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Managing Customer Data Spatially: Insights from the Fifth Annual GIS Conference

This presentation by Serena Coetzee from the University of Pretoria discusses the importance of managing customer data spatially, which involves integrating geographic information systems with customer data for enhanced business intelligence. Key points include the necessity of a master address database, the implementation of a spatial information strategy, addressing data quality issues, and the transformative impact of spatially enabling customer data. The insights shared are especially relevant for businesses looking to improve operations, customer service, and decision-making processes within South Africa's diverse urban landscape.

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Managing Customer Data Spatially: Insights from the Fifth Annual GIS Conference

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  1. Managing customer data spatially Fifth Annual GIS 2007 (Melbourne) Serena Coetzee University of Pretoria 2 May 2007

  2. South Africa & Tshwane Afrikaans, English IsiZulu IsiXhosa SiSwati Ndebele Southern Sotho Northern Sotho Tsonga SeTswana Venda Pretoria (executive) Bloemfontein (judicial) Cape Town (legislative)

  3. South Africa • 45 million people • 9 provinces • 262 municipalities • 6 metropolitan municipalities • 7 million land parcels • 6,3 million in (formal) urban areas • 40% in Gauteng • 25% in the Western Cape • 16% in Kwa-Zulu Natal • 500,000 sectional title properties • Largest address database: 3.5 million

  4. University of Pretoria (Tukkies) • 1906 Transvaal University College • University of Pretoria • 38 000 residential students • 28 000 undergraduates • 10 000 post-graduates • 47% male, 53% female • 2 000 international students from 60 countries • Faculties • Economics & Management Sciences • Humanities • Health Sciences • Engineering, the Built Environment & Information Technology • Natural & Agricultural Sciences • Education • Law • Theology • Veterinary Sciences

  5. History and Research Interests ReGIS, Autodesk World Spatial Datasets, PropertySPI GI Standards NAD on the grid Can we establish a virtual NAD for South Africa in the form of a data grid? + + =

  6. Overview Managing customer data spatially • Why manage customer data spatially? • Spatially enabling customer data • Planning • Spatial Information Strategy • Customer address data model • Master address database • Implementation • Integrate the address data model • Transform customers into spatial customers • Coping with uncertainty • Operation • The address data life cycle • Using spatial customer data

  7. Managing customer data spatially • Why manage customer data spatially? • Spatially enabling customer data • Planning • Spatial Information Strategy • Customer address data model • Master address database • Implementation • Integrate the address data model • Transform customers into spatial customers • Coping with uncertainty • Operation • The address data life cycle • Using spatial customer data

  8. Why manage customer data spatially? The Future of I.T.: What's on Tap for 2007 and Beyond • Customer Service Surges as a Top Priority for 2007 • Business Intelligence Tops the Strategic Technology List Source: www.cioinsight.com 1 2

  9. Why manage customer data spatially? The 30 Most Important IT Trends for 2007 Technology • The move to a new architecture marches on • Enterprise applications start losing their luster • Data quality demands attention • IT reluctantly embraces Web 2.0 • IT innovation loses traction • Business process management services and software will frustrate users • For business intelligence, the best is yet to come • IT organizations start going green Source: www.cioinsight.com 1 2 3 4 5 6 7 8

  10. Why manage customer data spatially? “More than 25% of critical data used in large corporations is flawed due to human data-entry error, customer profile changes (e.g. change of address), poor processes and a lack of proper corporate data standards.” The result: soiled statistics, faulty forecasting and sagging sales Source: Gartner Research quoted on www.cioinsight.com

  11. Why manage customer data spatially? “Through 2007, more than 50% of data-warehousing projects will experience limited acceptance, if not outright failure, because they will not proactively address data-quality issues.” Source: Gartner Research quoted on www.cioinsight.com

  12. Why manage customer data spatially? Source: www.gwsae.org

  13. Why manage customer data spatially? The insurance industry is ready for the corporate wide proliferation of geographic information systems as insurers rely on data that has a geographic component to determine accurate underwriting, risk analysis and claims management. Employ Geographic Information Systems to Manage Risk for Property and Casualty Insurers, 11 October 2006, Stephen Forte Source: www.gartner.com

  14. Why manage customer data spatially? • Data quality • Address verification • Return to sender improvements • Business intelligence for improved customer service • Routing and deliveries • Geo-marketing • Outlet planning • Demarcation (sales areas, etc.)

  15. Managing customer data spatially • Why manage customer data spatially? • Spatially enabling customer data • Planning • Spatial Information Strategy • Customer address data model • Master address database • Implementation • Integrate the address data model • Transform customers into spatial customers • Coping with uncertainty • Operation • The address data life cycle • Using spatial customer data

  16. Planning Challenges • Buy-in on executive level • Continuous long term process • Customer’s perception of what his/her address should be

  17. Planning One of our strongest weapons is dialogue. Nelson Mandela

  18. Planning • Understand and articulate the benefits of spatial customer data • Convince non-technical executives about the benefits of spatial address data • Associate the benefits to an identified risk or business event Ready to start… 1 2 3

  19. Planning Spatial Information Strategy People Software Contracts Business data Process $$ $$ Spatial reference data Reference Data Infrastructure (hardware & networks)

  20. Planning Address Structuring & Cleaning Source: Watson Remembering the past (databases and data warehouse) Spatial Analysis Transactions Data People & technology Handling the present (TPS) Preparing for the future (BI, data mining, DSS, EIS, MIS, OLAP) Address capturing, for delivery New business systems

