This document summarizes Perficient's capabilities in providing master data management (MDM) solutions for financial services clients. Perficient has expertise in implementing MDM to create a unified customer view across systems and business units. Key benefits of MDM include improved customer experience, increased revenue opportunities, and reduced costs. The document also discusses current industry trends like social media, mobility, and big data that are driving greater need for MDM.

1. Create a „Customer 360‟ with MDM in
Financial Services
February 26, 2013

2. About Perficient
Perficient is a leading information technology consulting firm serving clients
throughout North America.
We help clients implement business-driven technology solutions that integrate
business processes, improve worker productivity, increase customer loyalty and create
a more agile enterprise to better respond to new business opportunities.

3. What We Bring to Our Clients
Industry-leading solution & Collaborative Approach
technology expertise • Work with our clients, adapting to
• ~2000 experienced colleagues their cultures
• Dedicated solution practices • Education and mentoring services
• Partnerships and certifications in
premier technologies Superior Service and Value
• Local client service teams
Disciplined project execution • Flexible resource and fee
• Highly experienced project managers arrangements
• Perficient’s Enable™ methodology • Delivery track record
based on best practices
Commitment and Quality
Innovative approaches and IP Assurance
• Perficient’s user-centered design • Track record of 2000 engagements
approach with 800+ clients
• Application migration methodology • ~85% of clients bring us back
• Quick Start Rulebook™ for Enterprise • Strong client references
Integration

4. Our Solutions Expertise
Business Solutions Technology Solutions
• Business Intelligence • Business Integration/SOA
• Business Process Management • Cloud Services
• Customer Experience and CRM • Commerce
• Enterprise Performance Management • Content Management
• Enterprise Resource Planning • Custom Application Development
• Experience Design (XD) • Education
• Management Consulting • Information Management
• Mobile Platforms
• Platform Integration
• Portal & Social

5. Financial Services Expertise
5

6. Our Speakers
Mike Panzarella, Director, Financial Services Practice
With 20 years of experience with Big Four consulting and
commercial banking, Mike has expertise in BI/DW platform
architectures for Fortune 100 financial service firms with a focus on
social media and mobile convergence. Mike also has extensive
experience in designing and implementing Big Data solutions for
Fortune 100 companies.
Ben Leeson, Data Governance Architect
Ben has over 10 years of Governance and IT leadership experience
with Fortune 50 Financial Services companies. Ben’s areas of focus
are in Data Governance, Data Stewardship, Data Quality, Data
Sourcing and Data Strategy. He has experience driving enterprise
level data management programs that span each line of business
and corporate banking functions.

7. What We Will Cover
2013
About Us Defining MDM Tr e n d s
Challenges Data Governance
Leverage IT
U n l o c k i n g B u s i n en v e Vamu e t s
I ss st l en Q & A

8. MDM Overview

9. What is Master Data Management?
Master Data Management (MDM)
comprises of a set of
processes, governance, policies, standar
ds and tools that consistently defines
and manages the master data of an
organization.

10. What is Master Data Management?
• Disciplines, technologies, and processes that accommodate, control
and manage master data across the organization
• A means to manage and deliver a unified view of an organization’s data
SOURCE SYSTEMS MASTER DATA ENTERPRISE
MANAGEMENT APPLICATIONS
CRM
Name: B. Jones INFORMATION
Address: 35 West 15th Street Sales
Address: Toledo, OH 12345 First: Bill
Last: Jones
ERP
Name: William Jones Address: 35 West 15th Street
Address: 35 West 15th St. Customer
City: Toledo
Address: Toledo, OH 12345 Support
State/Zip: OH / 12345
Legacy
Gender: M
Name: Billie Jones
Address: 36 West 15th St. Age: 30 Claims
Address: Toledo, OH 12345
DOB: 1/1/81
Master Data Management Needs Governance to Succeed
10

11. MDM Business Drivers
Strategic Initiative
•Consolidate data from silos/integrate new systems quickly
•Meet demands of new business channels
•Grow with the business
•Identify key relationships and hierarchies
Revenue
•Identify cross-sell, up-sell opportunities
•Customize product offerings and bundles
•Introduce new products quickly
•Identify high-value customers
•Improve customer retention
Cost
•Automate manual business processes
•Reduce data errors
•Eliminate excess mailings
•Identify credit risk
•Support system consolidation initiatives
Compliance
•Automate manual business processes
•Reduce data errors
•Eliminate excess mailings
•Identify risk (credit)
•Support system consolidation initiatives
11

12. I n d u s t r y Tr e n d s

13. Trend: Gartner‟s Nexus of Forces
The Nexus of Forces (mobility, social networks, information and cloud services) is accelerating
the pace and granularity of interconnected markets at a faster rate than ever.
Banks
Employees
and Customers
Social Corporate
Networks Data
Email, IM Retail and
Banking
End Transactions
Customers
Applications
Retail Stores
Source: Gartner (Jan. 2013) 13

14. Trend: Embracing Social
What is “Social MDM”?
• Increased social awareness in banking
• Need for social collaboration
• Evolution of CRM system and use of sensor data
• New systems of engagement = more data silos
• Data quality is increasingly important
• Pending regulatory standards (FFIEC)
• Golden Record vs. Golden Profile

