dossier - seminario sul ruolo del datawarehouse come componente attiva nella gestione dei processi a
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Massimo NappiTelco Industry Community of Expertise - Italy
Seminario sul ruolo del Datawarehousecome componente “ATTIVA” nella gestione dei processi aziendali
AGENDA
� INTRODUZIONE
� MATURITY MODEL� Evoluzione del business delle aziende
in relazione alla crescita del DWH
� ACTIVE DATAWAREHOUSE
� GESTIONE DELLE INFORMAZIONI E PROCESSI AZIENDALI
� ALCUNI CASI DI STUDIO� Il Customer Relationship
Management
� Il network management
NCR Corporation Overview
Financial Solutions Division
#CLIENTI
REVENUE
#DIPENDENTI
700>1000
$1,262 MILLION
$5,500 MILLION
4,00030,100
TERADATANCR
Maturity ModelEvoluzione del Business delle aziende
Operate Understand Change Grow Compete Innovate
Level 0 Level 2 Level 3Level 1 Level 4 Level 5
Business start-up; defining &
developing pro-ducts & services
Internal opera-tions; score-
cards are pro-duct & business
unit focused
Customer focused;scorecards are
cross-functionalor enterprise
wide
Market segmenta-tion across pro-ducts & businessunits; target mar-
kets drive strategies
Performancemeasured
againstcompetitors &
customer profitability
Managementinnovation
drives industrystandards, practices
& productivity
Maturity ModelEvoluzione del DWH e legame con l’evoluzione delle aziende
Operate Understand Change Grow Compete Innovate
Level 0 Level 2 Level 3Level 1 Level 4 Level 5
ì
Livello 0 - OperateS
up
po
rt
Netw
ork
Fin
an
ce
Cu
stom
er S
erv
ice
Mark
etin
g
Billin
g
Understand Change Grow Compete Innovate
Is it happening?
REPORTINGWhat happened?
ANALYSISWhy did it happen?
PREDICTIONWhat will happen?
OPERATIONALIZEWhat is happening?
ACTIVEMake it happen?
Operate
BUSINESS FOCUS• Aziende o Business Unit in fase di start-up • Focalizzazione sullo sviluppo processi interni• Implementazione dei sistemi operazionali• La pianificazione, il forecasting e l’analisi dei processi
interni avviene manualmente
DWH REQUIREMENTS & SCOPE• Non esiste DWH• Non ci sono sistemi analitici o a
supporto dei processi di business• Reporting limitato ad un insieme di
misure di performance• “Sta accadendo qualcosa?”
Livello 1 - UnderstandOperate Understand Change Grow Compete Innovate
Is it happening?
REPORTINGWhat happened?
ANALYSISWhy did it happen?
PREDICTIONWhat will happen?
OPERATIONALIZEWhat is happening?
ACTIVEMake it happen?
BUSINESS FOCUS• Aziende o Business Unit ancora focalizzata sui processi interni• Necessità di allineare gli obiettivi funzionali con quelli strategici• L’azienda deve misurare il revenue dei prodotti e deve tener
traccia di ordini e fatture verso il cliente• Il servizio clienti deve misurare la propria efficienza
DWH REQUIREMENTS & SCOPE• Vengono sviluppati Data Mart
indipendenti• Ogni DM estrae i dati di interesse dai
sistemi operazionali• I dati vengono inseriti in forma
aggregata e non di dettaglio• “Cosa è accaduto?”
Livello 2 - ChangeOperate Understand Change Grow Compete Innovate
Is it happening? REPORTINGWhat happened?
ANALYSISWhy did it happen?
PREDICTIONWhat will happen?
OPERATIONALIZEWhat is happening?
ACTIVEMake it happen?
BUSINESS FOCUS• L’azienda inizia a sviluppare strategie focalizzate sulla
“Customer Satisfaction”• Le risorse economiche non possono essere allocate su attività
se queste non garantiscono un adeguato ROI• Le performance devono essere misurate in ottica “Enterprise”
DWH REQUIREMENTS & SCOPE• Viene realizzato un Enterprise DWH• Nel DWH vengono inseriti i dati di
dettaglio provenienti da tutti i sistemi operazionali
• I dati sono organizzati secondo un modello logico in 3NF
• “Single version of the Truth”
Livello 3 - GrowOperate Understand Change Grow Compete Innovate
Is it happening?
REPORTINGWhat happened?
ANALYSISWhy did it happen?
OPERATIONALIZEWhat is happening?
ACTIVEMake it happen?
PREDICTIONWhat will happen?
BUSINESS FOCUS• L’azienda inizia a focalizzarsi verso l’esterno• Vengono sviluppati modelli predittivi (profiling & segmentation)• Le strategie di marketing e di vendita tendono ad individuare il
giusto mix di prodotti da offrire attraverso i canali preferiti• L’azienda inizia a domandarsi “Cosa accadrà?”
