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With the increasing complexity in the way businesses are being run globally, it has become a priority to maintain data integrity to drive business intelligence. Master data management (MDM) tools monitor and track essential company data assets and use the data to derive valuable insights to support business intelligence plans. It consists of tools and technology used to process master data across the enterprise. Businesses are empowered to create quality information and derive insights using standardizations and workflows. MDM software is multidomain in nature, supporting several departments such as IT, operations, finance, and others to utilize the data synchronously. Master data might be a small part of the company’s entire data repository, but it is the most complex and valuable of them all.
MDM tools can also include various user interfaces, model-driven APIs, and several automation workflows to drive real-time collaboration between teams. It also supports data governance. Data governance is the process wherein different teams define the data and data quality that the MDM solution will process. Data governance includes key directives that are required to manage several organization bodies, multi-domain teams, standard policies and procedures, qualities, and principles that help to assess the master data.
Multi-domain master data management acts as a single source of truth across different teams and departments and enables organizations to drive digital transformation by using master data. Master data acts as a golden record since it is cleaned and not erroneous in nature. Master data management enables the organization to make data-driven decisions concerning revenue generation, operational agility, time to market, and cross-functional team mobility, among others.
Leveraging master data to take actionable insights and intelligence is driving the need for master data management tools in any type of organization. By having quick access to the most critical data assets, companies can have faster product rollouts, design new marketing campaigns, spend budgets wisely, create cross-sell and upsell opportunities, and more. Data quality is key.
Types of master data
Master data, reference data, and metadata are key data points for any business process. Master data is the core data around which a business process is conducted, and is determined as most relevant to the organization. To understand the type of MDM tools, it is necessary to understand the different types of master data first.
Customer data: This includes information for a business such as customer names, addresses, contact details, customer domains, employee records, sales data, and any other enterprise data. Loyalty programs, online sales, surveys, and several other methods can be used to get customer data.
Product data: This includes information regarding the product or service that a business provides. Information such as product info, parts, and assets are included in this. Product information management (PIM) would manage all the data regarding a business product.
Location data: This includes the data that provides the geographical presence of the company across the globe. It also provides office location, geographic division data, and others.
Others: This includes any other information such as licensing data, warranty information, contract, and others.
Multi-domain MDM solutions can be applied across several different industries to improve operational efficiency. For example, consider a manufacturing company. A manufacturing company needs to be able to access critical data such as product information. In case a manufacturer obtains wrong information, it could cause severe production delays. By using master data management tools, critical data can be accessed via a single-view dashboard where various teams can see any change made to a manufacturing process, compliance, and product specifications and be notified of the changes. Different teams can observe the additions/deletions made to bills of materials and be notified of the same. They can monitor the addition/deletion of several SKUs and set compliance standards that everyone can access and need to follow. MDM solutions provide different teams with a 360-degree view of critical data.
The value of master data
A single error in data could cause several other errors that can have dire consequences. A wrong address for a customer could mean orders would be shipped to another location, credit card bills would never reach a customer, or even newspapers wouldn't be delivered. An incorrect label on a product could cause a company to lose millions of dollars in product recalls. Wrong account details could cause large sums of money to be deposited into the account of an unintended customer, causing severe losses. A single error could easily tarnish brand reputation in turn losing brand loyalty. In such a scenario, managing master data has become a necessity, hence companies are opting for MDM software.
What Does MDM Stand For?
MDM stands for master data management. Along with tracking and monitoring a company's most critical data points, master data management software also allows various business users to use multi-domain data to make meaningful decisions that are relevant to grow business value.
In terms of architecture, there are four different types of master data management designs:
Registry-style MDM
This is the simplest and least expensive type of master data management architecture. MDM tools work with record data or “stubs” that provide the data source, present location, and other required information. It is the least expensive architecture in terms of deployment because the data is in the form of stubs and not the actual data. The major drawback in registry-style master data management is that data movement is a one-way street where changes made to master data do not get conveyed back to data sources.
Consolidated-style MDM
This is an upgrade from registry-style master data management, the main difference is that actual data is moved from their sources to the data repository. It has a similar drawback as registry-style master data management.
Coexistent-style MDM
This type of MDM software synchronizes master data to move both upstream and downstream, which means that data can coexist in the data platform and the repository. Coexistent-style MDM has a high latency since the data is collected and sent back downstream.
Transactional-style MDM
This is the most complete and the most expensive type of MDM system. Master data is collected from the source and moved to the data repository, where it is cleaned, standardized, and sent back to the source. Transactional style master data management requires expertise and the right tools to ensure proper data flow both upstream and downstream.
