Business Intelligence BI Deployment Case Study Bruce Jones Director of Information Systems DC Lottery and Charitable Games Control Board 2009 NASPL IT.

Business Intelligence

BI Deployment Case Study

Bruce JonesDirector of Information SystemsDC Lottery and Charitable Games Control Board

2009 NASPL IT Subcommittee MeetingColorado Springs, COSeptember 14-17, 2009

BI Defined by Hans Peter Luhn

business is a collection of activities carried on for whatever purpose, be it science, technology, commerce, industry, law, government, defense, et cetera. The communication facility serving the conduct of a business (in the broad sense) may be referred to as an intelligence system. The notion of intelligence is also defined here, in a more general sense, as "the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.”

Luhn, H. P. (1958). A Business Intelligence System, IBM Journal, October 1958, 314-319.Retrieved from http://www.research.ibm.com/journal/rd/024/ibmrd0204H.pdf

Presentation Summary

• What we did• How we did it• What we accomplished

What we did

• Modernized the Lottery’s information technology

• Enterprise Architecture – what we had, where we wanted to go

• Data Warehouse and Business Intelligence technologies deployed throughout the Lottery

Goals and Objectives I

Information Technology• Provide strategic support to the Lottery• Support lottery with analytics• Drive success with innovated solutions

Goals and Objectives II

Enterprise and Business Units• Accurate answers• Valuable insights• On-time information• Actionable conclusions

Goals and Objectives III

• Leverage information to achieve improved business performance

• Democratization of information• Evidence-based decision making

How we did it

• The Team–People–Processes

• The Target– Technology–Data

Implementation Pathway Implementation Pathway

Key People

• Executive Sponsorship• Cross Departmental – Center of

Excellence (COE)– Sales and Marketing– Finance and Information Technology– Optimal Solutions Technology

DCLB Lottery Processes

The Target• Oracle Data Warehouse – A single logical repository for transactional and

operational data.– Gaming System sales and liability data

• Business Objects BI Suite– A platform designed to let IT manage and securely

deploy end-user tools and applications for reporting, query and analysis, a performance management

Building Data Warehouse

Data Warehouse Design I

A single logical repository for Lottery transactional and operational data.

Gaming System sales and liability data

Retailer key attributes

Data Warehouse Design II• A dimensional model/star schema implemented• The dimensional database can be conceived of as a database cube of three

or four dimensions where users can access a slice of the database along any of its dimensions

• The main table within this architecture is called the fact table. The other dimension table are connected to the fact table through foreign keys.

• Lottery Defined Dimension examples– Agent– Times– Location

• Lottery Defined Fact Tables examples– Daily Sales– Claim Sales

Star Schema ExampleDaily SalesFact Table with dimensions -

ProductAgent Fiscal Time

Data Integration

• Extract, Load and Transform• Data Quality– Operational vs. Analytical– Common, non-ambiguous, definitions– Single Point-of-Truth

Data Warehouse Process

BI Technologies

• Fifty years of constant and accelerating change and innovation

• Market consolidation and competition• Beyond spreadsheets, reporting and query

software– OLAP (Online Analytical Processing)– Business Performance Management– Digital Dashboards

What we accomplished

The BI Enabled Lottery

• Performance Reporting• Sales Forecasting and Analysis• Game Sale Summary and Product

Profitability• Market Analysis• What-if Analysis• DC Lottery Product Mix Analysis

Performance Dashboards I

Rich visual display of historical sales information by each product with a performance metrics

Performance Dashboards II

Compact, concise display of weekly sales information with bar chart (sales amounts) overlaid with line graph (percent goal attained)

Intranet Integration

Bringing Data to the Desktop with a Digital Dashboard Speedometer Integrated into the Lottery’s SharePoint Portal Homepage

Dashboard Speedometer

Typical intuitive analysis scenario for evidence-based decision making

Speedometer DC-4

Drill down by product for the week reveals major product sales goal not met.

Speedometer DC-4 Detail

Details available – the numbers behind the speedometer representation. Shows DC-4 product 15.74% off sales goal for the week.

Speedometer Lucky Numbers

Lucky Numbers product details – Shows the product 18.32% off sales goal for week.

Speedometer Powerball

Powerball product details – Shows Powerball 35.03% ahead of the sales goal for week.

Next Move

• Additional and Faster Data Integration• New Capabilities– Simulation– Forecasting– Optimization

• Improved User Adoption– Evidence-based decision making

Bringing it Together

Final Thoughts