Master Data Management Best Practices

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By: Sagar Sharma

15 Master Data Management Best Practices to Follow for MDM Success

Are you making your business decisions based on your experience?

If your answer is yes, then it’s really commendable.

But, are you sure it generates the best results for your organization? Of course, there won’t be any guarantee.

Data is the key element for every organization in this highly competitive era. It enables you with a lot of information about customers, maker trends, products, competitors, etc., and helps you make the right decisions.

When you collect the data from different channels, you receive it in a scattered form. You need to convert it into a structured way to get insights into the different aspects of your business.

Master Data Management (MDM) solution helps you in collecting and managing massive data in a well-structured way. Successful implementation of MDM provides you with consistent, trusted, controlled, and accurate master data. It aggregates your data, standardizes it, and matches the values to provide you with a consolidated view of different business entities.

Well, to manage the massive data of your organization, you have to adopt the best Mater Data Management practices. It helps you to run the business efficiently. Here are the best MDM practices that you should consider for quality data management.

15 Master Data Management Best Practices to Follow for MDM Success

1. Collect maximum information

The more data you can collect, the better insights you get, and the more effective decisions you can make to drive success for your business. You might be doing your best to collect the data from different channels and platforms but it’s not enough.

Keep exploring new ways that help you in getting more valuable data about your customers and competitors. With more information, you can drive more business opportunities.

All you need to do is, perform a quick analysis of how you are collecting information right now for your organization and how you can improve the data collection process to get better results.

Once you get clarity about the gaps in your existing data collection process, you can implement new strategies to collect more valuable and reliable data.

2. Consider Multi-domain Master Data

A good master type is used to solve any business problem. There are several master data types or domains on one platform which means holistic insights and very good business outcomes.

Today, different businesses silo their customers and also product master data. They let alone their supply chain, location, asset, and employee data.

They bring the complete data sources like transaction data or product data into their master data management letting them find the hidden connections of their business. Every user of the master data management best practices will get the desired benefits and develop their business further.

You can make across functions with more connections when you use a few master data silos. These functions can power real-time operations at scale. An excellent multi-domain is designed to bring together customer, supplier, product, and employee master data, and location, and let the business see the return on investment on a single customer segment of a complete marketing campaign especially in the region and shift the financial plan accordingly.

This is worthwhile to use the current supplier networks for direct-to-customer or omnichannel fulfillment. You can create linked and hyper-customized experiences for customers across the channels especially human interactions or digital interactions. You can combine various types of master data which goes far beyond the internal data sets. You have to properly use the data to win in the market.

3. Data governance is an integral part, Don’t Ignore It

The main parts of master data management are data quality and data governance. In order to be an excellent data governance framework, it must include several aspects like guardrails and a perfect workflow for cross-checking the data accuracy and redundancy. It successfully matches new data entering the system with the best current records.

An advanced master data management platform automates the majority of this work using artificial intelligence and machine learning. This lets users leverage the advantageous things associated with the master data management devoid of additional work required for ensuring its quality.

You can research and double-check everything about the Master Data Management best practices in detail and make an informed decision to reap benefits from these practices. Regular and outstanding updates of the master data management practices give you an array of benefits beyond doubt.

Data governance includes, but is not limited to the data stewards. Data stewards are vital to establishing absolute rules to ensure the master data is quality and accurate.

Business users use this data. Your master data management system must be easy and intuitive for a business user for immediate adoption. The latest Master Data Management platforms using artificial intelligence can be properly used by business users or data stewardship to train the overall matching models and enhance the accuracy of the data quality over time.

4. Check out for the data quality

More is not always reliable. When you receive a massive amount of information, you have to validate it by implementing a set of quality assurance processes.

Not every piece of data, that you receive, is valuable. Though the user enters the information by themselves, they also provide the wrong details. Thus, to get a more reliable view, it is essential to check the quality of the collected data.

Quality assurance doesn’t verify each and every piece of data for you. It just enables you with an audit system that checks the data at random periodically.

5. Build MDM that Meets Your Business Objectives

The IT department does not solely get involved in the process of creating the overall structure and reference data for the master data management. As a business owner, you should be well aware of the business objectives, how to handle business-critical data wisely and communicate your business goals to the MDM team.

You can start with KPIs, quarterly goals, financial plans, five-year plans, and other things to align the MDM with the business. You have to identify the metrics which make known the development and blank spots in the analytics and work backward. Connected, clean, and consistent master data have the best impact.

You have to consider and double-check everything about the customer master data management best practices and make an informed decision to reap benefits from it. Experts in the business sector start with the end goal in their mind and keep their master data management in the business context to make certain that they continuously re-examine it and evolve it further with the business.

This is worthwhile to know whether your MDM improves the customer experiences, boosts the conversion rates & revenues, helps you segment customers & identify customers fast across channels, reduces issue resolution times, enhances the efficiency of processes, accelerates the reporting for compliance, and detects fraud or revenue leakage.

6. Build a scalable and Easy to Use MDM Solution

The most recommended MDM practices reveal that business people start small with one subset of data and organize these data clearly to gain early wins. They get remarkable benefits from this tried-and-tested method in business. However, this method might make complications or fail when the master data management is not built to scale.

Traditional master data management systems are built as a monolith and include trouble scaling. An advanced master data management system is built on a scalable architecture to assist a phased method or let agility respond to altering the market conditions. You can scale the master data management using the option to add the maximum data attributes on the fly to bring in the maximum data which is the best practice option.

Every user of the latest product master data management best practices gets 100% satisfaction. They know and remember that the data model changes over time. They use a flexible data model which lets them alter quickly and include new elements as per requirements. Do not forget that demographic data is not enough for complete segmentation.

The business in any category needs to add psychographic data to the customer profiles or indicate whether the customers are frontline workers or healthcare professionals to offer a special pricing plan.

