Master Data Governance: Best Master Data Governance Practices

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By: Sagar Sharma

Master Data Governance: 21 Best Master Data Governance Practices

Every company has to manage the organizational data from different departments such as operations, marketing, sales, eCommerce, account, and human resources as well as individual employees and customers in more or less quantity. Explore how master data governance practices help companies manage all the organizational data accurately in a single platform.

How do you manage all of this organizational data?

You might be managing all the data in disparate systems.

If it is so, then let me ask you one more question.

Do you find that approach time and cost-efficient?

If your answer is YES, then I am sure you are not aware of the capabilities and benefits of centralized management of your organizational data. It saves a lot of time, money, and effort for your team in managing the data across multiple systems. Thus, it is highly recommended to mid-scale to large-scale organizations implement a Master Data Management system.

While developing and implementing an MDM solution, don’t miss to consider advanced security and compliance standards to protect your valuable data.

Most of the platforms available in the market come with the best security standards. But, if you want, you can add extra layers of compliance to avoid the risk of a data breach.

Before moving towards master data governance practices, let’s get an overview of master data management. Understanding MDM enables you to better clarify further in this post.

What is Master Data Management (MDM)?

Master Data Management creates a single master record of all the essential business data from external and internal data applications and sources. It involves the organization with a consistent and uniform set of extended identified attributes that present all the core business entities.

In MDM, companies can manage the data of their products, customers, employees, accounting, operations, partners, websites, and more.

To get better insights about MDM, read What is Master Data Management & How Can It Benefit Your Business?

What is Master Data Governance?

Master Data Governance is an application for data governance and compliance that helps brands improve the management of a subset of master data. Master data allows for managing all types of data that every entrepreneur needs to run an organization or business.

MDM helps companies to manage various operations too through centralized data management.

For example; you purchase the material from the suppliers to create products that you want to sell to your customers and deliver the products to partners.

The consistent and accurate material, product, supplier, partner, and customer data help you to boost the accuracy and efficiency of your various business processes such as record to report, procure to pay, and order to cash.

Now, it’s time to learn about the core topic. Yes, let’s explore the best practices of master data governance.

Why Master Data Governance is Important to Businesses?

Master data governance framework can be briefed as a system that involves business people, business processes, and the latest technologies for effective & efficient master data management. Well, this will give you a clear picture of the essence of MDM.

However, here are the lists of some key aspects that highlight the importance of having Master data governance at your business.

  • Master data governance defines who can access the master data and offers roles & responsibilities to the users accessing the master data.
  • Master data governance framework helps organizations to extract information from the master data easily and efficiently.
  • It helps businesses to share the right data with the right users at the right time.
  • The master data governance system offers optimized master data in a transparent, standard, and fully harmonized way all over the enterprise.
  • The system will act as a reliable source where all departments can share high-quality data and ensure uniform communication being shared within an organization.

21 Best Master Data Governance Practices

1. Definitions

Master data governance presents the core set of attributes that are part of the main master data definition and these attributes are consistent across the company.

For example; you want to create a master record of customer data in MDM. For that, MDM allows you to manage all the data that are relevant to your customer base such as

  • Name (full name of the business and customers you are selling the product)
  • Address (billing and shipping address to deliver the products)
  • Email
  • Mobile number
  • Payment terms, and many other attributes

In short, you can cover all the attributes that are essential for your business processes.

Here, the critical job is to define which attribute is important for your business. Otherwise, you will end up focusing on the least important attributes that negatively impact the success and agility of your master data management operations.

2. Data Quality Management

Data quality requirements differ from company to company. Thus, organizations need to consider tools and techniques to support data monitoring and validation processes. The data quality management processes include

  • Enabling effective reporting and quality monitoring
  • Creating control for validation
  • Data incident tracking
  • Enabling recommendation and root cause analysis
  • Supporting the triage process for assessing the level of incident severity

The right process for data quality management enables you with trustworthy data for analysis.

