8 Master Data Governance Best Practices for Better Customer Engagement & ROI
Over the past decades, the significance of data has amplified and in today every business operation, be it strategic decision-making or the daily function, is data-enabled. Researchers and data scientists are collaborating on a wider scale and bringing out breakthrough innovations in the space to master the ultimate potential of data in today’s time.
Despite the growing importance of data and its optimal management, there is still room for improvement in the space. There are still challenges of data synchronization, duplication and redundancy and the distributed nature of data across multiple systems within an organization are the key challenge businesses are encountering.
Here, comes the role of master data management and data governance and in short master data governance.
Before we delve deeper, let’s get a grip on the basics first.
What is Master Data?
Master data is an essential core data for business operations, represents the objects in specific businesses or business units and contains the most valuable, noncontroversial information shared across an organization. Master data may vary from one industry to another and even from one company to another within the same industry.
According to thought leaders, Master data is a uniform set of identifiers and extended attributes to represent the fundamental objects of a specific business such as customers, prospects, suppliers, and hierarchies, etc.
What is Master Data Management?
Master data management is the process of creating a uniform set of data on enterprise entities. MDM plays a substantial role in improving data quality by ensuring that the data pertaining to entities remain accurate, consistent across systems and applications as well as update.
What is Master Data Governance?
Master data governance can be defined as the process of leveraging data governance to improve the management of master data.
Why is Master Data Governance Required?
A popular adage cites “the things that can’t be measured can’t be managed”. Measuring the performance of any function, irrespective of its size and complexity is vital for business success. And, most would agree, data-driven insights are an essential component in enabling a holistic view of business operations.
Given the scopes of globalization and technological advancements, several businesses are planning to expand their operational boundaries overseas. With expanding operational boundaries comes an equal load of data to be managed, be it related to customers, clients, partners or suppliers. Businesses need a clear-cut strategy to cater to this multi-faceted data management scenario.
The distributed nature of data is a common phenomenon that can be attributed to business scalability. With multiple and different versions of data, getting a 360-degree view of business operations and to gauge the performance becomes a challenge.
Master Data Governance enables businesses to have a clear perspective on the day-to-day operations and performance KPIs. These performance metrics play a crucial role in shaping the long-term business objectives as well as strategy.
Is Master Data Governance Fail-proof?
Unfortunately, no! There are several pitfalls associated with master data governance such as
- Arriving at a consensus is the prime challenge: As the name suggests, master data governance is not a one member or one team effort. This responsibility lies with several departments within an organization and across multi-layer hierarchies. Deriving a consensus on common master data standards is one of the major pitfalls in master data governance.
- Data integration can be challenging: In the scenarios of business mergers and acquisitions, master data governance plays a critical role. It is responsible for reducing data incompatibilities, streamlining data integration, and ultimately optimizing operational efficacy. However, the challenge of agreeing on standard master data sets among business units can be even greater in the post-acquisition scenario.
8 Master Data Governance Best Practices
Define the Master Data
As we have covered early in the article, master data is a uniform set of identifiers and extended attributes that describe the key entities of an enterprise. The master data can be around the customers, prospects, suppliers, and hierarchies and chart of accounts.
Master data governance must identify and outline the core set of attributes for a master data set. Otherwise, too many attributes in your master data may bring down the efficiency of your master data management process. Defining master data attributes is crucial in ensuring the success of your master data management endeavor.
Lay Out the Internal Policies
To ensure the successful execution of master data governance programs, the stakeholders of MDM must lay out the policies oriented around data quality, privacy and protection, retention and deletion, and risk management.
Set out the Rules from the Onset
Rules are essential in executing and ensuring the successful enforcement of policies, be it internal or external. Businesses may create multiple rules for the execution of individual policies so as to serve the ultimate purpose.
Understanding master data, its source, and clarifying how it conforms to your internal business definitions and policies is critical for master data governance success. This will help reduce overhead costs, accelerate business performance driven by value, and may reduce financial risks involved or anticipated.
Mapping Out the Processes
Process mapping offers a holistic view of the interdependence and transactional nature of master data among the business functions. This offers better visibility of business functions, data usage, compliance risks.
This also enables businesses with the much-required insights to suggest when and where rules need to be embedded to ensure the smooth execution of policies set.
Master data governance offers visibility into the people across organizational functions who are key to the success of MDM activities.
- The data experts determine both standardized master data definitions for the organization and requisite quality thresholds for different business processes
- Legal and security teams ensure the safety, security, and privacy of master data, be it for customers, partners or suppliers
- The data leadership team is responsible for combating data quality issues for specific master data domains
- IT team plays the most critical role as the onus of managing the architecture of databases, applications and business processes lies with them
A proper outline of workflow enables all the stakeholders in the master data governance space to collaborate with ease and effectively.
A robust master data governance system should define the key performance metrics to measure and manage master data. Some of the key metrics are the number of duplicate records, the accuracy and completeness of master data, attribute encryption, etc.
If you are interested to explore more on master data governance, do check out Vinculum’s Vin MDM solution. It is a multi-domain master data management solution that synchronizes business systems to keep the master data clean and consistent across the organization.
It helps businesses derive actionable insights from the data to adapt to ever-changing market conditions and explore new possibilities for boosting business growth and ROI. Request a demo or connect with Vinculum experts today!
Subscribe to our blog and stay updated!