Master Data Management is the complete management of master data. It includes the cleaning, governance, tracking, and control of all master data into consolidated records. These ”golden records” can subsequently be used to improve business processes, workflows, and outcomes.
Master Data Management consists of a set of processes, disciplines, and technologies that enable the use of business-critical data in disparate systems across your enterprise.
Master Data Management allows you to align your people, processes, and technology, bringing value to your partners and customers through data integration and access. It gives you the tools to make intelligent and informed business decisions.
There are five major categories of master data:
- Parties – Everyone who conducts business with the enterprise, including customers, prospects, suppliers, and partners.
- Places – Actual places and how they are segmented, such as geographies, locations, subsidiaries, sites, and zones.
- Things – What the enterprise sells or manages, such as products, services, or assets.
- Financial and Organizational – Reporting and accounting categories, including organization structures, sales territories, chart of accounts, cost centers, business units, profit centers, and price lists.
- Reference Data – Smaller lists of values that give context to other master data and/or transactional data such as lists of countries, states, industry sectors, classifications, etc.
To really understand master data, it’s important to take a look at other data types in the enterprise that aren’t master data, but can sometimes look like it.
- Transactional Data – Transactional data describes business events and is responsible for generating the largest volume of data in the enterprise. It resides in the CRM, ERP, SCM, or other systems.
- Log Data – Log data records events or takes snapshots of process states at moments in time. It is extremely important to system operational efficiencies and preventive maintenance applications. Most big data, such as sensor data, machine data, and change-in-state data, are examples of log data.
- Metadata – Metadata is data that describes other data; it is the underlying definition or description of data. Master data, reference data, and log data all have related metadata.
- Big Data – Big data has many different definitions, but the most common is from Gartner’s Doug Laney. He characterized big data by “three Vs”: volume, variety, and velocity. Quite simply it is the combination of the previous four types of data: log data, transactional data, reference data, and master data.
What is a Master Data Management system?
A Master Data Management system helps organizations manage all of their data to enable data consistency with the goal of improving business processes and outcomes. A Master Data Management System may include multiple software systems and processes that are used to standardize data across an enterprise.
A few examples of what a Master Data Management system can do include:
- Ensure timely product recalls
- Facilitate privacy management
- Implement effective customer care programs
- Improve business processes
- Manage threats
- Reduce data errors and redundancies
- Address compliance concerns
- Manage risk
- Process and manage currency
- Reduce labor costs
- Optimize workflow processes
What is Master Data Management software?
Master Data Management software is cloud-based or on-premise software that utilizes internal and third-party data to improve business processes and outcomes.
Different types of Master Data Management software can be implemented as SaaS (Software as a Service) or on-prem.
SaaS Master Data Management software is cloud-based, and is isolated and encrypted in transit, allowing companies to start small and scale up fast with a modern, cloud-native architecture.
On-prem Master Data Management software is housed on a local server or even a laptop within a company’s own secured systems.
Many Master Data Management software companies allow you to migrate from on-prem to SaaS or another cloud service.
Master Data Management software can include the following components:
- Data aggregation
- Data applications
- Data services
- Data cleansing
- Data streaming
- Data anonymization
- Business intelligence and analytics
What is a Master Data Management solution?
A Master Data Management solution enables data teams to collaboratively manage, govern, and access a comprehensive data model with rules, policies, enrichment, validation, and workflows. Using batch processing or real-time, a Master Data Management solution enables you to quickly integrate any existing apps to transform source data into high quality golden records for analytical or operational needs.
A few examples of what Master Data Management solutions can facilitate:
Empowering business leaders by giving business decision-makers the ability to guess less, know more, and make better business decisions based on a single source of truth and easy access to actionable data insights.
Enhancing data teams by optimizing their ability to build data applications that your business decision-makers need to win a competitive advantage and make collaboration fast and effective.
Master Data Management solutions allow businesses in any vertical market to:
- Onboard, understand, and document existing data sources.
- Move data across systems easily while reducing integration costs.
- Automate enforcement of data quality with third-party reference data.
- Collaboratively access, manage, organize, validate, and publish data.
- Enable 100% trusted insights for analytical and operational reporting.
- Establish enterprise data policies, glossaries, and governance workflows.
