In today’s Global marketplace, Organizations are under pressure to be more cost effective and have a responsive, business oriented IT Organizations. Because of economy erode due to deep recession, we see a different set of business scenarios happening around the globe with mergers, acquisitions, divestitures, reorganizations and other changes aimed at optimizing existing business processes and IT landscape consolidations.
The critical objectives in an ERP Business transformation project are:
Support the sustainable performance of your business productivity and innovation
Drive business process improvements that help you achieve target organizational goals
Develop the most optimal IT strategy and align it with your business strategy
Optimize efforts to generate benefits using the best practices solutions
Most organizations preparing for an ERP Business Transformation project focus mostly on process reengineering and application configuration strategies with the implementation partners and ignore the complexities with the Data migration and integrations. Per the Gartner research on these initiatives, 70% of the projects have no Data strategy or have done any due diligence on the data readiness for their business transformation and ERP implementation. They realize the data issues very late in the project and resulting in project delays and cost over-runs.
Key Data challenges in a ERP Implementation
Ensure business participation in the Data migration (Data preparation, Collection and validation)
Align Business process with Data
Selection of right technology for Data conversions and migration
Continued Data Integration
Number of Data sources for the critical business objects
Decision Technologies have recently worked on two projects in Semiconductor and Electronic manufacturing services (EMS) industries on data migrations to help implementing the business transformation projects.
The Semiconductor client had migrated from SAP 4.7, Oracle into ECC 6.0.
The EMS client had migrated from multiple Legacy systems into SAP SRM, SAP MDM, ECC & SAP BI.
Key learning from the SAP ERP Implementations at our clients
Data assessment at the beginning of the Project to optimize the SAP Configuration settings, avoid duplicate & redundant entries, estimate the data quality effort requirements
Determine the SAP Enterprise settings early ( Company Codes, Plants, Sales Org, Distribution channel, Purchase Org, GL Accounts, Bank Master, Controlling data, Hierarchies and others) which will drive all the data migration activities i.e. Master data and Transactional data.
Design & Develop an appropriate Data conversion architecture to effectively control the time and cost for the opted technology
Do not build excessive business logic in the SAP data upload programs. Have a good ETL tool to implement all the data transformations before transferring the data to SAP
Involve the Business super users and process owners early in the Data migration workflow to validate the data
Determine the multi-language support requirements at the beginning of solution design
Our Approach to address the Data challenges
Begin a Data audit in the early stages of Project to identify the critical fields required to support the business
Map the Business objects( Field mapping) to the new SAP system and identify gaps for design& development
Build a implementation plan to align the data activities with the SAP Configuration activities
Focus on the data quality requirements to make the data ready for business process
Design a flexible technical architecture which supports multiple iterations of data testing for the full data volumes
Automate the High volume Data activities to avoid delays with manual operations
Develop a workflow process to have a clear delegation of responsibilities to validate and address the data quality issues during the data migration.