DWH REQUIREMENTS & SCOPE• Necessità di inserire ulteriori dati
storici di dettaglio e dati esterni• Sviluppo di sistemi di data mining• La comunità di utenti si estende ai
responsabili di BU• Si sviluppano Data Mart dipendenti a
supporto di applicazioni verticaliDM DMDM DMDMDM
Livello 4 - CompeteOperate Understand Change Grow Compete Innovate
Is it happening?
REPORTINGWhat happened?
ANALYSISWhy did it happen?
PREDICTIONWhat will happen?
OPERATION.What is happening?
ACTIVEMake it happen?
DM DMDM DMDMDM
BUSINESS FOCUS• L’azienda è focalizzata sull’acquisizione di posizioni più
competitive e sull’aumento della profittabilità• I costi interni necessitano di una gestione accurata• I clienti devono essere gestiti al fine di massimizzare il revenue• Necessità di rispondere velocemente ad ogni richiesta del cliente
DWH REQUIREMENTS & SCOPE• Il DWH deve supportare
interrogazioni tattiche• La comunità di utenti si estende al
personale “field”• Diventa critico il tempo di “latency”
delle informazioni• Inizia il processo di “Data Mart
Consolidation”
Livello 5 - InnovateOperate Understand Change Grow Compete Innovate
Is it happening? REPORTINGWhat happened?
ANALYSISWhy did it happen?
PREDICTIONWhat will happen?
OPERATIONALIZEWhat is happening?
ACTIVEMake it happen?
BUSINESS FOCUS• L’azienda è leader di mercato e definisce gli standard, i criteri di
successo e le best practice nella propria industry• I processi aziendali e l’infrastruttura IT sono ottimizzati per
supportare la propria “core value proposition”
DWH REQUIREMENTS & SCOPE• Il processo di “Data Mart
Consolidation” si è concluso• Il DWH è diventato parte attiva
dell’azienda• Il DWH fornisce supporto end-to-end
a tutti i processi di business aziendali• “Fai in modo che accada!”
Active Datawarehouse
Active Data Warehouse in AzionePackage Shipping
� Break Bulk - trucks arrive, unload, load, leave
� Should the truck leave if all trucks with packages for that destination have not arrived?� Evaluate all missing packages; service levels, previous service,
urgency, customer value� Evaluate packages on board; service levels, probability of
missing, customer value, urgency� Decide now whether to hold
� Requires up to date, complete, detailed data across the entire company
� Rental Car Business - service provider with limited (relatively) fixed inventory
� Rent the maximum number of vehicles at the maximum price possible under the constraint that all prices offered exceed variable cost of the rental � Pricing can be determined by forecasting demand and price
elasticity as it relates to demand� Differentiated pricing is the ultimate yield management strategy
� Requires up to date, complete, detailed data across the entire company
Active Data Warehouse in AzioneVehicle Rental
ADW: Caratteristiche tecnologiche
Scalable RDBMS
ContinuousLoad
TacticalQueries &Analytics
WorkloadMgmt
EventDetection
Near Real TimeDecisions
StrategicDecisions
TacticalDecisions
Event-basedDecisions
CRM FraudMgmt
Supply ChainMgmt FinancialsBusiness
Application
Business Requirement
Infrastructure Requirement
InfrastructureFoundation
ContinuousOperation
(7x24)
ADW: Architettura logica
Sistemioperazionali
IntranetReporting and DSS Tools WebPortal
EAI
Enterprise Data Warehouse
Data Transformation Layer
Virtual View Layer
Data Staging Layer
Materialized View Layer
3rd Normal Form Layer
Gestione delle informazioni e processi aziendaliAlcuni casi di studio nelle Telecomunicazioni
Business ProcessManagement
Operations Management
Regulatory Compliance
ServiceManagement
Staffing Management Provisioning
CustomerRelationship Mgt.
