Golden Rules [Best Practices] to tame the MDM/CDI Beast

Golden Rules [Best Practices] to tame the MDM/CDI Beast
Session# 2666

Mani Kumar Manda
Rhapsody Technologies, Inc.

OAUG Collaborate 2009, Orlando, Florida
Tuesday, May 5, 2009

©2009 Rhapsody Technologies, Inc., All rights reserved.
1
Bringing People, Processes and Technologies together

“Guiding Clients through the lesser known path”

Learning Objectives
As a result of this presentation, you will
•
learn:
Challenges of Customer Data Management
The current state of CDI Technologies
Golden Rules [Best Practices] for MDM/CDI Projects

2

Speaker’s Qualifications
Mr. Mani Kumar Manda had been working with Oracle
Applications for over 15 years and has implemented
Technology Solutions for clients in many industries.
Mr. Manda is also the founder and chair for Customer Data
Management SIG
Mr. Manda is an active and frequent speaker of topics
associated with Customer Data Management
Mr. Manda is the President and Founder of Rhapsody
Technologies, Inc., a consulting firm with specialization in
implementing Customer Master/Customer Hub solutions.

3

About Rhapsody
■ Founded in 1998
■ A niche firm in implementing Master Data Management solutions
■ Offers Customer Data Quality Assessment Services
■ Offers MDM/CDI Strategy/Auditing/Evaluation Services
■ Offers services to build Semantic Customer Model for your organization
■ Offers Onsite Seminars that include Master Data Management,
Customer Data Management, Customer Data Hub, TCA,
Implementation strategies, Customer Data Modeling, etc.
■ Provides half day and one day CDI awareness sessions for C level executives,
functional/departmental heads.
■ Provides a week long training on ‘Functional fundamentals of Customer Data
Management’ covering topics such as challenges of customer data management,
best practices, tasks that need to be considered, TCA and the features of the
Oracle Customer Data Hub product.

4

About Rhapsody
Partial list of our Customers
ADP DoubleClick Motorola

Haworth Hologic KCI

Office Depot Overland Storage Hologic

Partial list of Industries
Retail Advertising Manufacturing

High-Tech Healthcare Services

Some of Our Partners
Oracle Dun & Bradstreet

Trillium Deloitte Consulting

Hub Solution Designs Transitions II

5

Defining MDM for Customer Domain

6

MDM for Customer domain according to Rhapsody is
About establishing the Single Source of Truth, in other words a System
•
of Record that is reliable, available when needed and always maintained.
About cross-referencing the Customer Data across heterogeneous
•
systems to establish a Single View of the Customer
About providing 3600 view of the Customer.
•
About establishing a Data Governance structure for welfare of the
•
Customer Master solution by establishing Roles and Responsibilities;
Policies and Procedures to maintain data quality on an ongoing basis
About defining and maintaining Analytics and Segmentation to drive top
•
line growth (Revenue) and increase bottom-line (Profits) by increasing
the effectivity of various business processes
Increasing the operational excellence across the Enterprise
•

7

What is a 3600 view of the Customer?

8

What is 3600 view of the Customer? Quotes
Orders
Invoices
Receipts
Service
Contracts
“Rather than Installbase
Agreements
Etc.
thinking about the Customer itself,
we need to think
Inte
about the relationship ract
ions
that exists with the Customer,
and that lets us provide
Superior experience.” er
ips
tom
A ttr i
Cus tionsh es
bute
- Mani Kumar Manda s i
a
Rel erarch
Hi
/

Identity Attributes
Name, Address, Education, etc.
Behavioral Attributes
Hobbies
Tech Savvy, Old Timer, etc.
Financial Attributes
Income, Net worth, etc.
Corporate Hierarchies
Classification Attributes
Business specific hierarchies
Industry, Size, etc.
Past relationships
Relationship Attributes
Staff and Family Information
Account Number, Terms, etc.
Affiliation with Professional Associations
Segmentation Attributes
Categorization, etc.

9

Challenges of Customer Data!

