for example for customer creation,in MDM all basic data like name, address, city and country will be updated and it is syndicated to ECC systems.It is also possible to create data in ECC only so what is the purpose of MDM.
MDM makes more sense in a heterogeneous landscape as it provides key mapping,syndication capabilities to give you a "Golden source of record"
Whether MDM is used as a "System of record" or "System of reference",some data will be duplicated in different systems.It provides a single window for an user/application to have a look to know how a record is maintained in different systems thereby giving more accurate data.
Today in your scenario it may look redundant,but tomorrow if a new CRM is added and the stored data needs to be replicate,MDM would make things easier.
It is important to understand that MDM and ERP do not replace eachother rather complement each other.
Using SAPu2019s ERP suite as the foundation technology for an MDM implementation is problematic because, despite all the positives of ERP, flexibility is usually not associated with SAP systems.
SAP ERP doesnu2019t offer the tools to manage master data in the ways required by todayu2019s complex organizations.SAP ERP isnu2019t designed for active management of critical master data. Specifically, SAPu2019s data matching capabilities are too basic. Its search functions might be good at u201Cexact matchu201D but they are not as strong at the kind of u201Cfuzzy searchingu201D that is so important in uncovering duplicate entries with subtle differences. For the same reason, users are far more likely to create new duplicate customer records in SAP, and thereu2019s no way to create a u201Cgolden copyu201D of master data for use across multiple heterogeneous systems, or to maintain survivorship rules for overlapping data from multiple systems.
These problems are all compounded when you have more than a single SAP instance, or different ERPs altogether, which is a very real occurrence within large corporations that have grown through mergers & acquisitions. Even without multiple ERP instances, most mid-size and larger national firms are likely to pull data from many different systems. In fact, 10 to 30 source systems is not uncommon, and heterogeneous environments are now the norm. The siloed approach to data management whereby customer-facing data is in one system, product data in another, asset data in a third, and so forth, really complicates the integration of processes, data and workflow.
A dedicated MDM hub provides a multitude of benefits not attainable with an SAP ERP-based master data approach. First, a dedicated MDM system is just that -- dedicated to delivering the best possible manageability of your master data across the enterprise, and not just within your ERP technology stack. The focus of any high-quality, enterprise-grade MDM hub implementation is going to be on getting master data right; creating a single source of truth, with each distinct customer, product, etc. represented only once in the hub. This means you can maintain accurate, complete, timely and consistent master data through both data governance and hub technology, with robust data quality and matching capabilities.
MDM and ERP need to coexist for instance as one solution does not replace the other. From an investment perspective, it is important to leverage existing technologies such as data quality, extract-transfer-load (ETL) and data integration tools, middleware, business process management and workflow.
To summarise, the top five reasons not to master your data in SAP ERP are:
1. SAP ERP isnu2019t flexible enough.
2. Master data is different and canu2019t be proactively managed within an SAP ERP system.
3. SAPu2019s ERP products werenu2019t designed for active management of master data.
4. Mastering data in an ERP system is much more difficult with more than one instance or when different ERPs are used together.
5. An MDM hub creates a workspace between an organizationu2019s transactional and analytic systems meaning they fix it once and then extend it for use in back office systems and the data warehouse.
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