MDM - The Key to Successful Customer Experience Managment

Copyright © 2015 Earley Information Science1
MDM - The Key to
Successful Customer
Experience Management
Copyright © 2015 Earley Information Science
Tim Barnes
Dave Zwicker
Earley Information Science
Foundations for
Successful Digital
Transformation
Click to view a recording
of this webinar

Today’s Agenda
• Welcome & Housekeeping
– Session duration & questions
– Session recording & materials
– Take the survey!
• Introduction
– Dave Zwicker, CMO (@davezwicker)
• MDM – The Key to Successful
Customer Experience Management
– Tim Barnes, Director, Professional Services,
• https://www.linkedin.com/in/timothybarnes
• Questions & Answers

Requirements for a trusted 360-degree view of the customer to
enhance the customer experience (CX) are forcing information
leaders to initiate or expand master data management (MDM)
programs at an increasingly rapid pace.
[Gartner]
MDM and the Customer Experience…

Customer Experience – Why Companies Care
Better customer insights lead to better business outcomes:
• Sustained growth in customer acquisition
• Increases in revenue per customer
• Decreases customer acquisition cost
• Reductions in customer churn
• Enhancements to product offerings
Research findings from Gartner:
• 89% of companies will compete based on customer experience by 2016
• 65% have the equivalent of a chief customer officer (office of the CCO)
• 18% of marketing budgets in 2014 were spent on customer experience
• Customer experience is the top innovation project for 2015

Personalized
promotions
Seamless multi-
channel transactions
Streamlined
customer service
BUSINESS OUTCOMES
Product & service
innovation
BUSINESS OUTCOMES
Increased
customer value
Optimized pricing,
availability & delivery
Contextualized
cross-sell/upsell
Higher
Conversions
Improved
loyalty & retention
Reduced
acquisition cost
Personal
data
Big Data
sources
DATA SOURCES DATA SOURCES
Market
data
Product
data (PIM)
Purchase
history
Customer
data (CRM)
Operational
data (ERP)
Clickstream
data
Service
history
Data
warehouse
360° View of the Customer Experience
Customer Lifecycle by Forrester
VOC & loyalty
programs
Online
support
Social
Networks
Site search
& navigation
Mobile
commerce
Email
Promotions
TOUCHPOINTS
Internet
search
Advertising
Online/in-store
merchandising
Warranty &
registration
Call center
agents

By 2020, 75% of those organizations that neglect
MDM and EIM while creating a 360-degree view of
their customers to support the CX will adversely
affect CX metrics via the use of inaccurate data
during customer interactions.
[Gartner]
MDM and the Customer Experience…

Overcoming the Challenges

Tim Barnes
• Over 25 years experience in consulting, corporate IT and corporate
Finance.
• Consulted for Fortune 500 clients in the areas of strategy, working capital
management and MDM.
• Managed several large, complex MDM implementations
Director, Professional
Services
Earley Information
Science
SPECIALTIES
• Master Data Management
• Business Intelligence
• Customer Data Integration
• Working Capital Management
INDUSTRIES
• Insurance
• Business Services
• Telecommunications
• Travel

• Overcoming the Process Challenges
– Business alignment & process enablement
– Dataflow and workflow for master data
MDM Challenges: Two Sides of the Same Coin
Process
Data
• Overcoming the Data Challenges
– Data integration
– Data quality
– Data governance

The Data Integration Challenge
Order
Management
ERP CRM
Sales
Automation
eCommerce
Data Data Data Data Data
Customer
Location
Contract
Customer
Interactions
Contacts
Account Customer
Personas
Product
Product Contact
Info
Customer
Orders
Product
Location
Customer
Prospect
Contacts

The Data Quality Challenge
Data compiled by Talend

The Data Governance Challenge
• Set up your governance
framework
• Start small and build up
capabilities
• MDM areas of focus
– Data Architecture
– Data Quality Management
– Match/Merge Data Stewardship

Bridging the
divide between
IT practitioners
and business
stakeholders
The Business Process Challenge
IT cares about:
• Data quality (de-duping)
• Standardizing/centralizing data
• Data governance and compliance
• Data integration/synchronization
• Meeting operational SLAs
Business cares about:
• Revenue value of a customer
• Campaign response rates
• Cross-channel customer experiences
• Customer support success
• Customer loyalty and retention

• Identify producers, consumers
and owners
• Map the data workflow to identify
transformations and process
gaps
• Determine how the data is used
The Data Flow and Workflow Challenge
Business Intelligence
Operational Integration
Master
Data
Read/Write
Application
Read/Write
Application
Read/Write
Application
Read-Only
Application
Read-Only
Application
Read-Only
Application
MDM
Administration
MDM
Governance

Implementing MDM - A Systematic Approach

• Do you need an Operational or Analytical Customer Hub? Or both?
• Have you identified the producers, consumers and owners of the data
and how the users will access it?
• Have you identified the data sources?
• Have you determined which data sources should be mastered?
• Have you identified the Hierarchies, Relationships and Groupings that
need to be captured?
• Have you created an implementation plan that will bring business
benefit quickly?
• Do you have a framework for the data governance that’s required to
maintain a customer hub?
Have you answered these questions?

