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SWOC DAMA
Master Data Management
Peter Lamb
January 24, 2007
Master Data Management with Kalido
MDM – The Context
Capabilities of Kalido MDM
Commonalities with DIW
MDM Capabilities
How is MDM Used
Types of problems customers are solving with MDM
Benefits customers are deriving through the use of MDM
Guidelines for an MDM Implementation
Importance of business involvement
Technology evaluation
Planning
Implementation
Questions
2
Copyright © Kalido 2006
MDM – The Context
3
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Master Data Lifecycle
4
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Enterprise Wide / Cross Functional
Currencies
Customers
Regions
Brand Families
Cost Centers
Package Types
Market Segments
Business Lines
Products
Brands
Branches
Materials
SKUs
Sectors
Suppliers
Contribution Types
Departments
Product Groups
KPI definitions
Expense Types
Organization
Payees
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Assets
Units of Measurement
Channels
Sales Divisions
5
Employee Classes
Hundreds of
categories of
master data
Supply Locations
Tax Types
Why is Master Data Management So Difficult?
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
Finished Product
Target Industry
Segment
Catalog
SCM
Line Item
Master
Data
6
Product Usage
• Height
• Length
• Width
Partner
Master
Data
Copyright © Kalido 2006
ERP
ERP
DW
Master
Data
Product
Sub Group
Brand
Sub Group
Product Spec
Product
Product
Group
Brand
Product
• Size
CRM
Master
Data
Product
Manager
Product
• Colour
DW
Master
Data
How Well-Managed is Your Master Data?
Perception:
Reality:
• 1 definition of “Margin”
• 23 definitions of “Margin”
• Market 20,000 products
• Market 5,000 products
• Have 20,000 customers
• Have 6,000 customers
• Analysts analyze info
• Analysts spend 60% of their
time gathering info
(source: customer study)
30% of all operational errors are due to poor information quality
• Books closed in 8 days—not 3
• Millions lost annually on errant
shipments
• 30% of invoices are incorrect
7
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(Reuters)
• Incorrect commission, rebate
payments
• Customer goodwill lost
• Overspending in procurement
What an MDM Solution Provides
Enrich
Authorize
Browse
Master data model
Segment
Product
Sub Group
Brand
Sub Group
Product Usage
Product
Product
Manager
Product
• Colour
Product
• Size
Catalog
Finished Product
Line Item
Consolidation – 3600 view
Product
Group
Brand
Target Industry
Consistency – Harmonization
• Height
• Length
• Width
Control – Data governance
Product Spec
Finished Product
Target Industry
Segment
Catalog
SCM
Line Item
Master
Data
8
Product Usage
• Height
• Length
• Width
Partner
Master
Data
Copyright © Kalido 2006
ERP
ERP
DW
Master
Data
Product
Sub Group
Brand
Sub Group
Product Spec
Product
Product
Group
Brand
Product
• Size
CRM
Master
Data
Product
Manager
Product
• Colour
DW
Master
Data
Real Life MDM Solution
Oracle
ERP
Finance
Vendor
AP
SAP
Enrich
Authorize
Browse
Finance
Product
Vendor
Customer
Vendor
Customer
Employee
Kalido MDM
SAP
Planning
Product
Customer
Customer
Finance
Product
Call
Centre
DW
Master Data Repository
Product
Vendor
Customer
Legacy
Sales &
Dist
Data Quality
Reporting and
Analysis
Finance
Legacy
GL
User
Mailbox
User
Exchange
9
Copyright © Kalido 2006
Active
Directory
Job
Employee
HRIS
Product
Geography
Legacy
CDM
Active Information Management
DIW – Dynamic Information Warehouse
MDM – Master Data Management
MDM and DIW – Sister Products
Capture and manage change over time
Audit log of all changes to master data
Define, hold and present business model
Change and extend business model with minimal impact
Publish master data for consumption by other applications
11 Copyright © Kalido 2006
MDM and DIW – Key Differences (current release)
DIW
MDM
Transactional and reference data
Defined for master data only
Data integrity strictly enforced
Holds data that does not conform to defined
business rules
Standard validation rules
Complex validation rules may be defined at
the attribute or subject level
No workflow
Supports workflow for business management
of new, amended or invalid master data
subjects
Client not intended for direct data entry of
master data
Web based interface intended for business
user access
Load from files or ODBC
Loads only from flat files in current release.
