Using Business and Location Intelligence to Create Lasting Value

1. Using Business and Location Intelligence to Create Lasting Value Will Wilbrink Pitney Bowes MapInfo

2. Topics • Business & Location Intelligence • Examples • Demonstration

3. CHALLENGES OF GOVERNMENT • Demonstration of good governance • Intense public scrutiny • Demands for accountability • Continuous budget pressure • Must show continuous improvement . . . with less resources

4. LOTS OF DATA, LITTLE DECISION-READY INFORMATION • Reporting is cumbersome and static; typically paper-based with many versions of the truth • Manually intensive analysis processes; ad hoc analysis is rarely supported • Mainly manual processes for information gathering and collation • Data are hidden away in departments, databases, applications, geographies; impossible to coordinate • Data latency, accuracy, completeness issues

5. SOLUTION REQUIREMENTS • Improve visibility into business processes from aggregate to detail • Monitor, measure, and track performance against strategic objectives and benchmarks • Make performance information broadly or narrowly accessible, and securely via the Web • Simply satisfy mandatory reporting requirements

6. SINGLE DEFINITION OF THE TRUTH Single Platform for Decision Making

7. Strategic Positioning Business Intelligence Location Intelligence • BI Platforms • Enterprise • Integration • Technology • Analytic Applications • Process Driven • Process or Industry specific • LI Platform • Enterprise-wide • Integrated software/data • Technology Integration • Analytic Applications • Market specific data • Business process-driven • Sophisticated spatial modeling Measure Align Decide Discover Optimize Innovate Predict Business intelligence is the use of information that enables organizations to best decide, measure, manage and optimize performance to achieve efficiency and financial benefit. - Gartner, 2006

8. LocationIntelligence Knowledge • VisualisingPerformance • Analysing based on Location • BI with FACTS integrated with Location Intelligence • Cause and effect • Reporting • Analysis • (Data Mining,OLAP) • Distribution DemoGraphics GIS Location Intelligence for better business understanding Results Data Information • Clearer understanding • Better Decisions • Accurate Management • More effective Planning • Better resource utilisation • Data Integration • Aggregation • Data Warehousing • Data Marts • Structured DW DM DM WWW.COM • Unstructured Enhanced User Analysis EnrichedData Improved Performance

9. Interpretability Consistency Completeness Accuracy Uniqueness Co-Relation Data Challenges Atta, Mohammed a.k.a. Mohammed Bin Rasul Attaullah: Is this a personal name or a company name? What is the First Name Vs. Last Name? Are there multiple entities in that string? Tai-Tai Cheung Mei Lee Wang: Is this a personal name or a company name? Is Tai-Tai the First Name? Is the Gender Male or Female? Camomile Ct, 21108, Germantown MD: Is this a name or an address? Is 21108 an apt num or house num or perhaps a zip? Robert A. Smith – 123 PeachTree Ln and Mary Smith – 123 PeachTree Ln: Householding Pitney Bowes, Inc. Group 1 Software, Inc. Emtex, Inc. Print, Inc. Corporate Hierarchies One Name Many Variations: Abdaroaig,Abdaroaik,Abdaroaiq,Abdaroeig,Abderoaiq,Abderoeig,Abderoeik,Abderoeiq,Abderuaig,Abderuaik,Abder One Term Many Variations: International, Intl, Int’l, Interntl Account, Acct, Accnt, A/c NickNames/Abbreviations: Robert = Bob, Bobby, Rob, Robby IBM = International Business Machines Address Aliases: Avenue of the Americas = 6th Ave Dallas = Highland Park [Vanity City Name] St = Street or Saint [Context-Sensitive] Dates: 5/25/00 = May, 25th 2000 = 05-25-2000 International Pacific Trading – 123 Main St and Pacific Trading International – 122 Main Ave: Is this the same organization? Bob and Mary Smith – 21 PeachTree Ln and Robert A. Smith – 211 PeachTree Ln: Is this the same individual entity? Rahul Agwear and Raul Jose Aguiar: Does he match the OFAC List of Bad Guys? Int. Prod Chip Integrated Product Chip Is this the same Product? Navin Sharma, 21108 Camomile Ct, Germantown MD 20876-6919, 301-353-9359: Is this currently a valid address? Has the Street Name been converted? Is this a valid USPS deliverable address? Is this a valid non-USPS deliverable address? Is the address still associated with the person? Is that a valid Phone for the person? Is that a valid Phone for that address? Is this a residential or business address? 4200 Parliament, Lanham MD: Is there a Suffix to the Street? Is there a PostCode? Is there an Apt/Suite? Is there a valid Zip+4 for US Address?

