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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..” 2 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 3 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 4 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 5 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 6 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 7 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 8 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 9 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 10 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 11 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 12 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) 13 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 14 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 ... 15 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 16 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 17 IBM Software Group DW Solution Example 18 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 19 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 20 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 21 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 22 IBM Software Group 23