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Master Data Management

The role of master data management in data governance

In today’s digital economy, data management assumes more importance than ever before. Businesses need data to drive digital transformation, improve processes and find new sources of revenue in order to achieve a competitive advantage. Organisations need to pay attention to the quality and relevance of data. Handling colossal amounts of data from disparate sources and gaining a centralised view for decision making requires a data governance strategy.

Master data management (MDM) helps to create a single source of truth by ensuring that data for all business entities across the enterprise remains consistent and accurate. Master data is essentially the non-transactional data for business entities that are used across the enterprise. It comprises the data of the core assets of the business. For example, products, suppliers, customers, locations, and the chart of accounts are business entities. Master data is comparatively smaller in volume as compared to transactional data. However, it is, in fact, more complex and the most valuable, as it lays the foundation for effective data governance and decision making. For instance, accurate information about customers helps the marketing team understand the target audience better, and accordingly create effective marketing campaigns that appeal to the core customer base.

MDM can add value to data governance practices as it helps with the standardisation of data and integration of data across disparate sources. Implementing MDM increases data consistency for operational purposes and analytics. For instance, customer service executives always see accurate shipping addresses. Business Intelligence (BI) applications can access data across different domains with multi-domain MDM, resulting in a holistic view of business leader dashboards. Implementing MDM also helps with regulatory compliance requirements for businesses. Using MDM improves the quality of data, which helps with the overall metrics regarding data quality.


Data governance with MDM

Data governance is all about having a trusted source of data.  This can be accomplished with standard MDM practices that lead to high-quality data.

Organisations should identify all business entities and their attributes to create master data definitions. Each of these business entities is a domain in MDM. These domains vary by industry. For example, an insurance enterprise may have agents, customers, assets, locations, and partners. A manufacturing enterprise may have suppliers, materials, products, equipment, and so on. For a successful MDM implementation, enterprises need to specify the master data definitions. These define the entities and the respective attributes for each domain. For example, in an insurance enterprise, the various attributes for the “Agent” entity may be the agent code, name, business address, business phone number, licence number, etc. Defining entities and attributes ensures that data for each domain has the same attributes across disparate systems and applications and can be easily assembled whenever needed. The master data catalogue should store domains, attributes, and their relationships, along with information regarding their storage locations  – on-premises/cloud –  and the applications in which they are stored. This information can be used during data integration for analytics. It is also useful from a compliance standpoint. MDM data policies and rules establish the regulations that need to be adhered to when using and accessing the data. These include regulations around the definition of data, data privacy, protection, and any specific policies related to the various data domains. MDM policies also help organisations stay compliant with external regulatory requirements. MDM data rules enforce the policies. For example, to enforce a data privacy policy, the company would require specific consent from the customer to share data with a third party as needed by the business.

To manage the master data, enterprises must also define MDM stakeholders and workflows. Stakeholders are the groups that are responsible for managing the master data. These include the IT and security department which manages the MDM solution*, business folks who define MDM rules and policies, the legal department that specifies regulations and compliances to be followed, data stewards to ensure high-quality data and business leaders across functions who are invested in data governance. The MDM workflows define the rules for creation, modification, and deletion of master data, and help to improve productivity when coordination is required between multiple stakeholders. For instance, onboarding a new partner may require collaboration between teams, vendors, and the legal department. Well-defined workflows ensure that the master data is vetted by all stakeholders after all the processes are followed, which ultimately leads to a single source of truth.

Effective data governance requires tracking the movement of data to understand the consumers of the data, and the purpose it is being used for. These help with compliance, as well as understanding how to optimise business processes, and use artificial intelligence-based automation. Defining MDM metrics helps to keep track of the effectiveness of MDM practices in data governance.

In a dynamic and digital world, data-driven decisions are increasingly critical for businesses. MDM can be foundational to data governance success, helping drive organisational growth and transformation.

*For organizations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed on organizational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like a living organism, will be imperative for business excellence going forward. A comprehensive, yet modular suite of services is doing exactly that. Equipping organizations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organizations that are innovating collaboratively for the future.


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