All You Need to Know About Master Data Management (MDM) [Steps & Roadmap to Create Strategic MDM]
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By: Sagar Sharma

All You Need to Know About Master Data Management (MDM) [Steps & Roadmap to Create Strategic MDM]

There are many definitions of Master Data Management because it’s still in its infancy. But let me put it in simple words, MDM is a process that creates a uniform set of data of products, suppliers, customers, and other business entities from different IT systems. So, your burden of managing complex data is taken care of by Master Data Management-MDM.

What is Master Data Management (MDM)?

MDM is a central data holder of all kinds of data, which eliminates the risk of losing important data. Master data represents the trans-active entities. Master Data is the entity that the organization tracks.

It is the entity subject to control. Master Data Management controls unstructured data, Metadata, Hierarchical Data, Transactional data, and Reference data.

Master data is a key, which manages all locks of complex data. Unstructured data is found in log files, XML documents, configuration files, etc. Metadata is a super MDM domain because it is critical to understanding the relationships between master data. Hierarchical data includes codes for countries, states, currencies, time zones, etc.

To learn about Master Data Management, don’t forget to visit What is Master Data Management & How Can It Benefit Your Business?

Why is Master Data Management Becoming So Popular?

Increased Globalization

Organizations have become united under central governments. They are now integrated globally and carry more information than ever. This globalization has increased complications from the data management perspective which include multilingual, multi-character issues, 24/7 data availability, which is only possible with MDM.

MDM Issues

Master data is the most important data that an organization holds. So, there is no choice but to fix even the smallest mistake of the past which might cause viral problems in this federated environment. Those who solve their MDM issues have been found to have a competitive advantage over others.

Opportunity for All

MDM is a big as well as a complicated problem. Therefore, it is an opportunity for product vendors and systems integrators. That is why MDM data hubs have been developed. Modern data hub technologies are SOA-enabled and benefit several other modern technologies as well. It is also a major opportunity for application-centric vendors to expand their application scope.

Compliance Initiatives

Whether it’s compliance with a law or regulation or it might rely on a system of internal controls, it surely adds corporate pressure. Without a sound MDM solution, enterprises face increasingly difficult problems.

Avoid Data Duplication

Data duplication leads to a lot of confusion which leads to errors. Not only in the master data process but also in other business processes that are dependent on master data.

Challenges of Master Data Management (MDM)

While most organizations are successful in collecting master data on their customers, suppliers, and products, a considerable number of organizations are still struggling with it. MDM is an emerging market and that is why educating the business on why MDM is so important can also become a challenge in itself.

Data Complexity

There are multiple versions of data sources used outside and within the organization due to which the data is maintained in legacy systems. This leads to duplications and errors.

Data Quality

Incomplete, inconsistent data is used throughout the business and pushed to various channels. Such unstructured data can complicate and even block your entry to new channels.

Data Errors

Data errors resulting from low-quality data sources and manual entries end up in all channels such as ERP to catalogs. As a result customer service, product returns, and communication suffer drastic damage.

Loss of Trust

Not knowing which elements of the data are outdated or incorrect can make one question its effectiveness. Loss of trust can cause you more trouble than you can think of.

Data Syndication

Lack of control on which data is being pushed to which channel results in a difference in product data information per retailer, and nothing is as scary as that.

Lack of Data Governance

The absence of a centralized system for data gives birth to compliance issues like safety regulations.

Modeling

Organizations typically lack a Data Mastering Model, which is important in defining the primary, secondary, and slaves of master data. Therefore, making integration of master data is complex.

To learn about more challenges that any data-driven organizations face in the absence of MDM, visit Top 10 Challenges that Businesses Can Address with Master Data Management.

How to Build a Strong Master Data Management (MDM) Program?

MDM is not just a technological problem. It would be easy to install a piece of technology and have everything sorted out but that doesn’t work here. So what does a strong MDM program entail?

Organization

Getting the right people in place throughout the MDM program is most important. Organization people include master data owners, data keepers, and governance participants.

Governance

Directives that manage the organizational policies, principles, and bodies to promote access to certified and accurate master data. This process helps the cross-functional team define the various aspects of the MDM program.

Measurement

Measurement should look at data quality and track continuous improvement to provide a sense of progress compared to your stated goals.

Process

There should be defined processes across the data lifecycle to manage master data effectively.

Technology

The master data hub and any other enabling technology work for MDM. Master data hub technologies are SOA-enabled and benefit several other modern technologies as well.

Policy

The requirements, standards, and policies to which the MDM program should adhere will give better clarity within your organization.

What Involves in a Master Data Management (MDM) Program?

Data Governance

Data governance users dictate data stewards on how data should be managed and hold them accountable for following those requirements. These users also dictate to administrators what to create during the implementation of the MDM solution, especially from a quality perspective.

Data Stewards

These are the individuals responsible for cleaning, fixing, and managing the data directly within the solution. Generally, data stewards come from departments such as finance and marketing but the activities that data stewards take on are defined by data governance users.

Administrators

These are individuals from IT who are responsible for setting up and configuring the solution.

