Master Data Management: The What, Why, Who and How
By Nicole Higle/
April 27, 2017

It is day three of driving a brand-new, shiny SUV around town when the letter carrier delivers an unexpected letter from an unfamiliar tire manufacturer. The letter explains the tires on which the oh-so-pretty SUV sits have been observed to unexpectedly explode when travelling at high speeds. After remembering going eighty-five down the highway in a rush to get to work yesterday, the following question arises – how do tire manufacturers determine who is driving on their tires? The answer – Master Data Management (MDM).

What is MDM?

MDM is a process-based model used by companies to consolidate and distribute important information, or master data. The idea is to have an accurate version of master data available for the entire organization to reference.

Master data is the agreed-upon core data set of a business. As opposed to reference or transactional data, which could be something as mundane as the amount of invoices completed in a day, master data refers to data directly linked to the meat of a business.

Master data varies depending on the organization and industry, but typically includes detailed information about vendors, customers, products, and accounts. Master data is critical, because conducting business transactions without it is near impossible. Without first establishing product codes for a particular model of tire, the manufacturer would not be able to track which tires are sold to which customers.

Why is MDM Important?

In the example above, the only way the tire manufacturer would have the correct customer information for the owner of the new SUV is if the dealership gave it to them. And you can already see why maintaining a database of all their customers is important. Sure, they might inundate their customers with flyers and ads in the mail, but wouldn’t you appreciate the notification about potential tire explosions?

Managing master data is important, because business decisions are based on the story the company’s data is telling. Even the simplest of errors in master data will trickle down, causing magnified errors in other applications utilizing the flawed information.

Companies with non-existent or underdeveloped MDM processes often encounter finger-pointing and displaced blame as a result of data discrepancies. Data discrepancies can be seen when month-end sales reports are delivered with conflicting data in the accounting systems and manufacturing systems. Discrepancies make it difficult to determine which system, if any, has the most accurate information.

Who is Responsible for MDM?

MDM is often mistaken for data quality projects or technology systems owned by IT. Although IT may be involved in the distribution of master data, there is not one sole owner of MDM. To be successful in maintaining the integrity of critical company data, there must be a company-wide effort and to the ongoing maintenance of master data.

It is important to clearly define ownership of the components of MDM including: establishing data governance (standards around how data is used), creating an MDM strategy, and developing procedures for maintaining and distributing information to the people who need it.

A successful MDM program should include holding people accountable for maintaining master data and streamlining the sharing of critical data between departments.

How Do I Create an MDM Organization?

Improper maintenance of master data causes reporting inaccuracies and can lead to poor business decisions. The steps below should be followed to establish an MDM organization:

  1. Define which data is master data—products, customers, vendors, etc.
  2. Determine primary data sources and consumers—the CRM system owns the customer master list which is owned by the credit department and used by sales team.
  3. Designate ownership of each master data set—the AP Clerk is responsible for entering and updating vendor information.
  4. Develop data governance processes—all new product information requires review/approval from the management team prior to product entry into the accounting and manufacturing systems.
  5. Design necessary tools and workflows—technology can be implemented to help automate approvals and the flow of information.
  6. Deploy processes for maintaining master data—businesses can create templates and enforce procedures to capture requested master data updates.

Organizations large and small are faced with data challenges. Occasional focus on cleaning up critical data is not enough. Creating a comprehensive MDM strategy is the starting point to having confidence in company data. Avoid the pitfalls of poorly maintained master data by establishing processes to manage the creation of new master data and enforcing everyday practices to maintain the data over time.


Trenegy is a management consulting firm equipping energy and manufacturing companies for growth and change.