Master Data Management -...
Transcript of Master Data Management -...
Andy Hayler
CEO, The Information Difference
June 3, 2009
Master Data Management: Avoiding the Potholes
Speakers
Andy Hayler
CEO,
The Information Difference
Michael DesteinSolutions Marketing Director,
MDM,
Informatica
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Master Data Management: Avoiding the Potholes
Andy HaylerCEO, The Information Difference
© The Information Difference Ltd 2009
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Agenda
• What is Master Data Management (MDM) ?
• The business case for an MDM program
• From the trenches: MDM in action
• MDM potholes
• Benefits that can be achieved
• Lessons
© The Information Difference Ltd 2009
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What Is Master Data?
Data that is shared between computer systems
Examples: product, customer, asset, location,...
Master Data Management is the process of managing master data from an enterprise viewpoint
It is not just a technology. MDM includes the data governance structures and processes to support the lifecycle of master data
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Locations
CDI & PIM & MDM
Products (PIM)
Customers (CDI) Suppliers
Business lines
Materials
Assets
Brands SKUs
Channels
RegionsDepartments
Employee Classes
Units of Measurement
Product Groups
Branches
Currencies
Others
Organisations
Reference
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How Many Systems Generate Master Data?
Source: 2008 Information Difference Survey (115 large companies took part)
Overall # of Systems
Generating Customer data?
Generating Product Data?
Median Over 100? Highest
15
6
9
13% 2,000
13%
11%
300
768
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• Partial views scattered across enterprise
> In applications, data warehouses—even spreadsheets, etc.
• Inconsistent formats, codes, definitions
• Slow to reflect market consolidation, reorganizations, and
other business changes
• Data changes are uncontrolled—often made redundantly and
inaccurately
Why is Master Data Management So Difficult?
CRMMasterData
PartnerMasterData
SCMMasterData
ERP
ERPDW
MasterData
DWMasterData
Product
Brand
BrandSub Group
• Size
Product Usage
Target Industry
Product
Segment
Catalog
Line Item
Finished Product
• Height
• Length
• Width
Product Spec
Product Sub Group
Product Group
Product Manager
• Colour
Product
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How Well-Managed is Your Master Data?
Perception
• 1 definition of ―Margin‖
• Market 20,000 products
• 20,000 customers
• Analysts analyze information(source: customer study)
Reality
• 23 definitions of ―Margin‖
• Market 5,000 products
• 6,000 customers
• Analysts spend 60% of their time gathering information
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The Business Case for MDM
• Shell downstream attributed much of a 1% margin improvement ($140M annually) gained to managing master data and acting on clear analytics
• A Unilever executive has estimated that consistent operational master data is worth $200M/year in procurement savings alone
• BP‘s estimated that improved master data management is worth to them at ‗conservatively‘ $400M per year
This is clearly a problem worth tackling
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Home Depot Canada On-line Retailing
Company-wide product master data management – as well as product safety data, shipping and delivery information
STEP product repository is linked to multiple internal systems such as order management, and external systems such as shipping and delivery.
Customers have extensive ability to research products, and in many cases to purchase and have them delivered.
Following the Stibo STEP implementation, on-boarding a new product is reduced to just 10 days on average.
Analytic back-end to the system allows monitoring of the on-line behaviour of customers, allowing new insights
Much improved data quality
Home Depot needed to expand its retail presence from stores to on-line retailing. On-boarding new products currently takes an average of 10 weeks.
On-line retailing requires significant additional product information to that traditionally stored in internal systems to enable customers to research and purchase.
The Canadian market requires that descriptive information is stored in French as well as English.
Challenge Solution Benefits
Home Depot is the second largest US retailer
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Shell Oil Products Global Product Catalog
Eliminated duplicate product offerings, reducing global product catalog by 80%
Saved millions in R&D expense via increased efficiency
Global procurement improves customer service
Decentralized R&D led to duplicate localization of products, wasting millions in R&D expense
No way to provide major customers with global purchasing service
Inefficient inventory and sales management
Shell Oil Products is a worldwide supplier of fuel and lubricants
―(the MDM system) has allowed us to manage global products centrally, giving fast access to vital data for local operating units, and ensuring maximum efficiency in R&D."
Iain Pearson, Head of Global Product Management and Supply Chain for Lubricants, Shell
Global product master data management
Define product master data centrally
Subsidiaries map their views to corporate
Transparent views of product catalog information across subsidiaries and customers
Challenge Solution Benefits
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Provide daily extended supply chain information delivery before 8 a.m. across five time zones
Reduction of costly infrastructure, development and support resources duplication
Unprecedented regional view of the supply chain process, customer demand, planning, and stocks
Gain a clear view of business performance across 34 companies in 19 countries
Harmonize business processes and performance management across Latin America operations for reduced IT and administration costs
Create new economies of scale in the extended supply chain and capitalize on cross-border opportunities
Challenge Solution Benefits
Unilever Latin America Sinfonia Project
Unilever LA is Latin America’s leading manufacturer of consumer packaged goods
“We were delivering 100% of the correct information before 8 a.m. on the very first day, without any performance or quality issues…“
Fernando Rocha, Head of Info Mgt
Supply ChainManagement
Extract accurate, reliable data that adapts efficiently to organization and market change
Use MDM software to provide greater visibility of performance for improved planning and cost efficiency initiatives
Enterprise data warehouse: 12 TB, 1 billion transactions, 2,500 users
© The Information Difference Ltd 2009
Lack of Business Engagement
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Projects get pulled in different directions -IT should not lead MDM projects
© The Information Difference Ltd 2009
Poor Business Cases Risk Funding Crises
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You don’t want to run out of money part way
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Turf Wars
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When data governance goes bad....
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Data Quality Denial
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How bad did you say our data quality was?