  21. Planning Source: DM Functional Framework by DAMA Data Management Functions

  22. Planning • Who is responsible for customer address? • Information (CIO) • Analytics (GIS) • Development (IT) • Business (CRM) • Decide why you need spatial customer data • Design the address data model

  23. Planning Purpose: Address Verification 101 Koljander Avenue Newlands Pretoria Gauteng 28.273632 -25.792344

  24. Planning Purpose: Deliveries

  25. Planning Purpose: Customer profiling 101 Koljander Avenue Newlands Pretoria Gauteng 45 Nutmeg Avenue Newlands Pretoria Gauteng 28.270885 -25.790764

  26. Managing customer data spatially • Why manage customer data spatially? • Spatially enabling customer data • Planning • Spatial Information Strategy • Customer address data model • Master address database • Implementation • Integrate the address data model • Transform customers into spatial customers • Coping with uncertainty • Operation • The address data life cycle • Using spatial customer data

  27. Cow of many - well milked and badly fed Spanish proverb

  28. Planning: Address data models Geographic Information – Address standard SANS1883 Address = StreetAddress | BuildingAddress | IntersectionAddress | … StreetAddress = StreetAddressPart, Locality StreetAddressPart = [CompleteStreetNumber | StreetNumberRange], CompleteStreetName Locality = PlaceName, [TownName], [MunicipalityName], [Province], [SAPOPostcode], [Country] | [CountryCode]

  29. Planning: Address data models Geographic Information – Rural and urban addressing AS/NZS 4819:2003 An urban address includes, in order, the following: • Sub-dwelling (flat/unit) number or identifier • Level number of sub-dwelling • Private road name (if applicable) • Utility name (if applicable) • Address site name (if applicable) • Single urban address number or urban address number range • Road name • Locality • State/territory • Postcode (optional) • Country

  30. Planning: Address data models Organization for the Advancement of Structured Information Standards (OASIS) • www.oasis-open.org • Members • Over 5,000 Members from 100+ countries of OASIS • Software vendors, industry organizations, governments, universities and research centers, individuals • Co-operation with other standards bodies • Best known for web services, e-business, security and document format standards • Open and royalty-free standards

  31. Planning: Address data models OASIS Customer Quality Information TC • http://www.oasis-open.org/committees/ciq • Chairman: Ram Kumar, Mastersoft, Australia • XML Specifications • for defining, representing, interoperating and managing party information • name, address, party specific information including party relationships • open, vendor neutral, industry and application independent, • "Global" (international) • Extensible Address Language (xAL) to define a party’s address(es)

  32. Planning: Address data models

  33. Planning: Address data models xNAL (xNL + xAL) Model

  34. Planning: Address data models xAL Model

  35. Planning: Address data models • Customer’s perception and preferences • 14 Castle Pine Crescent (English) • 14 Castle Pine Singel (Afrikaans) • 477 Chopin Street, Glenstantia (Post Office) • 477 Chopin Street, Constantia Park (Surveyed) • 17 Glenvista Street, Woodhill (colloquial) • 17 Glenvista Street (erf 672), Pretoriuspark Ext 8 (registered at the deeds office)

  36. Managing customer data spatially • Why manage customer data spatially? • Spatially enabling customer data • Planning • Spatial Information Strategy • Customer address data model • Master address database • Implementation • Integrate the address data model • Transform customers into spatial customers • Coping with uncertainty • Operation • The address data life cycle • Using spatial customer data

  37. Planning: Master address database • Source: official vs unofficial • Maintenance cycle • Coverage • Data model • Level of detail • Address • Address Range • Street • Suburb • Postcode and/or post office • Region • Country

  38. Planning: Master address database Cadastral Addresses • Based on cadastral boundaries • Street numbers sourced from relevant official bodies • Link street address to property information • owner, price, bond information, etc. • Accommodates for anomalies (panhandle, skip numbers) • Address verification, routing, deliveries, customer profiles 12B 2 4 8 10 16 12A GORDON STREET

  39. Planning: Master address database Address Range • Street numbers surveyed at street corners • Street numbers evenly allocated in between • Includes street numbers that do not exist • Cannot link the street address to property information • Routing, deliveries, customer profiles • Not good enough for address verification 2 4 6 8 10 12 14 16 2 16 GORDON STREET GORDON STREET

  40. Planning: Master address database Street

  41. Planning: Master address database Suburb or Region

  42. Planning: Master address database Postcode and/or post office

  43. Planning: Master address database • Mapping to customer address data model • Plan for the future • Master address database independent • Increasing levels of detail • Accessibility by all departments • Tools • Knowledge Management • What address information is available? • How do I access the address information? • What can I do with the address information? • What tools are available? • How is the address captured?

  44. Managing customer data spatially • Why manage customer data spatially? • Spatially enabling customer data • Planning • Spatial Information Strategy • Customer address data model • Master address database • Implementation • Integrate the address data model • Transform customers into spatial customers • Coping with uncertainty • Operation • The address data life cycle • Using spatial customer data

  45. Implementation: Integrate data model • Address is not an attribute of the customer! • Link an address entity/object to the customer

  46. Implementation: Integrate data model

  47. Implementation: Integrate data model Source: GINIE project

  48. It is a capital mistake to theorize before one has data. Sir Arthur Conan Doyle, “A Scandal in Bohemia”, The Adventures of Sherlock Holmens 1891

  49. Managing customer data spatially • Why manage customer data spatially? • Spatially enabling customer data • Planning • Spatial Information Strategy • Customer address data model • Master address database • Implementation • Integrate the address data model • Transform customers into spatial customers • Coping with uncertainty • Operation • The address data life cycle • Using spatial customer data

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