Data strategy reimagined: Leveraging the power of MDM and the Data Maturity Compass™
By: Willem Koenders and Shri Salem
Navigating the complex landscape of data management requires solutions that address the core needs of an organization. That’s why we’re excited to introduce our latest advancement in data strategy: the Data Maturity Compass™ (DMC), with a special emphasis on our new Master Data Management (MDM) module. It is critical to have a fact-based understanding of critical capabilities and key gaps to be able to design and launch a sequenced roadmap to achieve short-term ROI. Organizations that launch into MDM enhancement without having a quantified understanding of their ambitions and current state vs. target state capabilities structurally fail to implement a solution that delivers impact.
The remainder of this article explores how our DMC MDM assessment solution transforms the way organizations approach growing the maturity of their MDM capability in a way that results in the highest ROI.
Importance of MDM in overall data strategy
Before we outline how we can assess the maturity of your MDM capability, let’s unpack why we should do that.
Master Data Management is a pivotal foundation for any organization embarking on its data governance journey. Implementing an MDM solution typically involves critical phases like strategy formulation, data governance framework development, data quality management, and continuous monitoring and maintenance. These steps are essential in establishing a strong governance framework, ensuring the accuracy and reliability of master data, and setting the stage for broader data management practices.
MDM’s significance extends beyond managing reference and master data; it strategically elevates overall data management capabilities. An effective MDM implementation drives value when it aligns with an overarching data strategy, establishing a reliable source of truth for critical business data. This alignment fosters a culture of data ownership and accountability, which is crucial in data governance. Furthermore, the integration of data from diverse sources under MDM fosters strong interoperability and integration practices, essential for seamless data operations across an organization.
Key to the MDM implementation is the focus on data quality, ensuring trust and adoption of the master data across the organization. This focus on quality establishes best practices and standards that can be applied to future data quality efforts. Additionally, robust data security measures are put in place during MDM implementation, setting a precedent for comprehensive data security across the organization. Thus, MDM not only enhances specific aspects of data management but also serves as a catalyst for an enterprise-wide data governance strategy.
MDM’s critical role in contextualizing data
MDM plays a crucial role in contextualizing and leveraging data across an organization. Master data refers to the core information that is essential for the operations of a business. This includes key data related to customers, products, vendors, employees, and other strategic areas. These data elements are used widely throughout various business processes and transactions, forming the backbone of an organization’s operational and analytical processes. Sound master data management is vital because it directly impacts the organization’s use cases and business processes, driving value through improved accuracy, consistency, and reliability of this essential data.
A case study with a major global technology company highlights the critical role of MDM in business operations and strategy. This company faced ongoing challenges with its product data, which was recognized as a major pain point affecting various aspects of its operations. Despite the clear issues, developing a lasting business case for a dedicated platform to manage and ensure the quality of this data was challenging. The breakthrough came when we collaborated with the company’s key business leaders to review their top data-driven use cases, which ranged from market research and marketing campaign optimization to product design and supply chain enhancement. This review revealed that over 50% of these use cases depended, either directly or indirectly, on accurate and reliable master product data.
With many of these use cases tied to significant revenue, cost, or risk factors, the need for a robust MDM solution became undeniable. We quantified that over $100M of additional revenue potential directly depended on it. This demonstrated that the value of master data, and thus the importance of MDM, extended far beyond a single capability. It was intrinsically and explicitly linked to the broader enterprise data and business strategy.
The imperative of assessment in Master Data Management
The journey towards mastering MDM begins with a critical step: assessment. This stage is pivotal, especially in complex organizations characterized by strong demarcations along regional, business unit, product, or data domain lines. Within these enterprises often lie reusable pockets of expertise and platforms, which, if identified, can serve as scalable best practices throughout the organization. Without an assessment, you will not be aware of them, and end up reinventing the proverbial wheel.
For instance, a large medical technology company showcased a mature MDM capability in product data, yet had negligible development in managing customer and employee data. The existing platform — complete with its licenses, standards, processes, and best practices — presented an opportunity for reuse and scaling. Similarly, in a large national insurance company, varying MDM capabilities existed across different business lines. Some were thriving, while others faced challenges. This disparity offered a unique opportunity to align practices and standards through shared learning.
