Tips & tricks to drive effective Master Data Management & ERP harmonization

1. Tips & Tricks to drive effective
Master Data Management & ERP
Harmonization
Hosted By:
SAPinsider
Quality Master Data for Improved Business Performance

2. Master Data Performance Solutions
Verdantis, Inc. is the evolution of Zynapse – a
division of Zycus, Inc. to its own company with its own
corporate identity
Verdantis comes from the Latin word for truth –
veritas - and the word verdant – meaning abundant and
sustainable

3. Today Speakers
Jeffrey Karson
Project Manager, Business Integration
Siemens Water Technologies Corp.
About Jeffrey Karson
Jeffrey is a Project Manager at SWT which is a division of Siemens AG.
He has been active in the area of project management and material management
for over 15 years. His current responsibilities involve the implementation of a new
ERP system (SAP) at Siemens Water Technologies with focus on the loading of
harmonized master data.
Arthur Raguette
Vice President, Business Development
Verdantis Inc.
About Arthur Raguette
Arthur Raguette drives strategic partner development, industry alliances, and new
business initiatives for Verdantis. His career of creating collaborative business
relationships that deliver enterprise-class master data management and spend
management solutions to Global 2000 customers spans over 15 years.

4. Unlocking ROI from ERP Investments –
The Master Data Management Story
Arthur Raguette
Executive Vice President
Verdantis, Inc.

5. Introduction
• ERP Systems Are Indispensable to Business Operations in Large
Organizations
• Master Data Quality affects the Accuracy, Efficiency, and Reliability of
business processes
• Master Data Has a Material Impact on the Financial and Operational
Health of an Organization
• Consistent Data Management keeps Enterprise Applications in Shape
• Master Data Rationalization Is a foundation for increasing the ROI of an
existing ERP Investment

6. The Role of Master Data in the Enterprise
The items it makes
The items it buys
The employees who work there
The customers to whom it sells
The suppliers it buys from
Master Data
Quality Issues
Ripple Across
the Enterprise

7. A Challenge of Master Data in the Enterprise
A disorganized approach toward Maintaining Master
Data Is more common than you may think…
Customer Master
CRM Teams
Vendor Master
Procurement/Accounts
Payable
Item Master
No clear Owners

8. Multi-domain MDM Challenges
Business Stakeholders
Enterprise Applications
Information Technology
Processes related to
 Customers
 Materials
 Products/Services
 Vendors
 Has specific functionality
 Rules in its own fashion
 Handles the business
context of data
 Individual understanding of
data attributes
Heterogeneity
Global Data
Synchronization
Information is inconsistent across the organization
Sharing and synchronizing information across enterprise applications
further creates complexities




Conflicting data across business factions
Lack of stakeholder ownership
Delayed request for information
Lost ROI from ERP investment

9. Current Issues in Master Data Success: The Root
Cause is Data Quality
•Various master record formats
•Various systems of record
•Incongruent naming standards or no naming standard
•Lack of a standardized classification convention
•Incomplete fields and missing data elements
The Effect of Bad Master Data on Business Initiatives Is Profound
• Merger and Acquisition Activities
• ERP System Consolidation
• Enterprise Spend Management
• Sourcing Strategies and the make-v/s-buy process
• Inventory Visibility
• Decreased Plant and Equipment Availability
• Part Reuse in Design
• Decreased Employee Productivity

10. Incomplete Approaches towards Master Data
Rationalization
ETL Solutions
(Extract, Transform, Load)
These solutions are too generic in functionality to deal with the complexities of
item master records. ETL solutions do not perform classification and attribute
enrichment. Moreover, there is considerable effort and expense in setting up
these solutions for repeated use.
Asset Management Solutions
Asset management solutions typically target only a subset of item master data,
namely MRO (maintenance, repair, and operations) items. This is
not sufficient for ERP consolidation or for comprehensive spend analysis. In
addition, there is significant manual effort involved.
Commerce Catalog Solutions
Commerce catalog solutions tend to focus only on the items sold, rather than
those procured. These solutions are less experienced in tapping the various
internal and external sources of item data and fail in the subject-matter expert
department. Furthermore, they do not automate the attribute enrichment,
automating instead only the workflow.
Manual Content Factories
Manual content factories, or manual approaches in general, were common
before the advent of artificial intelligence tools for master data rationalization.
The manual approach cannot scale nor can it meet the throughput demands of
large projects.