10

Nature of Customer Data
Organization Name
1. Legal Name
What’s in a Name?
•
2. Doing Business As (DBA) Name
3. Customer Preferred Name
– Customer Name for Organizations
4. Phonetic Name
5. Former (Previous) Name
– Customer or Contact Name for
Persons
Contact/Person Name
Locations
1. Multiple Parts
•
a. First (Given) Name
b. Middle Name
Contacts
•
c. Last (Sur or Family) Name
d. Name Prefixes
Phones
•
e. Name Suffixes
2. Nick Names
Other
•
3. No Last Names
4. Name changes thru Marriage/Divorce

Locations Contacts Phones Other
1. IM IDs
1. Multiple Locations and Location Uses 1. Area code Changes Hotmail, Yahoo
2. Varying Attributes 1. Come and Go 2. Inter/Intra Office Moves 2. Social Networking
States/Provinces/Prefectures/… 2. Role Changes 3. Multiple Phone Numbers Facebook, Myspace
3. Formatting by Country 3. Inter/Intra Office Moves Home, Mobile-Personal 3. Professional Networking
4. Right Field Wrong Purpose 4. Name Changes Work, Mobile-Work LinkedIn
5. Postal Code variations Fax 4. Blogging IDs
Twitter

11

Short Video

12

Customer Data is Dynamic – Facts
17% of Business Names change in a year (D&B)
•
i.e., 11 companies change their name in next 60 minutes
–
US population will grow to 394 Million by 2050 (Census Bureau)
•
Growth of 2.5 Million each year including 1 Million through immigration
–
During 1995, 2.3 Million Marriages and 1.2 Million divorces took place (Census Bureau)
•
6400 marriages a day
–
3200 divorces a day
–
About 14% of the nation’s population moves every year
•
Generating 45 million address changes (USPS)
–
And 18% of telephone number changes
–
Mail is big business (USPS)
•
Mailing is $900 billion a year
–
Correspondence & transactions — $36 billion
–
Business advertising — $18.9 billion
–
Expedited delivery — $5.5 billion
–
Publications delivery — $2.2 billion
–
Standard package delivery — $2.2 billion
–
International mail — $1.8 billion
–

13

Data Quality - Global Challenges[1]
36+ Personal Name Formats
•
Personal names, company names and job titles differ in terms of order, casing, gender coding and
–
titles etc., by language, country and region.
US
•
First Name, Middle Name(s) (or Initial) and Last Name
–
Last Name followed by First Name with ‘comma’ after the Last Name
–
France
•
LAST NAME (in Upper Case) followed by First Name
–
Japan
•
Given names are not used in business. Family Name + Job Title are used for business correspondence.
–
Mexico
•
First Name, Family Name followed by Mothers family name
–

241 Countries
•
Around 5,000+ languages (dialects)
•
Has specific scripts
–
Writing directions
–
130+ address formats
•
Addresses vary in terms of required content, order, numbering, casing, postboxes and postal
–
coding by language, country and region.
Lack of address validation references in all countries
–
Addresses changes are not available in all countries
–

[1] Various Sources -- Harte-Hanks, OASIS, Merriam Webster’s Guide to International Business Communications

14

Data Quality - Global Challenges …
Other Data formats – dates, time, numbers can be very diverse based on
•
language, country and region
– MM/DD/YY in US until Year 2000 and MM/DD/YYYY after that
– DD/MM/YY in India
– DD-MON-YY or DD-MON-YYYY in Oracle Applications
Cultural Issues
•
Multiple Character Sets
•
Privacy Issues
•
Attitudes to data ownership
•

15

Corporate Asset

“One of the most valuable asset of any
Organization is its customer
information. Everyday millions of
dollars in potential profits are lost at
many organizations due to inability to
provide reliable, accurate, well
maintained and readily available
customer data.”
Mani Kumar Manda

16

Current State of CDI Technologies

17

Current State of CDI Technologies
• The CDI and MDM Technologies are still evolving
• Vendor focus is varied
– Domain specific solutions
– Common platforms for multiple domains of MDM
• Consolidation among Vendors will continue
– Eventually small and niche players gobbled up by large players
• Implementation approaches are still evolving
• Lack of Awareness and Knowledge both at the User level
and Consulting level