A large insurance company, consisting of various national entities, embarked on their data management journeys in isolation. Recognizing existing platforms and best practices across these entities was crucial to identifying cost-effective solutions for enhancing and scaling MDM capabilities internationally.
Besides identifying existing best practices and reusable capabilities that can accelerate scaling and save costs in new solutions, there is a very practical reason that an assessment is critical. As the next section will show, MDM is not just about a technical platform — there is a wide array of complementing capabilities and processes without which the solution will fail to deliver value. The assessment enables you to identify what the full set of critical capabilities is and the gaps for each of them. This is critical to inform a properly sequenced roadmap as some items are hard prerequisites for others.
Beyond platform focus: Configuration and governance
MDM is often mistakenly perceived as being solely about the platform. Complaints may arise from business or compliance departments, but the information technology department often finds no fault with the MDM platform itself. In most cases, they are correct. The real challenge lies in the configuration of the solution, the data governance and stewardship processes, and the implementation of MDM governance roles and responsibilities across the organization.
Implementing MDM is more than just purchasing and installing a solution. It demands a clear identification of goals, objectives, and success metrics, followed by configuring the related governance process. For instance, business or subject matter experts may be required to configure business rules and thresholds that guide entity resolution, matching, and merging processes. This necessitates identifying roles like data stewards and providing necessary onboarding and training for the personnel in these roles.
An assessment in MDM does more than just evaluate the current state against a desired future state. It provides the granular inputs needed for a tailored, MDM-specific roadmap. This roadmap identifies the precise enhancement initiatives required to increase maturity and their sequence. It is not merely about understanding where the organization stands today; it is about strategically planning how to elevate its MDM capabilities to the next level efficiently and effectively.
Dedicated module for MDM
Recognizing the critical, strategic value of MDM, we have created a separate, dedicated module within our Data Maturity Compass solution to drive and enhance its foundational capability. This MDM-specific module is an extension of the overall DMC solution, which includes automated maturity assessment and real-time roadmap generation across various levels of maturity.
The MDM module delves deeper into the aspects of Master Data Management, decomposing its foundational maturity into several key components:
Master Data Strategy: This forms the apex of the framework, emphasizing the need for a strategic approach to MDM. It involves identifying data assets and trusted sources, and aligning MDM with tactical use cases within the organization. Performance indicators are established to measure the value created by MDM, particularly in areas like marketing and sales campaigns.
Governance: This layer translates strategy into practice, encompassing policies, standards, roles, and responsibilities. It ensures that MDM is implemented effectively, with clear compliance processes and governance forums. MDM governance is designed to integrate with broader data governance frameworks, thus enhancing overall data management.
People, Process, Technology (PPT):
- People: This component involves identifying and assigning key roles like Data Owners, Data Stewards, and Process Owners. It includes defining required skills, providing training, and implementing an adoption program.
- Process: This includes various processes integral to MDM, such as Data Modeling, Metadata Management, Data Quality processes, Data Capture and Integration, Entity Resolution and Survivorship, MDM Remediation, and Sharing and Consumption of master data.
- Technology: Focuses on the technologies and capabilities needed to support MDM roles and processes, including data architecture, workflows, audit trails, and system operations and maintenance.
Implementation: Implementation channels and strategies are outlined, focusing on domains, transformation programs, business processes, and remediation programs. This component emphasizes the integration of MDM principles into transformation initiatives and business processes, ensuring that MDM best practices are observed in every relevant aspect of the organization.
In addition to these foundational aspects, the module includes domain-specific deep-dives. It goes beyond a general platform approach, applying MDM principles to specific domains like Customer Data and Product Data. This allows for a rapid and sector-relative assessment of domain-level maturity, providing a nuanced understanding of MDM’s role in enhancing enterprise-wide data governance and management capabilities.
Closure
The integration of a dedicated, deepened MDM module into our Data Maturity Compass™ encapsulates our commitment to offering solutions that are both driving holistic foundational capabilities and tailored to the unique needs of specific data domains. We are setting new standards in data maturity assessments and enhancements, empowering organizations to harness their data strategically and effectively for optimal business outcomes.
If you have any questions or want to learn more, please feel free to reach out to us (Willem Koenders and Shri Salem).