Project Manager

Develops and manages project plans. They ensure timely, quality delivery and report project progress. They are responsible for risk and issue management. Although their level of involvement is close to zero.

Program Manager

Owns the data management strategy and platform. They are more involved than a project manager.

Developer

Developers implement custom SDK and workflow solutions to extend MDM platforms.

Benefits of Good Master Data Management Program

1. High Data Quality

As the MDM application streamlines the data, it helps in eliminating the unused, redundant data. Users can work with updated data that is of better quality. Thus, the efficiency of working performance gets boosted up.

If master data is stored in various channels, it increases the chances of data overlapping which might result in loss of trust in the user. Since various processes rely on the master data for their tasks, it is imperative to eliminate any inconsistencies and reduce different data sources.

2. Time and Cost

Managing the increasing volume of data without MDM can be challenging for companies. This complexity makes manual data processing time-consuming. And will also take a lot of money to process master data accurately.

This application automates most aspects of the data management process hence saving an enormous amount of time. The companies need to employ fewer resources to manage the data with MDM hence reducing the data management and processing costs.

3. Avoid Data Duplication

Redundancy is the biggest problem with decentralized data applications. Many data sources mean data overlapping which also results in data duplication. Data duplication leads to a lot of confusion which leads to errors not only in the master data process but also in other business processes that are dependent on master data.

An MDM solution helps build a single data source that eliminates the duplication of data.

4. Increased Data Accuracy

MDM eliminates duplication and inconsistencies in the data. Variances in master data are known to have a ripple effect on most business areas of the organization. Hence, it’s crucial to get it right at the master data level so that it reduces the risk of data inaccuracy. It also gives the data a proper structure which helps in avoiding any confusion while retrieving the data from the application.

5. Data Compliance

Regulations and policies around data are getting stricter by the day. Non-compliance with data regulations may lead to far-reaching implications including penalties and loss of reputation.

6. Decision Making

MDM offers better control over the organization’s data. Wrong, incomplete information would allow management to make misinformed decisions that would negatively impact the long-term growth of the company. Access to quality and updated data however would assist the managers to develop effective strategies. This application helps the leadership, senior management, and middle management to make informed and better decisions.

7. Handling Change Request

Master data is the single source of important data used by the departments across the organization. Therefore, it is vital to protect the data from misuse. MDM helps companies restrict access to change the master data to only specific individuals. Restricted access to change data helps ensure data security as well as enable data consistency.

8. Easy Data Edits

Without MDM, users would record data in multiple destinations. MDM helps to control and consolidate the master data. Therefore, any changes made to the master data will reflect across all the relevant data destinations. This will help in ensuring data consistency.

9. Single Source

MDM software is one of the best programs to overcome the challenges of manual data management, redundant data, and any data discrepancies in master data. There is no need for cumbersome spreadsheets anymore. It streamlines all the processes related to the master data management of the company.

Creating a Strategic Master Data Management Roadmap in Five Steps

1. Current State Assessment

This is the first step in the strategic MDM roadmap process. Within the context of MDM and data governance, review the organization’s people and culture and then subsequently review the business processes, technology, and information.

The review from this stage is referred to as the Findings and Recommendations document which is reviewed with the project sponsor as well as other core team members.

2. Define the Desired Future State

This includes a selected group of people from various parts of the business and IT. The first thing is to decide the appropriate time frame for the MDM roadmap. Usually, it ranges from short term i.e.1 to 2 years to long term i.e. 3 to 5 years.

Then look at these dimensions over time: Master data management, Data Quality, Data Integration, Data governance, and Data enrichment

Find out what the organization’s overall strategic objectives are. Then see if it aligns with MDM strategy and supports those overall corporate objectives or not. The review will address how to deliver value to the business over the desired period.

3. Conduct Gap Analysis

Here, we figure out what are the gaps between who we are and what we want to become. Then subsequently we develop gap closure strategies to help move from the current state to the desired future state.

The gap closure strategies can be classified into four domains of enterprise architecture: Business, Application, Information, and Technology. The review here is a list of the gaps grouped by type with the corresponding gap closure strategies.

4. Prioritize and Sequence

Here we assign high, medium, and low priorities to each gap closure strategy. This helps in ensuring if we are covering the high-priority items first or not. However, do not discard the medium and low priority items as they may be needed as the predecessor to a high priority item.

5. Develop the MDM Roadmap

This roadmap ties together the deliverables from the previous steps:

  • The Findings and Recommendations document from the Current State Assessment summarizes the issues that need to be solved.
  • The Future State Definition document describes “when” i.e. the time frame, the vision for the initiative and how the MDM strategy supports, the “what” i.e. the overall corporate strategy, and the “why” i.e. the value and benefits of the program.
  • The “how” i.e. the list of gaps and corresponding gap closure strategies.

Conclusion

Thus, the importance of Master Data Management is gaining popularity and it sure does help businesses in growing the way they want. MDM is a single central platform that makes your working performance smooth and saves you from many hindrances that you may come across without MDM.

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