18

Oracle’s MDM Foot Print

Supplier
MDM Sites/
Customer Product COA COA
Domains
Customer Locations

Analytical
Operational MDM Applications
MDM Apps

Analytical Hub
Financial Hub
Site Hub
MDM
UCM

CDH

PIM
Apps

Biz Hyperion
Siebel Oracle eBusiness Suite
Apps DRM

19

Golden Rules
[Best Practices]

20

Best Practices – Rhapsody’s “The TWENTY FIVE Golden Rules of CDI©”

1. Executive (CXO) Sponsorship 13. Implementation Approach
14. Data Quality Metrics
2. Data Governance Program
15. Hybrid Project Implementation
3. Stakeholders with Enforcement
Methodology
Authority
16. Go beyond the Identity Data, in
4. Strong Data Stewardship stages
17. Data Profiling
5. Trading Community Model (TCM)
18. Enrich Data
6. Design Considerations
19. Data Standardization
7. Conceptual Customer Model
20. Validate Addresses
8. Canonical Designs
21. Classify, Classify, Classify !!!
9. Define and Enforce Data Security 22. Analytical Use Cases
10. Data Privacy 23. Certify Data
24. Latest Versions
11. Regulatory Compliance
25. Search UI with robust Parameters
12. DPL Compliance

21

1. Executive (CXO) Sponsorship

• To succeed you must have CXO (executive) support for
CDI/CDH initiatives
• Many projects that do not have CXO support or lost support
soon after launching the initiative have failed
• An increasing number of projects are facing challenges
(Reference—Gartner: The Top Seven Trends for Master Data Management in 1Q08)
–

• Not only Securing but ongoing support of Executive is very
important for long term success
• Making a Business Case
– Defining ROI
– Create Upside potential vs. avoid downside Risks

22

2. Data Governance Program
Establishing Data Governance is all about
•
establishing the framework for the
“decision rights” and “accountability” for
the welfare of the data
Data Governance initiative as part of
•
MDM project is a must
You must begin the Data Governance in
•
parallel with other parts off the project
Data Governance program should be
•
designed at the Enterprise level addressing
multiple domains of MDM, not just CDI
Base framework established by the time
•
Analysis phase is done, but no later than
early design phase

23

Data Governance and Data Management
Framework and Structure

EXECUTIVE
EMPOWERMENT
CEO

EXECUTIVE
CM
O CI
CF O Council
O O
CO
CXO(s)

ERP & CRM
Membership

HR & Other
Marketing

Finance
Service
Sales

HR
IT
Data Governance
Council
Impact Analysis Data Security
Change Control Compliance
Data Governance Liaison Data Stewards
Data Management Project Management
Data Management
App. Experts

BI/Analytics
Data Quality

Document-
Functional

Cust. Data

Training
Organization
Experts
Experts

SME’s
SME’s

ation

24

Come
Together

Business

IT

25

3. Stakeholders with Enforcement Authority
• Data Governance Council must have stakeholders that have
enforcement authority
– Otherwise the good decisions that are made by the council get lost
resulting in project failures
• You should include Departmental Heads, Business Unit
Leaders, at least one of key CXO
– Governance council is not the place for some one who does not
have enforcement responsibilities.
– Senior persons with correct background who want to take part or
need to take part in CDI initiative that do not have enforcement
responsibility can be part of Data Steward Team.

26

4. Strong Data Stewardship
• Data Stewardship team is the one facilitating many decisions
associated with data elements related to CDI domain
– What attributes to host in CDI instance?
– What entities should be brought over to CDI?
– What is the phasing approach?
– To what extent standards should be enforced for Source
Applications
– Departmental Politics
• Identify Data Stewards internally
– Provide training to internally recruited Data Stewards

27

MDM – A foundational Application
“he who does not lay
his foundation beforehand,
may by dint of great ability
lay them afterwards,
yet it must be
with the most extreme labour
on the part of the architect and
with the greatest danger
to the building”

taken from
“The Portfolio” - Vol. 7 (1819)

28

5. Trading Community Model (Semantic Model)
A fresh business perspective with an objective to identify the people and
•
the entities and all relationships between them should be done at an early
stage of the CDI project
– The TCM is not based on any application rather it is focused completely on
business
This will facilitate the decision of what people, entities and relationships
•
to host in CDI Instance
Surprise Factor
•
– At several clients, this task revealed surprises:
• Good portion of people, entities and relationships were never captured in any
application in the first place. Of those missing, some are very critical to the
business
• No single person or department has complete view of the Trading community. It
often took interviewing about 100 to 200 people from various business units and
departments to be able to put this portrait (picture) together

29

A sample trading community of a Financial Institution

30

6. Design Considerations

Your
Customers
Business

Design
Considerations

How you
Your Business Intend to do
Business?

