A Successful Guide to Master Data Management

Nov 16 2022

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Master Data Management for a Heterogeneous Ecosystem | A Game Changer Approach

The amount of data everyone produces per day is truly mind-boggling. On average, humans generate 2.5 quintillion bytes of data, flooding out of the dozens of IoT-connected devices and mobiles. It is indubitably making data management no easy task.

In today's competitive business environment, the ability to manage and classify data to be used for analysis and decision-making is essential. Almost every industry produces a vast quantity of data from an equally vast number of sources.

So, how can you tackle data management in bringing alignment to your corporate data?

“A master data management solution can transform your business by gaining a harmonized view of enterprise data and a single source of truth to make better, more informed business decisions.”

In this blog, you will go through the underlying issues of traditional data silos and a holistic approach to implementing a Master Data Management strategy in your business.

Data Silos, Why They’re a Problem?

Did you know? By 2025, global data creation will reach 180 zettabytes from 97 zettabytes in 2022. - Statista

Let’s look at the modern organization data management structure. On average, 7 out of 10 organizations hold 1000s of customer records underutilized. This is because of the poor data management structure. The data present across the departments is not connected at all. This creates a challenge for IT to keep data synced and secure.

The current state of decision-making amongst marketers is unstable. Around 65% of decisions made are more complex.

Every year, poor data quality costs organizations an average of USD 12.9 million.

Data management has become a daunting challenge as data volume, velocity, and variety increase. For instance, businesses operate 100s of applications and systems that cross multiple departments. As multiple people touch the data, it can become siloed, outdated, or contradictory. So, it can impact the decision-making process because data is crucial for business decisions.

What is Master Data Management?

Master Data Management, or MDM, is an enterprise-level systematic process to manage and extract relevant data from multiple sources to create a unified database. In other words, maintaining one reference master data record for all critical business data is known as master data management. Doing so will allow you to eliminate inconsistent and redundant versions of same data in your organization.

Master Data Management Benefits

Now that you’ve understood the basics of MDM let’s deeply look into the benefits associated with any master data management software. In general, Master Data Management has four main benefits covered by implementation:

Accurate Business Insights and Data-driven Decisions

MDM increases data reliability and becomes the single source of truth for your data-driven business strategies. Unlike traditional data silos, this transformed and accurate data benefits different business domains that need data to survive. For instance, this data helps in making effective strategic decisions, optimizing the supply chain, better risk management, and accurate reporting for finance and sales.

Apparently, master data is crucial for your business’s success. MDM offers accurate, consistent, and accessible data that leaves positive impact on different areas of your business.

Reduced Errors

With a traditional data management approach, there are great chances of incorrect information. For instance, a person might have two different contact numbers. Instead of adding others to the existing record, there are chances that system is considering it two different persons. Now, if you’re using a well-planned MDM strategy, it will figure out and update the existing record.

To put it simply, MDM merges and reconciles data duplication, which helps in reducing errors and redundancies in data across multiple applications.

Greater Data Control

Having good control of your data is essential. You get better data storage controls if you implement an MDM strategy in your business. For instance, MDM offers a single source of truth per customer, which helps you safely dispose of irrelevant and old records. Not only this, but MDM also holds the power of enhanced data integration; your customers’ data can easily flow between the cloud and on-site or between different database systems.

With companies increasing the number of platforms and adapting to new technologies, a good MDM strategy makes data migration easier.

Improved Productivity & Reduced Workload

With all the benefits listed above, your business will experience improved productivity with accurate decisions and effective business strategies. Not only this but MDM implementation in your business will also allow you to free up multiple departments that worked with and required the same set of master data. This way, workload is reduced while eradicating delays and bottlenecks in operations.

Additionally, MDM plays an important role in increasing and enhancing agility among people and processes because they have access to reliable data for bringing ideas and innovations.

5 Challenges of MDM Implementation

When choosing a master data management strategy, it is imperative to understand the associated challenges. This way, you can be ready with the solutions to tackle them. Let’s look at the top five challenges you will face while implementing MDM in your business structure.