11. Proper Master Data Management requires
a consistent automated process!
Key Issues with Concurrent
MDM Approaches
•
•
•
•
•





Limited Scope of Organizational Data
Narrow Focus
Lack of Scalability
High manual intervention
Multiparty data manipulation
How repeatable is the process?
Can the system learn?
What is the throughput of the system?
How strong are the algorithms used for the automated processing?
Can the process be integrated into daily operations?

12. Integrating Master Data Rationalization Into
ERP Consolidation or Upgrade Planning
83% of data migration
projects fall/overrun
• Half exceed timescales
by three-quarters
• Budgets are exceeded by
two-thirds
• A third of these fail
entirely
Standish group Study 2008
ERP initiatives, the importance of data
migration & the emergence of Master Data
Management (MDM)
During Data Migration, multiple masters are migrated
•Small Masters - Chart of Accounts Master, Currency Master, etc
•Key Masters - Material, Vendor, Customer, etc
Handling of the key masters during migrations is the key to unlocking the ROI from an ERP investment
•Material Master ROI
•Supplier Master ROI
•Customer Master ROI
Handling Key Masters need a specialist
•IT services provider or ERP implementation partners cannot do it
•Data migration of Key masters needs strong domain expertise
•Specialized cleaning tools and knowledge repositories are needed
Master Data Management (MDM) of the Key Masters has to be part of the ERP blueprint

13. Master Data Rationalization
Extraction and
Aggregation
Cleansing
Classification
Attribute
Extraction and
Enrichment
Final Duplicate
Record
Identification
Demonstrable ROI in
•
Greater and quicker ROI realization form ERP Investments
•
Increased Leverage of the existing systems
•
Increased Contract Compliance
•
Spend Leverage through supplier consolidation
•
Global Inventory optimization
•
Reduction of Inventory Carrying costs
•
Increased Plant Uptime
•
Increased Worker productivity
•
Reduced Mean Time to Delivery of Products
Building the right
business Case for
Master Data
Rationalization

14. The bottom line
• Clean, Reliable Master Data Enables Successful Enterprise Initiatives
• Master Data Rationalization Is Required to Ensure Master Data Quality
• Build Master Data Rationalization Into ERP
Consolidation Planning
• Master Data Rationalization Is a Key
Component to Achieve Data Quality
Maturity

15. Siemens Water Technologies
Master Data Management & ERP Harmonization Initiative
Jeffrey Karson
Project Manager, Business Integration
Siemens Water Technologies Corp.

16. About Siemens Water Technology
Siemens Water Technologies is a
Leading water
& wastewater
treatment
company in the
world
leading global provider of cost
effective
and
reliable
water
treatment systems and services,
offering
emergency
conventional
everything
water
from
supply
water
and
treatment
Has developed
more than 850
products and
technologies
processes to wastewater reuse
systems, membrane bioreactors,
Siemens
Water
Technologies
Provides
comprehensive
water
treatment
solutions
UV disinfection systems and RO
cleaning
contracts.
The
company's products and services
are designed to help keep your
city
safe,
profitable.
or
your
company
Company has
over 200,000
installations;
174 office &
plant locations
Has presence
in the
Americas,
Europe, Middle
East, Africa, &
Asia-Pacific

17. The SWT Legacy- The Need For MDM
Key Events
•
Siemens acquisition of US Filter in 2004
•
US Filter’ history of a lengthy series of mergers, acquisitions, and divestitures
Identify common
nomenclature for
master data
Understand the Problem:
•
Fragmented business system landscape
•
No master data or process standardization
•
Virtually no information transparency
Enrich master data
to populate missing
attributes
SWT's strategic goals
•
Partner/align with SAP implementation
•
Improve visibility and control of information
•
Improve operational efficiency
•
Improve working capital management and business process management
•
Comply with SIEMENS standards
Identify and
remove
duplicates
Consolidated &
Cleansed
Master Data