31

6. Design Considerations …

1. How does your Customer Operates their business and how are they organized?
Has multiple Branches and Divisions
–
Global Player
–
Number of Business Units
–
Centralized vs. Decentralized
–
2. How do you want to do business with your Customer?
Treat Customer as one Entity vs. each branch or division or business unit as separate
–
entity
At what level of the Customer do you want to track?
–

Answers to Question 1 & 2 determines how many Parties need to be created for
the Customer.

32

3. How is your business organized?
Global vs. Local
–
Number of business units (lines)
–
Profitability and Accountability tracking within the firm
–
How are Sales teams organized?
–

How many accounts gets created is influenced by answers to Q.2 and Q.3

33


4. How much you want the D&B Data to influence?
Model along D&B Data (DUNS Number)
–
Capture customer entities regardless of biz relationship
–
How much to maintain?
–
5. Does Your Legacy System continue to exist?
Do Oracle Customer and Transactional Data need to be interfaced back to Legacy
–
system?
Any other systems need Customer and Transactional Data besides Legacy system?
–

How many parties gets created is also influenced by the answer to Q.4 and
probably by answers to Q.5

34

7. Conceptual Customer Model
• The flexible functionality of a CDI solutions leads into the
ability to create same set of customer data in multiple ways
– For example in Oracle CDH, the TCA allows you to create customer
data in many ways
– If you have a customer with 3 locations
• Option#1 – Site Centric Model – Create One party with 3 locations
• Option#2 – Party Centric Model – Create Three parties with each party
having one location and relate these parties to form a (corporate)
hierarchy
• Option#3 – Some where between Option #1 and Option #2

Customer
Usability
Model

35

Option #1 - Site Centric Model

Widely known as
Old AR model
Release 11 Model

36

Option #2 - Party Centric Model

37

8. Canonical Designs
Adopt an open standard based Canonical
•
Mapping for integrating data between Source
Applications and CDH and CDH and Target
Applications
– Open Applications Group
(http://www.openapplications.org)
The Canonical format should be
•
accommodating needs at enterprise level, not at
departmental or a specific application level
– Global Design with Phased Implementation
If needed, start with a standards based canonical
•
model and customize it further
Some products support open standards
•
– CDH with their Application Integration
Architecture (AIA) and Process Integration
Packs (PIP) leverages OAGIS standards

38

9. Define and Enforce Data Security
• Data security is important for a global CDI solution
• Carefully evaluate users in terms of their access requirements
• Utilize built in security functions of the tool
– Data Sharing and Security (DSS) functionality in CDH
• Make sure to identify all regulatory requirements for data
Security
– Doing otherwise will lead the firm into regulatory nightmare
– Recent Examples
• Lost data
– BNY Mellon Shareowner Services lost Tapes containing SSN data
• Hacks
– TJ Maxx (TJX) pegs data breach tab at $118 Million

39

10. Data Privacy
Data Privacy in a digital age is very important
•
– Pertains to Personally Identifiable Information (PII)
– Laws
• US
– Federal Laws
» Privacy Act of 2005 – Attempts to strictly limit the display, purchase or sale of
PII without the person’s consent
» Anti-Phishing Act of 2005 – To prevent the acquiring of PII through phishing.
» HIPAA – Health Insurance Portability and Accountability Act – Patient
Information
» Social Security Number Protect Act 2005 – Limit the distribution of SSN
» Identity Theft Protect Act 2005 – Limit the distribution of SSN
» Information Protection and Security Act of 2005
» Consumer Privacy Protection Act of 2005
» Wireless 411 Privacy Act
» US ‘Safe Harbor’ Rules (EU Harmonization)
» Title 18 of United States Code, Section 1028d(7)
– State Laws
» California – OPPA – Online Privacy Protection Act of 2003