15. Trend: Digital Disruption
• Investment in mobile innovations
• Create a seamless customer
cross-channel experience
• Validating data Geolocation data
• Data quality known issue
• Manage privacy issues
• Compliance
“GoBank” mobile account
from Green Dot
15

16. Trend: The Big Data Ecosystem
• Better processing and management of
Big Data
• Enhanced metadata and social
analytic preprocessing
16

17. Trend: MDM in the Cloud
• Proliferation of cloud based
solutions
• New entrants into marketplace
• Value-added services and solutions
for “social listening”
• Commoditization of data
• Data is data is data
• Cost of pulling data in
• Regulatory compliance standards
17

18. Trend: Creating a „Customer 360‟ View

19. MDM Challenges
• Sponsorship at the enterprise level
• Data hoarding & mistrust of data centralization
• Addition of business process alignment
• Continued customer data integration
• Introduction of external/new data sources
• SOA and SLO compliance
• Scalability of architecture

20. Data Governance
20

21. MDM Questions to Ask
• What is the Data Strategy?
Strategy • How does it support the business strategy?
• How is data utilized in the fulfillment of business processes?
• Does poor data quality impact the company functions?
Quality • Is data cleansing simply assumed as part of doing business?
• How can data better serve the business? (i.e. Analytics, Operations)
Value
• Does the company have the skills to fulfill the data strategy?
Resources
• Who is pushing funding for the data solution(s)?
Funding
• What is the current and future architecture of the company?
Arch.
21

22. What is Enterprise Data?
Types of Enterprise Data
Entity Data
Master Data is a subset
(Something exists)
Transactional Data Analytical Data
(Something happened) (data for enabling future action)
22

23. What is Enterprise Data?
Another View
Govern the Data
Contribute
Data Data Master Enable Deliver Data
Providers Quality Data Sharing Consumers
Update
Enrich
23

24. Audiences for MDM
MDM, especially the customer domain, requires business input.
It’s important to know your audience when implementing a MDM solution.
The terms may change but the concepts are similar.
Business Perspective: Technology Perspective:
data flow, data supply data lineage, metadata, system
chain, data producer, data of record, source system, and
supplier, and business process integration
Data Environment Master Data Data Consumers
Management
Support
Ops
Sales
24

25. Impacts of Changes to Data
Data Data profiling & data
Originator cleansing – now a hop
Q
(Upstream) or more removed from
the source: telephone
game
Data
Provider
B
Transformations to fit the
schema of the new
system: e.g. changing the Data
format of date Consumer
H (Downstream)
Data lineage management enables systems to account for the downstream
impacts of a change to the data.
The change can appear to be relatively benign like cleaning up data, to the more
intentional like changing the context of a business element.
If Data Provider B changes the format of a data element the downstream systems
need to be aware of the change and adjust their code to account for it. Data Provider B
is responsible for communicating to their Data Consumers the changes.
25

26. Data Governance Focus Areas
Identify Associated Business Processes
Develop the Analyst Community: Who are they? What are their Requirements?
People & Process
Share ideas, best practices, common resources, communication channels
Standardize the Common Business Language: Project Delivery Process:
Business glossary, information domains, conceptual data Gather data requirements early in the
models process
Stand up a Governance Structure:
Executive Support and SME Participation
Create & maintain routines, policies, standards, review processes (exceptions), and communications
Define Data Governance Roles and Responsibilities:
Data management executive, data stewards, data custodians, information architects, analysts, SAs, and more
Establish Master Data and Data Provisioning Management:
Determine authoritative data sources are and the process for attaining data from them
Technology
Data Metadata Data Quality
Integration/Movement Management Management
Technical & Data Quality
Operational Standards &
Metadata Measures
Data management tools are unified and the platform is maximized 26

27. Data Governance Primary Roles
To weave sustainable data governance into the fabric of the
company, executive level participation must occur in the administrative
component
Data Governance Administrator Data Steward Data Custodian
(Formal Oversight) (Business Requirements) (Technical Requirements)
Direction Business Strategy Data Integration
Scope Business Terms Objective Data Quality
Prioritization Data Standards Data Modeling
Governance Structure Business Rules Metadata Management
Organizational Alignment Business Process Data Lineage
Policy Definition Subjective Data Quality Work Flow Management
Issue Resolution Data Analytics Data Security
Roles and Responsibilities Identify Opportunities
Authority and Accountability Identify Risk
Funding
Education
Communication
Enable Data Management Manage the Data
27

28. Unlocking Business Value

29. Enterprise Risk Management
Alignment of Risk Model:
• Reputational
• Operational
• Regulatory & Compliance

30. Solution Architecture
Mobile Web CRM
Business Applications
ESB
Data Warehouse/Data Mart
ETL/ELT
Legacy
Social
Files EDW
Systems

31. The “Golden Social Profile”
Social Profiles Customer Service/LOB
MDM Hub
Targeted Marketing
Bank Source
Systems
31

32. Questions?
32

33. Come See Us at Bank Innovation!
Perficient.com/BankInnovation
33

34. Connect with Perficient
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