<Insert Picture Here>

Oracle Customer Hub (UCM) Functional Overview

Dan Gilboa01.2012

Oracle Consulting The Leading Consulting group for implementing Oracle products

• Part of EMEA Consulting organization, 17,000+ consultants worldwide• Connected to thousands more through consulting professional communities• Access to world-wide consulting partners and resources• Extensive Global projects experience• Extensive local implementations and roll-outs experience• Direct link to Oracle Development and Oracle Support• Siebel and Siebel UCM Projects

                                                          

3

“#1 reason CRM projects fail: Data Quality.” “..Fortune 1000 enterprises will lose more money in operational inefficiency due to data quality issues than they will spend on data warehouse and CRM initiatives.” “…recent study cited poor data quality as the biggest inhibitor to successful CRM implementations…” “Only 30% of BI/DW implementations fully succeed. The top

two reasons for failure? Budget constraints and data quality.” “Data integration and data quality are fundamental prerequisites for the successful implementation of enterprise applications, such as CRM, SCM, and ERP.”

האתגר על פי גרטנר

Siebel Universal Customer Master

A comprehensive application used to create, maintain, and distribute trusted customer information that is unique, complete, accurate and synchronized across the enterprise

– Know your customers better– Improve your data quality– Build and utilize your customer insight– Comply with privacy and regulatory

requirements– Reduce data management costs

Data Quality Functionality in a Glance

ProfilingProfiling

Cleansing &Standardization

Cleansing &Standardization

Matching & Merging

Matching & Merging

EnrichmentEnrichment

Understand data status, deduce patterns

NULL מהטלפונים מכילים 30% מהשמות הפרטיים מכילים תו 22%אחד01.01.1111 מתאריכי הלידה הם 18%

ת"א = תל אביב = תל-אביב

רח' = רחוב

DD/MM/YYYYתאריכים =

Spot and correct data errors; transform to std format/phrase

Identify and eliminate duplicates

Attach additional attributes and categorizations

מליון ש"ח50היקף פעילות שנתית

2500מספר עובדים

Functionality

Customer Data example

Feature

שוש לוי = לוי שושנה

דר' דן גלבוע = מר דני גלבוע

6

Data Quality

Profiling

Standardization

Address Validation

Matching

Enrichment

Merging

Data Quality Components

Oracle Data Quality

IDQ Profiling

9.0.1

IDQ 9.0.1

IIR-ASM 9.0.1

IIR 9.0.1

3rd Party (D&B)

OCH 8.1.1.4

Cross Referencing

ERP

CRM

DW

WEB

Legacy

Customer ID:23-3445

Customer ID:GH78GH

UID App ID

1ASCLSCC Legacy A31-32Z

1ASCLSCC Legacy B37-84U

1ASCLSCC CRM GH78GH

1ASCLSCC ERP 23-3445

… … …

Universal ID:1ASCLSCC

Customer ID:B37-84U

Customer ID:A31-32Z

• Stores all customer identifiers for the operational applications connected to UCM

• Provides critical mappings used for data synchronization, reporting, and analytics

• Supports 1-to-many cases in which multiple customer records exist in an application that map to one master customer record

• Based on the Cross eferencing, UCM can publish customer data to interested applications

Partner

Custom

Cross Referencing – Universal Unique Identifier

• UID is generated by UCM to uniquely identify a customer across the enterprise

• UCM publishes the UID to operational applications and data warehouses for data synchronization, reporting, and analytics purposes

• The UID is guaranteed to be unique over the lifetime of the deployment

Leasing

Mortgage

BI

CallCenter

Loan

TreasuryWeb Site

Partner

WEB

# JK-674-HJ# JK-674-HJ# JK-674-HJ# JK-674-HJ# JK-674-HJ# JK-674-HJ# JK-674-HJ# JK-674-HJ# JK-674-HJ# JK-674-HJ

Create “Best” Customer Record – Matching

• Best of breed matching technology embedded from SSA

• Matching on name, address, and other attributes• configurable for other attributes

• Configurable for real time and batch

• Suspect duplicates quarantined for review by the Data Steward

MatchCleanse

DataLoad

IIR

Match Score Calculation

92 82 100 100 70

92 * 8 = 736 82 * 4 = 328 100 * 2 = 200

100 * 2 = 200

70* 2 = 140

736 + 328 + 200 + 200 + 140 = 1604

Weighted Actual

800 + 400 + 200 + 200 + 200 = 1800

Weighted Potential *

= 89.1Weighted Score

Field Pattern Score

Field Weighted

Score

UCM Lower Threshold <= 80

UCM Upper Threshold => 97

Auto LinkCreate New Manual Review

Dan Gilboa 203-56-9820 Hod Hasharon IL 45242

Gilbao Dan 203-56-9802 Hod Hasharon IL 45241

Name SSN City State Zipcode

* Maximum score a field can achieve

Create “Best Version” Process: Merge and survivorship

• Intelligent Merge – create best of breed surviving record by selecting fields from the duplicate records

• Intelligent Update – selectively

update fields for the master record based on confidence rules set for the source of the data

• Automerge duplicates with very high match scores

• Unmerge reverses an erroneous

merge process

Maybe

IIR

Yes

Match

New

Survivorship

Merge

Cleanse

No

Yes

Manual Review

DataLoad

No

Merging by Data Steward (Suspect Match)• For manual review case, a new record will be created with

the “Suspect” (Pending Review) status

• The new record and potential duplicates will be stored in “Existing Duplicates” views for data steward to review later

• The Data Steward can choose to Merge the new record with any of the suspected duplicates or to reject them

• Survivorship decisions can be done by pre-set rules or manually by the steward using “Guided Merge”

Survivorship: Consolidates multiple records into Master

First Mary

Last Smith

Address1 1867 Pierce

Address2 #4

City San Francisco

State CA 94110

Tel. 510-681-1399

ID 117-78-1856

Status Single

Since 1974

First Mary

Last Evans

Address1 1867 Pierce

Address2 #4

City San Francisco

State CA 94110

Tel. 415-437-1790

ID 117-78-1856

Status Divorced

Since 1990

Name Mary

Last Smith

Address1 2333 Harrison

Address2

City Piedmont

State CA 95810

Tel. 415-437-1790

SSN 117-78-1586

Status Divorced

Since 1996

Which last name does Mary use today?

Which address is correct?

Is this her latest phone number?

•The most recent data survives.

Recent

•The oldest data survives.

History

•The data of source system with the highest confidence level survives.

Source

•Indicates the attribute group settings that enable you to configure any supported rules engine to set specific survivorship rules.

External

•The values in Oracle Customer Hub (UCM) will always win over the incoming record

Master

•The values sent by external application into Oracle Customer Hub (UCM) will always win over the values in the existing best version record

Slave

Survivorship Comparison Criteria

© 2009 Oracle Corporation – Proprietary and Confidential

תודה