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Copyright © 2011 CSG Systems International, Inc. and/or its affiliates (“CSG International”). All rights reserved.1
Information Excellence SeriesToday’s Speaker
Telecom BI Reference Architecture for enhancing customer intimacy
A Practitioner’s Deep Dive
Jawahar Sabapathy
Principal Architect, CSG International
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Telecom Enterprise BI Reference ArchitectureEnhancing customer intimacyJawahar Sabapathy
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In the Next Hour
Typical BI applications in different industries – 5 minutes Sample Telecom industry applications – 15 minutes Enterprise BI Reference Architecture - 15 minutes
• Subject areas• Source systems to get 360 degree view• Top level usecases realized using this
- OLAP as RADAR- Mining as targeted precision instrument for the usecases
Deep dive in to a specific application – say Retention Management – brief on important variables that are potential drivers, a process for valued customer retention. – 15 Mts
Challenges/Enablers for achieving BI unique to the industry –10 minutes
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Vertical use-case scenarios
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BI is Used Everywhere
TheBusiness Intelligence
Domain
Sales PatternsIntegrated Customer ViewCampaign ManagementMarket Basket AnalysisCustomer ValuationAnalytical CRM
Order Li fe CycleInventory AnalysisQA/TQMSupplier ComplianceDistribution AnalysisAnalytical SCM
Cal l Behavior AnalysisFraud DetectionChurn AnalysisService Usage AnalysisPromotion EffectivenessAnalytical CRM
Credit RiskMonetary RiskBASEL/AML/ALMAnalytical CRMInsurance rating engines
P & L AnalysisCompl ianceProfi tabilityPerformance AnalysisSegmentation Analysis
ALLINDUSTRIES
MFG
RETAIL TELECOM
FINANCIAL
GOVERNMENTNational SecurityCrime AnalysisHealthFraud DetectionContractsImmigration
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BI is Used Everywhere
TheBusiness Intelligence
Domain
Sales PatternsIntegrated Customer ViewCampaign ManagementMarket Basket AnalysisCustomer ValuationAnalytical CRM
Order Li fe CycleInventory AnalysisQA/TQMSupplier ComplianceDistribution AnalysisAnalytical SCM
Cal l Behavior AnalysisFraud DetectionChurn AnalysisService Usage AnalysisPromotion EffectivenessAnalytical CRM
Credit RiskMonetary RiskBASEL/AML/ALMAnalytical CRMInsurance rating engines
P & L AnalysisCompl ianceProfi tabilityPerformance AnalysisSegmentation Analysis
ALLINDUSTRIES
MFG
RETAIL TELECOM
FINANCIAL
GOVERNMENTNational SecurityCrime AnalysisHealthFraud DetectionContractsImmigration
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Telecom Vertical
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Telecom Transformation
Fixed Mobile Voice Data + Voice Postpaid -> Prepaid “Minute Factories” -> App factories Outsourcing Waves Business models change ( Carriers, Tower businesses,
Franchisees)
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India Key Points
Wait List -> On Demand Phone connection High Competitive industry Talkative nation Sachets market Growth reaching stages of revenue plateau, high
subscriber additions, multi sims Growth in rural markets Relatively Low Broadband penetration Mobile will be access to data / services / net and
community !