API supports real time updates
Manages delta detection
Delta detection, if required, must be managed
in external ETL
12 Copyright © Kalido 2006
Key Capabilities of Kalido MDM
MDM – Terms
Category
Attribute
Logical column or field defined in a category
Subject
Logical table or data set sharing common attributes and
business validation rules
Data member of a category
Catalogue
Grouping of objects in MDM – these could be model objects
such as categories or groupings of subjects selected from one
or multiple categories
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Key Capabilities - Model
Generic Model
Holds master data of any type as defined by the business
Hold and Present the Business Model
Define categories and attributes
Define relationships
Define complex business rules to identify non conforming data
Present the model to consuming application and to business users
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Key Capabilities – Managing Invalid Data
Hold but identify data that does not conform to business
rules
Empty values for mandatory attributes
Incorrect number of values for an attribute
Invalid parenting
Invalid format or data types
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Key Capabilities – Complex Identification of Invalid Data
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Key Capabilities – Audit and Control
Time variant capture and management of master data
values by attribute
Full audit logging of all changes
Definable security
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Key Capabilities – Governance
Workflow
Definable workflow to direct subjects into the inbox of a party
(group of users)
Users can approve, reject, authorize subjects
Issues can be raised and addressed
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Key Capabilities – Standard Interface
Standard Interface
Simple, but users have accepted it well
Consistent
Searching / browsing capabilities
Mass update – basket operations
Mapping capabilities to simplify updates
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Basket Operations
•Delete
•Catalog
•Re-catalog
•Amend ownership
•Set security
•Edit fields
•Approve
•Authorize
•Reject
•Submit for approval
Key Capabilities – Customizable Interface
Customizable Data Management Forms
HTML Style Sheets
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Key Capabilities – Publishing / Implementation
Master Data Publishing
Category reporting scripts provide a simple and consistent presentation
for consumption of master data
Outbound publishing of non-conformant subject data for reporting
API access
Direct access possible to underlying tables
Fast to Deliver
Simple to build
Simple to change
Prototyping an option
Business Analysis, Not The Technology
22 Copyright © Kalido 2006
Benefits Derived from MDM
Cross functional data integration
Data quality
Data decoration
Audit logging
Workflow
Interface
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Implementation Guidelines
Guidelines / Best Practices - Business
Engage with the business early and at every step along the way
Business commitment is crucial
Not a ‘one-off’ project – success will drive more demand
Executive support
Definition of global master data standards
What constitutes master data in the organization
Define standards
Conflict resolution
Business Must Lead
Considerable Business Time Is Required
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Guidelines / Best Practices - Evaluation
Allow up to three months for the evaluation process
Interview reference customers
Consult Kalido P.S. to confirm suitability of MDM as the
solution
Proof of Value
Prove the technology
Set realistic business expectations
Build confidence, interest and excitement
Have Business Users Involved in the POV
26 Copyright © Kalido 2006
Guidelines / Best Practices - Planning
Set a clear scope
Limit scope, and extend as needs arise
Business prioritization for greatest return
Try to focus on a single subject area
Define the vision
Seek buy-in immediately
Refer to existing business processes
Ensure commitment to new business processes
Step by step approach
27 Copyright © Kalido 2006
Guidelines / Best Practices - Implementation
Training personnel fully
Focus where it is required – may need multiple sessions
Engage P.S. – coaching during development
Include key business users in training – model definition as well
as interface
Get input from vendor consultants
Do not lose momentum
Iterative approach better than waterfall
Many lessons learned as first categories are implemented
Use real data and be ready for surprises that can change
priorities
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Guidelines / Best Practices - Model
Business involvement is critical in defining the model
Aim to resolve ambiguity – do not add to it
Use business definitions
Use business names for categories and labels
Identify business owner for each object
Identify system of record for each object
Identify data that will be maintained in MDM and the business
users that will be managing it
Define basic validation rules including unique identifiers
Publish the model for IT and business users
Graphic representation of category relationships
Detail on categories and attributes
Use MDM metadata
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Guidelines / Best Practices - Model
Understand where the business expects to be going –
build for current requirements, but keep long term plans
in mind
Expect to extend validation rules during the
implementation phase
Keep in mind how the data quality can be improved
How can value be added beyond initial requirements
Identify security requirements
Sensitive data must be secure or business owner is not likely to
make it available
Build confidence by demonstrating security
Split categories based on security if required to ensure control
30 Copyright © Kalido 2006
Guidelines / Best Practices – Data In and Out
Use real data during development
Load from spreadsheets rather than ETL for initial testing
Business will respond to real data and often ignore test data
Loading real data uncovers many conformance issues – do not
wait for ETL to load the data
Confirm unique keys
Expect model to change as data is loaded
Determine Outbound Requirements
Generic – an approach for all data
Specific – what feeds to consumer systems must be delivered
for the project to be successful
Define how invalid data will be handled – will it be published?
