We’ve entered an era of radical disruption, where industry leaders are leveraging data to discover new sources of revenue and propel themselves past competitors. Yet, for many, capitalizing on their data remains a pipe dream. In fact, Accenture research shows that only 19% of companies excel at maximizing value from their data.
The reason? They’re overlooking a crucial element—effective data management. Without a robust master data management strategy (MDM), you are not only missing out on growth opportunities; but also wasting valuable resources. Additionally, there’s a real risk of losing sight of which data matters and even what is available in your systems.
To prevent such outcomes, we’ve prepared a detailed guide on how to create an effective MDM strategy, so you too can gain a 360-degree view of your most important data assets.
Table of contents:
Master data management is a comprehensive framework that helps organizations manage critical data assets across the enterprise. MDM uses technology, tools, and processes to create a single source of truth—for each person, place, and thing in a business. Once the data is stored and secured in a centralized repository, it can be shared and used by various departments within the organization to streamline operations and ensure consistent data handling.
To understand master data management, you first need to understand the meaning of master data. This data is unique information that describes a business's core entities. Master data is distinct from transactional data (which captures specific business data like sales and purchases) and analytical data (used for reporting). Instead, it represents key business entities such as customers, products, suppliers, or locations critical for day-to-day operations. Here are a few examples:
Customer data: Includes customer-related information, such as personal details, contact info, transaction history, and preferences.
Product data: Contains product information such as specifications, pricing, and lifecycle details.
Supplier data: Consists of data related to suppliers, including contracts and payment terms.
Employee data: Collect information about your workforce, such as different roles, departments, and employment history.
By creating a single source of truth for all this data, master data management ensures consistency and accuracy across all systems. Without proper systems and protocols, users may have conflicting data about the same customer or product, leading to inefficiencies, errors, and missed opportunities.
1. Better insights and decision-making
Master data management gives users the accessibility and visibility they need to see the bigger picture and make decisions grounded in data, leaving inaccurate assumptions behind. When data teams and business users have uninterrupted access to the information they need, decision-making naturally becomes more efficient. Plus, by establishing a trusted and reusable source of data, you empower your data team to model data, predict outcomes, and uncover hidden insights.
Pro tip: You can use advanced augmented analytics solutions like ThoughtSpot to further accelerate the time it takes to generate insights. For instance, by using SpotIQ, you can automatically analyze billions of rows of data and discover new trends and insights on the fly.
2. Reduces errors and inconsistencies
When you make assumptions, especially in the realm of data and interpretation, it can lead to significant failures. A critical aspect of master data management is identifying which data matters and how it will be governed across the organization. With MDM, you can create binding guidelines for data format, quality, frequency, service level, and management, These guidelines and benchmarks set the integrity and reliability of data, leading to fewer errors and inconsistencies.
3. Improved customer experience
Customers today want to feel a personal connection with the brands they interact with. With master data management, you have customer data primed and ready for action. This proactive approach can help your business teams easily resolve customer queries, create personalized interactions, and even identify cross-selling opportunities.
Pro tip: When paired with a modern analytics solution like ThoughtSpot, you can take your CX game to the next level. For instance, analyzing KPIs and metrics can help you identify which marketing channels or strategies drive the most sales and segment customers according. Taking a closer look at customer patterns and behavior will help you refine your efforts and deliver highly targeted campaigns without burning marketing dollars.
For example, using ThoughtSpot Northmill’s team was able to easily access and analyze its user data and find out where people usually stop during the sign-up process. By utilizing this information, the bank was able to make changes to its onboarding process, boosting its conversion rate by a whopping 30%.
Master data management isn’t just a single framework—it’s a dynamic ecosystem of interconnected elements working seamlessly together. Some of the important components include:
Data governance: This framework refers to the policies, standards, and processes that ensure the data is managed properly. Data governance sets the rules for how data is collected, stored, and used across the organization. Following such initiatives promotes data security and ensures compliance with regulatory requirements.
Data quality management: Ensuring high-quality data is essential to the success of any master data management initiative. A data quality program involves identifying and addressing issues such as duplicate records, missing information, and incorrect entries. Regular data audits and validation processes are equally essential.
Data integration: Your data is scattered across multiple systems, departments, and even geographic locations. A master data management strategy outlines how to integrate this fragmented data into a single, unified view. This approach involves which data integration tools you will use, what processes you will follow, and where you will store it.
A master data hub: This process involves creating and managing a centralized repository where master data is stored and managed. With this hub, all departments and systems within an organization have access to the same set of accurate, up-to-date master data.
Workflow and business processes: MDM is not just about technology; it's also about ensuring that the right processes are in place for managing data across its lifecycle. Workflows help define how data is created, updated, validated, and retired within an organization.
To build a golden record that contains the most up-to-date information, you must integrate data from every business unit into a single repository and update it regularly as more information becomes available. However, remember that the journey to excellent master data management is incremental, and each small step requires careful planning and following best practices. With that said, here are seven steps you need to follow to ensure your golden records remain accurate and reliable:
Data discovery: The first step is identifying what data needs to be managed. This involves cataloging master data across the organization and assessing its current quality, completeness, and accuracy.
Data standardization: Once the data has been identified, you need to standardize it. This process includes setting consistent formats, creating clear metadata definitions, and setting uniform standards for various data elements.
Data cleansing: In this phase, errors in the data are identified and corrected. It is important to remove duplicate entries, fill in missing information, identify outliers, or update outdated records to maintain data integrity and reliability.
Selecting a master data hub: Choose a centralized repository that allows organizations to store large amounts of structured and unstructured data. This type of storage should offer the flexibility to store all types of master data so it can be accessed, analyzed, and managed quickly and easily.
Data integration: Outline the different tools and steps you will follow to integrate data from multiple sources into your master data hub. Doing so ensures all systems and departments can access the same, up-to-date data.
Data governance: Next, create and enforce governance policies and processes to manage the ongoing quality and integrity of the data. It is also important to assign a solid team of individuals—often composed of leadership—who decide on the strategies, protocols, and standards that define how data governance is actually implemented across the organization.
Ongoing monitoring: Establishing master data management is not a one-time effort; it requires continuous monitoring and maintenance. Regular audits, validation processes, and updates help ensure that master data remains accurate and reliable.
Businesses are bracing themselves for an era of supercharged productivity and innovation sparked by GenAI. However, as companies take bold steps into this new world, many find they do not have a solid and reliable data management foundation to support a culture of innovation. To create a value-driven data management strategy, you need an augmented analytics solution that not only offers accessibility but also enhances the speed and accuracy of insights.
Leading in AI-Powered Analytics, ThoughtSpot offers a powerful search experience that allows users to identify and integrate important data assets. With Verified Liveboards and advanced data governance controls, you have the security and visibility you need without impeding collaboration. Even better, your entire team—business users included—can easily access and visualize real-time data and find all the answers they need without relying on IT or data teams.
Experience how ThoughtSpot’s AI-Powered Analytics can help you turn your master data into a valuable business asset—request a live demo.