3. Data Access Management

For data access security, two aspects are considered under master data governance practices.

1. Provision of access to available assets

It is essential to provide data services that allow organizations to access their respective data. The companies need surety that apart from the company, no other individual or company can access their data. Most of the cloud platform providers offer varied methods for developing data services.

2. Prevention of unauthorized or improper access

You need to develop a Master Data Management solution that allows you to define roles, groups, and identities in order to assign access rights to establish a level of managed access rights.

Data access management is the best practice to manage the master data access services and interoperating with the cloud provider’s access and identity management services by allocating and managing access keys, defining roles, and specifying access rights for ensuring that authenticated and authorized systems and individuals are able to access data assets according to determined rules.

4. Policies

Master Data Governance practices makes sure that external regulations and internal policies are taken care of as a part of master data management. These policies should be relevant to many aspects of the master data governance such as privacy and protection, risk management, data quality, and retention and deletion.

To address the regulation and policies, it is important for you to separate the duty in terms of

  • Who can create the master data for the cost center in a general ledger system
  • Who is allowed to approve the creation of cost centers (it is a risk control policy in order to prevent accounting fraud)

5. Rules

You might be thinking, we have already discussed the policies then why do we need to talk about rules? It’s indirectly a part of the policy.

Well, it’s not so.

Policies are supposed to define what you want to do. On the other hand, rules define how to enforce and execute policies.

Want to understand this difference in detail? And, how do policy and rules work hand in hand? Let’s look into it.

Policy: Before you use the personal information of a customer, you must obtain approval for processing.

Rule 1: Define the consent attributes that need to be a part of customers’ master data definition such as marketing, third-party sharing, and billing.

Rule 2: Before the customer record is created and approved, enforce the collection of those consent attributes.

Rule 3: Check out all the marketing consent attributes before the custom data can be used in a marketing automation system.

This example makes it clear to you that it is quite normal if you define multiple rules to address the requirements of a single policy.

6. People

By creating the documentation of master data governance practices, you can provide visibility to your different teams across the organization who are continuously working towards the success of MDM activities. These people from your team could be:

IT team

Your network team is responsible for the architecture and management of various business processes, applications, and databases.

Subject matter experts

Subject matter experts are mainly responsible to define both standardized master data definitions along with the levels for the business and types of the quality threshold needed for varied business processes.

Data steward staff

They are responsible for remediating data quality problems for specific master data domains.

Legal and security team

This team is responsible for data protection and privacy.

Cross-functional leaders

Cross-functional leaders, who comprise the council or the governing board, are responsible for solving disputes amongst varied functions within the business.

7. Workflow

Once you determine the core team who are going to utilize the master data management. You also need to define the workflow in the document that allows your teams to collaborate effectively. With the help of workflow, you can

  • Define a mechanism for creating the request for master data creation requests.
  • Allow multiple people from different organizations who need to be involved with parallel approval, workflows, go-live distribution, and activation of applications.
  • Determine which master data steward the request is routed to, based on domain responsibility.

8. Catalog

By implementing a robust Master Data Management system with the right Master Data Governance practices, you can get access to several cataloging capabilities.

  • Assuring the quality (completeness and accuracy) of master data across every single source
  • Verifying the consistency of master data definition across different sources
  • Exploring and documenting which master data domains are available across different systems, applications, and other sources such as lakes, data warehouses, and more.

The Master Data Management system understands the master records you have, knows where the required data is located, and clarifies how it conforms to your policies and definitions.

Mergers and acquisitions are very common strategies that businesses adopt to expand and grow in a new market. You need to understand the master data available in the source systems of the company you acquired. Also, you need to map that company’s data with your master data definition. By performing these activities, you can reduce financial reporting risks, reduce integration costs, and accelerate business value.

