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What are the most effective ways to ensure buy-in for master data management?

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Master data management (MDM) is the process of creating and maintaining a single, consistent, and accurate source of truth for key business data, such as customers, products, suppliers, and locations. MDM can help data engineers improve data quality, reduce data duplication, streamline data integration, and enable data governance. However, MDM is not just a technical project, but also a business and cultural change that requires buy-in from various stakeholders across the organization. How can you ensure that your MDM initiative gets the support and commitment it needs to succeed? Here are some effective ways to ensure buy-in for master data management.

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Suraj Jaiswal

Data Engineer at adidas
Sandra Vázquez

Especialista Datos Maestros | MBA| Green belt | Ing Biomédica
Mohamed Farahat

Data & Software Engineer | MERN Stack Developer | MSc @ WQU | McKinsey Forward Program Graduate | Young Think Tank…

1 Define the business value

Before you start your MDM project, you need to clearly define the business value and benefits that it will deliver. This means identifying the key business drivers, goals, and metrics that MDM will support, such as increasing customer satisfaction, reducing operational costs, enhancing compliance, or enabling innovation. You also need to quantify the impact and ROI of MDM, such as how much it will save, generate, or improve in terms of revenue, efficiency, quality, or risk. By defining the business value, you can align your MDM project with the strategic priorities and expectations of the organization, and communicate it effectively to the stakeholders.

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Suraj Jaiswal

Data Engineer at adidas
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- Define clear business objectives and benefits of master data management - Identify key stakeholders and involve them in the planning and implementation process - Establish data governance policies and roles to ensure data quality and consistency - Provide training and support to data users and data stewards - Demonstrate the value and impact of master data management through metrics and use cases

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Mohamed Farahat

Data & Software Engineer | MERN Stack Developer | MSc @ WQU | McKinsey Forward Program Graduate | Young Think Tank Innovator @ YBY
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Beyond revenue and cost savings, consider the cultural impact. In a global tech firm adopting MDM, the business value extended to fostering a data-centric culture. Employees at all levels embraced data-driven decision-making, creating a ripple effect that transcended the initial financial gains. This cultural shift became a significant, often underestimated, outcome of their MDM initiative

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2 Identify and engage the stakeholders

MDM affects multiple departments, functions, and roles within the organization, so you need to identify and engage the stakeholders who will be involved in or impacted by the MDM project. This includes the executive sponsors, who can provide the vision, direction, and resources for the project; the business owners, who can define the business requirements, rules, and processes for the master data; the data stewards, who can ensure the data quality, consistency, and governance of the master data; and the data consumers, who can use the master data for their analysis, reporting, or decision making. By identifying and engaging the stakeholders, you can understand their needs, expectations, and challenges, and address them accordingly.

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Sandra Vázquez

Especialista Datos Maestros | MBA| Green belt | Ing Biomédica
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Involucrar tanto los Data Stewards así cómo los funcionales o personas que están en la área operativa. Aquellas personas que siempre están en la operación ayudarán a resaltar hallazgos que ayuden a definir los datos maestros y que obstáculos tienen a la hora de usarlos y entender mejor cómo se mueven los datos, esto ayudará a tener una mejor visión de cómo garantizar la calidad de los datos.

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Mohamed Farahat

Data & Software Engineer | MERN Stack Developer | MSc @ WQU | McKinsey Forward Program Graduate | Young Think Tank Innovator @ YBY
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Real World Scenario: In a healthcare setting, the engagement of clinicians, administrative staff, and IT professionals becomes pivotal during MDM implementation. Picture a scenario where a data steward collaborates with clinicians to enhance patient data accuracy. This collaboration ensures that medical histories, treatment plans, and billing information align seamlessly, optimizing both patient care and administrative processes.

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3 Establish a governance framework

MDM requires a governance framework that defines the roles, responsibilities, and policies for managing the master data throughout its lifecycle. A governance framework can help you ensure that the master data is accurate, complete, consistent, and compliant with the business rules and standards. It can also help you resolve any data conflicts, issues, or changes that may arise during the MDM project. A governance framework should involve the stakeholders from different levels and domains of the organization, and provide them with the authority, accountability, and collaboration mechanisms for the MDM project. By establishing a governance framework, you can ensure that the master data is trusted, reliable, and usable for the organization.

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Mohamed Farahat

Data & Software Engineer | MERN Stack Developer | MSc @ WQU | McKinsey Forward Program Graduate | Young Think Tank Innovator @ YBY
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One of the challenges in implementing an MDM governance framework lies in balancing flexibility and control. For instance, in a multinational corporation, ensuring a consistent customer data governance approach across diverse regional offices poses a challenge. The governance framework needs to be adaptable to regional nuances while maintaining a standardized approach for global data integrity.

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4 Implement an iterative approach

MDM is not a one-time project, but a continuous process that evolves with the changing needs and demands of the organization. Therefore, you should implement an iterative approach that allows you to deliver incremental value and results with your MDM project. An iterative approach can help you break down your MDM project into smaller and manageable phases, such as defining the scope, designing the architecture, developing the solution, testing the quality, and deploying the master data. It can also help you get feedback, validation, and adoption from the stakeholders at each phase, and make adjustments and improvements as needed. By implementing an iterative approach, you can ensure that your MDM project is flexible, agile, and responsive to the organization.

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Mohamed Farahat

Data & Software Engineer | MERN Stack Developer | MSc @ WQU | McKinsey Forward Program Graduate | Young Think Tank Innovator @ YBY
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As a use case, consider an iterative approach in a retail chain implementing MDM to consolidate product information. Each iteration could focus on a specific product category. This phased approach allows the organization to address unique challenges related to different product types, from clothing to electronics, ensuring that the MDM system is finely tuned to the intricacies of each category.

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5 Demonstrate the outcomes and benefits

Finally, you need to demonstrate the outcomes and benefits that your MDM project delivers to the organization. This means measuring and reporting the key performance indicators (KPIs) that show how MDM supports the business drivers, goals, and metrics that you defined earlier. It also means showcasing the success stories and best practices that illustrate how MDM improves the data quality, integration, and governance for the organization. Additionally, it means celebrating and rewarding the achievements and contributions of the stakeholders who participated in or supported the MDM project. By demonstrating the outcomes and benefits, you can ensure that your MDM project gets the recognition, appreciation, and endorsement it deserves.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What are the most effective ways to ensure buy-in for master data management?

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3

4

5

6

1 Define the business value

2 Identify and engage the stakeholders

3 Establish a governance framework

4 Implement an iterative approach

5 Demonstrate the outcomes and benefits

6 Here’s what else to consider

Data Engineering

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What are the most effective ways to ensure buy-in for master data management?

1

2

3

4

5

6

1 Define the business value

2 Identify and engage the stakeholders

3 Establish a governance framework

4 Implement an iterative approach

5 Demonstrate the outcomes and benefits

6 Here’s what else to consider

Data Engineering

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