MDM systems are a great way to ensure that a company is making the best use of its critical data through data visualization, by using a single-view dashboard. The following are some core master data management features that can help users in several ways:
Data matching and linking: This is the core feature of MDM solutions. Along with pulling real-time data from different sources, MDM software should have a matching and linking feature. While managing a large list of contacts, there are often possibilities of duplicates being created since data is collected and stored from multiple departments. By using the matching and linking feature, duplicate and redundant data is eliminated all the while maintaining the data integrity and ensuring data validation. This cleaned-up data is known as the golden record. Since this task is automated, companies can save up on resources rather than manually cleaning the data. Master data management software demonstrates the element of cleansing and correcting erroneous data.
Data Governance: MDM tools allow executive teams to set up standards and centralized procedures that every member of the organization needs to follow. When business rules are centralized, each team has access to the set of regulations and standard procedures to be followed. These rules are directly implemented into the software without any need for back-end support.
Data privacy support: As an organization expands, the amount of data being generated in a single day increases exponentially. New customers are being added, new transactions are being recorded, and the amount of data keeps growing. In such a scenario, companies need to ensure that the highest echelons of data privacy policies and processes are being followed. MDM systems allow the concerned personnel to set up access rights to any data source. By setting up rights and restricting actions, master data can be kept private. Master data management solutions also have additional features where they can encrypt data, so users will require a secure password or multi-factor authentication (MFA) to gain access to the data. By doing this, the company is protected from security breaches and hacks.
Data protection regulations: To protect data within geo-boundaries, countries are coming up with strict data regulation policies such as the General Data Protection Regulation (GDPR). Certain data cannot cross regions and borders. By using master data management tools, companies can ensure the data is well within regulatory policies.
Data enrichment: Data enrichment is defined as a process to improve data quality from various sources. Under data enrichment, data is validated, cleansed, streamlined, and finally integrated with other external data sources to derive detailed information. This golden data is used to analyze trends, identify patterns, and allow firms to make decisions proactively by setting up workflows. Data enrichment can also help teams specifically to solve several issues. For example, marketing teams can understand customer buying behavior, identify patterns, and derive tailor-made products, offers, and discounts to retain a customer. MDM software is a single source of truth for all teams across an organization to observe the enriched data.
Software integration and validation: MDM tools are designed to work smoothly with other existing business systems, which include CRM, ERP, and others. A user should be able to easily export master data management data as necessary to be used with other software tools.
Some of the key benefits of master data management software include:
Act as a single source repository and improve data quality: MDM platforms help organizations collect, process, manage different sets of customer data across different departments. Having all master data of a company within a multi-domain software prevents duplicate data occurrences and combines any incomplete data to create new, valuable data called the golden record. Data that needs to be updated, edited, or deleted can be done by using the MDM software. All the data is finally used to create an end-to-end solution.
Drive customer engagement: By having enterprise data from different departments collated in a single software, marketing teams and customer engagement teams can obtain a 360-degree view of customers and create personalized ads and campaigns. Marketing and sales teams of organizations can come up with strategies and promotions to grow business value by attracting more customers and retaining old ones. Since master data management helps remove duplicate entries, it can also help organizations avoid errors such as sending emails to a wrong email ID, sending duplicate catalogs to a single address, sending bills to an incorrect address, and several other embarrassing situations.
Improve product life cycle: The main goal of MDM software is to improve efficiency by having all master data collected and acting as a single source of truth. By doing this, numerous teams such as logistics and supply chain teams, product teams, customer care teams, marketing teams, and others will have access to the same data assets and thereby work cohesively to develop product plans. Teams can set up tighter milestones and handle order requests in a short period. All teams are made well aware of any product changes and have real-time access to the product data.
Reduce processing time and cost: The complex nature of data makes manual processing of data difficult, time-consuming, and costly.MDM solutions support data automation, thereby saving a large amount of time. Since employees do not have to manually clean up the data, it reduces processing costs and lets the employees focus on other tasks.
Improve decision-making: By having all master data under a single dashboard providing better data visualization, teams and executives can use the enterprise data to drive business intelligence and make proactive decisions.
Business users and leaders: Data-driven decisions are integral to business intelligence. By using MDM tools, business users and CXOs can use this information to analyze efficiencies and track ROI. In addition, the tracking of master data will allow business leaders to align company goals with business values and objectives and derive methods to achieve success. Data analytics is one of the core competencies for any organization to be successful, and by having a master data management software that manages and organizes data, firms only stand to benefit further. Management will be able to maintain strong relationships with various stakeholders by providing them with trustworthy data.