CustomerAcquisition
CustomerRetention
CustomerGrowth
AssetManagement
SwitchCap Mgmt
NetworkCap Mgmt
DSLCap Mgmt
NetworkCost Opt Network QOS
FinancialManagement
Credit &Acct Recv
SettlementsAssurance
BillingAssurance
FraudManagement
Process Business Improvement Opportunities (BIOs)
Corporate Data Warehouse
Billing CDRs ExternalCustomerRecords
Enterprise Mgmt
Products
Marketing
OrdersTroubles
Customer Service Finance Network Support
Il CRM nelle Telecomunicazioni
Tipico processo di CRM
Alcune metriche di valutazione del CRM
Case study 1L’evoluzione dell’azienda
Case study 1Il processo di gestione delle relazioni con il cliente
Action
Channels
InternetE
Mail/FaxSales/
Direct Mail
Mobile Agent/Call Center
Insight
Draw Insight - Marketing
Inter-Action
Execution - Touch Points
Capture Data
IntelligenceDevelopCustomer Base - IT
Disk arrayCustomer Info
Marketing &Customer Strategy
Benchmarking
DataWarehousing
Enterprise architectureCentralized platformKey Performance Indicator
Marketingautomation
Easy to use Channel IntegrationSyntactic MonitoringRecurring Campaign Multi-Channel Campaign Multi-step Campaign Segmentation Event-driven CampaignSemantic Monitoring
Interaction
SMSCall Center OutboundCall Center OutsourcingCall Center InboundLocation UpdateMailingE-MailPoint of Sale
BusinessIntelligence
Propensity to BuyChurn & Risk ManagementBehavioural Scoring
Player 1 Player 2 Customer
Marketing automation capabilities
low priority
high priority Custom Native Implemented Planned
Cross segment analysysPercentile profiling
Segmentation/ Re-segmentationExclusion listImport external listCustomer de-duplicationCampaign history
Reactive Campaign -Event DetectionPush CampaignScheduled CampaignMulti-step Campaings
Channel InterfaceCollect campaign result
Report on change in customer BehaviorRedemption report Financial report
Campaign Results
Descriptive analysys reporting
Targeting/segmentation
Campaign Design & Planning
Campaign Execution
FUNCTIONALITY STATUSUSER REQUIREMENTS
Case study 1Il Datawarehouse come fonte di dati per il processo CRM
Case study 1Miglioramenti nella gestione delle relazioni
BEFORE� Capacity limitation
� Lack of automation
� No events reaction(i.e. customer requests, network failures, etc.)
� Campaign management process poorly integrated
� Limitated monitoring functionalities
� High volumes and number of campaigns managed growth
� High automation of campaing creation and management
� First events automatically managed.
� End-to-end campaign management
� from strategy definition to response capture
� real time information to call center agents for inbound campaign
� Real time redemption monitoring
AFTER
Case study 1Alcuni risultati qualitativi e quantitativi
The new infrastructure ( technology, procedures, people & skills)
supports the “Customer Insight” process, enabling the following
capabilities:
� High Customer base contact rotation
Potential: each customer contacted once a month
Actual (2003): each customer contacted once every 5 months
� Effective channel management
optimisation of contact rules - non over-contacting
throughput of leads/day is in line with channel performance
� High potential leads generation
potential throughput: 500K leads/day
� Consistent integration between Collaborative & Analytical CRManalytical CRM leverages operational CRM
closing the CRM loop
Case study 2Revenue Assurance: il problema
� What is it due to?� Fraud
�network, finance, etc
� Leakage�Especially from billing systems
� Where?� 2% Network and 1st Mediation Layer� 30% 2nd Mediation Layer� 68% Billing Systems
� This generates BIG revenue problems!
Case study 2Revenue assurance: la soluzione
� Consolidate Data and build a Business Intelligence System� Based on the data already present in the CDW
� data need to be integrated
� Built and managed by the CDW group� Solves the interest conflict
� acts only as a control system, whose users are the Billing people
� Is also able to show WHO is in backlog and not only WHY� can focus on customers who produce most backlog
� Modular Development� “Self-Learning System”
� Implementation of new checks basing on the result of the analysis
Case study 2Obiettivi del progetto
� Objective 1: demographics control� Analisys of demographics anomalies inside and cross the system
� Objective 2: from system backlog to company backlog� Increase the precision of backlog calculation for CDW.� Analisys of “backlog Alert” on discharge traffic from Mediation Layer� compare CDW backlog and ML backlog� “Unguided” CDW Traffic Analysis
� Objective 3: analytical control� Historical backlog behaviour Analysis
� backlog aging and error aging� Statistic backlog growth indicators per customer, product and customer/product
� Objective 4: Prioritization and operations control� Prioritization through identification of backlog related to customers,
billing accounts, CLI� Operation Control
� through historical management of relevant errors (to be corrected)
Case study 2Scenario di riferimento
� Surveillance System for backlog “symptoms”� it’s often impossible to detect directly the backlog causes, it’s always
possible to identify some controls for backlog detection.
� Uses “vertical” controls already existing within the systems� The control has generally a limited scenario to the system to which it
belongs.� Only few “new” controls were created, mainly to verify the
congruency of CLIs inside the systems where they are used� Cross Controls have been added
� Indipendent from Billing Systems discards� Some problems to extract CDR data more than once a month� The Billing Systems have been accessed only to collect the working
demographics and billing details.
Case study 2Architettura del sistema
OperatingOperating SystemsSystems
CCRMCCRM DeliveryDelivery MediationMediationLayerLayer
BillingBillingSystemsSystems
week1
CLI Backlog
Backlog
Errori
Errori
No Errori
No Backlog
week2
CLI Backlog
Backlog
Errori
Errori
No Errori
No Backlog
week3
CLI Backlog
Backlog
Errori
Errori
No Errori
No Backlog
week4
CustomerBA…
CLI;
Backlog
Backlog
Error
Error
No Error
No Backlog
Analysis•historical backlogbehaviour•backlog aging•migration of error causes
Operation•workflow order
Control•historical data corrections
Time
CDWCDW RatingRatingManagerManager
BillingBillingManagerManager
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