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IBM Software Group
Case Study for Telecommunications
TDW Reference Implementation
David Cope
EDW Architect – Asia Pacific
© 2007 IBM Corporation
IBM Software Group
Data Warehouse Vision
“…to enable Customer Relationship Management
(CRM) across the client organization and reduce
operating costs. The Solution becomes an integral
component to the formation of the customer knowledge
database to support CRM front office applications and
business intelligence functions. The ultimate goal is to
form a closed loop integrated environment between
operational and analytical CRM to facilitate customer
relationship management..”
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IBM Software Group
Project Structure
Project Sponsor:
Chief Operating Officer
Key User Community:
Customer Base Analytics Group
Project covers the following divisions:
Sales & Marketing
International & Wholesale
Finance
Product Development
Information Technology
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IBM Software Group
Why TDW and IBM?
Several vendors and associated products were evaluated
Teradata, Microsoft, Oracle and IBM
TDW offered the highest degree of flexibility and scalability
Complete solution with capability to expand with business
TDW provided a strong fit to the organization, with over 90% of the business
and data requirements being met out-of-the-box
Open technology approach – looking for an open scalable solution rather than a
proprietary architecture / technology
IBM services had a proven ability in data warehouse implementation, and it was
believed that the success of the project lay heavily on a robust and sound
industry model, together with the delivery team’s proven ability to implement
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IBM Software Group
TDWM embraces different views of the business to
support various analysis requirements
Example – how a single user view can be interpreted in TDWM:
Churned
Customer
Involved Party-1;
Account-1; Customer
Involved Party-1;
Account-2; Customer
Churn
Win-Back
Service Instance-1;
Product-1; Plan-1
Acquisition
Migrate Price
Plan-1 to Price
Plan-2
Service Instance-2;
Product-2; Plan-1
Cross-sell Product-2
Service Instance-2;
Product-2; Plan-2
Prospect
Customer
Time
t0
t1
t2
t3
t4
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IBM Software Group
Project Objectives and Phasing
Project Objectives
Implement a Data Warehouse Infrastructure to deliver business intelligence
capabilities and Closed Loop CRM Capabilities
Establish a customer knowledge environment, addressing the existing
business & technical issues through an integrated and reliable platform
(Cost, Security, Integrity, Access, Tools, etc.)
A fully secured environment that safeguards assets.
Implementation Phasing
Phase 1 – Integrated Data Warehouse Infrastructure
Phase 2 – Business Intelligence Applications
Phase 2A – Campaign Management Solution
Phase 2B – Data Mining Solution
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IBM Software Group
Implementation Phases
Phase 2
Phase 1
Deployed a new Campaign
Management System and integrated
Data Mining environment with the
Data Warehouse Infrastructure to
support their campaign operations
and analytics.
Established the core Data
Warehouse using the Telecom
Data Warehouse Model (TDWM)
to immediately support flexible, ad
hoc query analytical capabilities
within the environment.
Com plai nts Analys is Dim ensio ns
Com plai nts Analys is Dim ensio ns
Pr oduc t
BST: m1 Scope
Com plai nts Analys is Dim ensio ns
Logical
TDWM
Pr oduc t
Chan
geitSer
vice
Busin ess
Un
Ge o
gr aphy
Nor th
Pr oduc t Access Ser vice
West
Fina ncial En gi neer in g
East
Tr adi ng Ser vices
Sout h
Supp or t Ser vices
Busin ess Un it Ge o gr aphy
Nor th
Line o f Busi ness
West
Tr ust
East
Retail
Sout h
Com m er cial
Busin ess Un it Ge o gr aphy
Nor th
Whol esale
West
Gr ou p Ser vices
Line o f Busi ness
East
Tr ust
Sout h
Retail
Cust om er Mar ket Se gmCom
en t m er cial
Whol esale
Line o f Busi ness
Tr ust
Gr ou p Ser vices
Retail
Com m er cial
Cust om er Mar ket Se gm
en tesale
Whol
Gr ou p Ser vices
Meas ur es
Num ber o f C om plai nts
Pr oduc t
BSTs
AverLar
agege
Res
po nse
C om
m er tim
ciale
Sm all/m edium Com m er cial
High Net W or t h In divi dua ls
Indivi d uals
Num ber o f C om plai nts
ities
Aver age Res po nseChar
tim e
Cust om er Mar ket Se gm en t
Meas ur es
Meas ur es
Num ber o f C om plai nts
Aver age Res po nse tim e
Physical
BST: Reports and Graphs
Provisioning,
billing and
OSS/BSS apps.
