0
Customer Data
&
Location Intelligence
James Brayshaw – CDLI Vice President EMEA
January 2014
It’s not just about

maps…
It’s about the
Strategy

Governance
Quality Provenance
Integration Accuracy
currency

Integration

quality

data!

accurac...
Do I know where all my Customers are?
Top Challenges for
Managing my Customer Data

Data is highly
fragmented, in
incompatible formats &
difficult to access.

C...
How Location Intelligence and Customer Information Management
fits Into a client Journey

Company

Data
Management

Spatia...
The Future - Insight to Location Market
dynamics
What do we mean by Location Intelligence?
Combining
Spatial/Location &
non-spatial,
querying structured
& unstructured dat...
User evolution of LI and Business Challenges
Moves to Systems
Approach/IT Domain
Spectrum &
Spectrum Spatial,
Data & BI In...
Location Intelligence Strength and Focus
The capability to organize and understand complex relationships
between location ...
The approach to becoming
Location Intelligent and
improving Customer Data
Becoming Location Intelligent
(It’s about the data)

Create a data governance strategy to regularise,
match, clean, sort, ...
Data Challenges

Bad Data: Behaves like a virus;
it starts with one record and
spreads to other databases.
Stop bad addresses from leading you astray!

14
Data quality is key for Location Intelligence
• Are there problems in your data?

Multiple names

Incorrect address

Name
...
Customer data in Silos!

Account: A123
Auto Policy

Account: HO123
Home Policy

Account: A768
Auto Policy

Account: A768
A...
Data Improvement Opportunities – Customer
Integrate customer information into one single view
Account: A123
Auto Policy

A...
Better customer data improves relationships
that drive millions in revenue - location is Key

INFLUENCE
GROW
ACQUIRE

CONV...
Global Data Content needed

Global data provided in 3 key areas…

Location Data

Demographics

Analytical Datasets

Backgr...
Global Data – Unique coverage

20
Data Categories

21
Enterprise Data platform
What we can learn from other industries
Enterprise EDM – Bring together all elements

Current Solutions:

MDM

Analytics

• Multiple Vendors
with competing,
overl...
What Does this mean?
• Solution enabler around
information to improve business
decisions.
• Use your enterprise informatio...
Customer data is a REAL business asset.
Spectrum helps companies maximize its value.

Deliver
Personalized
Customer
Experi...
Case Study: Single Customer View

Spectrum has enabled Citibank to:
•

Generate and maintain a single customer identity ac...
Case Study: Customer & Asset location

Spectrum has enabled Home Depot to:
•

Customer Address Validation covering 220 cou...
Case Study: Understanding of Risk

Spectrum has enabled Willis to:
•

Fast, Accurate Global Geocoding

•

Understand impac...
Case Study: Master Data Management
Logistics

Spectrum has enabled FedEx to:
•

Customer Master Data Management – a key co...
Case Study: Retail Planning, Sales &
Service Delivery
Challenge
•

Required accurate territory data to minimise franchisee...
Case Study: Running my Network business
Challenge
•

Required more intuitive way of drilling-down into sales data to ident...
How - Telenor Integration with BI SAP
Business Objects
Case Study: Context of real time Location
Challenge
•

Solution required to provide highly accurate international geocodin...
Extending LI into Infrastructure and
BIM
Infrastructure Asset Management
What

Who

Why

An enterprise solution that includes
GIS, CRM, task management,
financial ...
MapInfo -Autodesk Partnership
Urban Planning/Infrastructure Lifecycle

Performance
Management

MapInfo
Pro

Visioning
Poli...
3D City Modelling
Base Station Coverage Modelling

• Display models as Voxels
• Calculate Volumes
• Slice in X, Y & Z
• Di...
Thank You
James.brayshaw1@pb.com
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It’s not about Maps – it’s about Data! - Location enabled data for Utilities

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At GeoUtilities 2014, James Brayshaw, Vice President Location Intelligence Business (MapInfo) EMEA, Pitney Bowes Software, showed how location enabled data can make a real difference for utilities in understanding who are their customers and where there is a revenue collection and upsell opportunity. James highlights the three important steps that businesses need to consider to integrate enterprise location intelligence into the broader customer data strategy, and gives some useful case studies that demonstrate the value of this type of approach.

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Transcript of "It’s not about Maps – it’s about Data! - Location enabled data for Utilities"

