ENSURING A SUCCESSFUL SAP DATA
MIGRATION
Presented By
EXPEDIEN & KENNAMETAL
• Eric Stridinger, Global Data Management/EIM
Lead/Manager, Kennametal
• Jeff Coombs, SVP, Marketing – Expedien
• Shibajee D Gupta – Lead EIM Consultant, Expedien
• Contact email: [email protected]
•
Introduction
• SAP Data Migration
• Kennametal Success Story
• Q&A
• Enterprise Data Management Solutions & Services
Provider Firm.
• 240+ strong team of professionals with over 1500 person
years of rich experience in Enterprise Data Management
and SAP.
• Founded in 2003, headquartered in Houston TX with other
offices in Santa Clara and Noida, India.
• For more information, please visit http://www.expedien.net
Expedien Services
• EDM • Data Quality • Data Migration • Data Integration • Master Data Management • Data Governance • Data Warehousing • Business Intelligence • SAP Functional & TechnicalConsulting • SAP Portal
Data Migration – Start to Evolution
Legacy Data
Data
MigrationERP Implementation
MDM/Data Governance - EILM
Business Intelligence
Business Value – BVIA™
Master Data Current State Integrated State Evolution BV BV BV EnrichmentEngagement Scope Readiness Assessment Business Process Roadmap & Strategy Data Integration Data Migration Evolution Knowledge Transfer Competency Center Data Retention &
Archival Data Quality Validation MDM & Metadata Management Enterprise Data Warehouse Reusable Business Components Data Governance
Plan, Design & Implementation
Special Customer Need
Data Life-Cycle Management
Data Retention & Archival
Data Quality Data Migration
Enterprise BI Balance Scorecards Management Dashboards Operation Dashboards OLAP Reporting Business Value Delivery
Expedien Knowledge Repository/Accelerators
Technology & EDM Components Selection Data Quality Metrics Definition Roadmap & Strategy Governance Strategy Data Assessments •Quality •Enrichment Rules •Business Value Integration Evolution Knowledge Transfer Competency Center Reusable Components Data Reconciliation & Acceptance Data Integration Data Migration and BV™ Validation Data Quality Validation MDM & Metadata Management Enterprise Data Warehouse
Plan, Design & Implementation Engagement Scope Business Case Information Collection Enterprise BI Balance Scorecards Business Value Delivery
Expedien Rightway™ Enterprise Information Life Cycle Management
(EILM) Methodology
Five Steps Data Migration Landscape and Process
L eg acy S y st em s an d S A P 4. 6 Identify Data Candidates DQ Assessment Standardization, Matching and RankingLegacy to SAP ECC 6.0 Data Migration
S A P E CC 6 .0 DQ Rules Definition Data Business Values Analysis
Data Migration PMO and Steering Committee Establishment
Define Key Quality Indicators Define Legacy to Object Mapping Infrastructure Setup
SAP Configuration Data
Define Progress Scorecards DQ Rules Monitoring DQ Rules Build DQ Rules Validation Data Business Values Enrichment Data Business Values Validation Data Business Values Publishing Build ETL Maps Unit Test by Object Monitor Progress Modify ETL Maps Capture and Reprocess Drop outs Check Data load threshold Prepare Data for Test Cycle Prepare for post load reconciliation Load Method Decision Point IDOC OR BAPI LSMW ABAP or Other Methods Platform - ETL/Data Quality such as SAP Business Objects Data Services and Information Steward
SAP ECC Dev SAP ECC T01 SAP ECC T02 SAP ECC T03 SAP ECC PRD Cutover PRD Cutover 2 Cutover 3 Cutover 1 SAP ECC 6.0 Partially Cleaned Master Data Object Cleansed Master Data Object
1st Dry Run 2nd Cycle 3rd Cycle 4th Cycle 5th Cycle
Data Cleansing Cycles
Project Management
Start early. Setup a strong PMO and define progress metrics and scorecards. It is very easy to underestimate the data migration aspect of an SAP implementation.
Legacy Data
Light the fire. Identify and prioritize all possible legacy systems and kick off DQ Assessment upfront.
Data Quality
Define Data Quality rules from a repeatable framework perspective.
Data Migration Team
Should participate actively in the business process workshops during blue printing
Load Methods
Distinctly categorize the load methods by objects upfront. This eliminates considerable downtime once the data sets are ready.
Five Don’ts of Data Migration
Project Management
Do not over scope the project. Scope the project optimally. Biting off more than the chewable capacity can result in serious negative impacts, e.g. cost and time over runs.
Legacy Data
Do not underestimate the number of legacy data systems. There could be random spreadsheets and mini database sitting on standalone computers.
Data Quality
Do not overestimate the legacy data quality and bypass Data Quality Assessment steps. It doesn’t hurt to profile good quality data.
Data Migration Team
Do not over engineer the build and test process. This can result in resource burn out in the long run. Make sure the mapping documentation has the absolute critical data elements passing through the quality gates.
Load Method
Do not overlook the historical data load strategy. Identify the strategy and then plan the load process and method keeping the data dependency in view.
Kennametal
Introduction:
ERP Project Goal/ Charter:
Kennametal is a $2.5+ B manufacturing company, pioneer in tooling
solutions, engineered components and advanced materials. Due to the nature of its business Kennametal often goes through Merger and Acquisitions, that results into integration of legacy systems into the SAP ECC system of record.
Project Rapid –
•Implement Business Transformation
• Upgrade SAP R3 4.6 system to ECC 6.0 to streamline global processes/data • Implement SAP new dimension products such as PLM, SCM, SRM, HCM and
CRM
•Drive towards 90% Standard Processes •Move towards a Customer Centric Model •Need for Data Governance
Kennametal - Data Strategy
Criticalities:
Enrichment:
Value Addition:
•Integration of non SAP Data
•Multi-Language Data Conversion
• Business Transformation for Materials and Inventory Management • Build a reusable / repeatable conversion process
• Huge dependency on success factors
•Plant and Storage location naming convention •Plant and Storage location re-alignment
•Material Grouping modification
•Material ID and D&B number integration
•Home grown MDM process
•Inventory valuation of aged Material and identification for better housekeeping as a positive fallout
•Foundations for Data Governance
•Establishment of an infrastructural and process framework by Expedien® with expert knowledge transfer to make Kennametal self sufficient in the long run.
Results:
• Go to market milestone was achieved • Legacy systems decommissioned
• System downtime dropped reasonably • IT staff changes to focus on the future
• Critical Master Data consistency and accuracy
• Foundation for Data Governance and overall EDM strategy
Bottom line Benefits:
• Increased sales and revenue
- Single view of customer = Improved targeted marketing. - Ability to up-sell and cross-sell
• Significant cost reductions
- Accurate product & catalog information
• Call center productivity increased considerably
Recap
• It is crucial to have resource mix of business and technology in projects like this.
• The Landscape and processes should be of repeatable nature so that future data migration will be a little easier every time.
• Data Quality efforts including measurement against data quality metrics and continuous monitoring– A must for successful data migration.
• Take data migration as an opportunity to build foundation for data governance and master data management.
• It is absolutely must to add right resources in right spots of the project and also make sure the resources have the right skill sets as such projects do not have any room for newbies.