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Transformation Axes
Technology driven requiring huge capex/opex (LTE re-engg) - 4G, All IP, M2M
Regulatory driven • on tariffs, security, customer care and SLA, MNP removing last
stickiness Competition driven
• forcing tariffs down, ask for higher innovation rate• Encourages better CRM / BI• New corners of competition such as OTT, more playersd vying for same
digital content / pipe Customer driven
• Profiling and Mass Customisation, More Data / Apps Business Model driven
• Cloud• Eco system of Content and App Providers, OTT, Value Chain
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Telecom EA – TMF eToM / Business Process Framework
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Telecom EA – TMF eToM / Business Process Framework
OperationsFulfillment Assurance Billing & Revenue
ManagementOperations Support & Readiness
Service Management &Operations
Resource Management &Operations
Supplier/Partner RelationshipManagement
Customer RelationshipManagement
Retention & Loyalty
Customer Interface Management
Selling
Resource Data Collection & Distribution
Supplier/Partner Interface Management
S/P PerformanceManagement
S/P Problem Reporting &Management
S/P Requisition
Management
ResourceProvisioning
ResourceTrouble
Management
ResourcePerformance Management
ServiceQuality
Management
ServiceProblem
Management
CustomerQoS / SLA
Management
S/P Settlements& Payments
Management
Service Guiding & Mediation
MarketingFulfillmentResponse
S/PRMSupport &Readiness
SM&O Support &Readiness
RM&O Support &Readiness
CRM Support &Readiness
ServiceConfiguration & Activation
OrderHandling
ProblemHandling
Bill Payments & Receivables Mgt.Bill Invoice
Management Manage
Billing Events Charging
Bill InquiryHandling
Resource Mediation& Reporting
Manage Workforce
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Telecom EA – TMF eToM / Business Process Framework
InfrastructureLifecycle Management
ProductLifecycle Management
Strategy & Commit
Strategy, Infrastructure & Product
Marketing & Offer Management
Service Development & Management
Resource Development & Management
Supply Chain Development & Management
Sales Development
Product Marketing Communications
& Promotion
ServiceDevelopment &
Retirement
ResourceDevelopment &
Retirement
Supply Chain Development
& Change Management
MarketingCapability Delivery
Product & OfferCapability Delivery
Product & Offer Portfolio Planning
MarketStrategy &
Policy
ServiceCapabilityDelivery
Service Strategy & Planning
Resource Strategy & Planning
Supply ChainStrategy & Planning
ResourceCapabilityDelivery
Supply ChainCapabilityDelivery
Product & OfferDevelopment& Retirement
Sales Development
Product Marketing Communications
& Promotion
ServiceDevelopment &
Retirement
ResourceDevelopment &
Retirement
Supply Chain Development
& Change Management
MarketingCapability Delivery
Product & OfferCapability Delivery
Product & Offer Portfolio Planning
MarketStrategy &
Policy
ServiceCapabilityDelivery
Service Strategy & Planning
Resource Strategy & Planning
Supply ChainStrategy & Planning
ResourceCapabilityDelivery
Supply ChainCapabilityDelivery
Product & OfferDevelopment& Retirement
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Telecom BI Applications
Sales & Marketing Product management and VAS Customer Care Financials Network & Traffic CxO Compliance & Regulatory
Being a system linking Ops to
Strategy, BI has to solve business problems using
transactions data
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Decision Support Use-case Scenarios
Customer Intimacy - CRM• Segmentation by ARPU, Loyalty, Geography
- Use this for Larger Loyalty Card Program /Co Branding- Use this to sell advertisement space in Mobile Bills
• Study current High ARPU customers and refine Acquisition Strategy ( Location, Profile, Dealers, Payment Type)
• Package Migration for increased loyalty• Customer Care Feedback – to reduce customer care costs and shorten query
resolution, TCE• Use Segmentation as a backdrop in many applications such as network design,
Product Uptake, Policy decisions, Retention Churn / Retention
• Model, Segment, Offer and Retain
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Decision Support Use-case Scenarios
Product Mgmt / Marketing• New product based on traffic ( micro segmentation) – Examples• New product creation/refine based on Distribution of key facts such as subs,
MoU, Invoice, Voucher Type, Prepaid Plan• Leverage Successful, high margin products into other geographies• Promotional Offers on Products using the Past Trends and justify financially –
Shorter Product Approval cycles • Understanding Major contributors to Revenue and Protect/Nurturing those
(80:20 rules)• Bundling of VAS products (what goes well , market basket)
- Broadband + 3G- Ring Tone and Ring Backs combo- Logos / Wall papers. Themes
Sales and Marketing• Identify affinity segments for up sell/cross sell of new services• Advertising / Co branding• CLM ( Right Offer to Right Customer at Right time) – See which offers have more uptake
– to what segment• Dealer Performance and Dealer Fraud
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Decision Support Use case Scenarios
Finance• Payment Patterns and Promotional Schemes for early payment encouragement• Rated Revenue vs Invoiced Revenue – Effect of Subscription and Discounts on Products• Promotions Approval based on traffic trends – What If
Planning/ Traffic engg / Route Optimization• Where do we add next BSC ? • Where do we strengthen the POP Capacity ( for which circle , which operator ) • Where we need to add eNodeBs/ femto cells ? • Fault / Performance mgmt data trending and prediction• Evolution into CEM• Roaming Trends
Performance • Rank Circles by Customers / Revenues / Churners
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DSS Use case Scenarios
Fraud / Revenue Assurance• Has specialized products that employ data analytics and
techniques such as finger printing, prediction to identify fraud and preventing them to minimize revenue leaks.