With a Master Data Management solution, you will be able to seamlessly:
- Develop applications, analytics, and BI reports for any business vertical with customizable workflows and interfaces driven by your data.
- Manage the lifecycle of all products, and increase product and process integrity for all optimal supply chain creation, lineage, consolidation, and maintenance across geographies with a centralized hub for all data.
- Streamline time-to-value using a single software platform for governance, master data, reference data, data quality, enrichment, and workflows.
What is the best Master Data Management solution?
Over the past decade, embracing a Master Data Management solution has become critical for the integration of systems, data, people, and processes.
The best Master Data Management solution is built to empower your people, conform to your needs, and enable data-informed decision-making across your enterprise, all in one platform.
Leading organizations rely on Semarchy’s Master Data Management solution to solve their customer, product, location, supply chain, reference, or multi-domain data challenges simultaneously while delivering business value in weeks.
Semarchy’s integrated data management platform is a flexible, future-proof, affordable way to capture ROI fast. It’s a one-stop shop for business-centric data management, powerful data integration, and intelligent data governance. With Semarchy, any size business can build trust in a single source of truth.
- Why is Semarchy the best Master Data Management solution?
- Semarchy’s rapid time to value approach and platform is designed to be agile so you can build custom apps in days and measure ROI in weeks.
- Intuitive, low-code UI lets you rapidly build custom data apps and deliver business value in days not months.
- Easily create custom, fit-for-need automations for all your data operations without code or complicated templates.
- Seamless scalability with effortless change.
- We commit to your success with exceptional delivery assurance, simple and transparent pricing, flexible implementations, and award-winning support.
- We provide customer support to ensure your data projects are successful, whether working with just us, your existing vendors, or our MDM implementation partners.
- You get seamless integration with industry-leading software like Salesforce, SAP, Oracle, MS Dynamics, NetSuite, and Marketo, as well as data blending with external providers like Melissa, Google, Bing, and more.
Semarchy has won a number of industry awards including:
- 2021 Gartner® Magic Quadrant™ for Master Data Management Solutions
- 2020 Customer Choice in Master Data Management
- The Forrester Wave™: Master Data Management Solutions, Q4 2021
Semarchy is rated by respected industry analysts and partners with leading industry brands around the world. Explore the Semarchy Unified Data Platform here, then try it.
What is a Master Data Management tool?
A Master Data Management tool is used to collaboratively govern core data elements in an agile and measurable environment for a single version of the truth.
Master Data Management tools bring together information from different applications so that it can be managed, leveraged, and integrated across the enterprise, without the burden and expense of managing multiple, siloed systems.
- Master Data Management tools aim to:
- Reduce duplication of effort in multiple systems, manual data entry, and user errors.
- Manage increased data volume to minimize data governance issues and the loss of data value over time.
- Reduce costs for managing multiple, siloed systems.
Selecting a Master Data Management tool that will fit the scope, context, and identified requirements for a data management project can be challenging. You will need to review a few considerations including:
- Master Data Management business requirements
- Master Data Management functional requirements
- Integration needs
- Data quality and governance
- Deployment models
Today’s Master Data Management tools are agile, adaptable, and easy to deploy, allowing you to connect and standardize your data across the enterprise for improved business continuity. Sec. Content
Why is Master Data Management (MDM) Important?
Master Data Management (MDM) is important for optimizing business processes and increasing business intelligence to maximize operational effectiveness and efficiency.
Regardless of industry, MDM is a critical tool for improving financial and analytical reporting, customer care and Know Your Customer (KYC) initiatives, compliance and regulatory adherence, cross-selling and up-selling opportunities, privacy and security management, supply chain optimization, and many other uses.
Master Data Management is important for business entities that want to:
- Identify relationships between datasets
- Improve overall data quality
- Reduce manual data entry, data duplication, and data redundancies
- Manage increased data volume with efficiency
- Reduce costs for managing multiple, siloed systems
- Enable informed business decisions based on trusted data
- Empower business users with data accuracy and improved performance
- Streamline operations for efficient and scalable growth
Master Data Management allows you to align your people, processes, and technology, bringing value to your partners and customers through data integration and access, and giving you the tools to make intelligent and informed business decisions.
Why use Master Data Management?