Data Warehouse Database
Campaign
Management and
Data Mining Apps
BST: Reports and Graphs
Static & Adhoc Reporting
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IBM Software Group
Business Requirement Analysis
Adopting the Telecommunications Data Warehouse Business Solution
Templates (BST) to guide the investigation and scope the requirements
Sales
Sales and
and Marketing
Marketing
Campaign
CampaignAnalysis
Analysis
Cross
CrossSell
Sell Analysis
Analysis
Customer
CustomerAcquisition
AcquisitionAnalysis
Analysis
Data
Package
Sales
Analysis
Data Package Sales Analysis
Number
NumberPortability
PortabilityAnalysis
Analysis
Retail
Transaction
Analysis
Retail Transaction Analysis
Sales
SalesChannel
Channel Analysis
Analysis
Churn
Churn Management
Management
Operations
Operations and
and Finance
Finance
Contract
ContractRenewal
Renewal Analysis
Analysis
Customer
Churn
Analysis
Customer Churn Analysis
NLD/IDD
NLD/IDDDefection
DefectionAnalysis
Analysis
Customer
CustomerBilling
BillingAnalysis
Analysis
Financial
Management
Financial ManagementAnalysis
Analysis
Income
IncomeAnalysis
Analysis
Product
Product Lifecycle
Lifecycle
Management
Management
Product
ProductProfitability
ProfitabilityAnalysis
Analysis
Postpaid
PostpaidRevenue
RevenueAnalysis
Analysis
Prepaid
PrepaidRevenue
RevenueAnalysis
Analysis
Usage
Usage Profiling
Profiling
Content
ContentUsage
UsageAnalysis
Analysis
E-Commerce
E-CommerceAnalysis
Analysis
Inbound
InboundRoamer
RoamerUsage
UsageAnalysis
Analysis
Outbound
OutboundRoaming
RoamingAnalysis
Analysis
Pre-rated
Pre-ratedCDR
CDRAnalysis
Analysis
SMS/MMS
Usage
SMS/MMS UsageAnalysis
Analysis
Wireless
WirelessData
DataUsage
UsageAnalysis
Analysis
Wireless
Voice
Usage
Wireless Voice UsageAnalysis
Analysis
Wireline
WirelineData
DataUsage
UsageAnalysis
Analysis
Wireline
WirelineVoice
VoiceUsage
UsageAnalysis
Analysis
CRM
CRM && Segmentation
Segmentation
Commercial
Commercial Customer
CustomerFinancial
Financial Analysis
Analysis
Customer
CustomerArrangement
ArrangementAnalysis
Analysis
Customer
CustomerLifetime
LifetimeValue
ValueAnalysis
Analysis
Customer
CustomerProfitability
ProfitabilityAnalysis
Analysis
Individual
Individual Customer
CustomerFinancial
Financial Analysis
Analysis
Customer
Complaints
Analysis
Customer Complaints Analysis
Wallet
WalletShare
ShareAnalysis
Analysis
Service
Service Quality
QualityManagement
Management
CSR
CSRPerformance
PerformanceAnalysis
Analysis
Service
ServiceOrder
OrderProcessing
ProcessingAnalysis
Analysis
Credit
Credit Risk
Risk Management
Management
Credit
Creditand
andCollections
CollectionsAnalysis
Analysis
Customer
Delinquency
Customer DelinquencyAnalysis
Analysis
Individual
Credit
Risk
Profile
Individual Credit Risk Profile
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IBM Software Group
Solution Outline - Requirement Definition Approach
BST’s
JAD
Sessions to
customise
multiple
BST’s
Top Down
Determine
Measure and
Dimension
Requirements
Determine
Analysts to Measure and
review
Dimension
reports for Requirements
analysis
requirements
Reports
Information Framework
Define Critical Information
Elements and assist in the
identification of candidate
data sources and change
data capture specifications
Workshops
Business
Business
Requirements
Requirements
Report
Report
CrossReference to
Requirements
Develop the framework for a
cross-functional Enterprise
Information Architecture and
specify common (and
divergent) definitions of
business definitions
Bottom Up
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IBM Software Group
Solution Outline - Requirement Analysis Approach
Information Framework
Determine
Measure and
Dimension
Availability
Expand into a
Subject Area
Specific Model
Match Data
Requirements
to Data
Availability
Conceptual Data Model
Logical Data Model
Determine Data Elements
that cannot be provided
together with reasons,
recommendations & impacts
CrossReference to
Requirements
and map to
TDWM LDM
Migration
Migration
Plan
Plan
Data Discovery
Analysts to review
source systems for data
quality & availability
Gap
Gap
Analysis
Analysis
Report
Report
Determine and
evaluate
approaches for
Data Migration