Enterprise Risk management
1
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Summary Usecases
Customer Intimacy – Achieve and leverage Enterprise wide Products Performance - Measure / Track / Manage Targeted, personalised marketing – Closed Loop Trends and Patterns – Measure and Leverage for Products,
Traffic, Network Plans Popular Countries/Carriers – Measure and manage for
capacity, products Financials – Justification for new Products / Promos,
Campaign ROI, Effect of Discounts on revenue, 80-20 discoveries
Risk management• Fraud, RA
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Tier One CSPs Rank their BI Priorities
0 2 4 6 8
Customer & Product ProfitabilityAnalysesMarket Segmentation
Customer Churn
Service Provisioning/ActivationAnalysesRevenue Assurance
Channel Performance
Customer Service Performance
Increasing Financial Visibility
Network PerformanceManagementNetwork Planning and designB
usin
ess
Inte
llige
nce
Prio
ritie
s
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CUSTOMER INTIMACY PAYS DIVIDEND
TDWI Best Practices Awards: APAC operator
(Data Warehousing on a Limited Budget category)
Since launch in late 2000, the company has grown aggressively by pioneering new products and services, including eliminating contracts, offering free voicemail, and billing by the second. The strategy has shaken up the industry, leading some competitors to offer similar services. Company saw the need for a robust data warehousing system that would underpin the architecture and turn information about customers into vital business intelligence from day one. This meant it had to be up and running in less than four months.
IN UK, in successive surveys, company was rated to have BETTER NETWORK/COVEREGAE/QUALITY.
COMPARED TO ITS COMPETITION.
The SECRET IS………
Company is A MVNO!
HAS NO NETWORK OF ITS OWN!!
GETS CAPACITY FROM ITS COMPETITION!!!
CUSTOMER CARE CAN CREATE A GREAT SATISFACTION/PERCEPTION
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Enterprise BI Architecture
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Architectural components
Subject Areas Tuned, Comprehensive Data Model with detail and summaries enabling
slice & dice, drill down / drill thru.• Enabling 360 degree customer view
Source Systems Data Staging and Integration EDW Pre-select building blocks
• OLAP as RADAR including CXO Dashboard, BSCs• Mining • ETL/DB• Short Term R/T Profiling• CEM• Search and BI
Metadata / MDM Integrated business rules for specific apps
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Subject Areas
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Subject Areas
Usage Analysis Interconnect Usage Analysis IP Usage Analysis Customer Churn/Retention Customer Profiling Up-sell/Cross-Sell Sales/Marketing Campaign
management (Promotion Response)
Contact History Customer Orders, Order
Lifecycle, Order Fulfillment Customer Payment,
Customer Billing Revenue Analysis Prepaid Revenue Analysis
Contract Analysis Supplier Order Fulfillment Cost Analysis Sales Performance / Channel
Profitability Content Network Analysis Network Capacity SLA Compliance
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Architecture at a glance
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BI PlatformIntegrating Integrating customer insight into business customer insight into business processes and systemsprocesses and systems
Dimensions
Facts
Aggregates
Scoring History
Data Sources
Intelligence HubProfitability Voluntary
Churn
Channels
Direct Mail
Scoring Engine
ETL
Search
IVR Survey
Segmentation Engine
Involuntary Churn
Customer Experience
Bad Debt, Credit score
Collections
Behavior
Response Attribution
Call Center
Customer Intelligence Platform
Performance Reporting
External Sources
Surveys
News/Internet
Source C
Web Service
ETL
CRM & Call Centre
Billing
Order Mgmt
Mediation
Network
SDP
OLAP/Visualization/CxODashboard
OSS
Meta Data
Presentation Layer
CEM
Campaigns
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Top-down / Bottoms-Up
“… The data warehouse is nothing more than the union of all the data marts …” Ralph Kimball Dec. 29, 1997.
