Part 1: Why do I need Master Data Management?
What is Master Data?
The data within an organization that should be considered master data usually occurs within one or more of these categories:
- Data that is used by multiple departments or entities in the organization. For example, the chart of accounts and product catalog will be used by accounting, sales, and order fulfillment teams.
- Data that is required by multiple applications or systems. Again, the chart of accounts will be used by ERP, EPM, and analytics applications.
- Data that creates relationships between other data elements. An example of this is a list of regional locations, which would connect data about personnel, sales, and expenses. This sort of master data allows the slicing and dicing of other data, to reveal new insights.
- Data that is critical to the functioning of the organization. This can be thought of as the minimum data that must be input when recording an order or a new customer.
Master data is usually recording an object, not an action. So, the unique ID of a customer is master data, whereas the record of the customer’s orders is not. Similarly, an entry in the chart of accounts is master data, but the transactions carried on for that entry are not. It is also the case that not all the attributes of a master data entity are master data because not all of them are essential. The individual’s name is an essential part of a customer contact record, but their date of birth might not be. A task in setting up a master data management solution is to determine what data is essential for your business.
Why is Master Data Management Important?
Two key requirements for master data are consistency and uniformity. Consistency means that data formats must remain constant across all systems that use the data. If an account code is numeric in the accounting system, it must not be alphanumeric in the forecasting system. Uniformity means that datasets must be the same in all systems. If the product catalog in the stock control system does not use the same ID codes as in the invoicing system then information from the two systems cannot be consolidated on a single report. Consistent and uniform master data is often referred to as “a single version of the truth”.
As organizations grow, achieving consistency and uniformity of the master data becomes increasingly challenging. The number of applications in use across the organization increases, and they may not all use the same data formats - making it harder to maintain consistency. Mergers and acquisitions create challenges for uniformity because different businesses will have different conventions for identifying data. Added to this is the increasing use of external datasets such as geospatial data to enrich the data generated by internal systems, presenting challenges to both consistency and uniformity.
When master data is inconsistent and variable, organizations experience numerous problems. Without a single version of the truth, data becomes inconsistent and can no longer be relied upon for decision-making and forward planning. Automated systems rely on consistent and predictable data, so when that is not present organizations increasingly rely on expensive and error-prone manual data manipulation. The lack of effective data governance that stems from unreliable master data creates problems of accuracy and security.
It is important that organizations establish a proactive policy of Master Data Management. MDM is not an application or a tool; it is the creation and operation of an accurate, reliable, and secure datastore providing master data to the organization’s key business processes.
In our next post, we’ll look at the steps necessary to create a successful Master Data Management process.