9. Process Mapping

Process mapping provides visibility on how the master data flows between different sources as a part of business activities. It is more or less similar to the catalog documents where the master data resides. Knowing how the master data flow through processes or understanding the source helps you to better visualize the varied things like

  • Where rules require to be introduced into the process to enforce the policies
  • Compliance risk exposure
  • How the master data is being used

In the process of mapping, you need to understand from where the master data is collected, which systems the data flows to, and what third-party systems the data is shared. Thus, you can enforce policies and standards for clinical data submissions and acquisitions.

10. Auditing

To ensure that the systems are working as they are designed to act, companies need to access their systems. Data auditing, monitoring, and tracking (who has made what changes and when and with what information) helps your data security teams to collect data, identify risks, and act on them before any data damage or data loss occurs.

To avoid any data security threats, it is important to perform regular audits for your master data where you check the effectiveness of the security controls by analyzing overall security health and mitigating threats quickly.

11. Data Protection

Most companies have Perimeter security that is not enough to protect your sensitive business data. There is a risk of data leak as the users with limited access to your data cannot access all of your data but some of your data can be exposed by that user anyhow.

You need to adopt advanced data protection methodologies to make sure that exposed data cannot be read. Here you can consider various methods like

  • Encryption in transit
  • Permanent deletion
  • Encryption at rest
  • Data masking

12. Data Literacy

Ensuring the success of data governance relies on training, education, and a true understanding of what can’t and can be done with your data.

But the adoption of technology alone is not enough. It takes policies, people, and processes to drive the organization-level change and enables users to protect and see the value of their data as a business asset.

13. Metrics

When it comes to managing and measuring the master data, master data governance practices allows businesses to define matrices. It contains varied technical metrics such as the completion and accuracy of master data, how many personal data attributes are masked or encrypted, and the number of duplicate records in an application.

These types of metrics help you in the technical management of master data, leading companies will frequently also try to future determine how consistency and quality of supplier and material master data help you mitigate supply disruption risk, reduce inventory carrying risks, and negotiate better procurement terms.

14. Focus on your scope of data governance

For better data governance, you need to focus mainly on the master data entities. Often for a business master data entities like cash, reporting records, payment procedures, and hiring to retire are the most critical processes. Those entities may differ from business to business in terms of attributes.

Defining the master data entities with a minimum set of attributes is essential for businesses to maintain data governance consistent across the systems. Once you manage to maintain the consistency of your master data entities you can ensure your business process is carried out efficiently and effectively.

Also, governing master data with too many attributes is not an easy job and it will be a daunting task for business leaders and stakeholders. Master data entities with too many attributes will get delayed for implementation because of that reason.

15. Create a better business policy with the help of experts

To run a business successfully and also smoothly, you need to have a better business policy that needs to satisfy the regulatory requirements. Many top-level businesses around the world have separate policies for meeting the requirements of national, state, and industry regulators.

Here are the lists of policies and regulators to which businesses need to pay attention for running a smooth and successful business.

  • Privacy regulation from the European GDPR (General Data Protection Regulation) & CCPA (California Consumer Privacy Act).
  • Financial regulations from the IFRS (International Financial Reporting Standards) and GAAP (Generally Accepted Accounting Principles).
  • Industry Regulations like BCBS 239 in banking and Sunshine Act in healthcare.

Apart from that, people from the verticals like legal, and finance will require expertise and knowledge to meet the needs of the regulators.

16. Defining ownership and accountability

When it comes to master data governance practices, governing the operation of master data can be approached in two different parts, such as.

  • The first and foremost part is defining the rules. These rules’ definitions should be subjected to the matters involved by businesses.
  • The second part would be creating executable codes for enforcing the defined rules. Just like performing an API call to verify the postal address.

Both parts play a crucial role in master data governance practices. The second part which involves the creation of executable codes must be handled by the IT department and deployed in business applications and tools which perform management operations.

17. Automating master data lineage and data mapping process

In today’s virtual business world, almost all businesses are experiencing potential growth of their business data and it has become a tedious job for data managers to do data management operations.