“You can catch all the minnows in the ocean and stack them together and they still do not make a whale.” Bill Inmon Jan. 8, 1998.
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Source Systems
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Source Systems - Dimensions
CRM/Customer Care• Customer Demographics (Age, Sex, Profession, Address & zip,
household) Dealer Management Billing
- Product / Services
Prepaid- Products, Vouchers
Reference• Cell Geography• PLMNs / Operating areas / Telcos
Include all business units ( Fixed, Mobile, ISP…)
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Source Systems - Facts
Facts• Billing & Prepaid
- Rated usage, MoU, BoU- Invoices & Payment- Vouchers , Topups
• Mediation- Raw Minutes of Use, BoU
• Network- Usage, Traffic, Performance data, Faults
• SDP- Content, Content Provider- VAS
• Roaming & Interconnect• Call Centre
- Inbound events
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Key Dimensions
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Key Dimensions & facts
Demographics ARPU Length of Stay Products Geography Cell Geography Time Business Units Origin and Destination
analysis SNA
Calls / MoU / BoU / Events Invoice amounts Payments Topups Quote to Cash (Fulfilment
Velocity) Time to resolve # of churners, additions Suspense revenue Detail and Aggregates
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Applications
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Pre Integration / Pre-selection
Support popular, Industry standard• ETL, DB, OLAP, Mining, Marketing
Adapters for popular Billing systems, CRM, Mediation and Network
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OLAP is your RADAR
platinum customers
Region 1 contributes highest
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Radar High lights
Plan ABC/XYZ people are not only concentrating High ARPU, +
High Rated Amount High SMS Usage High GPRS/MMS Adapters High STD/ISD User
•Trend Setters and Early adapters, Loyal
Good target
customer base for the LTE Launch
Campaigns
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Visualization evolution
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Products Performance – Distributions
0
1000
2000
3000
4000
5000
6000
Plan Unlimited
Plan 2GB Plan Lite Plan M2M
DatainMB/month
See distribution of various facts ( Data Volume, Revenue, SMS,MMS, MoU) by dimensions such as Package, Customer segments to understand the distribution. Extremely useful in tuning Product offerings, fixing Free Units, Overage charges, financial modelling for What If.
Analyse by device categories to refine
Device Bundling plans
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Retention Management
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Satisfaction , Loyalty & Competition - HBR
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Churn – some industry details
Barriers to switching communication providers been so low. MNP, Data ! And while loyalty tends to be high among older consumers, younger consumers
are accustomed to continuously shopping around for the best plans, features, and perhaps most importantly – the coolest phones.
According to global consulting firm,Accenture, the steady increase in customer churn rates is being driven by several factors, including equipment envy, flexible pricing plans, customer service, network performance, and number portability.
And as deregulation continues and technology advances, the players in the communications industry continue to expand beyond the traditional telecommunications companies to include cable providers, wireless service providers, satellite service operators, and broadband phone service providers.
Customer retention statistics for consideration:• Customer churn among cable and telecommunications companies is projected to cost
organizations up to $10 billion annually worldwide.• Carriers will lose 15% to 30% of their customers each year. In the U.S. alone, 20 to 30
million customers or more are expected to defect annually.
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Area of focus for churn applications
Non-paymentBankruptcyFraud
Going to the competition (‘on system’ churn)
Affordability
Cancelling altogether (‘off system’ churn)DeathMoving out of service area
Stolen phone
No need
Network coverageService dissatisfactionBillingOld/broken equipment
PricingPromotion
What are the different facets of churn ?
Total churn(100%)
Uncontrollable reasons(10%)
Controllable reasons(65%)
Involuntary churn(25%)
Voluntary churn(75%)
Churn segments Examples of churnExamples of churn
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Why do customers churn ?
Product Price
Product FeaturesComplaint Resolution
Branch LocationMistakes
Poor ServiceDeath
Long Queues
Other
0% 5% 10% 15% 20%
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Churn Reduction Methods
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Data Mining Techniques in Retention Management
The churn analysis consists of :• Comparing customers categorized as Churners and those categorized as
Non Churners according to their characteristics which are gathered from historical data.
• Identify the principal characteristic differences between Churners and Non churners.