Businesses use Master Data Management for a number of different reasons. There are many business use cases for Master Data Management, depending on specific industry and business requirements like improving business efficiency, increasing business intelligence, and ensuring data quality. With the growing number of interactions and observations that enterprises are collecting through various data acquisition points, it is becoming critical to collaboratively govern these core data elements in an agile and measurable environment for a single version of the truth.
Some of the reasons that businesses use Master Data Management include:
- Legacy systems hindering business performance
- Duplication of effort in multiple systems, manual data entry, and user errors
- Increasing data volume
- Data quality and governance issues
- Increasing costs associated with multiple, siloed systems
The most important question to ask is why do you need Master Data Management? Master Data Management can improve your business outcomes with tools to help you manage all data initiatives in a single environment. Instead of having to manage multiple systems with silos of data, you can integrate and transform data from any source, define quality policies, and empower all of your teams with data-driven insights.
What is the purpose of Master Data Management?
The purpose of Master Data Management is to help businesses manage their critical data assets for improved business intelligence and efficiency. With Master Data Management in place, businesses can leverage their existing data assets. They can organize, integrate, store, enrich, validate, secure, and publish data consumed or produced by critical enterprise business processes while enabling business/IT users to collaboratively access and manage this data.
Many businesses use Master Data Management for the following purposes:
- Automate, cleanse, and standardize data across the enterprise
- Optimize business processes
- Streamline operations
- Enforce data quality and governance
- Integrate multiple internal and third-party data sources
- Enable 100% trusted insights
- Measure the value of managed data and workflow process efficiencies with analytical and operational metrics
- Make decisions based on standardized workflows and processes
- Build libraries of data-driven applications
- Increase revenue generating opportunities
Business applications leverage xDM in their core processes to guarantee semantic consistency across the enterprise, reducing costs and risks while increasing revenue-generating opportunities.
What is Master Data Management strategy?
Master Data Management strategy includes the scope, context, and identified requirements and desired outcomes for a MDM project. Depending on the enterprise and business model, there are different MDM strategies you can use to improve your business process agility and outcomes.
With the right MDM strategy, everything from geographic, facilities, and supply chain data to schedules and customer and product information is centrally stored, allowing you to connect and standardize your data across the enterprise for improved business continuity, speed, and efficiency. Developing an MDM strategy that will fit the scope, context, and identified requirements for your business use cases can be challenging. A few considerations you will need to review include:
- Master Data Management business requirements
- Master Data Management functional requirements
- Integration needs
- Data quality and governance
- Deployment models
The right MDM strategy enables businesses to reduce risk with complete control over all data, including who has access and under what conditions. With a single software platform for governance, master data, reference data, data quality, enrichment, and workflows, you can implement privacy best practices from development to productization across your enterprise. Here are six key areas to review when planning your MDM strategy:
- Master Data Management Requirements: Context and Scope
- Define the projected context and scope of your project. Will you start small, and eventually increase your Master Data Management requirements? Will your MDM solution need to be global, or in one location? Geography will make a difference in the solution’s scope, capabilities, and ongoing support.
- Does the solution fit into your Master Data Management business requirements? Determining the track record for the solution in your industry is key.
- What range of data domains will you need to meet your functional requirements?
- A single domain MDM solution covering, for example, customer data or product data?
- A multi-domain MDM solution covering several data domains like customer data, other party data, product data, and other master data that matters in your industry?
- The right Master Data Management strategy can deliver comprehensive information on all locations and assets, so you can connect functions and teams to improve your performance and business continuity.
- Master Data Management Requirements: Functional Requirements – There are a handful of general capabilities that must be prioritized within a MDM strategy, including:
- Hierarchy management
- Workflow management
- Versioning of master data/product information
- Flexible data models
- Data import/export
- Data governance/analytics/reporting
- Legacy system and application integrations – The right MDM strategy involves flexible data integration and access to improve your business outcomes, create operational efficiencies, and reduce operational costs. Be sure you consider projects that not only serve your current business use case, but support additional use cases for other departments and projects down the road.