In addition to the exponential growth of the master data, a business may witness a lot of data integration operations and date movements around the entity. To tackle such things, modern-day businesses create a lot of jobs for performing data integration and data movement operations.

Data managers prefer modern tools that use AI (Artificial Intelligence) & metadata for scaling their operational efficiency. Often tool drives more efficiency by introducing automation in the data lineage mapping process.

This helps businesses to identify the data movement processes easily. In addition, the automated lineage mapping facilitates a greater collaboration among the relative master data that paves the path for productivity increase.

18. Deploying auto function on data discovery and cataloging

For a successful business, data identification is an important process. Once you can identify the right data you need to work on your data catalog for leveraging the benefits of quality data.

In general, an organization utilizing the data catalogs will have the opportunity to improve their overall ROI, customer base, streamlined business operation and so.

Once your business starts experiencing exponential growth of business data, you would need technological assistance through tools using AI (Artificial Intelligence) and metadata. With such tools, you can easily automate the process of data discovery and cataloging of the master data which plays a key role in improving business efficiency.

In addition, modern data management tools come with advanced data-sharing capabilities and full audibility access. So, the person who is responsible to access the tool can have the power to share data and conduct data auditing operations with ease.

19. Defining roles and requirements properly

When it comes to driving a business towards the success path, as a business stakeholder you need to design roles and responsibilities for the sake of business benefits. The roles and responsibilities should be defined according to the person who holds the position.

This enables you to identify and hire a potential person for the post according to the defined roles and responsibilities of that particular post.

Instead, you can define the desired technical skills and management skills along with business knowledge. By doing so, you can ensure hiring a desired and successful person for performing that role efficiently.

Once you hired all people for all the posts, then determine about training the hired people with the right knowledgeable people from your business house. This gives you a perfect ideology for hiring the right people for your business and pinpointing whether you need to source a workforce externally for completing the project.

20. Streamlining and optimizing your business workflows

Data managers or an organization should work along with the business stakeholders so that they can understand how effectively they need to manage the master data. Often business activities are performed by different groups which are connected together.

With a proper understanding between data managers and business stakeholders, data managers can design a highly structured workflow.

Once, the business workflow gets optimized and streamlined, business stakeholders can focus on automating task prioritization that will pave the path for productivity increase and brings more efficiency to work.

At the same time, you need to make sure on conducting a proper full audit trail on every step performed for workflow optimization. So that, if any issues occurred you can easily roll back to the previous version.

21. Measuring business value accurately

When it comes to master data management, technical data metrics are a pretty important role in managing your business processes efficiently. So, if you really want to predict your accurate business value, then you need to focus on your technical data metrics.

You need to design a metrics hierarchy by linking all the data responsible for the business process which also includes shipping data, delivery data, order invoice data, accurate tax details, and so.

All those above-enlisted data metrics play a crucial impact on days sales outstanding (DSO). The DSO (Days Sales Outstanding) proves your business efficacy and value. Having a better master of data management will help any organization to drive better data efficiency in the long run in today’s competitive market.

Benefits of Having Master Data Governance

Still, thinking about why master data governance needs to be implemented in your business? Well, this section will force you to deploy master data governance by explaining its business benefits.

1. Workload reduction

To handle and manage all the business data, almost all the departments of an organization should play a major role. However, with the master data management system the workload of departments on handling and managing the data gets reduced dramatically.

Having an MDM system will completely get rid of the work of data collection from all departments, also the system eliminates the presence of data duplications among the departments.

Master data management is specifically designed to carry out the data management and data governance process. This makes the departments free from the work of collecting, storing, and managing business data.

2. Improves the quality of data

As the ultimate goal of the master data management system is to streamline and regulate the data management process in an organization, the MDM system takes all the necessary steps to improve the master data quality.

At first, the MDM system provides a proper structure to the business data through a centralized data management system.