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Typical MDM Benefits Achieved - Summary
Financial and Regulatory• Improve product margins• Lose fewer sales • Improve effectiveness of marketing spend• Demonstrate to regulators better risk managementCorporate Insight• Increase profitability via better decisionsBusiness Insights• Move to a single business language IT• Lower maintenance (one version of master data)• Faster rollouts of new systems (simpler interfaces)
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Best Practices
• Develop quantified business case
• Establish Data Governance structures
• Implement iteratively, not via a ―waterfall‖ process
• Budget adequately for data quality
• Obtain adequate input from vendor consultants
• Train personnel fully
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Think big, start small, evolve, measure
• Information management should be an enterprise initiative/discipline
• Pick a start point that gives you a return on investment
• Have a roadmap and follow it
• Measure progress (e.g. stage by data area)
• Measure quality (e.g. amount of redundancy)
• Be prepared to learn as you go
Business Unit
Sector
Enterprise
4. Definition Agreed
3. Official SourcesIdentified
7. Sustaining Data MgmtProcesses in Place
1. Data SubjectIdentified
8. Data Quality Measuresin Place & Performed
5. Data harmonized
2. Ownership agreed
6. Golden copy activated
Customer
Corporate
Individual
Person
1 2 3 4 5 6 7 8
Material
Finance
Vendor
Product
Location
DATA MANAGEMENT EVOLUTION STEPS
Data Areas
Local
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Agenda
• A key prediction
• Challenges of Master Data Management
• The Foundation for MDM
• What does Informatica do for MDM?
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Breadth & Redundancy
65% of Global 2000
organizations will deploy
two or more domain-
specific, MDM supporting
technologies
Gartner Predicts
Dec 2009
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Breadth & Redundancy
65% of Global 2000
organizations will deploy
two or more domain-
specific, MDM supporting
technologies
Gartner Predicts
Dec 2009
Organizations have
5.2CDI solutions on
average.
Customer Data Integration
Phillip Russom, TDWI
Oct 2008
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Lay a foundation of data integration and data quality to give you flexibility to adapt to changes
Data
Integration
1
Basic Data
Quality
2
Data Quality
Platform &
Identity Resolution
3
Single Domain
Hub
4
Cross Enterprise
MDM
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Forrester MDM Maturity Model
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Data Integration Requirements
• Accessing data inside
and outside the firewall
• Bi-directional
transformation
• Multiple latencies
• Process orchestration
• Data Federation
• Metadata visibility
This is not your
father’s ETL!
It’s a sophisticated
data integration platform
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It’s the master data!
You are going to use it everywhere
It’s your trusted source of truth
You will make decisions using it
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Ensuring Data Quality for Master Data
• You can’t fix it just once
• You need to monitor and manage it as a process
• It’s not just Address
Correction
• It’s accuracy, consistency, completeness, enrichment, matching and validation
• You need to know the source
of the problems
• You won’t be successful just
writing a few scripts
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Why are customer data integration projects challenging?
• Identity data is subject to
considerable error and
variation
• Databases about people &
organisations often contain
international data
• Basic search techniques
frequently miss matches or
find too many matches
• Data cleansing is not the
complete answer
EXAMPLES
• Mary Anne, Maryanne
• Easthartford, Hartford East, Hartford
• Browne – Brown
• Johnson, Jhonson
• Hannah, Hamah
• IBM/International Business Machines
• Fedex/Federal Express
• Chris – Christine, Christopher, Tina
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Hybrid Approach to Identity Matching
Heuristic
Probabilistic
Deterministic
PhoneticLinguistic
Empirical
Use a combination of methods and algorithms to
compensate for different classes of error and
variation present in identity data.
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Simply put,
MDM without a foundation ofData Integration,Data Quality, andIdentity Resolutionis unstable
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Informatica:The Flexible Foundation for MDM
Data
WarehouseApplications Documents SaaS
Customers
Products
Locations
Assets
Employees
Suppliers
All Master Data Domains
Analytical
Registry
Co-existence
Transactional
All Hub Styles
Buy
Packaged
MDM
Build
Your
Own
All Purchase Models
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Using Informatica for Master Data Management
Flat File
• PowerCenter drives initial loads of MDM Hub
• Informatica Data Quality to cleanse and monitor the quality of the data
• Informatica Identity Resolution matches and links common entities under a global ID
• PowerCenter supports on-going updates and distributes master data in any latency: batch, message based, real-time
Database
MDM
Hub
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Open to All MDM Hub Options
CRM
ERP
Data
Warehouse
Custom Built Packaged MDM Existing Systems
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The Informatica PlatformThe MDM Foundation For These Customers
Build Your Own
Build Your Own
SAP MDMInitiate Systems
Data Warehouse
Oracle MDMSiperian
MDM
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Data Warehouse
DataMigration
DataConsolidation
Master DataManagement
Data Synchronization
B2B Data
Exchange
Information
Lifecycle
Management
*Source: Gartner EXP (February 2007)
UnstructuredApplication DatabaseOn-Demand B2B
HIPAA
SEPA
NACHA
SWIFT
The Informatica ApproachComprehensive, Unified, Open and Economical platform
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Information Platform for MDM
Flexible foundation for MDM
Proven platform for data integration, data
profiling and data quality
Most accurate matching results for MDM
Improved
Agility
Increased
confidence
Increased
operational
efficiency
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Next steps…
Start with a small
MDM Project now
with data integration,
data quality, and
identity resolution
as the foundation
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Next steps…
Start with a small
MDM Project now
with data integration,
data quality, and
identity resolution
as the foundation A good place to
start is with a
Customer Registry
Contact Information
• If you have further questions or comments:
Andy Hayler, The Information [email protected]
• Michael Destein, [email protected]