Yusuf AliIntegration Specialist ATS EMEA

SFDC CRMadoption as a

CDI/MDM Source

Agenda

• Master Data Management (MDM) at a glance– What is it?

– What problem does it solve?

– What are the business drivers that justify MDM investments?

– What are the technical requirements?

• Salesforce SFA for Customer Master Data

• Resources & Groups

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Master Data Management(MDM)

at a glance

What is Master Data Management?Gartner Forrester Wikipedia

Master data is the consistent and uniform set of identifiers and extended attributes that describe the core entities of the enterprise — and are used across multiple business processes.

Some examples of core entities are: parties (customers, prospects, people, citizens, employees, vendors, suppliers or trading partners), places (locations, offices, regional alignments or geographies) and things (accounts, assets, policies, products or services).

Groupings of master data include: organizational hierarchies, sales territories, product roll-ups, pricing lists, customer segmentations, preferred suppliers and so forth.

Master data management (MDM) is a business capability enabled through the alignment of multiple information management technologies, business process improvements, and organizational commitments.

MDM is much more than a single technology solution; it requires an ecosystem of technologies to allow the creation, management, and distribution of high-quality master data throughout the organization.

Master data management (MDM) comprises a set of processes and tools that consistently defines and manages the non-transactional data entities of an organization (also called reference data).

MDM has the objective of providing processes for collecting, aggregating, matching, consolidating, quality-assuring, persisting and distributing such data throughout an organization to ensure consistency and control in the ongoing maintenance and application use of this information.

The Information ChallengeHow to Synthesize and Govern Data Across Silos and Providers?

Application LegacyCloud Computing Unstructured

CUSTOMER PRODUCT

CUSTOMER LOCATION

Third Party Data

ORDER LOCATION

ORDER PRODUCT

CUSTOMER PRODUCT

CUSTOMER LOCATION

ORDER ORDER

LOCATION PRODUCT

Manufacturing & Inventory

Mgmt

Vendor & MaterialsManagement

Order & ChannelManagement

Sales & MktgOperations

EmployeeManagement

DataGovernance

?No Single Version of the Truth

No Single Version of the Truth

No Single Version of the TruthImpedes Key Business Imperatives

Application LegacyCloud Computing Unstructured

CUSTOMER PRODUCT

CUSTOMER LOCATION

Third Party Data

ORDER LOCATION

ORDER PRODUCT

CUSTOMER PRODUCT

CUSTOMER LOCATION

ORDER ORDER

LOCATION PRODUCT

Manufacturing & Inventory

Mgmt

Vendor & MaterialsManagement

Order & ChannelManagement

Sales & MktgOperations

EmployeeManagement

Improving Efficiency & Reduce

Costs

Acquiring & Retaining

Customers

GovernanceRisk

Compliance

MergersAcquisitions

& Divestitures

Improving Decisions

Impedes Key Business Imperatives…

Governance, Risk, Compliance Pressures

SOX and Basel II require firms to provide transparency and auditability in their financial reporting.Inconsistent and unreliable data impedes compliance efforts resulting in steep financial penalties and negative market perceptions, not to mention potential jail time for corporate officers.

Difficulty Acquiring & Retaining Customers

Inability to Increase Profitability: Profits drained when high-cost services are delivered to low profit customers. Profitable customer loyalty jeopardized when high value customers receive low end service

Inability to Increase Revenue: Revenue lost and customer loyalty jeopardized when you make the wrong offer.

Business Drivers forData Governance and Master Data Management

Increase cross sale and up sale success

Improve customer loyalty, reduce attrition/churn

Reduce marketing costs

Solicit greater campaign demand

Create “right” products for “right” customers

Increase sales

Increase Revenue

& Marketing Efficiency $

Reduce account setup time and remove incorrect & duplicate data entry

Improve customer service wait time

Provide consolidated statements

Single opt in – opt out preferences

Improve Customer Communications

(Risk managementAccurate books &

recordsCompliance with

AML & KYC regulations

Compliance with corporate standards and policies

Avoid regulatory fines and penalties

Mitigate Risk & Fraud

Provide accurate

& consistent customer information through all channels at all touch points

Reduce customer acquisition and account setup costs

Streamline territory management

Identify and eliminate commission payment overlap

Streamline Operations

*

Business value drives requirements and pace of adoptionYour architecture should support incremental value over time with a

long term view towards of the future enterprise data architecture

But wait a minute…

Don’t I already do this in my data warehouse?

Let’s take a look at what many do today

ERP-1 ERP-2 CRM Web Other

Data Mart

Load dimensional data and fact data into a data mart

• Cleanse it along the way• De-duplicate records• Organize into groups and hierarchies

And they do it for every data mart

ERP-1 ERP-2 CRM Web Other

Data Mart Data MartData Mart . . .

And what about the operational systems?

How do they share common data about customers and products?

Centralize Master Data

ERP-1 ERP-2 CRM Web Other

Data Mart Data MartData Mart . . .

MDM Hub

Centrally manage:• Reference data• Cross References to accounts

& transactions• Groupings and Hierarchies• Make data available to analytical

systems AND operational systems

The High Level Requirements for MDM

Complete Platform for MDM and Data

Governance

MDM Hub

Data Quality

Integration

MD

M M

atu

rity

What goes into a MDM Hub?