The centralized data system acts as a single source of truth for data which helps businesses to eradicate all the problems in data reporting and handling data on cross-functional processes.

In addition, the centralized data repository reduces the risk of data errors and improves the data quality significantly.

Quality data becomes the ultimate weapon for businesses to succeed in the competitive market, this makes the master data management system an integral part of the modern-day business which delivers supreme data quality.

3. Data governance and data compliance

As mentioned above, the master data management system offers a centralized system for the effective management of data. This makes all the existing master data of an organization accumulated in a single place.

Having all master data in a single place will be helpful for business stakeholders or data managers to easily manage and define structured responsibilities. This allows businesses to set up a dedicated data compliance team to satisfy all the terms of the regulators.

Above all, the structured data provided by the MDM with responsibilities allows data managers to optimize it easily and quickly according to the evolving market condition.

Conclusively, having a good master data management system will help data managers and businesses to improve their master data quality through which businesses can attain their goals and objectives quicker.

4. Reduces new product’s time-to-market

With the presence of a centralized master data system, launching a new system becomes much easier for businesses. In general, launching a new business product will take a lot of setup efforts if it is handled manually.

Now, with the arrival of an automatic data management system, the new products will get the required master data directly and instantly from the system. This reduces a lot of time and allows the team to initiate the product launch much before the deadline.

Apart from that, with the master data management system the sales and marketing team gets accurate data on the new products well before the launch. This allows them to imitate their work in time and helps to enhance the product reach to the more potential audience quickly.

5. Enhances the efficiency of business processes

The centralized data processing system offered by the master data management system acts as a perfect single source of truth for data which supports business processes in many ways.

The accurate and up-to-date data provided by the master data management system helps data managers to utilize them wisely on various applications and devices.

This ensures high-quality data are being served to the end-users at the right time. Also, employees accessing the right data will improve their work efficiency as they don’t need to rework or alter the data to improve its quality. Thus, it improves the efficiency of the business processes.

6. Helps business leaders to take impactful business decisions

Master Data Management offers a holistic, comprehensive, and complete view of the business or master data which can be accessed all across an organization. This results in the enhancement of organizational-wide improvement in work efficiency because almost all the work processes rely on quality master data.

With the high quality, accurate, and up-to-date master data, business stakeholders, executives, senior level management professionals along with all level employees will have a complete awareness of the project. This helps business leaders or stakeholders to make impactful business decisions during crunching times.

7. Bring automation by eliminating manual processing

Companies opting for manual tasks for managing all their master data will face the huge risk of data loss during data handling and manual errors while entering data. Yes! You may have few benefits but when compared with the risk factors manual process of managing master data is just a nightmare for businesses looking to gain a competitive edge in today’s evolving market.

Having a good master data management system will help businesses to manage their master data without any hassles.

In addition, the MDM system allows data managers to easily share the data among the systems easily and quickly. Instead, the system offers easy data governance processes along with an easy-to-use interface.

Make Salability Your Core Focus for Master Data Governance Technologies

Master data governance technology is all about determining the types of capabilities that need to enhance master data governance. It’s not about implementing the MDM. These technologies involve metadata scanners and connectivity to help the catalog master data across different sources. Moreover, process management and linage capabilities assist with workflow and process mapping.

Pimcore’s MDM Enables You with Better Master Data Governance Practices

Pimcore is an advanced platform that allows you to build a Master Data Management system that contains advanced master data governance technologies to ensure the security and protection of your organizational data.

Whether you need policy and rule management, data quality, data integration, data protection, privacy, or data cataloging, Pimcore MDM enables you with incredible capabilities for master data management and governance.

Credencys enables you with end-to-end master data management capabilities integrated into a modular or comprehensive Pimcore platform that is powered by advanced technologies as well as powerful in-built frameworks. To understand the Pimcore master data governance, feel free to get in touch with our experts.

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