1. Applying Business Context

Every business is different so does its data and data management requirements. And defining a business context instead of an IT context for the integration of MDM solutions is daunting. You need to set standards for your master data to align with all data available in your organization.

Therefore, planning your business context and relevant data standardization is recommended in advance. Y You need to align MDM with all your data sources consistently. Otherwise, the process of MDM implementation can become cumbersome.

2. Data Integration

When you implement the MDM approach to your business, the following step is data collection from various enterprise software and sales channels for centralized management. While transferring data from one application or another, there are fair chances of mistakes like missing out on some important data, etc. Moreover, this process of data collection and integration is time-consuming.

To mitigate any complication during data integration, you can opt for advanced software that doesn’t only automate the whole process but also ensures consistency and accuracy. For example, ASTM international utilized RPA approach to convert 100+ years old physical forms of written technical standards into digital assets with complete accuracy.

3. Long-term Maintenance and Modernization

With technology, long-term Maintenance and  always accompany. Though you have set up an MDM solution and integrated data into it in the best way, the maintenance and modernization can be complex. For the right data governance policies and other business rules adherence, you need to allocate a professional who can keep a check on data operations clarity for the long run.

Not only maintenance but developing and implementing MDM solutions with the help of experts who have talent and proven expertise in the same field is a must.

4. Change Adoption

Data is dynamic and keeps on adding over time. If there is any change of data in any source channel, it needs to be directed toward your master data management solution. Otherwise, your single source of truth can become vague over time.

Therefore, it becomes important for you to adapt to the changes in the sources frequently. You can rely on the MDM experts for the same.

5. Trained Personnel

Although MDM is not a complex albatross nowadays, you still need to be careful with its implementation. Whenever you make any data-driven decision, all eyes will be on MDM solution. But if you’ve failed in its implementation or failed in appropriate data integration or maintenance, there are higher chances of disappointment.

You need to look for trained MDM experts in its implementation and maintenance. It is the best approach to follow if you’re occupied with other aspects of your business.

Considering all these challenges, you need to opt for an in-depth master data management consulting before choosing the right MDM solution is always recommended.

Workflow of Master Data Management

The major goal of any MDM or Master Data Management is to ensure the accuracy and consistency of data. Two primary goals of MDM are:

Creating Initial Master Data Record:

To create a master data record, the software screens all your data (for matching and reconciliation) in different departments, e.g., customer data, product data, etc. Now the data will be compared to each other to figure out any inconsistency; if there is any duplication, data will be merged.

Maintaining Master Data:

Data keeps adding to the databases with new leads and prospects. A dedicated master data management software gets involved in cleansing, transforming, and integrating this new data to protect the quality and consistency of the data records. Today’s AI-powered MDM solutions can automate and accelerate most of these tasks.

Master Data Management Best Practices

Best practices for Master data management starts with handling the above-listed challenges adequately. However, there is a brief list of best MDM practices that you can go through for greater success in data management.

Consider Business Goals: Defining your business goals is the foremost step before choosing or implementing your MDM strategy.

Data Lifecycle Management: Data is dynamic and keeps on changing or adding to your sources. So, defining a data lifecycle is a must.

Data Security: Apart from choosing and implementing the best MDM solution in your organization, data security factor is not to forget about. You cannot risk data over any software or solution.

Use of MDM Tools or Software: Choosing the best MDM tool or software is a critical task. To ensure accuracy and success, you can seek assistance from experts who’ve proven work records.

Simple and Scalable MDM: Choose and implement an easy-to-understand, maintain, and scale MDM solution to address your future data management needs. Always look for future-ready MDM systems.

Adopting AI & ML Approach: AI and ML make any software or system intelligent and stronger. Go for AI-powered and ML-integrated MDM solutions.

Choosing the Best Approach for MDM Implementation

In today’s competitive landscape, data is your most important business asset. You can use it as a magic wand to boost profits and sales. From marketing to business operations, data plays a vital role in decision-making. Therefore, you need to align data in accordance with your business needs.

Choosing the best MDM solution and implementing it in your business is the best strategy instead of a mere project. Explore Icreon’s data engineering consulting services.