31 Copyright © Kalido 2006
Guidelines / Best Practices – Tracking and Purging
Track data - timestamp
Ideally, timestamp and track all data. This includes input feeds.
Normally multiple interfaces and sources, with many possibilities
of failure
No one likes to admit to a data problem
ETL
Source
MDM
Define an approach for deleting subject data
Focus is to get data in – data may need to be removed
May be physical delete - purge
May be flag values
Be clear - ‘inactive’ and ‘deleted’ are not the same
32 Copyright © Kalido 2006
Guidelines / Best Practices – Validity & Governance
Continuously review validation rules
Define workflow requirements
Workflow requirements may be defined in the initial model, but
clarity over data quality and ownership is likely to result in
changes
Monitor business processes that may be in place to integrate
MDM workflow where possible
Data volumes will have an impact
33 Copyright © Kalido 2006
Guidelines / Best Practices – Quality
Quality counts
Data and ETL quality is critical
Do not risk a loss in confidence – be able to prove that the data
is correct
Modularize ETL
Solid process control including error messaging required
Be prepared to restructure feeds – you may need to move from
daily to hourly
Outsourcing development not recommended
34 Copyright © Kalido 2006
Summary
Master Data Management with Kalido
SCM
Data Loader & APIs
ERP
ACTIVE INFORMATION
MANAGEMENT
Business Modeling
Change Management
Master Data Repository
EDW
Data Marts
Data
Warehouse
Manage
Notify
Workflow
Application Service (SOA)
Sources
Recipient
BI Systems & Users
Flexible storage
Data Stewardship
Output
• Business-model driven
• Extensible to all subject areas
• Handles non-conformant, invalid
and incomplete master data
• Enterprise-wide view
• Time-variant model and data
•
•
•
•
•
•
• Valid, authorized data
• Master data as a service
• EAI, Web Service, ETL & file
interfaces
36 Copyright © Kalido 2006
Search
Enrichment
Mapping
Authorization
Collaboration
Workflow-controlled
Intranet
Ventana Research Conclusions
All respondents felt KALIDO MDM was an excellent
foundation on which to roll out master data management
They spoke highly of the service provided by Kalido
consultants and commended their levels of commitment and
expertise
Most were in the early stages of implementation and felt it
was too early to quantify benefits. Nonetheless, all were
convinced benefits were accruing and would eventually be
realized and measured
Most organizations did not develop a formal business case
but they saw implementing KALIDO MDM as an essential
step toward effective information management
37 Copyright © Kalido 2006
Ventana Research – Why Kalido
Flexibility to accommodate business change
Effective dating – time dependency functionality
Fast to implement – low dependence on IT
Ability to build business rules and ensure compliance
Supports and helps enforce need to address master data ‘challenges’
Very often no business case developed as such
Often supported on basis of bigger initiative
Is ‘self evident’ that its needed
Provides excellent ‘foundation’ for MDM
Early to have ‘quantified’ business benefits but all convinced they are there
38 Copyright © Kalido 2006
Questions…
Peter Lamb
+1 416-538-6231
[email protected]