Master Data Management

All you need to know about combining MDM and data governance

Data is the lifeblood of a business and empowers various business domains. A report on data fragmentation pointed out that optimised data organisations derive more than twice the business value from data. However, a recent Forrester research revealed that 41% of business leaders find it extremely challenging to make data-driven decisions. To create easily accessible and reliable data, businesses need to adopt a combination of master data management (MDM) and data governance to ensure accuracy and trustworthiness.

What is master data governance?

Data governance is the process of ensuring the integrity, security, usability, and availability of data in your business systems. It establishes definitions, sources, methods, policies, rules, measurements, and people to improve data management. Thus, it creates an important master record of vital business aspects in the form of a ‘single version of the truth’ or the golden record.

The importance of master data governance

Transparent and high-quality master data is vital for revenue growth, operational efficiency, risk and compliance management, and digital transformation.* However, a recently published report on data management states that almost 78% of companies believe that they are losing business value due to poor governance of data assets, although 85% understand that data is one of their most valuable assets. As such, data governance assumes significance due to the following factors:

  • Master data governance strategy derives value and improves efficiencies of processes by mitigating duplicity and reducing errors, thus saving time, effort, and money for your business.
  • Data governance establishes clear definitions regarding core data and the rules that govern how data is collected, stored, retrieved, and updated. Over time, it results in increased competence.
  • Data governance ensures efficient risk management and compliance. Changing global regulatory compliance scenarios require organisations to take their data security more seriously, comply with privacy norms, and monitor timely changes without errors.
  • Good data governance provides clarity and assurance that all data is trustworthy, standardised, and accurate. It speeds up the deployment of tech-driven models such as AI and ML to streamline the digital transformation of a business.

Key benefits of master data governance

To be able to answer a simple question such as ‘Who are my most profitable customers?’, organisations need to collect customer data from multiple channels within the enterprise, analyse the products they buy, the costs involved in sales and marketing, and calculate the revenue. In the case of multinational companies with subsidiaries, this process is even more complex. Master data governance helps businesses to actively manage and control data by setting up processes, policies, standards, and procedures in place to ensure that data is accurate and consistent, along with a few benefits, such as:

  • Standardising processes for MDM to deliver better insights for decision-making
  • Addressing data quality issues in dealing with inconsistencies, security, and integrity of the data
  • Creating a clear, documented process for dispute resolution
  • Increasing scalability and centralising control to reduce data management cost
  • Assuring security and privacy through monitoring and reviewing policies
  • Driving quick coordination thanks to an optimised multi-domain MDM
  • Encouraging clear and transparent communication across the business

MDM versus master data governance

MDM and governance are two different aspects of data management. Yet, they must be closely aligned to create a unified view of all business entities. MDM includes processes that involve creating master data and its disposal, while data governance defines the rules of the operational processes within the process systems. Data governance and stewardship frameworks are essential for efficient MDM because they assist, analyse, manage, utilise, monitor, improve, preserve, and safeguard data. However, many data governance projects fail to meet their stated aims because data leaders are unable to develop a comprehensive data governance strategy to address the most prevalent data issues.

Drawing up a data governance strategy

As the volume and frequency of data increases, it is critical that enterprises have well-documented, scalable digital strategy. A data governance plan establishes a framework for connecting technology, processes, and people. It delegates authority and holds certain people accountable for specific data domains. A comprehensive strategy guarantees that data teams and stakeholders follow a consistent approach and objectives related to data. This maintains data integrity by keeping it accurate, clean, and useable. In the realm of analytics, poor data results in bad decisions. A data governance strategy helps avoid bad data that result in bad decisions. Here’s how to build a master data governance strategy.

  • Access the areas that need improvement in data quality and prioritise objectively. Defining the starting point is key to planning the program’s expansion in later stages.
  • Introduce best practices in data integration enterprise-wide to maximise availability. Governance is only possible when data becomes easily accessible.
  • The biggest problem with data governance is accountability. Creating data stewardship teams and processes helps clearly define responsibility, thus improving the trustworthiness of the master data.
  • Enrich data to maintain quality by regularly profiling it based on predefined metrics. Check for data integrity and monitor the validity of the data to ensure accuracy and applicability.
  • Build an accountability structure to define data ownership to keep data integrity and quality high.
  • Adopt enterprise-wide multi-domain MDM for accuracy of the master data and effective data governance. Legacy systems create data silos and fragmented data that are barriers to optimum use of enterprise data.
  • Introduce a feedback mechanism for continual assessment and timely improvement to the data governance process.

How can Infosys BPM help?

Infosys BPM provides end-to-end MDM services, including advisory, data quality management, and digital transformation. The ongoing MDM support ensures effective data governance by implementing RPA-, AI-, and ML-led solutions. We leverage our deep industry experience and dedicated enterprise data management service across various domains to customise solutions to suit client needs. Learn more about our offerings.

*For organisations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed on organisational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like a living organism, will be imperative for business excellence going forward. A comprehensive, yet modular suite of services is doing exactly that. Equipping organisations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organisations that are innovating collaboratively for the future.

Recent Posts