Reference Data

Cross References

Name, Address, etc

Account 1

Account 2

Account n

Hierarchies

Hub Requirements Reference Data and Cross References

Global ID First Name Last Name DOB Address

Reference Data

Global ID System Name System ID

Cross References

92882983 Christopher Vandersmidt07/21/1950124 Elm Street, Erie PA

92882983 CRM 90018

92882983 Billing PO-38989

92882983 Billing PO-54681

92882983 Web cv_erie108

92882983 Credit Agency 883125-AX

• Reference data is only good if it’s accurate, complete, and consistent

• Data Quality tools are needed to ensure you are meeting this requirement

• To ensure that you have the correct cross references and the complete set of cross references, you will need Identity Matching capabilities

Hub Requirements: Relationships and Hierarchies

Spouse Spouse

Child 1 Child 2

Household

Product

Component 1

Component 2

Component 3

Component 4

Bill of Materials

Global Parent

Subsidiary

Division Division

Subsidiary

Division Division

Corporate Structure

Colleague

Colleague

ColleagueColleague

Colleague

Social Networks

Knows

Worksfor

Owns

Produces

Requirements

Access

Profiling

Transformation

Cleansing

Data Model

Identity Resolution

Data Stewardship

Hierarchy Management

Synchronization

Requirements

Access X X X X

Profiling X X X X

Transformation X X X X

Cleansing X Done at sources X Data is authored in hub

Data Model X Limited X X

Identity Resolution

X X X Data is authored in hub

Data Stewardship

X X X Data is authored in hub

Hierarchy Management

X Sometimes X X

Synchronization Only feeds BI/DW X Only unique ID’s

Various MDM Hub StylesCo-Existence

StyleCentralized

StyleConsolidation

Style

Consolidates data to be fed into data

warehouse

RegistryStyle

Creates an index of places where an

individual product or customer

appears

Consolidates and synchronizes data from multiple source systems into a “composite” record

Becomes the single source of master

reference data. All other systems adopt

Hub

Typical MDM Implementation Lifecycle

Profile and Prioritize

• Quality Profiling

• Establish Data Quality Metrics

• Establish Business Metrics

• Prioritize data entities and processes

Migrate Data

• Define MDM Data Model

• Identify Source Data & Gaps

• Identify Reference Codes

• Transform and Load (Batch & Real-time)

Create Composite Record

• Cleanse Data• Define

Scorecard• Define

matching rules

• Merge records• Relate master

data entities

Provision Master Data

• Capture Data Changes

• Create Data Services

• Synchronize using proper modality

• Orchestrate data management processes

Expand to includemore source and target systems, data entities, and data attributes

Data Governance Principles

Enterprise Data Access &Delivery

Identity Management

Data Transformation

Master RecordComposition

Data Models &Management

Data Analysis & Profiling

Relationship & Hierarchy Management

MDM Data Flow and Functional Lifecycle

Data Correction & Cleansing

ERP

Operational Systems and 3rd party Data

CRM

Metadata Management

Typical MDM Logical Architecture

Dat

a A

cces

s

| D

ata

Syn

chro

niz

atio

n

|

Dat

a Tr

ansf

orm

atio

n

MDM Data Sources

Orchestration | Human Workflow

Metadata Management

Dat

a P

ub

lish

ing

|

Web

Ser

vice

s |

D

ata

Del

iver

y

Customer FacingApplications

eCommerce

Campaign Management

Customer Portal

Data Profiling

Data Cleansing

Hierarchy Management

Role Based Security

Master Data Hub

Data Modeling

Master Record Composition

Data Steward Interface

Identity Resolution

OtherApplications

Upstream Applications

Downstream Applications

SFDC SFA for

Customer Master Data

Salesforce SFAAdoption for Customer Data Integration (CDI) / MDM

• Which Style(s)– Registry (Optimal)– Centralised (need to address bi-directional synchronisation)

• Which Master Domain(s)– Customer (Corporate / Individuals)

• Salesforce Objects: Accounts, Contacts, Vendors, Employee (?HR?) – Products (may not be a good fit)

• Salesforce Objects: Products

• Which Industry Verticals– Financial :- Client-on-boarding, Agent/Broker Management, Contacts, etc.

– Insurance :- Policy Management, Wealth Management, etc.– Retail & CPG :- Product Introduction, Brand Management, etc.

• Architecture/Process Flow– Technology :- Access (Loaders), Data Quality, SFDC SFA,…– People :- Data Stewards, Data Governors and Analysts– Methodology :- Data Management/CDI Best Practises

EDW

ERP

BILLING

Salesforce SFA CDI HubRegistry Style

SFDC ID First Name Last Name

111 John Smith

SFDCID

SourceSystem

External ID

111 CRM 929992

111 ERP AKK-111

111 Legacy 098388188

Primary Key First Name Last Name

929992 John Smith

Primary Key

First Name Last Name

AKK-111 Johnson Smith

Primary Key

Full Name

098388188

John Smith

Master Domain Registry

• Registry’s Cross-Reference using the External-ID link to source system;

• Leverage Jigsaw for maintaining data quality thresholds;

• Provide Customer Master Data to external sources via WS APIs.

Customer

Billing

Customer

ERP

Salesforce SFA CDI HubArchitecture/Process Flow

Customer

EDW

Orchestration / Workflow

Master Customer Modeling

Customer

Master Hub

Role Based Security

AnalyticsReporting / Dashboards

Load

Sync

Data Steward / Data Governance Principles

Data

In

teg

rati

on

/ Q

uality

/

Syn

ch

ron

izati

on

In

terf

ace

Relationships & Hierarchies ??

Matching??

Customer Master Management Methodology / Best Practices

Usages

Registry• Customer Search• Account Lookup• Single View of Customer

Analytical• Business Intelligence• Key Performance Indicators (KPIs) via

Dashboards

Centralized MDM Hub• Introduction of new Customer/Product • Source of truth• Common master data for entire application

suite

Resources&

Chatter Groups

More Information

• Resources– MDM Resource Guide - http://www.mdmsource.com/

– MDM Book - http://mdmbook.com/