- Master Data Management Requirements: Data Quality Requirements – Ensuring data quality is often a main reason for implementing a Master Data Management (MDM) solution. The key questions for data quality capabilities are:
- Data matching/deduplication/formation of golden records
- Data integration with third-party business directories
- Data discovery and data profiling
- Dashboards for measuring data quality dimensions
- Master Data Management Requirements: Product Information and Syndication Requirements – If the solution is going to handle product information management within your organization, and syndication of product information from suppliers and/or to resellers, you will need to consider:
- Product classification and attribution standards
- Collection of product information from suppliers
- Providing product information to resellers
- Publishing and/or creation of materials
- Additionally, it must be clarified if the solution should cover the use of the Global Data Synchronization Network by GS1 or other industry-specific data pools. Ensuring that your MDM solution has not only your current requirements but also your future considerations is key. In order to prevent costly change management programs and embrace intelligent, informed growth and expansion, enterprises large and small need increased traceability and transparency. This will help to initiate and sustain business continuity and profitability, unlocking maximum business value while controlling data infrastructure costs.
- Master Data Management Requirements: MDM Deployment Requirements
- A key question in solutions selection will be if you need to have the solution installed on-premises, on-cloud, or a hybrid between these two options.
- For cloud and hybrid solutions, the cloud platform also matters. Some prefer Microsoft Azure, Amazon AWS, Google, etc.
- Cloud migrations demand changes and enhancements to the data and architecture. Data migration experts need tools and utilities that can migrate and enhance data quickly. One of the most important factors when choosing a data integration solution is the cost of ownership. Optimizing resources and costs is key. You don’t want to purchase a solution that you can’t support internally for the foreseeable future. Make sure your business accelerates your data access with an easy, fast, and agile data integration implementation.
- Master Data Management Requirements: MDM Selection Process
- Once you have your Master Data Management requirements list complete and have narrowed your search, you will then be able to start the vendor selection process.
- This may include issuing a written Request for Information (RFI) to select vendors.
- The key to a successful Master Data Management Strategy is to identify the business domain that has the most manageable data set, and start with that one. Adding on functionality and new data sets for various business cases iteratively is beneficial in order to save time and resources and to ensure the successful implementation for multiple stakeholders and end users.
What are the benefits of Master Data Management?
The benefits of Master Data Management center around the access and usability of more accurate data for businesses that want to stay competitive, increase revenue, minimize risks, and continue to evolve. Master Data Management (MDM) simplifies data stewardship, data governance, and data integration for improved business intelligence and outcomes. The top benefits of a Master Data Management system can include:
- Improved privacy, security, and compliance
- Increased operational efficiencies
- Streamlined business processes
- Reduced costs associated with data and system redundancies
- Optimized workflow processes
- Improved business intelligence, analytics, and reporting
- Automated processes to enable data-rich applications
- Trusted and accurate insights for vendors, customers, and partners.
MDM is critical to maximize operational effectiveness and efficiency for financial reporting, customer management, customer care, compliance, product regulatory adherence, cross-selling and up-selling, privacy management, supply chain, security management, and many other critical functions.
How is Master Data Management different from data governance?
Data governance is a set of processes that ensures that important data assets are formally managed throughout the enterprise. It ensures that trusted information is used for critical business processes, decision making and accounting.
Master Data Management (MDM) consists of a set of processes, disciplines, and technologies that enable the use of this business-critical data that is located in disparate systems across your enterprise. This crucial data comes into your business systems externally, and more data is usually being created or updated internally. All of that information needs to be ‘governed’ so you have good data.
- Data governance includes:
- Rules for inputting and maintaining data (accepted definitions, stylistic rules, etc.)
- Enforcement of those rules
- Management of the data: data stewards and users within the company working on the data in accordance with those laws.
Data governance is important because it ensures that data is clean, accurate, and complete. Data governance increases efficiency, reduces duplication, and ensures that all business users are on the same page when it comes to core data sources, definitions, and rules governing that data.
Implementing the necessary people, process, and technology for effective data governance requires capabilities that span the master data management landscape.
Effective data governance requires a flexible and complete framework for mastering, stewarding, modeling, profiling, and cleansing data in a collaborative fashion. Applications that focus on governance policies, reports, and workflows alone fall short of the comprehensive business requirements for enterprise applications. Collaboration is a key component to successful data governance strategies.