7. Implement a common metadata layer

The development and integration of a common metadata layer allow you to share information across your analytical and management platforms. It lets you drive more efficiency in every aspect of your application and data-gathering process.

The metadata layer helps you learn market trends before you launch your brand-new products and understand how well your social media campaign performed. The layer streamlines most of your data-gathering processes and provides you with meaningful data that is easy to understand and use.

8. Set Up a Single Data Management Foundation for Your Master Data

Many business users have access to a single view of the master data. They get consistent and real-time information and insights as expected. Though, you feed the updated data into various business systems and analytic applications with the aid of a siloed MDM system yet the data might not get updated in real-time. To overcome this problem, you have to follow the latest master data management practices and get the desired benefits.

Every supplier master data management best practice is dedicated to providing prompt assistance and professional services to every customer. You require a single data management foundation to be agile and achieve the quick time to value while responding to the overall changes in the business.

The first-class graph technology captures the complete relationships and provides fast searches. Every business focuses on the transformation of the customer experience, the skill to leverage the relationships, and connections in data to make operational decisions and power them very important.

Graph technology successfully captures relationships and gives fast searches. Every business focuses on the successful transformation of the customer experience, the chance to leverage the associations and connections in data to make operational decisions and power them. Advanced practices integrate data into each business element and which brings the next best business practice.

9. Organize your data in a meaningful way

From the unstructured data, you won’t be able to drive any insight. So it is very essential to organize your information in a structured way. Simplify your data storage and retrieval process so you can find the information you are looking for without digging through files and files.

It especially helps your data analytics team which is constantly analyzing the data as they need to invest a lot of time in finding the information they require. Make sure all your business information has a place and users can access the needed data seamlessly to achieve their objectives.

10. Master Data Should be accessed by Different Teams

Businesses around the globe are keen to make data-driven decisions for their business growth. Business people produce and consume data. They have to be dependent on IT for data. They want their business to be data-driven and agile. The data cannot be held by the IT department. A master data management solution has to be easy for business users to access data for insights and complete operational use.

Every business user uses the data and empowers them to define the data based on their business requirements. They use it to enhance their master data management and their data literacy over time.

Linking various master data types is vital to bring the maximum insights and make data responsible for everyone to bring ideas to the table. You can improve the support for real-time operations with the advanced and agile MDM. You can shift to customer-centricity and power regulatory compliance as efficiently as possible.

You can research the fundamentals of the master data management best practices for success and get an overview of how to successfully develop the business within a short period. You can seek advice from specialists in master data management and enhance your skills to efficiently use the master data management system.

11. Provide quick access to data to the right user

Well-organized data allow for easier access. To improve your data retrieval process, you need to remove all the barriers between your staff and the data they require.

Avoid setting up complex access rights as it directly impacts the productivity of your employees. They can perform the tasks assigned to them without using the data they require.

Sometimes, it becomes confusing for your teams too, and that’s why they are not able to access the data they need to perform their tasks. Thus, avoid such situations by making data access easy for all.

12. Improve security standards to address cyber-attacks

Data is the key asset for any organization, thus it is very essential to manage your data securely. We come across many cases of cyber-attacks and data hacking every now and then. There are chances hackers erase your all data or the data slips into the hand of your competitors. In such a situation, you end up losing your innovative edge.

Thus, you have to consider and implement data security strategies and tools to protect your critical business information. You have to apply advanced security standards to your Master Data Management solution where you can manage all your projects, internal files, and insightful market data.

13. Update Data Consciously for Security and Privacy Management

The starting point of data privacy regulations is GDPR and CCPA. Many regulations will arise for consumer privacy protections along with the rise of technology which leads businesses to deal with maximum data. Critical data is a valuable asset to hackers and competitors to hold data for ransom and use data to gain an advantage respectively.

Legacy master data management with slow updates struggles to respond to the preferences of customers quickly. They need hours or days of downtime for updating the security and software.

Advanced MDM includes automatic background security updates and connected customer data. However, if you have disconnected and disjointed customer data which are scattered across the business system makes it is impossible with this practice. Having a modern SaaS MDM platform that allows businesses to update their data policies regularly would be the best solution for maintaining perfect security and privacy policy for your business.

14. Provide roles and rights access permissions

This supports data security. Different levels of executives are required to access a specific and different set of data. To enable the right user with the right information, you can protect your business data.

Everyone in your organization should be aware of their roles and the information they are allowed to access. The entry-level executives can access the basic information while the C-level executives can access high profile information.

Data is a serious business so each member of your organization should take responsibility to protect it. Rather than threaten them for the security of data available in the Master Data Management system; enable them with advanced tools that help them in performing their responsibility of enterprise data protection efficiently.

15. Keep adopting the latest technology trends

Leveraging the new technologies, you can improve the capabilities of the Master Data Management solution. Eland about the latest MDM trends and advanced technologies to boost your data security, data cleansing, duplicate data removal, and data organization processes faster and easier.

Verdict

I guess, it is very clear to you that any random Master Data Management system cannot deliver you the best result. You need to consider the robust MDM solution that offers an advanced feature set and allows you to integrate advanced tools and technologies to enable you with reliable data.

Credencys can develop and implement a next-generation Master Data Management system for you by harnessing the potential Pimcore platform. We offer a wide range of Pimcore development services to build a custom MDM solution as per your specific business needs.

We have a team of highly skilled Pimcore developers who have successfully built and delivered MDM systems to varied industry domains as per their development and integration requirements. Moreover, it will be pretty easy for you to apply all these practices to your Pimcore-based Master Data Management system.

Do you want to manage your data in a well-organized way in a bespoke MDM solution that provides meaningful information? Let’s connect with our Pimcore experts.

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