18. The Challenges
• Non-uniform data due to multiple legacy systems
• Huge volumes of historical data
Master Data
Legacy
Systems
• Data from multiple source systems
• Transition from JD Edwards and Baan ERP platforms to SAP
• No governance process to maintain Master Data
• Inefficient search process
Governance
• Lack of visibility across all locations
Process

19. SWT’ Master data harmonization requirements
LEGACY SYSTEMS
• 8 brands in the U.S
• 13 instances
• 3 instances that consolidate businesses
MATERIALS
• 1,300,000 active materials
• No common nomenclature for part descriptions or attribute callouts
• Duplicates within and across legacy systems
• No common or SIEMENS-required classification
BUSINESS PARTNERS
• 102K customers; 63K suppliers
• No common protocol; duplicates across legacy systems
• No global visibility into business partner relationships
• Little industry classification

20. The MDM initiative at SWT
•
•
•
•
Planning
Stakeholders
Budgets
Timelines
Design the Process & Roadmap:
•Harmonize primary legacy ERP master data
•Governance for new data creation, change & data life-cycle
management
•Migrate legacy data to SAP
•Comply with corporate global applications
Verdantis Harmonize for Historical Data Cleansing & Enrichment
Verdantis Integrity Solution to manage master data
creation and maintenance going forward
The MDM Blueprint

21. Business vs. Technical Effort- Finding the balance
Role of the Project Team –Design, Engage, Lead &
Support
•
Champion & Vision
•
Roadmap & Budget
•
Sell & Garner Support
•
Communicate & Demonstrate
•
Manage & Support Business Effort
Business people -Design, Definition & Acceptance
Testing
•
Harmonization & Solution Design/Acceptance
•
Knowledge of the business & requirements
•
Owners and experts of the data
•
Have the most at stake
•
More likely to drive & sponsor deployment,
troubleshooting and continuous improvement
Other Support
•
Executive & Business Leadership –Approval &
Support for Business Resources
•
IT –Legacy Interfaces, Data Rationalization, Data
Migration
Executive
Sponsorship
Business
Leadership
Business
Functional
Process
Owners
SAP Team
MD Project
Core Team
IT
Business
Technical
Engineering
Business
Technical –
Purchasing
The Stakeholders
Centralized Core Team
Decentralized Resources & Support

22. Harmonization Process and Team Roles
Legacy
Master Data
Business to
Provide details
Necessary to
Classify & enrich
items
BC Owner to
Validate
Inactive list
IT/Project Team/Technology tools
Legacy
Interface
Business to
Update legacy
Data as
appropriate
Consultant/Project Team/Business Technical Support
Rationalize
Active Item
List
Classify
Items
Data Setup & Rationalization
Harmonization








Complete
Spec
Attribute
Establish connectivity
Create Rules for Inactivity
Establish Metrics for Harmonization
Deliver Data to Harmonizer consultant
Establish Numbering Scheme
Select Classification Criteria
Create Standard Attribute Requirements
Transform Data
Eliminate
Dupes &
Assign
Unique
Number
Central
Master Data
Repository

23. The Governance Process
Daily : Review & edit new records created in the Master Data Repositories
Tools/Master Data Repository (MDR)
MDR
MDDM Team
Accumulate
KPIs for
Monthly
report
Review for
quality and
edit record
In MDM
Daily Report of
Newly created
records
MDM
Feedback : Local Business
Noncompliant
Record list
sent
To
businesses
Business
edit records
Monthly : Audit the ERP Databases
Audit: Software tools
ERP Databases
Extract
Master
Records
Legacy
ORACLE
Accumulate
KPIs for
Monthly
report
Review for
quality and
edit record
In MDM
SAP
MDM
SAP
 Check record number type (system or assigned)
 Check for classification
 Check for other
Non SAP
 Check for Master Control Number
 Check for classification
 Check for other
Feedback : Local Business
Noncompliant
Record
list sent to
businesses
Business
edit
records

