, Profitability, Credit Risk, Customer, Marketing, Collection  Communications  Churn, Retention, Pricing, Collection, Customer Care  Retail  POS, Loyalty, Customer Behavior, Retention  Web  Social Media, Online Sales  Transportation/Logistics  Activity Based Mgmt, Optimization  Education  Enrollment, Student Affairs, Operations Mgmt, Benchmarking
  • 11. 11 Copyright © 2010, SAS Institute Inc. All rights reserved. Case Study: University of Central Florida  UCF’s mission: Provide students with a world-class education.  Business Issue: UCF required a reporting and analysis platform for enrollment planning, strategic planning, management analysis and exploratory analysis to provide university leaders with insight that supports proactive decision making. Sandra Archer, PhD, Director, Office of University Analysis and Planning Support “The university's customers are its students. Our analytical work helps the leadership team make informed decisions to further UCF's mission.” “The goal analytics is to gain a better understanding of what’s happening with students so that we can determine how our university can serve them better.” - Sandra Archer, PhD
  • 12. 12 Copyright © 2010, SAS Institute Inc. All rights reserved.  Challenges:  Disparate data.  Slow! 2 days to 3 weeks to get information …. and confidence was lacking.  Could only get the basic information….Leading to “reactive” management.  Challenged to see changes occurring across multiple years.  The Solution Journey:  Strategic Plan placed an emphasis on:  Data quality  Data accuracy  Data integrity  Data accessibility.  An integrated solutions for data management, analysis and information delivery across the organization. Case Study: University of Central Florida
  • 13. 13 Copyright © 2010, SAS Institute Inc. All rights reserved.  Enabled: Enrollment Planning  Accurate enrollment planning is crucial for UCF.  Help university decision makers  Forecast demand  Formulate institutional policies. “We look at population projections and high school graduation rates,, to determine a demand forecast for enrollment. Enrollment is a significant focus for us; predictive analysis ensures we stay on top of it.” “We go back each year to assess the accuracy of our results – our model is accurate within 1%. We implement correction factors on a year-to-year basis to continually teach the model and improve the future accuracy.” “This projection is used to establish budgets, determine what courses will be offered and how many faculty resources will be needed. The projections are also used by the state to determine aspects of funding the university receives.” – Sandra Archer, PhD Case Study: University of Central Florida
  • 14. 14 Copyright © 2010, SAS Institute Inc. All rights reserved.  Enabled: Strategic Planning  UCF performs benchmarking analysis against two quantitatively generated lists: similar institutional peers and aspirational peers.  The benchmarks rely on data from the National Center for Educational Statistics and are used by a wide variety of university staff. UCF uses the data to look at how other institutions are organized, student characteristics, student-to- faculty ratios and student retention/graduation rates. “Eight years ago we developed a set of benchmarking peers and held the list static over time. Recently, we used a new clustering analysis technique to rework the lists, and we looked back to see how the institution had changed compared to the two original lists. Some of the institutions that we once considered aspirational had become comparison peers.” – Sandra Archer, PhD Case Study: University of Central Florida
  • 15. 15 Copyright © 2010, SAS Institute Inc. All rights reserved. “We look at students over their entire life cycle here, as well as post-graduation success factors. We look at what their majors are at graduation and compare that to their majors at the time of registration. We can see how many times they’ve changed majors, and how many graduated with a typical number of credit hours. With data from the National Student Clearinghouse’s StudentTracker Data System, we’ve launched a project that helps us track students after graduation. For instance, this allows us to see whether they enrolled elsewhere after UCF. I also can tap into data from the state of Florida to determine how many UCF graduates find employment within the state. It gives the university a clearer picture of how we are preparing students for life after UCF.” – Sandra Archer, PhD Case Study: University of Central Florida  Enabled: Management Analysis  It’s to provide university leadership with insight on student behavior while at school and after they graduate.  Deep analysis and reports on its colleges, programs, student life cycles – admissions, course taking behavior, retention and completion/continuation patterns.
