Every organization has some form of “master data.” Whether the information is about customers, products, parts, suppliers, business units, chemicals, material, equipment or other factors, this data is the lifeblood of your organization. The data contained within a master data collection is highly visible in its final form and used throughout an organization by way of invoices, statements, packing slips, warehouse inventory lists, marketing catalogs, supplier listings and customer information. The challenge many organizations have is that their staffs may not recognize this type at information as master data. Master data touches every functional group, including the executive team, legal, finance, human capital, marketing, transportation and logistics, and facilities.
Master data not only consists of data elements viewed or recognized by the end user, it also contains metadata (data about the data) that often acts as the differentiator between what appear to be duplicate data entries. The exposure and proper management of the metadata must be communicated to the organization because removal of what may appear to be a duplicate entry of the master data could prove to be very costly. Secondary or associated data is another element often overlooked when organizations begin to manage their master data. This secondary data is often referred to as the “child” portion of the “parent-child” data relationship. The child data is information that further defines the “parent.” For example, for an online order, the customer name, address and account number comprise the parent data. Different types of child data would include credit card, logon and password information, as well as a list of the items purchased, dollar amount, conversion rate, date of purchase and credit card posting date. If validation rules addressing the management of secondary data are poorly designed, the results could be costly. Examples of poorly designed rules might specify to delete all primary data sets if no secondary data is present or if a customer’s password has not been accessed in 18 months. Master data with such high exposure requires a strong governance program. Everyone within the organization, as well as third-party suppliers, contractors, etc. are responsible for maintaining its integrity, accuracy and longevity. A governance program provides strategic leadership for an organization by setting the direction for collecting, maintaining and protecting its master data through a series of policies, processes, training and audits.
Methods of Management
Many organizations house master data in various databases and/or software applications, ranging from the very simple to extremely complex. Consequently, managing this data can become extensive and resource draining. The need for management must go beyond simply ensuring that the data is complete and correct - it must be part of the overall governance of the organization. Master data housed in multiple applications and databases requires a very stringent method of management and a commitment from all who have access to any piece or combination of the data. It requires strict accountability, access controls and authorization levels for the various access points of the data. When housed in multiple locations, the data is passed from point to point, depending on the coding instructions. It is possible that authorized individuals will alter data after it appears in its “final format.” What rules are in place to monitor and validate changes in the final format? Is there a process to maintain configuration control, that is, track these changes back and alter the data in its original location? If not, additional data is being created, adding to the proliferation master data - and providing a false statistics base for making business decisions.
Many articles have been written recently promoting master data stored in a centralized repository. This may not be feasible for some organizations because of infrastructure, cost or resource availability. However, decentralized and centralized data repositories face common challenges. These include extensive data cleansing and validation of all components, which takes time, resources and commitment from the organization. Data redundancy occurs with data backup and archival practices; protections and restrictions on duplicating sensitive data such as credit card numbers, passwords, and individual financial information cause additional challenges. Privacy protection acts such as the Patriot Act, Fair Credit Reporting Act, European Privacy/Data Protection Directive, HIPAA, and the Australian Information Privacy Principles are more requirements to consider. In some instances, the subordinate or child connection data may outlive its usefulness and be removed prior to the parent. This may result in an “orphaned” dataset during data cleansing or validation.
Many organizations do not include master data management (MDM) as part of their records management program. In more cases than not, master data is the product (for example, invoices, catalogs and marketing material) managed within a records management program. Managing “structured data” may not even appear on the records manager’s radar because structured data is traditionally regarded as the IT department’s territory. A comprehensive records management program should comprise the management of electronically stored data that includes master data.