Data Migration Strategy
Define High
Level
Infrastructure
Design
Customize the TDWM
LDM to specific
requirements
Define High
Level
Infrastructure
Design
Infrastructure Design
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IBM Software Group
Requirements: Business and Data
Business Requirements
360o
Support
customer base analysis
Complete & consistent view of customers
Customer Grouping & Segmentation
Customer Value Recognition & Measures
Customer Profiling & Predictive Modeling
Customer Lifecycle Management
Customer Contact Management
Customer Calling & Usage Patterns
Channel Performance
Ex-Customer History
Billed Revenue and Discount Information
Product Hierarchy & Analysis
Data Integrity Management
Accurate, complete, reliable and timely data
Data Security
Comprehensive Metadata Repository
Query & Analysis Tools
Data Requirements
Customer Hierarchy
Customer Profile
Service Profile
Usage Pattern
Spending/Rebate/Payment Pattern
Customer Behavior
Customer Contact & Campaign History
Roamers Profile
Pre-paid SIM Information
Revenue/Cost Information
Prospects
Product Hierarchy
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IBM Software Group
Gap Analysis Approach
Activity Level Costing
Business Process Scope
(Data Capture and Definition)
Business Requirement
Scope
DW
OLAP
Adhoc
Mining
Customer
Demographics
Scoping Assumptions
-
No OSS/BSS Changes in Phase 1.
No Business Process Changes in Phase 1
No Data Cleansing in Phase 1
No End-user Application Development or
Re-engineering
Information
Discovery Scope
ERP (G/L, A/P,
A/R, H/R)
Example Reasons for Gaps
Data not Available
Unstructured Data
Additional Process Required
Unclear Business Process
Unidentified Data Ownership
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IBM Software Group
Gap Analysis Report
Business Process
Process Data GAPS
System Process GAPS
Business
Requirement
Application System
System Data GAPS
Higher Priority
Business Impact Measurement
-
Lower Priority
Breadth of Impact (Org, BU, Team)
Intensity of Impact (Critical, High, Medium, Low)
Urgency (<6 Months, < 1 Year, < 2 Years)
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IBM Software Group
The DW Solution
A TDWM based Enterprise Data Warehouse
The existing Data Marts were re-engineered into the IBM Telecommunications
Data Warehouse Model and implemented on DB2 DWE, DB2 OLAP Server,
Ascential DataStage, Business Objects and ERwin.
Business Objects
DB2 OLAP Server
BI Applications
Business Solutions
Templates (BSTs)
Analysis Structures
DB2 DWE
Summary Tables
Telecommunications
Data Warehouse
Relational Model (TDWM)
System of Record (3NF)
Ascential DataStage
Change Data Capture
(Staging Flat Files)
Legacy OSS, BSS & DSS
Data Sources
Source Systems and
Interface Architecture
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IBM Software Group
DW – Complete Solution View
Non-Call Center
Touchpoints
Interaction with Customers
and Prospects through SMS,
e-Mail, Direct Mail, etc.
Campaign Execution and
Target Customer
Information
Customer Contact and
Campaign Response
Information
Data Mining
Solution
Customer Contact and
Campaign Response
Information
Creation, Execution and
Refinement of Campaigns
Customer
Profile,
Transaction,
Score,
Segment &
Propensity
Information
Customer Profile and
Transactional Summaries
Campaign Creation,
Execution and Target
Customer Information
Campaign
Management
Solution
Campaign
Creation,
Execution,
Customer
Contact &
Results
Information
Integrated Data
Warehouse (IDW)
Center of Closed Loop CRM Solution
Customer Segmentation,
Scoring and Propensity
Scoring, Segmentation and
Propensity Results
Call Center
Interaction with Customers
and Prospects by Phone
Customer
Snapshot &
Scorecard
Information
Direct Query Access to all
Cube, Mart and underlying
Warehouse Information
Centralized Enterprise
Wide Reporting Solution
Analytical
Environment
OLAP, Ad-hoc and Static
Reporting Solution
Centralized Store of Integrated Customer
Information to support all CRM solutions
Operational Systems Source Data focused on
Billing
Call Center
Solution
ERP
Customer Profile, Transactional and Interaction Data
VAS
MNP
...
