Simplifying IT with Master Data Management and SOA

We will assume that systems A and C in our example (Figure 1, Stage 1) can be retired by consolidating data and authorship to an operational transactional MDM hub, while system B provides additional functionality that needs to remain in use. For a realistic view, we presume that retirement of legacy systems is accomplished through an iterative, phased approach due to scope and impact of work. We derive an interim logical diagram (Figure1, Stage 2) by introducing or promoting an existing SOA enterprise standard data distribution layer, and retiring systems A/A2 into a newly introduced MDM hub. Systems B/C/C2 feed the MDM hub or are alternatively connected through SOA directly to consumers as an interim solution in order to avoid disruption of service. Since the information of systems C / C2 needs to be migrated to the MDM hub anyway, mapping to and populating the MDM hub in the interim state is preferred to SOA enabling the legacy systems which would be a throwaway effort. We derive an end state (Figure 1, Stage 3) by retiring systems C/C2 and extending SOA integration to include data acquisition to the MDM hub, which depicts how MDM and SOA simplify the integration and improve the consistency of information delivered to consumers. 

The combination of information consolidation through MDM and integration streamlining through SOA has proven to provide drastic long-term cost reductions to IT organizations by eliminating redundant infrastructure and reducing labor training, development and maintenance hours (see Figure 2). Secondary benefits include higher data quality, customer satisfaction and, thus, increased profits. In order to achieve IT infrastructure efficiencies, companies need to start with consolidation of information to a central MDM hub to allow the retirement of the legacy source systems and migration of associated authoring processes under MDM.

• The goals of this data consolidation include: increased data quality, enablement of strategic business initiatives facilitation of SOA integration, improved alignment to business requirements, reduction of data management costs (acquisition, cleansing, maintenance, delivery), and retirement or standardization of legacy systems with associated processes. 
• Critical success factors for the information consolidation include: CIO and business sponsorship, identification of cross MDM domain (or best of breed) SOA-enabled MDM products, an iterative approach with legacy system retirement to offset new architecture costs, roadmap to clarify exponential cost savings achieved at end state, and acceptance of an enterprise cross-domain canonical enterprise schema. 

• Infrastructure simplification is achieved through retirement of legacy hardware, applications and databases, as well as reduced associated product licensing and maintenance (monitoring, upgrades, and patches) of the retired systems. A cost benefit analysis should validate that cost savings exceed MDM investment in the long term.
• Information simplification is accomplished by consolidation of application-specific models into an enterprise canonical schema; a simpler acquisition, maintenance and distribution of master data and metadata; a solid foundation for enterprise information scalability; the enablement of the integration layer to leverage the same canonical model for messaging and Web services schemas; and the simplified security and compliance due to centralization of information in one system.
• Cost savings are attained due to infrastructure and information simplification, and reduction of related labor activities (acquisition, storage, analysis, enhancement, maintenance, troubleshooting, archival and distribution), as well as required training across multiple technologies and development languages or products; and, through the ability to negotiate better rates for resources with standardized skills.
• Customer satisfaction is increased due to better data quality, the improved alignment of solutions delivery to business requirements, and the reduced requirements-to-delivery response time.

• The goals of the SOA-enabled integration on top of MDM include: architectural agility and ability to quickly accommodate business requirements through decoupling consumers from physical implementation and data schemas, MDM amplification through standardized integration acquisition and delivery mechanisms, reduction of integration maintenance through acceptance and leverage of preferred communication methods, and reduction of effort and cost for new integration efforts. 
• Critical success factors for the integration enablement include: identification of mature SOA fabric products that can handle multiple delivery methods (messaging, Web services, enterprise information integration, etc.), and executive business sponsorship (CIO, COO and CFO) with authority to retire legacy integration products and processes. 

• Infrastructure simplification is achieved by leveraging a messaging bus or network architecture versus point-to-point connections, as well as reduced product licensing and maintenance (monitoring, upgrades and patches) due to streamlined integration infrastructure. 
• Integration simplification is accomplished through migration from system-specific integration to the preferred enterprise integration standard product and methods; simpler integration maintenance, monitoring, governance and reporting due to centralized infrastructure; a solid foundation for enterprise integration scalability; and simplified security and compliance due to a single integration solution.
• Cost savings are attained through the infrastructure and integration simplification which encompass reduction of integration-related labor activities and training costs that are no longer required across multiple methods, technologies and products, and increased labor efficiencies once resources build expertise around the standardized integration framework and toolset.
• Customer satisfaction is increased through improved speed of data delivery (near real time) and freshness of data, reduced time to delivery, and a centralized data access area abstracting physical complexities of source systems.

Figure 3

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