• A churn model mathematically quantifies the pertinent correlations between these characteristics and the Churn score of each customer.
C hurn/CP S D isp lay ed va ria b le MOS _ FILE - Fi l te r cri teria (CH UR NE RS , 5 ) - Se g men t se le cte d 1 0 0 va l id cu sto me rs / 1 0 0 se le cted cu sto mers
+2 .00 0 0
+3 6 .00 0 0
N _R e sp N o n _C h urn e rs Ch u rne rs T o tal
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Retention Management process
Prepare and Audit Churn Datamart with relevant variables and history, including customers who churned
Use tools to build, validate and train model (lift) Scoring of current customers Use OLAP to identify segments of interetst – customers
with high LTV, LoS, or e.g Use campaign management tools for design , execute
and track retention campaign Model Performance and stability over time
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Churn model exampleVARIABLES CATEGORIES & WEIGHTS
Age <27 27-49 >=49 143,2 36,1 2,7
Months of Service <22 22-23 23-28 28-40 >=4050,6 68,5 78,9 -1,4 -3,2
Tariff Plan Code M0 M1 M2 M343,7 -34,6 5,3 11,3
Total Invoice M-4 <18 18-27 27-83 >=8310,8 57,6 33,4 29,7
# months to end of contract <2 >=245,6 33,0
# calls to call center <2 >=229,8 89,5
ZIP Code M0 M1 M2 M3 M4229,0 44,7 7,1 85,4 19,5
# calls to fixed line <5 5-12 12-15 15-18 >=1848,6 19,8 -13,3 48,4 21,2
# out calls to competitors <13 13-34 34-63 >=6339,4 13,6 70,8 30,9
Duration of out calls <19 >=1935,0 -1,0
Duration off peak calls <12 12-44 44-59 >=5939,7 15,1 68,3 27,7
Typical profile of a churner• Less than 27 years old• MoS : less than 28
months • Low M- 4 Invoice mostly
between 12 and 27 EURO• Calls Customer Care
more than twice a month• Calls between 45 and 60
minutes per month during off peak hours
• TariffPlanCode = A,M,Y,Z• ZIPCode = 22, 44, 48, 79
• Social Network Analysis
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Key Variables
Data Modeling Campaign Available Identification. Critical Critical Churn information. Critical - Subscription information. Critical Critical Names & addresses - (Critical) Handset type & manufacturer Critical Critical Customer information Critical Critical Socio-demographic information Nice to have Nice to have Billing information Critical Critical Services and Provisioning Critical Critical Bundle of minutes Critical Critical Customer Service information Critical Critical Out-going traffic, per destination Critical Critical Out-going traffic, per period of the day Critical Critical In-coming traffic, per destination Critical Critical In-coming traffic, per period of the day Critical Critical Roaming information Critical Critical Network quality Critical Critical
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Evolving Tactics for retention mgmt
Bundling increases stickiness–• As much of a customer acquisition as a customer retention tool,• the more products a consumer has from a single vendor, the higher
the exit barrier.
Predictive Analysis –• Customer data analytics allow CSPs to analyze• customer profitability and predict churn.
Outreach –• Historically, outbound activity in the communications sector has
almost entirely been devoted to customer acquisition. Now, outreach programs actively target high-value, at-risk customers with marketing offers to prevent churn. * careful – anti spam, regulatory compliance
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Final Nail
Technology, services, products can be copied - but not the organizational culture
Leverage and exploit data fullest to your advantage Maximize every customer interaction
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Industry Specific Challenges to BI
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Telecom EBI challenges / Pros
Data !!! Big Data• Large sub base – 10 – 150 million for e.g• Heavy transactions / sub / day – 30+
Long Medium trends vs quick RT profiles Data availability, quality
• Harder to get in some places Terminology / Business Rules & MDM Internal Support / Exec Buy-in Longer Implementation times Pros
• Have the contact and billing relationship• Almost all data is collectable automatically
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Hurdles Implementing Business Intelligence
0 2 4 6 8
Accuracy of data from sourcesystemsBusiness Justification
Disparate data definitions
Internal organizationalresistanceScalability
Availability of skilled staff
Volume of Available Data
Accessibility to legacy systems
Availability of Solutions
1= Smallest Obstacle, 10=Largest Obstacle