  • 16. 16 Copyright © 2010, SAS Institute Inc. All rights reserved. Case Study: University of Central Florida  Enabled: Exploratory Analysis  It’s to provide insights in support of forward-looking decisions and formulate institutional policies.  Internal research on university management – eg. cost studies, faculty activity, benchmarking and resource utilization “SAS gives us the ability to perform a lot of analytics quickly, which allows more time to pause and look at the bigger picture. It also helps us find patterns in the data that we might not otherwise have noticed.” - Sandra Archer, PhD
  • 17. 17 Copyright © 2010, SAS Institute Inc. All rights reserved. What Needs to be Done + + Integrated Source Data Equip Decision Makers Platform for Analytics Know-How Discover the relationships of factors Enables: 1. Hindsight …… understand the past 2. Insight ….….. manage the present 3. Foresight ……. create the future
  • 18. 18 Copyright © 2010, SAS Institute Inc. All rights reserved. In Conclusion  We encourage IPTAs to use Analytics to enhance Governance  Establish the analytics platform  Inculcate a culture of analytics  Build the know-how and seek answers to the right questions  Industry collaboration for greater insight and foresight Govern with confidence Hindsight ………..… Insight ..............….… Foresight
  • 19. Copyright © 2010 SAS Institute Inc. All rights reserved. THANK YOU www.sas.com/education

Notas do Editor

  1. Good afternoon Before I begin, allow me to first introduce myself and the organization I work for -SAS. I am presently the director for professional services for SAS Malaysia and my responsibility is for oversight and success of all our client engagements in Malaysia. I am trained as an engineer but made a career shift to management consulting when I first joined management consulting firm Andersen Consulting which subsequently became Accenture. After 9 years there I moved on to work for the world largest outsourcing company EDS for 7 years and I have now been with SAS for 2 years. It is indeed an honor for me to be invited to speak at this conference. SAS and I express our gratitude for this opportunity.
  2. I have to say something about SAS – otherwise “potong gaji” SAS has its roots in acedemia – it was born out of software that was developed by Prof Jim Goodnight and some of his colleagues for agricultural research. Over 35 years it has grown to be: The worlds largest privately held software company. 50,000 customer over 127 countries. 90% of the Fortune 100 companies uses SAS. SAS has a unique culture in its campus in NC (focusing on R&D) and has ranked No. 1 in Fortune Magazine’s best place to work – beating companies like Google
  3. In line with the theme of this conference, I’m going to be speaking about how analytics can enable fact based governance in universities and IPTAs. Education is about Advancement of Knowledge and Dissemination of Truth. But this is not limited to the lecture halls but also for university operations and its governance Hindsight, …. Insight,…..Foresight I will first like to share with you Generically how to enable fact based governance What is Analytics How Analytics is enabling fact based governance in other industries A case study of how Analytics enabled fact based governance
  4. As we were invited to speak here about 10 days ago we didi a little research on what typical university goals and aspirations are. In governing Universities there are many areas that require hindsight, insight and foresight. A simple example is in income generation Hindsight: Essential to know how income has been trending over the last few years by college, by section, etc Insight: What are the income and cost elements that have been increasing or decreasing and why? Foresight: How does income change with for example, combination of virtual learning environments and physical learning environments? Similarly for employability – what has been the trend? Hindsight. What are the known factors? Insight. By changing course content, language skills or industry knowledge, will it improve? Foresight.
  5. Step 1. Integrate Data across the enterprise Challenge : Fragmented data at multiple systems in multiple departments – a common challenge across all industries Step 2. Equip all decision makers with reporting and analysis capabilities This is not about producing reporting packs on a monthly basis – but about putting in the hands of decision makers analysis capabilities. For example a bank that we are working with is embarking on having their analytical reports on the ipads of board members for to drill down and understand and make swift fact based decisions in the boardroom.
  6. Identify current and future trends by applying analytical techniques Discover the complex relationship between factors and model them …. This is predictive analytics. From “How many first-year students dropped out each past semester?” to “Why did these students drop out?” to “How many will drop out next year?” to “What is the best intervention for the future?”