40

11. Regulatory Compliance
Fair Credit Reporting Act
•
– Regulates the collection, dissemination and use of consumer credit
information
Gramm-Leach-Bliely Act
•
– Requires all financial companies in US to put policies and procedures that
govern the collection, disclosure and protection of consumers non-public
personal information (PII)
HIPAA
•
– Requires all healthcare organizations to use National Provider Identifier
(NPI) in claims submitted to CMS
SOX
•
– The Section 404 of Sarbanes-Oxley Act requires Organizations to take an
active interest in the accuracy, consistency and timeliness of the data
SEC
•
– Requires public companies to report risk exposure for bottom-line and top
line numbers

41

12. DPL Compliance
Denied Party List (aka DPL) is a list of persons and entities with whom no
one should be doing business with.

US
•
– Department of Treasury
Specially Designated Nationals and Blocked Persons (SDN)
•
Narcotics Trafficking Sanctions
•
Anti-Terrorism Sanctions
•
Non-proliferation Sanctions
•
– Bureau of Industry and Security
• Denied Persons List
• The Entities List
– FBI
• Most wanted list
• Issued Watch List
– US Department of State
• Debarred Parties List
• Designated Terrorist Organizations
42

43

13. Implementation Approach
• CDI/CDH – Stand Alone environment CDH
– Decisions can be made independent of
operational system
SOA
– Can apply patches when needed
– Implementation cycle not dependant upon
operational application EBS

• CDI/CDH – Operational eBusiness
Suite (EBS)
– Reduced Licensing Costs
– Inability to apply patches when needed EBS
– Implementation cycle is influenced by CDH
operational needs of other modules
– Modeling impact

44

14. Data Quality Metrics
• No CDI initiative will be fully successful, unless
– Data Quality objectives are set upfront
– The quality of the initial data is measured
– The data can be monitored over a period of time to identify the
increase in data quality
• The project must include the time and resources for defining
Data Quality Metrics, Procedures that facilitate the tracking
of Data Quality Metrics and reporting of improvement in
data quality

45

15. Hybrid Project Implementation Methodology
• Many CDI projects often take years to complete to obtain
the vision of 3600 view, if at all one reaches that destination
• Risk of losing executive and/or user support
• Approach the project with global design but phased
implementation
• Mature the CDI initiative in an incremental manner

46

Project Implementation Approach – Spiral Methodology

Incorporate LL
Requirements
Support
Validation & Prioritization
Evaluate
As-Is Study
Lessons Learned (LL) 4
4 Acceptance Test Plan
Maintain 3 Requirements
Support &
& Analysis
Evaluate 2
2 3
1
1

1 1
2 2

3
3
Implement Design
4
Build/Develop,
4
Unit Test Architecture
Integration Test Design
System Test, UAT, CRP1, 2, …
Training
Production Rollout

47

16. Go beyond Identity Data – In Stages
• Identity data is a must to achieve the single view of the
Customer
– Even then – Bring One source at a time into CDI
• Data for which CDI is also suitable is
– Account Layer
– Industry specific information
• Healthcare
– Hospital information such as specialties, number of beds, physicians, …
– Segmentation
• Make sure that the CDI instance matures over a period of
time in multiple phases

48

Replication of Customer Data

n
tio fo
a
ic In
pl fic
Ap eci
Sp

ip Usually this data is is
sh n f o not replicated
nI
tio t) across applications
la n
R e c ou
c
(A

fo
In
y A good portion of the
tit data is replicated
en
Id across many
applications

Most of this data is
replicated across
applications

49

17. Data Profiling
• Helps in identifying
– The good data that can be brought over to CDI Application
– Bad data that can be ignored or fixed prior to conversion
– Attributes that can be Standardized
– Identify the data that is misrepresented
• Data Profiling is a must do task
– Done prior to Conversion usually during early stages of Analysis
– Done periodically after go-live to monitor the state of data quality
• Invest in a third party tool to facilitate the data profiling
– OWB
– Trillium (a unit of Harte-Hanks)

50

If you think Customer data is bad…..