24. Data Governance -The MDM Lifeline
Search
Define
Authorize
Create
Update
NO
Approve?
Systems
Legacy User
Tools/Master
Data
Repository
MDM
YES
Master
Data
Repository
NO
Approve?
SAP
Local
Authorizer
Oracle User
Record:
Definition
Classification
YES
YES
Record:
Definition
Classification
Control No.
NO
ORACLE
SAP User
AutoApprove?
Potential
Match?
NO
YES
SYS
Legacy (s)

25. Benefits of master data harmonization
and governance initiatives at SWT
BUSINESS
•
Process standardization
drives continuous
improvement
•
Provides consistent and
actionable information
•
Enables elimination of
duplicated data entry
across applications
•Cleansed & enriched
Master Data for effective
sourcing
•Greater savings on total
Spend for different
Indirect Commodities
Enriched Master
Data
Single Version of
Truth
•Enhanced visibility across
the enterprise
•Effective Data
Governance
FINANCIAL
•
Improves spend
and supply
management
•
Enables part
standardization
and lean inventory
•Item Master Deduplication by duplicate
identification in the
inventory
•Reduced Inventory
Carrying Cost reduction
Optimized Inventory
TECHNICAL
•
Improves success of SAP
implementation
•
Facilitates interfaces
between and among
applications
•
Enables centralized
maintenance and change
management
Effective Search of
Parts
•Consistently enriched
data provides fast and
accurate search
•Unique attribute-based
search
•De-duplication of data at
source
•Automated attribute
enrichment at data
creation point
Effective
Governance Process

26. Measuring Results and Performance
Harmonization
•
•
•
•
•
Data count after rationalization
Classification Success
Number of Classification
Specifications
Enrichment rate
Source active data count
Governance
•
•
•
•
Duplicates avoided
Non-compliant records in ERP
systems
Non-compliant transformation
turnaround
Data quality
Migration
• Legacy data match up with basic
views from Master Data
Repositories
Corporate Applications
• Alignment of data common to
multiple application
• Eliminate duplicate creation &
effort –feed from the most logical
source
• Quality of data feed
• Quantity of rejected records

27. Driving People, Process & Cost Efficiency
Financial:
• Improved spend and supply management
• Greater savings by empowering procurement with greater bargaining power
• Enabled part standardization and inventory optimization driving reduced inventory
cost
Business Process
• Greater visibility into and optimum utilization of enterprise assets
• Enhanced overall procurement process and end-user efficiency
• Elimination of duplicated data entry across applications and factories
• Business process standardization drives continuous improvement
End-Users:
• An easy-to-use bolt-on-SAP solution for ongoing MDM
• Greater end-user productivity and adoption of data governance frameworks
• Standardization of data by eliminating the perception difference between people and plants
Ensuring Value is Added!

28. Why we chose Verdantis?
• Only provider that had a complete solution engineered specifically for what SWT needed
• The Verdantis Harmonize Solution to harmonize existing data and bolt on the Verdantis Integrity
Solution to control new information flowing into SAP
• A detailed Proof of Concept to harmonize a subset of SWT's real material master data was a big
success.
• Verdantis parent company, Zycus already had a relationship with Siemens' Energy business in the
related area of Spend Analysis
• Expertise in the process of mapping Siemens' proprietary ESN materials coding system to the global
standard UNSPSC coding system
• The language agnostic nature of Verdantis artificial intelligence based automated MDM solution and
the ability to handle large volume of cryptic and complex descriptions in a short turn-around time
• The Easy-to-Use and Easy-to-Configure Verdantis Integrity Solution for maintaining data integrity and
providing ongoing data management.

29. Quality Master Data to Improve your
Business Performance
CLEAN IT WITH HARMONIZE
MATERIAL
HARMONIZE
SUPPLIER
HARMONIZE
CUSTOMER
HARMONIZE
PRODUCT
HARMONIZE
MATERIAL
INTEGRITY (MI)
SUPPLIER
INTEGRITY (SIM)
CUSTOMER
INTEGRITY (CIM)
PRODUCT
INTEGRITY (PIM)
KEEP IT CLEAN WITH INTEGRITY

30. Master Data Solutions
Get your copy of the Siemens ERP Harmonization case study
here.
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in our Knowledge hub!
www.verdantis.com
info@Verdantis.com
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31. Q&A
Quality Master Data for Improved Business Performance