Common Misconceptions About Master Data Management

In today’s highly data-reliant business environments, master data management (MDM) is essential. With historically high volumes of transactions sharing data and metadata across multiple systems and applications, factors including human error, inconsistent metadata, and failure to validate requests can negatively impact data quality and outcomes.

Implementing master data management¹ helps ensure your data is accurate, accessible, and trustworthy, and it provides a single source of truth across the entire organization.

7 Misconceptions About Master Data Management

Despite the well-documented benefits of master data management, some organizations resist introducing or increasing the maturity of a master data management strategy. This resistance can be due to several common misconceptions. 

1. Master data management is unnecessary if you have an ERP system.

Enterprise resource planning (ERP) software is an essential tool in many organizations. ERPs run the day-to-day operations of the business, including accounting, finance, procurement, project management, and supply chain processes.

However, there are some things most ERPs can’t do, and that’s where master data management fits in. Master data management solutions enrich your ERP systems’ capabilities by:

• Creating a shared repository of COA segments across finance systems

• Adding attributes

• Setting up business and validation rules

• Creating audit trails and workflow-enabled approvals

• Automating master data creation and maintenance

• Enforcing data governance policies

2. Master data management is a single solution.

Technically, you can implement a master data management tool, but that software is just one part of the overall solution. Master data management technology contributes to an organization’s larger data governance strategy. Together, they protect your data integrity.

Aligning master data management and data governance helps organizations streamline business processes, increase visibility, guarantee auditability, and improve data accuracy across all systems and applications. 

Some organizations have several MDM technical solutions. Each MDM platform has its own strengths and weaknesses when managing a specific type of master data, and it’s common to see an organization use one solution for customer 360 and another for finance master data.

3. Master data management is IT’s problem.

Historically, this was true. Today, IT still plays an essential role in supporting the technical side of a master data management deployment. However, master data management is key to obtaining a unified, centralized, and up-to-date view of data to improve processes, reengineer business models, and increase profitability, 

This requires business stakeholders to be involved from the onset to define requirements and ensure the master data management strategy meets their needs and solves their problems. Creating a transfer of ownership to the business is a critical measure of success when implementing a MDM solution.

4. Master data management will fix all of my data quality problems.

Master data management alone doesn’t ensure the accuracy and consistency of master data, especially when data frequently changes and multiple users are implementing changes to the master data.  Master data management helps automate and streamline end-to-end master data processes, but you need a regularly updated data governance framework  to ensure that the rules and policies meet current business needs.

Applying data quality rules throughout the data lifecycle and validating that the rules have been enforced helps organizations maintain the consistency and accuracy of master data before it is shared across the organization. In most cases, validated master data is a prerequisite to loading data to business systems, and most organizations that run these validations manually (e.g., via Excel or CSV) end up spending hours or days on routine tasks that can easily be automated.

5. Master data management is the same as data management.

Although they sound interchangeable, data management serves a broad function while master data management is one component of data management. Data management encompasses all of the processes needed to design, improve, store, and analyze an organization’s data assets, including:

• Data architecture

• Data quality

• Data integration 

• Data governance

• Data security

• Data warehousing

• Business analytics

• Master data management

Master data management is part of the broader data management strategy that manages how data assets are collected, stored, shared, and deployed. Master data management also ensures that metadata is standardized and accessible to all users and systems.

6. Master data management is expensive.

This misconception comes with a disclaimer: Master data management can be expensive, but doesn’t have to be. Master data management becomes quite expensive when left as a manual and disconnected process.

Like many technologies, SaaS solutions have lowered costs for master data management. In most cases, the cloud eliminates the need for costly hardware, backups, licensing, and storage. There are also code-free solutions on the market that allow business users to support master data management efforts without enlisting help from expensive IT resources.

It’s also important to consider pricing models. Some providers only offer per-node/per-record pricing, which gets expensive—and fast. Other solutions, such as EPMware, provide enterprise licensing with unlimited node count, which is more scalable and cost-effective than record-based subscription models.

7. Master data management is just for huge corporations.

Even if your organization isn’t a giant enterprise, as your business grows and data volume increases, at some point you will need to add technology to keep up. Customers usually realize this quickly because application administrators end up spending hours and days maintaining master data across systems. Typically, business users discover MDM issues when comparing reports across business systems, which is when a frantic push for a solution drives a selection of an MDM technology that may not be in the best interest of all business units. 

When your organization scales up to the level where you are running multiple systems—including ERP, CRM, SCM, and data warehouse—your data must be consistent and accurate across them all or your analytics and business intelligence will suffer. The enterprise-wide need for a master data management solution often occurs quickly, and at an inconvenient time. The best-prepared organizations lead with MDM as a core program to business system administration.  

Streamline MDM with a Unified Solution That Includes Governance

Understanding the facts about master data management is the first step in improving your organization’s overall data quality and accessibility. Implementing a solution that combines master data management with data governance capabilities simplifies implementation so you realize the benefits of your strategy faster. 

Contact us to learn how EPMware’s unified master data management and data governance solution integrates with many of the most popular ERP, EPM, and CPM applications and centralizes your master data so you can enforce data governance standards in real time.

¹ https://www.gartner.com/en/information-technology/glossary/master-data-management-mdm