Master data is the core of an organization’s systems; it is the central entity around which the business of an organization revolves. Inconsistencies in master data affect business and IT functions in terms of operational efficiencies, customer management and infrastructure optimizations.

Though organizations are striving to manage master data as an enterprise asset, unfortunately the success of master data management programs is quite low. Successful MDM requires strategic planning and vision plus executive sponsorships and buy-in of key stakeholders. The organization should also ensure that MDM is a business-led initiative and should jointly be owned by business units and the IT department.

The objective of this MDM maturity model is to assist organizations in assessing their current MDM capabilities and to help define the future state of MDM. It shapes the roadmap for MDM with distinct phases of maturity and the way to acquire missing capabilities. This maturity model offers a schematic approach to define and prioritize MDM activities toward stepwise improvement of the organization’s MDM maturity.

Levels of Maturity

In general, organizations need to follow a sequential step-by-step approach toward MDM maturity. However, new organizations with evolving business and IT applications can plan to build MDM while creating their operational systems. These organizations can try to achieve the higher levels of maturity right off the bat.

There are six distinct levels of MDM maturity.

Level 0: Ignorant (No MDM, Unaware of MDM)

Symptoms: This level may be viewed as the pre-MDM stage. At this stage, the organization is unaware of MDM terms, values and needs. Typically, individual business groups suffer from data quality and consistency issues. Day-to-day operations run with inaccurate and incomplete master data. Analytic processes run on outdated master data sets. Manual, expensive and time-consuming processes are being followed toward data reconciliation and integration.

Actions to be taken: The organization should initiate an MDM awareness program. Educate business and IT groups on the need for and benefits of master data management, data quality and data governance. MDM success stories should be discussed, and external faculty/thought leaders may be invited to discuss the MDM journey, benefits and best practices.

Level 1: Initial (Awareness of MDM)

Symptoms: At the initial stage of an organization’s MDM maturity, the organization is aware of its master data issues and how they affect business processes; however, what is lacking is the capabilities aspect. While the need for MDM, data quality and data governance is recognized, there is a lack of clear vision and strategic direction, and no buy-in from CXOs. Funding and executive sponsorship are the major challenges. Data ownership and governance are missing. Data quality initiatives are run in a fragmented and distributed manner. A centralized repository for data and processes does not exist.

Actions to be taken: The organization should continue with MDM awareness initiatives and try to propagate MDM concepts to all groups and levels. Organize one-to-one session with CXOs, executive sponsors, business and IT leads. Closely link MDM with business issues and enterprise data problems. MDM should be defined as the core component of the organization’s enterprise information management landscape. Establish correlation between the MDM program and organization goals.

Level 2: Isolated (Isolated MDM Initiatives)

Symptoms: At this level, there is recognition of problems arising due to duplicate master data and its effect on the business. As a result, reactive/firefighting attempts to resolve the issues are undertaken. Various business and IT groups in the organization are engaged in these isolated reactive data management initiatives. Enterprise-level initiatives are lacking; duplication of effort/initiatives exists across the groups.

Some attempts are made to fix data quality issues at an individual application level, tools are evaluated and purchased but still are managed as technical resources. The IT department often takes the lead and struggles to get the business engaged in this journey of MDM.

Actions to be taken: Create a business case for department/group-level MDM; look for some business issues that can be solved using an MDM or data quality management program. Try to connect the various business and IT groups engaged in isolated MDM and data quality initiatives. Inject the need for a common data governance framework so that different groups can interface and decide a common strategy to deal with master data and data quality issues.

Level 3: Organized (Planned Siloed MDM Initiatives)

Symptoms: At this level, there is serious focus on particular master data domains or use cases and proactive initiatives are launched to build siloed MDM for broader audiences. (For example, MDM to support the analytics, product information management to support supply chain, etc.)

CXOs advocate the need for MDM and recognize it as a key enabler; needs are clearly stated for a single view of the customer or product to improve the accuracy/effectiveness of business processes (for example, customer data integration for better customer relationship management and analytics, PIM to improve the order-to-deliver cycle, etc.).

