Data Quality

What is Master Data Management and Why Does it Matter?

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Every company thrives on data. But what happens if that data differs across your internal systems? 

The ability to effectively leverage customer data—including names, addresses, emails, and account numbers—is integral for creating an ideal customer experience. But when you have information being funneled into your business from a variety of sources, it’s inevitable that your data will eventually become stale and start to vary across your datasets.

Left unchecked, duplicate and incorrect data adds friction to your customer experience and makes it harder for your sales reps to effectively engage your customers. This damages your brand reputation and causes your customers to turn to your competitors for a more seamless, personalized experience. 

The best way to instill trust in your data—no matter which or how many data solutions you use—is by implementing a master data management (MDM) strategy. Let’s explain what master data management is, tips for starting and maintaining an effective MDM strategy, and how to find the best MDM solution for your team. 

What is master data management (MDM)?

Master data management is a process that aims to unify your data across different systems. 

Your data will be different across systems based on the specific need for each data point, how that data was collected, and whether your team has prioritized data maintenance and quality. Following MDM best practices will help your team improve your data quality, make it easier to share data, and ensure that all your teams and systems are working with trusted data.  

MDM generally involves two processes that you can address separately or at the same time: 

Analytical MDM

The goal of analytical master data management is to provide consistent data for data warehouses and analytics systems to store or digest. Down the line, this will improve your company’s decision-making.

Operational MDM

The goal of operational master data management is to ensure data in core business systems is consistent, including in finance, purchasing, payroll, sales, marketing, or other departmental tools. Operational MDM starts where your data is first created—such as your CRM or ERP—and connects these master data sources to other systems within your organization.  

What data should you manage as master data?

How you define master data—which is also called a “golden record” or “single source of truth”—will depend on your industry, business type, and goals. Retailers and ecommerce companies, for example, typically view customer names, addresses, and account details as master data, as well as coupon codes and product pricing or details. A bank on the other hand will typically prioritize account numbers, customer names, and financial products as master data.

The key with MDM is to first understand all of the different types of data you collect and store, and how that data informs your business processes. Start by identifying the data that is most important for your organization and tailoring your MDM strategy to protect that data. 

Why is data quality so critical to master data management?

The goal of master data management is to maintain consistent data across your systems. If you can’t trust your data, you could be reaching out to customers in ineffective or incorrect ways that ultimately hurt your relationships with them.

Data quality is a cornerstone of master data management. Your reps need to understand where data in your system comes from, ways that it may decay in quality, and how to update it. If you fail to preserve your master data quality, then all downstream processes and systems will rely on bad data—leading to unwanted business outcomes. 

Tips for maintaining an effective MDM strategy

It’s easier to implement an MDM strategy than you might think, but it will require a companywide effort to preserve your data quality. Kick off your MDM strategy by following these tips:

Align your data stakeholders

An effective MDM strategy requires you to align your data stakeholders across your departments—including every decision-maker or executive working in your data systems—to agree on how you will structure your master data and the policies for updating it. Designate one or two teammates to lead your initial MDM efforts. From there, they can coordinate with other data stakeholders to nail down your strategy.

Centralize data

Understandably, your data will be stored and used across multiple systems. But it’s important to centralize your data where possible and consolidate any redundant systems or tools. It’s much easier to manage your data if it’s stored in fewer locations. Plus, practicing MDM within a smaller scope will prepare your team for any new tools or systems that might be added later. 

As you embark on your MDM journey, document every system and tool that either stores or uses your data. Use that list to identify possible areas where you can cut back (without sacrificing your quality of service). 

Strengthen data quality

As we discussed above, your data quality is critical to master data management. Regular data cleaning is an effective way to preserve your data quality and continue to refine your MDM strategy. Scrub your existing data before identifying your master data, and regularly train your team on ways to improve your data quality. 

Implement a common metadata layer

A common metadata layer will make it significantly easier to share or integrate information across your business management and analytics systems. Most master data management software (we share tips for finding the right one for your needs below) will make it easy to implement this metadata layer. 

Focus on cybersecurity

Your master data will include sensitive customer details and confidential information that you must protect. Ensure that you’ve implemented data security safeguards to protect the data from the risk of cyberattacks. If you do not have a cybersecurity expert on your team, we recommend that you consult a professional to understand potential security risks when managing master data and best practices for protecting it. 

Democratize access to data

You want everyone on your team to know when and how they should manage your customer data. Provide training and support resources like how-to guides and step-by-step videos that walk employees through MDM best practices and processes. Tips might include how to review and update customer data, signs that data may be low quality, and how to use data to make their jobs easier. 

Things to consider when choosing the right MDM solution

It can feel overwhelming to implement an MDM strategy. But don’t worry—there are data management software and tools that can make the entire process incredibly simple and intuitive. 

As with every business tool, finding the best master data management solution for your team will depend on your unique needs. How many data systems does your company use? How mature is your team in its data strategy? What is your goal for implementing an MDM solution? 

At minimum, we recommend that you explore these key MDM capabilities when assessing your options: 

Advanced integration with services

Arguably one of the most important considerations when selecting a master data management tool is which systems or services you need the MDM tool to integrate with. Your ideal MDM solution should connect with all your critical business systems and other data maintenance solutions, which could include a data cleansing tool. 

Ability to handle various domains on a single technology platform

Some MDM solutions are built to address single-domain needs, such as managing customer data, product data, or employee data. Advanced solutions, however, can handle multiple domains on the same technology platform, eliminating your need to use more than one MDM solution and significantly streamlining the experience for your team. Determine which approach works best for your business.

Flexible deployments

This is where things get technical. You can host your MDM solution on-premises, in the cloud, or a hybrid of both. If you prefer a cloud solution, you can choose between Microsoft Azure, Amazon AWS, and Google, among others. Ask your prospective MDM solution provider to explain the benefits of their deployment options. 

Cloud hosting provisioning and scaling

Depending on your volume of data and potential budget, cloud hosting may be a more efficient solution because you can easily scale up or down based on your needs. Many cloud providers will also offer security capabilities that further protect your data.

Supercharge your CRM with trusted data

The best way to preserve your data quality and make smarter business decisions is to empower all of your data users to understand how to support your master data management. 

The initial lift of scrubbing and tagging your data may take some time, but it’s an essential investment that will give your team a solid foundation to build from.

Looking for more resources to help you manage your customer data? Download our Ultimate CRM Admin Toolkit to help you overcome the latest challenges of CRM data administration.