Today’s organizations rely on many systems, with each containing business-critical information about customers, services, products, suppliers, and other entities. Sometimes, this is a result of organic growth. Other times, it is the result of a merger or acquisition. No matter how many data sources or systems are in play, master data management is important to the business’ success.
The master data collected by these disparate systems is often stored in multiple locations—independent from other systems’ data—and changes made in one location can take time to be reflected in other systems. These data silos create disconnected, inaccurate, and unreliable data sets that your organization relies on to drive business initiatives.
That’s a problem.
Poor quality data is responsible for numerous business failures, including missed opportunities, wasted marketing efforts, ruined customer experiences, and decreased compliance. For example, a lack of data quality can lead to marketing reaching out to contacts who have opted out of certain communications or a salesperson making a mistake in a billing address, delaying receipt of payment.
Over time, poor data quality can have a significant impact on revenue, customer trust, and productivity. Master data management can help.
What Is Master Data Management?
Master data management is a set of processes, tools, and technologies used to centralize information about key entities involved in your organization’s business transactions. Examples of these entities include:
Customers, employees, partners, vendors, suppliers
Attributes, assets, and spare parts
The primary objective of master data management is to create a single source of truth for an organization’s data. This means bringing together data from marketing, sales, supply chain management, and any other processes related to the entities listed above, and making that data available in a single point of reference for every domain and business system.
How to Get Buy-In from the C-Suite
Despite research showing that only five percent of the C-level executives have a high degree of confidence in their organization’s data, it can be difficult to get buy-in from leadership to fund a master data management initiative. In large part, this reluctance comes from not fully understanding how poor quality data impacts almost every corner of the business.
Defining the value and benefits that master data management will deliver to the business can help get key stakeholders invested in the plan. Those benefits include:
Revenue: Accurate data ensures that you send the right offers to the right people at the right time.
Customer experience: A personalized and consistent customer experience across channels increases customer loyalty and boosts sales.
Innovation: New product development is more efficient with accurate customer, supplier, vendor, and employee data readily available.
Time: Accessing real-time data—instead of relying on email and Excel—dramatically reduces the time-to-market for new products.
Supply chain: Centralized information about available inventory, out-of-stock products, and vendor status improves process efficiency and customer service.
Compliance: Accurate audit and reporting data are critical to avoid compliance and regulatory penalties.
How to Succeed in Industry 4.0
The manufacturing industry is in the midst of an evolution. The integration of computers and communication into the manufacturing process that began in the 1990s is now being replaced with advanced automation and smart technology.
The introduction of mobile devices, Internet of Things (IoT), and smart sensors on the production line will be accompanied by high volumes of data. If harnessed properly, this data can drive decision-making, increase efficiency, and reduce waste on a large scale.
This new era of manufacturing technology is known as Industry 4.0, and it is the ideal use case for master data management.
According to Tyler Warden, Vice President of Product at Syniti, data is beyond essential for manufacturers to succeed in Industry 4.0.
“If your data is not consistent, or if a sensor is saying a part is breaking down, but your ERP doesn’t have a consistent understanding of the part or can’t order it, the promise of Industry 4.0 falls apart.”
Warden’s comment, though directed at manufacturing, can apply to master data management in any industry. Here is an industry-agnostic list of the seven core efforts Syniti recommends for successful implementation of a master data management initiative:
Identify and focus only on relevant data.
Categorize data requiring human intervention first.
Arbitrate data-related decisions across business locations and operating units.
Utilize local and global data experts and owners for fast and realistic data-based decision-making.
Include data sourced from throughout the IT landscape, not just enterprise resource planning (ERP) software.
Take an Agile approach to deploy ongoing sprints of data improvement.
Create a meaningful link between business and technical metadata to drive and streamline decision-making.
Improve Data Quality with Master Data Management
Master data management isn’t easy, and it isn’t a silver bullet. But with an ongoing effort to orchestrate processes and enforce data quality, you can be sure that your master data is accurate and trustworthy.
Implementing Master Data Management enterprise-wide can be overwhelming. Take the first steps in understanding who to involve and where to start.
Now that you understand the importance of master data management, it’s time to implement it in your organization. The next step is to decide whether you should take this on yourself or hire a trusted partner. Learn how the Syniti Knowledge Platform can help you master your data.
About the AuthorFollow on Twitter Follow on Linkedin More Content by W. Matt Wagnon