  1. 1. Customer Data & Location Intelligence James Brayshaw – CDLI Vice President EMEA January 2014
  2. 2. It’s not just about maps…
  3. 3. It’s about the Strategy Governance Quality Provenance Integration Accuracy currency Integration quality data! accuracy
  4. 4. Do I know where all my Customers are?
  5. 5. Top Challenges for Managing my Customer Data Data is highly fragmented, in incompatible formats & difficult to access. Collecting & making sense of real-time data such as geo-positioning, messaging, etc. captured by mobile devices. Data is low quality, out of context and incomplete Growing concern around security & privacy of data Impact on business systems given increasing amount of corporate data is outside the firewalls. Exploding data from social media & other real-time IT/OT sources, arriving at high velocity.
  6. 6. How Location Intelligence and Customer Information Management fits Into a client Journey Company Data Management Spatial Data & Analysis Insight Strategy Communications Inbound & Outbound Channels Customers Data is the most valuable asset of any business and is the foundation for building relationships with our customers. Location intelligence will greatly enhance an organisation’s ability to understand customer behaviours.
  7. 7. The Future - Insight to Location Market dynamics
  8. 8. What do we mean by Location Intelligence? Combining Spatial/Location & non-spatial, querying structured & unstructured data Data matching Addressing DQ/enriching Layering, integrating, referencing Geocoding In All forms Routing In All forms Core Location Processes Spatial analysis and insight Mapping/Visualisation 3D &temporal thematics
  9. 9. User evolution of LI and Business Challenges Moves to Systems Approach/IT Domain Spectrum & Spectrum Spatial, Data & BI Integration Expands Use of GI Data MapInfo Pro, Stratus & Spectrum Spatial MapInfo Pro Plus Apps Enterprise LI Enterprise GIS Desktop GIS Data Data Local/Global Data Importance
  10. 10. Location Intelligence Strength and Focus The capability to organize and understand complex relationships between location and other data in order to drive business decisions through: Geocoding Spatial Data Management Spatial Analytics Data Mapping & Visualisation 10
  11. 11. The approach to becoming Location Intelligent and improving Customer Data
  12. 12. Becoming Location Intelligent (It’s about the data) Create a data governance strategy to regularise, match, clean, sort, enrich and store my data for use by a wide user base Find the right technology platform to integrate with my Enterprise system and desktop GIS and share my data Define a location-based strategy that delivers a real return on investment ROI to enhance understanding of customers, increase ARPU, retention etc. 12
  13. 13. Data Challenges Bad Data: Behaves like a virus; it starts with one record and spreads to other databases.
  14. 14. Stop bad addresses from leading you astray! 14
  15. 15. Data quality is key for Location Intelligence • Are there problems in your data? Multiple names Incorrect address Name Address Mike Ashmore Minton Place Victoria Street Michael Ashmore Minton Place William Street M & L Ashmore Pitney Bowes Software Victorian Street Windsor Mike Ashmore, Pitney Bowes Software Minton Place Victoria Street Windsor Abbreviations Mixed business & contact names County Typo Phone Email Berks SL4 1EG 01753 848 207 michael.ashmore@pb.com Berkshire Windsor Postcode SL41EG 1753848207 mike.ashmore@mapinfo.com SL$!EG 01753-848-207 email@michaelashmore.com Berkshire SL4 1EG Missing data 01753 848 207 Mis-fielded data Non standard formats 15
  16. 16. Customer data in Silos! Account: A123 Auto Policy Account: HO123 Home Policy Account: A768 Auto Policy Account: A768 Auto Claim Account: L345 Life Policy Customer ID Policy Number Status Premium Customer Name Customer Address Customer ID Policy Number Status Premium Customer Name Customer Address Customer ID Policy Number Status Premium Customer Name Customer Address Customer ID Policy Number Status Premium Customer Name Customer Address Customer ID Policy Number Status Premium Customer Name Customer Address Robert Mary Robert Mary Robert Mary Robert, Jr.
  17. 17. Data Improvement Opportunities – Customer Integrate customer information into one single view Account: A123 Auto Policy Account: HO123 Home Policy Account: A768 Auto Policy Account: A768 Auto Claim Account: L345 Life Policy Customer ID Policy Number Status Premium Customer Name Customer Address Customer ID Policy Number Status Premium Customer Name Customer Address Customer ID Policy Number Status Premium Customer Name Customer Address Customer ID Policy Number Status Premium Customer Name Customer Address Customer ID Policy Number Status Premium Customer Name Customer Address Robert Mary Robert Mary Robert Mary Robert, Jr. Policies Account: AHOA495 Children House Holding Auto Home Owners Life A768 HO 123 L345 Premium Location Premium Location • Customer ID A123 • Customer Name Premium Location • Demographics • Preferences A123 Premium Location • Relationships • Customer Value Claims Spouse Spouse Relationship Auto: A123 Payment Location Premium Location
  18. 18. Better customer data improves relationships that drive millions in revenue - location is Key INFLUENCE GROW ACQUIRE CONVERT SERVE ADVOCATE RETAIN RECONNECT DEFECTIONS
  19. 19. Global Data Content needed Global data provided in 3 key areas… Location Data Demographics Analytical Datasets Background Mapping Street Vector Data Points of Interest Postcode Boundaries Administrative Boundaries Demographics Geodemographics Business Data Business Points & Lists Business Summaries Purchasing Power Consumer Spend Retail Destinations Retail Pitch Risk Data 19
  20. 20. Global Data – Unique coverage 20
  21. 21. Data Categories 21
  22. 22. Enterprise Data platform What we can learn from other industries