10. Spatial ETL Spatial ETL is the process to extract, transform and load data using spatial analytics. Typical processing includes: • Address cleansing • Geocoding • Assigning demographic code • Assigning custom geography code to enable hierarchies (for example, precincts)

11. Example of Spatial ETL

12. Data Model

13. Data Modeling

14. Location Intelligence Component • Location Intelligence allows users to combine and integrate their Business Intelligence data with a mapping environment • Delivers Location Intelligence into the Boardroom via Dashboard integration • Brings Location Intelligence to the mainstream Business Intelligence user • Enables users to visualise critical data geographically • Enables users to query critical data using location • Enable users to access location from within the solutions that are already corporate standards for business intelligence • No new user interface • No new security layers • Utilise existing data warehouse • Makes optimum use of existing investmentin Business Intelligence

15. Data from BI Report TAB file (Geometry only) Controlled by named layers in mapping engine Data from report put into a memory array (Utilizes custom data provider to perform data binding) Report Layer Additional Map Layers (Must have corresponding named resource file) Base Map Concepts Map Content and Bind Layer

16. Thematic Mapping Thematic types: • Symbol – Line – Region • Graduated • Distribution Types • Equal Count • Equal Ranges • Natural Breaks • Standard Deviation • Custom Ranges

17. Graduated Symbol Thematic

18. Linear Width Thematic

19. Region Ranged Thematic

20. Knowledge Analysis Action Public Sector Solutions Constituent Data Cleansing Validate Postal Codes Enterprise Address Management Address Standardization Data Integration Crime Analysis Fraud Prevention Disaster Planning Data Visualization Tax Jurisdiction Assignment Asset Management Pre-Sort Constituent Mailings Electronic Bill Presentment Document Composition Document Storage / Retrieval Move Update Processing

21. NYPD

22. NYPD • Use: • A core group of analysts at NYPD has for many years used MapInfo to review the large volumes of crime data routinely collected. A BI system was put in place to allow for easy flow of the same data in report format to the precincts. The integration of MapInfo with the BI system allows the larger group of analysts at the precinct level to evaluate location-based trends. • Value: • More analysts now have fast, easy access to location-based trending. This increases the speed at which information can be processed. As a result more criminal cases are solved more quickly.

23. Cancer Care Ontario • Cancer Care Ontario is the provincial agency responsible for continually improving cancer services. As the government’s cancer advisor, Cancer Care Ontario works to reduce the number of people diagnosed with cancer and makes sure that patients receive better care every step of the way.

24. Wait Time Information System • Online tool used as a wait time collection tool and wait list management system for health care providers and facilities • Basic, Standard, and Complex levels of submission • 82 Facilities currently using WTIS • 2,600 clinicians, 1.6 million procedures (07/08) • Allows for collection of patient unavailable days and cases closed due to procedure no longer required

25. Snapshot view of key results Quick Facts Reports • Snapshot of current performance • Provincial view • User can drill down for LHIN and Facility information

26. Dig deeper for more details Detailed Analysis Reports • Detailed information • Define and customize with filtering options to get the information you need about your business priorities

27. Spatial/location intelligence • In order to properly manage wait lists and allocate funding, necessary for LHIN performance planners to have access to patient demographic information • Including Forward Sortation Area (FSA)

28. Demonstrations • Come see us at Booth 307