In addition to making proactive decisions to ensure continuous workflow, top executives can also ensure that company data is following all data compliance and regulatory standards set up geographically.
IT teams: This team would be responsible for handling the MDM software. This would involve tasks such as setting up, managing, organizing, synchronizing, and monitoring performance. Some of the important roles under this category include:
Department heads: Since MDM platforms would draw data from cross-functional teams such as finance, marketing, operations, sales, HR, and several others, this role includes subject matter experts of their respective departments who will be managing the data. They will be the ones to ensure that data quality is being maintained. They are tasked with profiling, cleaning, validating, and managing the data. They are also termed as data stewards who have agile self-service access to the software.
Master data management solutions can come with their own set of challenges.
Setting data standards: Data standards set by analyzing master data need to agree with all the various types of data available in the company. In addition, standards set need to be accepted and all the various departments need to adapt to these standards. It is a key challenge because if data standards are not planned well, the process can become quite cumbersome.
Data integration with other software: Integrating master data management tools with other applications and platforms can tend to become quite complicated. Data management, transfer, and integration with other platforms can cause errors, show compatibility issues, and even take a lot of time to close. In addition, integration errors could cause only some sections of data to be transferred.
Need for efficient data stewardship: To maintain the quality of data, data stewards need to maintain and monitor the data using the MDM software. The presence of bad data will cause management issues, cycle disruptions, and hamper data validation. Data stewards from various teams need to be established as efficient owners of their section of the data to prevent any issues.
Model agility and flexibility: One of the biggest challenges that companies face is to ensure that the right master data management solution is selected. Due to a large number of offerings as well as the complexity of handling data from different sources, it becomes increasingly challenging for companies to choose the right master data model best suited for the company. An inactive and ambiguous MDM software could do more harm than good.
Choosing the right MDM solution allows teams to have an efficient data management process by improving data governance, data delivery, and ultimately achieving business alignment.
Identify cost drivers: Before deciding to opt for a master data management solution, it is a good idea to understand the various cost drivers involved. The three main cost drivers in master data management software include:
Identify master data sources: A key step in deciding what master data is to be managed is to identify the various sources of master data. Firms might require only one type of master data to be managed, whereas large corporations would need to manage several master data categories.
Conduct feasibility analysis: Before choosing the master data management software, companies should undertake a requirement and feasibility study/analysis. Once done, the company can use the data to create reports of pain points that will assist to choose a master data management solution.
Integration support: Companies should choose a master data management software that smoothly integrates with all other existing applications that the firm uses. This protects existing tech investments and prevents the need for replacement which would again drive up costs. Choosing a master data management solution that smoothly integrates with other support systems, platforms and tools is a key factor when deciding on a master data management software.
After-sales service: Companies should look for a master data management software that offers efficient after-sales support. The software should be able to provide support at multiple levels and options based on the various devices being managed. In addition, for enterprises that are present across the globe, it would be a good idea to ensure that the master data management software has support teams in various countries and supports different languages.
Create a long list
It is a good practice to list out the pros and cons of different MDM software, and come up with a long list. Long lists help eliminate software that do not provide critical functionality, thereby reducing the list to be more compact and precise.
Create a short list
Once the list has been narrowed down, the customer can begin to compare different features and offerings of the MDM software as per the company requirements as well as the data sources that will be managed. Pricing decisions need to be compared at this stage. A highly efficient method of comparing various MDM tools would be to opt for technology review platforms, such as g2.com, which provide unbiased reviews and different perspectives on the benefits/issues with various master data management software.
Conduct demos
Most master data management software vendors offer live demos, so it is a good practice to opt for these to ensure that companies have made the correct decision and that the master data management software is easily integrated within the IT environment.
Choose a selection team
Choosing the right team to work together on deciding on MDM software is a critical part of the process. The team should include a mix of different personas who have the required skills, interests, and time. Some roles include project manager, department heads, CXOs, and others.
Negotiation
Once the software is selected, teams can negotiate and come to the best pricing decision.
It is important to negotiate to include possible additional costs that might come in the future. These additional costs could include software upgrades, licensing costs, and other requirements.
Final decision
Once all the steps are complete, the final decision is made weighing all factors and scenarios. The decision is taken weighing in all the above factors, and the best possible master data management tool is identified.