Why a Master Data Strategy Is Key to Digital Transformation
Find out why deploying an effective master data strategy across an enterprise is an important foundation to building a successful digital transformation journey.
Digital transformation is the “buzzword du jour” in every industry. There have been many initiatives that should have led to a digital transformation across many industries — supply chain integration, global ERP systems, etc. These likely should have prepared us for the digital life. This fell far short in large part to one key element — data. Data is key to any digital transformation journey, but the foundation of all data is master data. Information about materials and products, customers and vendors are the bedrock of a digital framework. However, companies big and small need a strategy to manage that master data before they begin building their digital transformation dreams upon it.
Master data is the core data that gives meaning or context to transactions and data analytics. It can certainly include data that’s defined inside the organization from outside sources — suppliers/vendors, employees, customers, materials/products and organizational data (e.g., companies, business units, plants, consolidating entities). It’ll also include data defined outside an organization, either by industry organizations or other centralized entities (such as governments, ISO or The United Nations). This could include reference data such as country names and codes, state/provincial names and codes, currency codes, UN location codes and units of measure.
Some of this master data relates to other types of master data. Regarding materials and products from within a company, one attribute may be its classification as determined by the United Nations Standard Product and Services Code (UNSPSC). Master data such as this is essential for companies to exchange information between each other as customers and suppliers. Clearly, the geographical information that’s standardized by governments and international standards organizations is critical to determining the addresses and classifications of suppliers and customers (this also helps to determine duplicates.)
What are the key elements?
First and foremost, support (and enforcement) needs to have full management approval and buy-in at the enterprise level. Support from business units is also needed, but it’s secondary to support from the top of the organization. Enterprise support is also vital to the second element, the elimination of data silos, which also allows for a full data inventory. Oftentimes, master data and its processes are locked within business unit silos. These are often system-driven (e.g., global system for customer master data is SAP, but one or more business units have Salesforce CRM with its own customer master data that doesn’t tie to SAP).
By breaking down walls hiding pockets of data a full data inventory can be completed so that rules can be developed and applied. These rules may govern data field requirements, special coding or the definition of a duplicate record. In many cases, the enforcement of these rules can be handled by a centralized master data management or governance tool. Such a tool would capture all required master data and publish to the various systems that require it, giving all such systems a common master data record.
The next element of a master data strategy is data rule definition. This is usually mandated by a management or governance system, but it’s also key to process changes absent any system.