51

The data profiling reveals …

52

18. Enrich Data
• Data enrichment is often necessary step for many businesses
– D&B data to build corporate hierarchies
• Industry specific content providers
– Healthcare
• Verispan
• Solucient
• Sherlock
• Multiple providers may be needed some times

53

19. Data Standardization
• It is important to standardize the data for better data quality
– Use third party tools for data standardization
– Or build custom routines to standardize the data prior to or as part
of conversion
• Not all tools can help you standardize
– CDH can not standardize the data
– But can standardize the data for identifying duplicates only

54

20. Validate Addresses
• It is critical to validate and standardize the address data to
facilitate better duplicate identification
• Use the Vendor whose solution is pre-integrated with the
tool (For example – Trillium and First Logic for CDH)

55

21. Classify, Classify, Classify !!!
• It is important to identify all classification requirements of all
consuming applications
• Classify data as many ways as important to the business
• Classify at an appropriate level
– Party Level classification is not suitable for Account level entities
• Classification will facilitate the better intelligence of numbers
such as Sales, Receivables, etc.

56

22. Analytical Use Cases
• It is important to take into consideration of requirements (in
other words use cases) of Business Intelligence and Data
warehousing applications, which are downstream
applications to CDI application
• Could be as simple as data that is basis for Segmentation
• May Influence other analytical requirements

57

23. Certify Data
• Provide a means to identify the data that has been reviewed
and validated
• Search results should show the certification status of the data
• Various capabilities in tools
– CDH allows to mark the data with custom defined certification levels
and reasons
– Not all tools have this capability

58

24. Latest Versions
• The overall MDM is still maturing resulting in change in
approaches and functionalities in a product
• The products in this space are rapidly increasing their
functionality as well as fixing bugs
• Must upgrade to a latest Version
– Upgrading to R12 of CDH
– Latest versions provide new capabilities
• Business Object level integration vs. granular integration
• Must also apply all latest patches
– High level of Bugs requiring frequent patch application
– Spend time upfront in identifying patches in the functionality that
you plan to utilize

59

25. Search UI with robust parameters
• Should be able to query based on all key attributes
• Common perception is to provide key identity attributes
• You should also provide the ability to search based on
Source System References
• Ability to filter the result set by source systems
• Role based Search Parameters

60

CDM SIG – To Become a Member

Do one of
• You can join CDM SIG from OAUG site at http://www.oaug.com

Send a blank email to cdmsig-subscribe@yahoogroups.com
•
Go to CDMSIG Yahoo group at http://groups.yahoo.com/group/cdmsig
•
and click on ‘Join this Group’:
Or send an email to mmanda@rhaptech.com expressing your interest in
•
becoming CDMSIG member.

You will receive membership application in reply. Upon sending the completed
form to mmanda@rhaptech.com, your membership will be enabled.

Members can post their questions, comments, etc., by sending an email to
•
cdmsig@yahoogroups.com. You will have to become member in order to
post to this forum.
61

oy

62

Crystal Ball (5 to 10 years down the line)
The value of data will be treated as an Asset on the balance sheet
•
(Accounting Wise)
Data Governance will become mandatory (Regulatory perspective)
•
Reporting on data quality metrics becomes a necessary KPI in
•
financial statements
CXO’s held responsible for data quality
•
– lax in quality could become a punishable offense
CGO – Creation of a Chief Governance Officer as an executive level
•
position with CGO possibly reporting to CEO/CIO
CPO – Chief Privacy Officer possibly reporting to CGO
•
– This role exists in some web-centric organizations
IT will be looked upon as a key enabler in meeting above
•
requirements

63

QUESTIONS
ANSWERS

64

Q Session# 2666
& QUESTIONS

A ANSWERS

Can be reached at: Mani Kumar Manda
Rhapsody Technologies, Inc.
1700 Park Street, Suite 205
Naperville IL 60563

Phone: 630-717-1809
Email: MManda@RhapTech.com

Special Interest Groups:
http://cdmsig.oaug.org
http://groups.yahoo.com/group/cdmsig
http://groups.yahoo.com/group/ucmsig
http://groups.yahoo.com/group/cdi-mdm-jobs
Latest Versions can be obtained from:
http://www.rhaptech.com/resources.html

65

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