Total Organizational Project Governance
Program objective & success
criteria
Business case and charter
Assess current state
Identify data stakeholders
(Producers, Consumers and
Owners)
Develop implementation plan
Understand current maturity
state of data quality
Define future state and
roadmap
Build use cases
Software selection
Identify source systems
MDM functional requirements
Identify data elements
Identify match criteria
Perform data assessment
Determine data cleansing
and standardization rules
Identify hierarchies,
relationships and groupings
BI functional requirements
Identify consuming systems
Identify and prioritize
customer 360 components
Reporting & analytical
requirements
Logical data model
Analysis & Design
High level design
Detailed design
Data source extract
ETL
MDM hub configuration
Publish & integration
Physical data model
Development and unit testing
Match tuning
Testing
Integration
System (QA)
Performance
Knowledge transfer
System support
Prioritized rollout
Staggered implementation
Release management and
deployment
Assess
Define
Requirements
Design & Build Deploy
Program Manager
Information Architect
and Business
Analyst
Development
Architects & Team
(ETL, MDM,
Integration, BI)
Test Lead and
Testers
Roles
Phases
Business
Stakeholders
Provide strategic direction Provide functional
requirements
Assist w/ match tuning
Perform user acceptance
testing

Staged Implementation
Design & Build – Stage 1
MDM
Source Systems
• Order Mgmt
• ERP
BI
360 Components
• Demographic
• Financial
Deploy
Integration
Operational Systems
• eCommerce
• ERP
Assess Define Requirements
Business Objective
Operational Hub
Analytical Hub
Source System Prioritization
Good data quality
High utilization
Clear ownership
Easily integrated
Most trusted
BI Prioritization
Biggest business benefit
Low complexity
High utilization
Design & Build – Stage 2
MDM
Source Systems
• CRM
• Sales Automation
BI
360 Components
• Product Usage
• VOTC
Deploy
Integration
Operational Systems
• CRM
• Sales Automation
MDM
Source Systems
• eCommerce
BI
360 Components
• Third Party
• Predictive
Integration
Operational Systems
• Order Mgmt
Design & Build – Stage 3 Deploy
The determination of the business objective and prioritization of source systems will provide guidance for
a staged implementation to realize business value early and often

Summary of MDM Best Practices

Summary of MDM Best Practices
• Establish the business value that
an MDM initiative will enable
• Keep the focus on the data and
how the quality impacts match and
merge processes
• Create a ‘data governance’ track
concurrent to the MDM road map
• Focus on the day-to-day business
scenarios, not the exceptions
• Keep the MDM data lightweight
• Keep data transformations simple
• Don’t underestimate the time and
resources needed for the match
tuning process
• Emphasize finalizing and creating
the customer logical data model
• Understand the source system(s)

Customer Examples

Large Insurance Company | MDM Implementation
insurance
Business Challenge
• Policy centric legacy systems
resulted in customer information
across policies.
• Customer information unreliable
– no mechanism to identify
customer’s across policies.
• Underwriting was manually
creating a 360 degree view of
the customer
Solution
• Match and merge customer
information from three legacy
source systems to create
customer master records.
• Create households as well as
party-to-party relationships.
• Build a custom user interface to
expose data from the customer
hub and integrate the master
data to the legacy policy
administration systems.
• Integrate the customer master
data with marketing and
actuarial data
Outcome
• Underwriters able to reduce
underwriting time drastically
with the ability to view a
customer, their policies, their
household and relationships to
other customers.
• Marketing has a clear view of
the customer and is better able
to segment customers

Large B2B Service Company | Customer 360 Implementation
B2B
Business Challenge
• Five million small, mid and large
customer records with duplication
due to acquisitions and the
legacy system setup of one
customer per service sold.
• Multiple invoices were sent and
Accounts Receivable phone calls
made to the same customer
• Customers viewed the company
as separate business units
selling different products.
• Multiple business units were
selling to the same customer in
different locations.
Solution
• Implement a customer hub by
implementing MDM software and
matching and merging customer
data
• Add third party data sources to
the customer hub (D&B and
InfoUSA) to obtain the corporate
hierarchy of the client.
• Build data marts for revenue,
survey, billing, product and
prospects
• Layer a BI tool on top of the data
marts to provide a 360 degree
view of the customer
Outcome
• A new tool was rolled out to
sales, service, marketing and
executives to provide a 360
degree view of the customer
• Sales was able to visualize
where in the customer’s
hierarchy they were selling
enabling upsell opportunities
• Enabled predictive analytics for
next most likely purchase by
preparing better quality data
• Provided sales executives with a
“cheat sheet” of a customer prior
to a meeting

Large B2B and B2C Car Rental | Customer 360 Implementation
B2C/B2BCarRental
Business Challenge
• 50 million B2B and B2C
customers, with multiple
brands sharing customers
• No method to link customer
data across brands creating
duplicate customer data.
• No way to market across
brands or personalize their
experience online
Solution
• Integrate customer data
from the legacy customer
system, Salesforce.com
and the data warehouse
creating a customer hub.
• Provide a mechanism for
the website to consume the
customer data using web
services.
• Build a user interface for
customer service and
executives.
• Enable online marketing.
Outcome
• Marketing was able to
personalize the customer’s
online experience by
offering targeted ads based
on their purchases across
brands.
• Internal users were able to
quickly and easily view
details of a customer’s
buying habits.
• Customer segments were
created based on the
customer’s buying patterns

Your Question and Answers

Earley Information Science helps
organizations establish a strong
information architecture and content
management foundation
Realize your digital transformation
vision with EIS.
Earley Information Science (EIS)
Information Architects for the Digital Age
Founded – 1994
Headquarters – Boston, MA
www.earley.com
For more info contact:
Dave.Zwicker@earley.com

MDM - The Key to Successful Customer Experience Managment

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