Some examples of data governance include:
- Defining a list of values for data governance
- Managing your business glossary and the relationships between terms
- Identifying data lineage
A host of capabilities, such as data quality, enrichment, workflows, hierarchy, and metadata management, as well as catalogue, are required to meet this widespread business need, and ideally should be in a single platform for ease of use and fast time-to-value.
What is Customer Master Data Management?
Customer Master Data Management (MDM) allows companies to build better, more meaningful relationships with customers as individuals. Using Customer Master Data Management tools, businesses can use their data to create ideal customer journeys, and offer each consumer the right product or service at just the right moment.
Business strategies like Know Your Customer (KYC), customer retention, upselling and cross-selling all rely on good Customer Master Data management.
Large enterprise and even small companies use customer MDM to understand who their best customers are, what they care about, and how to find more of them. By analyzing customer behavior and feedback, any type of business can better position products and services to keep customers coming back.
Customer Master Database Management software can clean, organize and share large amounts of data on every aspect of customer interactions and products including:
- Customer purchase history
- Contact information
- Product inventory
- Physical assets
Some of the benefits of Customer Master Data Management include:
- Increase Upselling – Encourage buying additional features or upgrading to more expensive models.
- Expand Cross-selling – Encourage adding similar items to a purchase.
- Achieve Know Your Customer (KYC) goals – Enable business leads to drill into customer data like purchase history, location and other customer information to easily investigate strategic questions to pursue sales growth.
- Improve customer relations/service -Make it easier than ever before for customers to find what they need, complete transactions, and get the right support.
- Create internal/operational efficiencies – Customer Master Data Management software ensures you improve capacity planning, forecasting and budgeting via central management of all global business data.
Improve business agility and outcomes – Customer Master Data Management brings together information stored in different databases, spreadsheets, and systems and recognizes patterns that lead to timely sales.
- Promote compliance and risk management – Customer Master Data Management can help businesses manage compliance issues and reduce exposure to IP infringements.
- Develop intelligent pricing models – Comprehensive competitive analysis ensures you’re always one step ahead of the competition.
Mastering customer data can lead to success in any B2C or B2B enterprise.
What is the need for Master Data Management in healthcare?
The demand for the healthcare industry to include new data domains (e.g., Providers, Organizations, and Locations) and integrate data from outside sources (other health systems, public health data, or reference data) is growing exponentially. Healthcare Master Data Management tools solve this problem by enabling healthcare providers to share clinical, patient, medical, and pharma information across disparate systems with a high degree of data security and integrity. Healthcare leaders recognize that they must transform their data management systems to respond to rapid change and deliver tangible clinical and business benefits to their stakeholders. This is where Master Data Management in Healthcare comes in.
- Some of the benefits of Master Data Management in Healthcare include:
- Creating a high-quality Customer 360° View and single view of patient data while remaining compliant with growing data privacy and security requirements for healthcare organizations.
- Consolidating large volumes of sensitive data into a single unified solution for operations and analytics.
- Managing large volumes of healthcare data with improved data quality and governance to reduce errors, optimize costs, and increase patient safety and care compliance.
- Promoting interoperability for continuity of care across multiple platforms, EMR / EHR, ePrescribing and telehealth systems.
- Maximizing efficiency and connections with patients, providers, and partners for an up-to-date, holistic view of patients for consistent quality of care and improved patient outcomes.
- Ensuring the proper governance and data quality in healthcare is often an important reason for implementing Healthcare Master Data Management (MDM) solution.
- Increasing business efficiency and reducing costs by streamlining intakes, quality reporting, admissions, billing, and other clinical or revenue-driven initiatives.
- Safeguarding patient records for compliance while adapting quickly to changing requirements as they are published without impacting operational systems, including HIPAA and GDPR compliance and governance requirements.
- Driving innovation and enhancing decision-making with a single source of truth for analytics while improving internal operational efficiencies by eliminating the IT, administrative, and financial burden of managing multiple sources and software systems.
With Healthcare Master Data Management, providers can seamlessly integrate data and eliminate manual processes to bring clinical quality to patients and efficiency to business.
Master Data Management in Healthcare allows each clinical and financial process and workflow to be standardized and optimized. Healthcare administrators can easily investigate care quality, manage population health, or measure fee-for-service performance and improve patient experiences safely.