1. From Data Warehouse to Business Intelligence – Paradigm shift or simply new set of tools?
Kamalika Sandell, Associate CIO
Joyce Deroy, Director, Information Services
Matteo Becchi, BI Program Manager
American University

2. American University, Washington DC
Private 4-Year University, Chartered by Act of Congress in 1893
13,047 Undergraduate, Graduate, Law Students
6,827 Undergraduates, 5,725 Graduate , 495 Visiting
750 Full-Time Faculty; 430 Adjunct; 1,300 Full-Time Staff
105 Study Abroad Programs in 34 Countries
Politically and Socially Active Student Body

3. Objective of this presentation
Share our experiences and approach to BI
Explore what makes BI implementations different
Share lessons learned
Hoping to stimulate conversations, learn from you!

4. Where are institutions with their BI implementations?
How many of you are actively benefitting from a mature BI implementation?
How many of you are in the middle of your first round of BI implementation?
How many of you are thinking about starting BI implementations?
What are the most common challenges in today’s analytical environment that made you consider BI?

5. AU BI Analytics and Reporting Initiative Timeline
2009
2010
2011
Empowered Users
Self Service BI
BI competency center
AU analytical environment analysis
BI Tool Selection
BI Infrastructure Build
Widely used data warehouse
Broad set of data
Custom reports with prompts
Executive Dashboards Phase 1
Executive Dashboards Phase 2
Research Grants Financial Reports
Pre Awards Financial Reports
Development/ Alumni Relations Reports
UG Admissions Reports
Financial Reports - Facilities
Financial Reports - GL
Additional Domains
Self service BI for Finance and Budget
Rollout self service model
Pilot Predictive Analytics

6. Challenges in today’s analytical environment
Tons of data
Different systems, interpretation challenges
Data Quality, gaps in Source Systems
Focus on operational reports,
Not decision oriented reports!
Effort spent “developing” reports
Less time to analyze results!
Even less time to discuss “what needs to be done different”
Every day 15 petabytes of new information are generated. It is estimated that the codified information base of the world is now doubling every 11 hours.
Source: TED 2007: Predicting the Next 5000 Days of the Web. IBM analysis

7. The promise of BI
Intelligently harnessing data to make better decisions:
Right data
Right correlation
Right interpretation
Right access
Right people
Right set of analytics
Examples of measures that has impacted in business decisions

8. AU BI Success Stories SIGUCCS Award:
Best of Category for Printed Instructional Classroom Materials for "Research Grants Financial Reporting“
User Success Stories:
“I use it on a daily basis. Now that I'm familiar with it and the reports I like, it's really amazing. I can track a single expense in less than half the time it took before BI. I can provide PI's a snapshot of their budget in no time at all. In sum, it's substantially improved our ability to provide the faculty with information to make decisions on how best to utilize funding to accomplish the goals of their sponsored research projects.”
Bill Brown
Financial Operations Manager
School of Public Affairs
“A payment didn't make it to a vendor. In a few seconds I was able to see that the funds had not yet been encumbered, meaning the purchase order had not yet been processed. That information allowed me to quickly identify exactly whom I needed to contact. Problem solved. “ Mary Eschelbach Hansen Associate Professor Director of Undergraduate Studies Department of Economics

9. Thinking of BI – basic differentiators
Not merely a new tool
“Insights” derived with end goal in mind
Business processes with integration in mind
Analysis with context in mind
Refocusing users to “self serve”, and “explore”
.... And Refocusing users how to analyze effectively
Other differentiators?

10. Fundamentals of a BI strategy
Identify information needs/ gaps
Prioritize gaps, group into initiatives
Define roadmap, revisit constantly
Identify BI champions
Influence funding the program
Identify Pilot
Start with a group with defined use cases
Something “New”
Something not too complicated
Long term focus and strategic vision
Vision and Strategy
Business Process
Data Definition
Data Model
Technology
Training and Adoption
Governance BI

11. Formulating a BI Strategy, Implementation Plan
Information Requirements Framework
BI Implementation Plan
STEP 1
STEP 2
RESULTS
Information Needs Analysis
BI Workshop
BI Plan & Business Case
Program Vision and Governance
ROI Analysis
Interview Stakeholders
Identify Performance Measures
Create Information Architecture/ Model
IT Facilitates and Observes – Stakeholders Decide
Brainstorm and Reach Consensus
Prioritize Top-down – Validate Bottom-up
Solution Architecture &
Technology Selection
Tool Requirements
Demos, Selection
Current Environment Analysis
Phased Rollout Plan
Identify Data Sources and Initiatives
Interview Technical Stakeholders
Identify Technologies & Standards
Assess Information Availability
Pilot and Incremental Phases
Project Team
Governance and Leadership

12. Information Requirements Framework— draft example

13. A few items to explore when implementing…….
Are campus administrators and faculty interested in participating?
Are users taking ownership?
How do we really define “self service” in the context of BI?
How can we think big and start small?
Is BI without data governance effective?
It will never make sense to start with a narrow vision – the investment will not warrant it. The business case will not be made. BI strategy needs to be holistic and broad and has to be able to be realized through smaller projects

14. BI implementation realities/ challenges
Tools and technology not the most difficult part
Data Modeling takes a lot of effort
Definitions and requirements take time
Self service usage  Self service learning
Invest in ongoing training program
Have a roadmap – haphazard deployment is confusing

15. AU’s BI Maturity Model: Where we were

16. AU’s BI Maturity Model: Where we would like to be

17. Continuing the BI maturity journey
Consistent Roadmap - keep it updated
Never stop raising awareness
Never stop highlighting business impact
Program Governance is key
Data quality has to be a continued focus
Need users who are excited and ready to champion
Focus needs to be on Enterprise Information Management, not one off BI projects

18. In essence – Plan to build out BI competency center
Enterprise Systems Project Team
Strategic BICC Membership:
Wisdom
Trends
Knowledge
Information
Tactical BICC Membership:
Decision Oriented Reports
Overall Measures and Dashboards
Operational Reports
Lists and Action Oriented Reports
BI Reporting and Analytics
IT Program Team
Image Source: How to Define and Run a Successful Business Intelligence Competency Center, Gartner, August 2007

19. The end game… what it means if we are successful
Empowered users, user driven innovation
Insights with context
Less dependence on IT
Data driven decision making
Have we instituted a culture of data driven assessments?
Recognizing it’s not just about having data, it’s about knowing how to use and analyze the data, so that you are using data to pull insight from the noise, in order to make decisions with facts instead of intuition

20. Questions or Comments?
THANK YOU!!!