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IBM Software Group
Fully Integrated, Closed-Loop, Multi-Channel Solution
Closed-loop Marketing Process
Multi-channels
Creative
Development
Value
Proposition
Definition
Contact
Target Customers
Campaign
Execution
Program
Planning
360oC
Customer
Knowledge
Segmentation/
Pre-Analysis
Response
Management
Campaign Message
Direct Response
SMS
Outbound Call
Email
Shop
Direct Mail
IVRS
Web
Call Centre
Inferred Response
Performance
Analysis
Response
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IBM Software Group
Closed Loop is complete with Campaign and Mining
Reports on
campaign results
Interaction results fed
back into the system
Interaction
results captured
back to the data
mart
Campaign
Data Mart
Summarized /
precalculated
Customer
information
Customer
Interaction
Results
CRM Applications
Customer
profile
information
Marketing department
to enter criteria for
target customer
selection
Target
Customer
List
Channels to contact
customers based on
the Target customer
list
Historical
customer
information
Effective customer segmentations
Key drivers for churn model
Key criteria for acquisition campaign target list
Mining Applications
IDW
Customer
Segmentation,
Scoring, etc.
selection
Characteristics of customers with propensity to
accept up-sell & cross-sell of varying products
under different situations
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IBM Software Group
DW Solution Example
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IBM Software Group
Case Study: Churn Management Application
Business Problem - High Pre-pay Churn and IDD Defection
The wireless operator was facing increasing churn rates due to a price war and the
introduction of Mobile Number Portability (MNP).
The wireless market is saturated with mobile penetration over 100%!
Detailed analysis revealed that churning pre-pay subscribers were either “porting-out”
or using competitor IDD gateways.
Consequently the operator was experiencing high churn rates, reduced market share
and impacts to ARPU.
Working with IBM the Operator developed BI applications to:
Define and measure pre-pay churn rates
Identify the re-sell and/or transfer of pre-pay phones and SIM cards
Define and measure IDD defection by pre-pay users
Develop retention programs targeted at pre-pay users
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IBM Software Group
Case Study: Churn Management Application
ANTICIPATE
Anticipate
– Churn Scoring:
• MNP Port-outs
• A/C and SIM
transfers
• IDD Defection
DETECT
Detect
–
–
–
–
MNP Porting
IDD Defection
Call Behavior
Handset Changes &
Transfers
– Service Complaints
– Dropped Calls
ACT
Act:
– Preventive Treatment
– Reactive Treatment
– Win-back Treatment
IMPROVE
Improve:
– Variance Analysis
– Detection Trigger
Performance
– Program Performance
Critical Success Factors
Operator developed a comprehensive Churn Management Strategy including Churn
Prediction, Detection and Treatment Programs
This required stable baselines (e.g. customer segments, propensity models), along with
common business definitions across the process (e.g. churned customer)
Operator implemented the solution through a closed-loop approach to continuously
improve churn analytics and subsequent treatment programs
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IBM Software Group
Case Study: Churn Management Application
Anticipate
Detect
Churn
ChurnScoring
Scoring&&
Segmentation
Segmentation
Score &
Segment
Customer
Customer
Account
Account
Invoice
Invoice
CDR
CDR
Generate
EDW
OSS/BSS
ETL
Source
Data
Data Donkeys
Business Travelers
Weekend Roamers
Customer
Account
Invoice
Segments
& Scores
Update Segments & Scores
Churn Propensity
Credit Risk Rating
Uptake Propensity
Upgrade Propensity
Usage
Interactions
Churn Analysis
Act
Load
Interactions
Interactions
Interactions
Load Leads &
Watch list
Load Behaviour
and Scores
Area
Value
Plan
Tenure
IMEI
Period
Churn
ChurnPrograms
Programs
Proactive/Reactive Churn Prevention & WinWin-back
Opening # of Accounts
Closing # of Accounts
# of Churned Accounts
Predicted Churn Score
Actual Churn Score
Entitlement Balance
Improve
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IBM Software Group
Case Study: Churn Management Application
Significantly reduced churn rates and IDD defection.
Operator is collecting useful customer data at all Touch Points to produce
actionable Business Intelligence
Operator remains the most profitable in the market with the highest ARPU and
the lowest port-outs
Operator is up-selling pre-pay users to lower churn, higher value post-pay
‘premium’ brands
Operator is retaining IDD revenue through the managed release of targeted
IDD prefixes for market segments
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IBM Software Group
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