Embed Size (px)
DESCRIPTION
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.
Citation preview
Customer Data
&
Location Intelligence
James Brayshaw – CDLI Vice President EMEA
January 2014
It’s not just about
maps…
It’s about the
data! Integration
Governance
Accuracy Quality
currency
Provenance
Strategy
Integration
accuracy
qu
ality
Do I know where all my Customers are?
Collecting & making sense
of real-time data such as
geo-positioning,
messaging, etc. captured
by mobile devices.
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.
Data is highly
fragmented, in
incompatible formats &
difficult to access.
Data is low
quality, out of
context and
incomplete
Growing concern
around
security & privacy of
data
Top Challenges for
Managing my Customer Data
How Location Intelligence and Customer Information Management
fits Into a client Journey
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.
Company Data
Management
Spatial Data
& Analysis Insight Strategy Communications
Inbound &
Outbound Channels
Customers
The Future - Insight to Location Market
dynamics
What do we mean by Location Intelligence?
Core Location
Processes
Data matching
Addressing
DQ/enriching
Layering, integrating,
referencing
Geocoding In
All forms
Routing In
All forms
Combining
Spatial/Location &
non-spatial,
querying structured
& unstructured data
Spatial analysis
and insight
Mapping/Visualisation
3D &temporal
thematics
User evolution of LI and Business Challenges
Desktop
GIS
MapInfo Pro
Plus Apps Enterprise
GIS
MapInfo Pro,
Stratus &
Spectrum Spatial
Enterprise
LI
Spectrum &
Spectrum Spatial,
Data & BI Integration
Data
Local/Global
Data Importance
Data
Expands Use
of GI Data
Moves to Systems
Approach/IT Domain
Location Intelligence Strength and Focus
10
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
The approach to becoming
Location Intelligent and
improving Customer Data
Becoming Location Intelligent
(It’s about the data)
12
Define a location-based strategy that delivers a real
return on investment ROI to enhance understanding
of customers, increase ARPU, retention etc.
Find the right technology platform to integrate
with my Enterprise system and desktop
GIS and share my data
Create a data governance strategy to regularise,
match, clean, sort, enrich and store my data for
use by a wide user base
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?
15
Name Address County Postcode Phone Email
Mike Ashmore Minton Place Victoria Street Windsor Berks SL4 1EG 01753 848 207 [email protected]
Michael Ashmore Minton Place William Street Berkshire SL41EG 1753848207 [email protected]
M & L Ashmore
Pitney
Bowes
Software
Victorian Street Windsor SL$!EG 01753-848-207 [email protected]
Mike Ashmore,
Pitney Bowes
Software
Minton Place Victoria Street Windsor Berkshire SL4 1EG 01753 848 207
Multiple names
Mixed business &
contact names
Incorrect address
Typo
Abbreviations
Missing data
Non standard
formats
Mis-fielded data
Customer data in Silos!
Account: A123
Auto Policy
Customer ID
Policy Number
Status
Premium
Customer Name
Customer Address
Account: HO123
Home Policy
Robert
Account: A768
Auto Policy
Robert, Jr.
Account: A768
Auto Claim
Mary
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
Robert Mary Robert Mary
Data Improvement Opportunities – Customer
Integrate customer information into one single view
Spouse
• Customer ID
• Customer Name
• Demographics
• Preferences
• Relationships
• Customer Value
Relationship
Children
Spouse
House Holding
Account: AHOA495 Policies
Home Owners Auto Life
L345 HO 123 A768
Premium
Location
Premium
Location
Premium
Location
Premium
Location
A123
Premium
Location
A123
Auto: A123
Payment
Location
Claims
Account: A123
Auto Policy
Customer ID
Policy Number
Status
Premium
Customer Name
Customer Address
Account: HO123
Home Policy
Robert
Account: A768
Auto Policy
Robert, Jr.
Account: A768
Auto Claim
Mary
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
Robert Mary Robert Mary
Better customer data improves relationships
that drive millions in revenue - location is Key
GROW
RETAIN
RECONNECT
SERVE CONVERT ACQUIRE
INFLUENCE
DEFECTIONS
ADVOCATE
Global data provided in 3 key areas…
Global Data Content needed
19
Location Data
Background Mapping
Street Vector Data
Points of Interest
Postcode Boundaries
Administrative
Boundaries
Demographics
Demographics
Geodemographics
Business Data
Business Points &
Lists
Business Summaries
Analytical Datasets
Purchasing Power
Consumer Spend
Retail Destinations
Retail Pitch
Risk Data
Global Data – Unique coverage
20
Data Categories
21
Enterprise Data platform
What we can learn from other industries
Location
Intelligence
Data Quality
An
aly
tics
M
DM
Data Integration
Current Solutions:
• Multiple Vendors
with competing,
overlapping
capabilities
• Too complex
• Too expensive
Vision: • Single unified framework
• Insight built on managed data
on customer, location and
assets
• Simple
• Cost effective
Enterprise EDM – Bring together all elements
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
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
Case Study: Single Customer View
26
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.
Case Study: Customer & Asset location
27
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
Case Study: Understanding of Risk
28
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
Case Study: Master Data Management
Logistics
29
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
Case Study: Retail Planning, Sales &
Service Delivery
30
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
Case Study: Running my Network business
31
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
How - Telenor Integration with BI SAP
Business Objects
Case Study: Context of real time Location
33
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
Extending LI into Infrastructure and
BIM
Infrastructure Asset Management
Roads & Highways Green Spaces
Waste & Cleansing
Road Maintenance
Property
Trees
Lighting
Utilities Work Zones
Pathways
Street Furniture
Signage
Bridges
What 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.
Who 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
Why Infrastructure drives our economy.
Tax payers are the customer and
they demand high quality services
Liability protection & financial
planning.
MapInfo -Autodesk Partnership
Urban Planning/Infrastructure Lifecycle
Design
Visioning
Policy
Strategy
Plan Build Manage Impact
Analysis
Performance
Management MapInfo
Pro
MapInfo
Pro Confirm
MapInfo
Pro/Stratus
Pitney Bowes
Solutions
Autodesk
Solutions
NavisWorks AutoCAD MAP
& Infraworks
Civil 3D
Revit
3D City 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
Base Station Coverage Modelling