Also at this level, a strategy has been outlined for use case/domain-based multiphase MDM implementations, and a business value-driven MDM roadmap is defined. There is a clear business-driven MDM initiative in place, and the business understands that it must take ownership and the lead in CDI and PIM initiatives. An MDM charter has been created and a program director is appointed. Data profiling and analysis has been done to understand the commonalities and divergence of the master data and its associations with the business processes. Overall, master data quality has been analyzed and key metrics have been defined to measure the quality of master data on an ongoing basis. MDM governance and stewardship structure has been established to support the MDM-related policies and decision-making. The governance and stewardship structure is evolving and in an initial stage of maturity.

Actions to be taken: Complete quick-win projects/pilots and realize business benefits and ROI. Spread the message of the business value of MDM and increase the overall acceptance. Get sponsorship for specific data domains and use cases, which is the next level of the MDM program. Evaluate and chose the right MDM tool and systems integrator partners, collaborate with other MDM groups and adopt the best practices to success. Effectively manage the politics associated with MDM, and enhance governance and stewardship.

Level 4: Unified (Enterprise-Level MDM Initiatives)

Symptoms: At this level, a unified, enterprise-level MDM strategy has been defined and established, MDM is top priority on the CXO’s agenda and executive sponsorship and funding is available to run the MDM program. MDM capabilities that span across data domains and use cases have started as part of a multiphase MDM program. MDM is recognized as a transformational initiative and viewed as the key step for an enterprise information management program. Existing siloed MDM initiatives are brought together and are governed by the enterprise-level MDM vision. A roadmap has been defined for phased migration from the legacy/old technology to the MDM hub on a business-case basis. A master data management competency center has been established to support ongoing multigenerational MDM programs. People, policies and processes have been centralized. A CDI and PIM reference architecture has been defined, and policies have been stated for data integration, data exchange, data synchronization and data quality management, etc. A shared technology infrastructure has been established to optimize the cost and increase usability. Enterprise-level MDM governance and stewardship is in place, with all key decisions being taken by the MDM governance council.

Actions to be taken: Operationalize the enterprise-wide strategy for MDM. Identify master data subject areas and implement MDM at the organization level (for example, a CDI solution to support party management at the organization level or a PIM solution to support the global data synchronization). Consolidate the siloed MDM implementations under the enterprise MDM framework. Enhance MDM competency center capabilities and make it the focal point for MDM initiatives. Make sure that common architecture and policies are being followed by all MDM projects.

Level 5: Optimized (Final Stage of MDM Maturity)

At this level, the MDM hub acts as the central repository and shares accurate, consistent and complete master data with different applications. MDM is recognized as a core enterprise application, and master data governance is in effect across the business units.

Applications are integrated through the service layer (service-oriented architecture andWeb services) with the master data hub. Master data synchronization and data quality management are embedded within the components of the MDM Hub. The MDM environment acts as the system of record/system of reference for master information. Managing master information through the MDM hub is a part of organizational culture. MDM capabilities support the ongoing enterprise information management journey. The MDM environment is being actively utilized by various operational and analytic systems.

Actions to be taken: Sustain MDM maturity, and look for opportunities for improvement. Make sure that MDM maturity is directly linked with business benefits. Ensure that there is uninterrupted sponsorship and funding to run the MDM program. Establish a feedback mechanism for periodic review and enhancement of MDM environment. Metrics should be defined to calculate the value and ROI realizations. A periodic review should get organized with the executive sponsors, business/IT heads and governance council.

Gauge Your Organization’s MDM Maturity

Figure 1 (see PDF below) provides the characteristics of different levels of MDM maturity against predefined parameters. This can help in making a quick assessment of the organization’s MDM maturity.

In the past couple of years, we have seen a strategic shift in the organizational vision toward MDM. MDM is recognized as a transformational initiative, and there has been rapid adoption of MDM by industry streams. Organizations are striving hard to enhance their MDM maturity to achieve a single version of the truth of master information. There has been increasing investment in MDM-related technologies, and many organizations are moving from home-grown MDM to sophisticated commercial off-the-shelf based environments.

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