  7. A simple definition, - analytics is the process of obtaining an optimal or realistic decision based on existing data or information. This information can be internally generated information or external information. Includes statistical analysis in order to discover and understand historical patterns to predict and improving business performance in the future. Analytics closely resembles statistical analysis and data mining, but tends to be based on modeling involving extensive computation.
  8. How can Analytics enable fact based governance - With the right reporting to identify what happened, how many, how often,…….. provide Hindsight With capabilities to drill down to where exactly the problem stems from, what actions are needed, why is it happening …….. provide Insight With ability to determine what impact if trends continue, what will be impacted next, whats the best course of action …….. Provide Foresight
  9. 1. Financial Services Banks are the biggest users of analytics. I was involved in a 2 year programme with a large bank where they were looking to improve their governance and management using analytics. We started with the basics – 1. Financials - first in planning and budgeting to understand where the expenses are then in profitability management. This area started with hindsight, insight and then foresight. Impact was huge – the bank discovered some lines of business were unprofitable for years, for example HP. The managment team and the board then had to consider big questions like – why should they continue to offer hire purchase and what could make it profitable? 2. Risk – we helped them establish the hindsight to understand their credit risk of their loan portfolios, we then helped them establish the insight so they head a clear determination based on their historical information, how risky some loans were and their probability of default. Finally we helped them establish foresight by determining based on their historical information and external information what are the key attributes for a loan applicant that had very low probability of default. This transforms who they market to and how they price their loans. 3. Customer Analytics – with the deep insight obtained from the financials and from the risk, the bank could now look at segmenting their customers based on customer lifetime value to the bank – they could see which customer were unprofitable and understand what to do to make them profitable, they had foresight to devise how to market to different segments of customer to cross sell products such as investment units trusts and personal loans to grow their business.
  10. Key decision makers across UCF were being challenged by rapid growth – and finding ways to support and enable this growth while optimizing student experiences. Enrollment at UCF more than doubled in the past 15 years to over 53,000 students. As it grew in size to #1 in Fl and #3 in the US, the school wanted to marshal its resources effectively. To do this, however, business users needed a way to let data drive decisions about students, programs, resources and facilities.
  11. Data was housed in multiple systems. Databases were disconnected, data management was ineffective. The staff took a few weeks to provide information to its’ consumers. There is little time left over for actual analysis – to derive insight. Most reports were in a simple format. Spotting trends was difficult. Drill down analysis for root causes is not possible The Solution Journey: Strategic Plan – Data Integrated solution – SAS Business Analytics Framework – for data warehouse, analytics and information delivery What was enabled: Deep analysis and reports on its colleges, programs, student life cycles – admissions, course taking behaviour, retention and completion/continuation patterns. Internal research on university management – eg. cost studies, faculty activity, benchmarking and resource utilization
  12. Enrollment planning is one of the four main areas for UCF. They used population projects and high school graduations rates to forecast enrollment and plan demand. They built a model of predictive analysis accurate to 1%. They now use this for their budgeting, faculty resource planning and course offering planning.
  13. Strategic planning is one of the four main areas for UCF. UCF benchamraks against 2 peer groups – institutional and aspirational. They use National Educational statistics to compare and understand – organization, student characteristics, faculty-student ratios, retention and graduation rates. Driving improvements through execution of their strategic plans some of the aspirational peers have become institutional peers.
  14. Management analysis is one of the four main areas for UCF. They look at the entire student life cycle and post graduataion success factors For example they see if they have enrolled elsewhere after UCF and determine how many are finding employment within state, etc.. It gives them a cleare picture of how they are doing at improving employability of their graduates.
  15. Exploratory analysis is one of the four main areas for UCF. Institutional Research on cost studies, faculty activity, benchmarking and resource utilization are a few examples of their exploratory analysis If you would like to find out more about this case study or other case studies visit sas.com/higher-education or you could go to our Youtube channel – look for the SAS Software channel and you will be able to see Dr Archer and her team share with you directly how they have enabled fact based governance at the university of central florida.