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