  23. 23. Enterprise EDM – Bring together all elements Current Solutions: MDM Analytics • Multiple Vendors with competing, overlapping capabilities • Too complex • Too expensive Data Quality Location Intelligence Data Integration Vision: • Single unified framework • Insight built on managed data on customer, location and assets • Simple • Cost effective
  24. 24. What Does this mean? • Solution enabler around information to improve business decisions. • Use your enterprise information assets to support strategic, tactical and operational decisions. • Platform is the core of a growing ecosystem of applications and services around customer, location and assets domains. 24
  25. 25. Customer data is a REAL business asset. Spectrum helps companies maximize its value. Deliver Personalized Customer Experience Accelerate Compliance & Reduce Risk Increase Efficiency of Business Operations
  26. 26. Case Study: Single Customer View Spectrum has enabled Citibank to: • Generate and maintain a single customer identity across the enterprise, including all Lines of Business and Geographies. • Enable any teller, banker, or agent to immediately understand the value of the customer standing in front of them. • Validate and standardize data migrated into the client’s MDM system. 26
  27. 27. Case Study: Customer & Asset location Spectrum has enabled Home Depot to: • Customer Address Validation covering 220 countries elimates delivery problems, delays and customer disatisifcation • Locate the nearest available store with sufficient stock to reduce delivery times and costs • Itineraries and truck-loading instructions based on optimal delivery routes, saving time and resources • Deliver detailed maps and directions to drivers 27
  28. 28. Case Study: Understanding of Risk Spectrum has enabled Willis to: • Fast, Accurate Global Geocoding • Understand impact of catastrophe’s and potential catastophe’s • Improved analyst productivity from 8 hours to 1 hour • Accurate results gives a more informed view of client’s projected exposure • Visualise a client’s exposure on a map improves Willis worth to it’s clients 28
  29. 29. Case Study: Master Data Management Logistics Spectrum has enabled FedEx to: • Customer Master Data Management – a key component in delivering the right package to the right address on time, while saving time and resources • Geocoding customer locations determines service eligibility, calculate distance, and sequence delivery routes. • Online address validation 29
  30. 30. Case Study: Retail Planning, Sales & Service Delivery Challenge • Required accurate territory data to minimise franchisee disputes • Needed ability to easily manage territories and keep them updated • Reduce or eliminate manual processing of unlisted addresses within territories Solution • Accurate data fed into franchise process • Addresses with territories determined within minutes through address boundaries • New address system interfaced with phone and online delivery services Results • Steamlined process of planning franchise territories • Manage and update territories quickly and easily • Reduce lost revenue through dead/unknown addresses • Internal productivity improvements through removal of barriers to process orders 30
  31. 31. Case Study: Running my Network business Challenge • Required more intuitive way of drilling-down into sales data to identify location based sales and product trends across the country • Wanted to visualise whole distribution network and maximise competitive advantage when devising sales and marketing campaigns Solution • Visualise whole distribution network to proactively resolve issues • Analyse sales performance of each region against KPIs • Visualise SIM card fraud cases Results • Expose hidden location centric information enabling management to monitor sales and distribution performance. • Implementation of activities to reduce sales-to-churn • Better allocate marketing resources 31
  32. 32. How - Telenor Integration with BI SAP Business Objects
  33. 33. Case Study: Context of real time Location Challenge • Solution required to provide highly accurate international geocoding within aggressive SLAs • Ability to quickly & accurately determine an address from set of coordinates when user checks-in Solution • Global geocoding, reverse goecoding, geo processing & data integration solution which met SLA target of <50ms • Accurately auto populate address fields using reverse geocoding during check-in Results • Use reverse geocoding during check-in process • Facebook redesigned platform to support location tags for pictures, status updates and timeline events 33
  34. 34. Extending LI into Infrastructure and BIM
  35. 35. Infrastructure Asset Management What Who Why An enterprise solution that includes GIS, CRM, task management, financial process management, business process logic, call centre and mobile working capabilities to manage infrastructure assets. Any public sector municipality who has a mandate to manage, repair and install assets or any private sector company who manage assets via outsourcing engagements for the public sector Infrastructure drives our economy. Tax payers are the customer and they demand high quality services Liability protection & financial planning. Property Waste & Cleansing Utilities Work Zones Street Furniture Road Maintenance Roads & Highways Trees Lighting Green Spaces Bridges Signage Pathways
  36. 36. MapInfo -Autodesk Partnership Urban Planning/Infrastructure Lifecycle Performance Management MapInfo Pro Visioning Policy Strategy Plan MapInfo Pro AutoCAD MAP & Infraworks Design Revit Civil 3D Build Manage Impact Analysis NavisWorks Confirm MapInfo Pro/Stratus Autodesk Solutions Pitney Bowes Solutions
  37. 37. 3D City Modelling Base Station Coverage Modelling • Display models as Voxels • Calculate Volumes • Slice in X, Y & Z • Display multiple cross- sections • Generate surfaces and footprint maps • Colour by different model properties • Export to common RFP, CAD, GIS and 3D formats
  38. 38. Thank You James.brayshaw1@pb.com
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