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7 Steps to Scope Out Master Data Management Requirements: A Quick Overview and Free eBook

By Scott Moore, Director of Presales, Semarchy

With the growing number of interactions and observations enterprises collect 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. However, this governance process comes with its own set of challenges. 

Some of the greatest challenges include:

  1. Legacy systems hindering business performance
  2. Duplication of effort in multiple systems, manual data entry, and user errors
  3. Increasing data volume leads to data governance issues and ultimately loss of value over time
  4. Managing costs for multiple, siloed systems
  5. Vast volumes of data from various sources

Overcoming these challenges requires robust data governance frameworks, establishing clear data ownership, defining data stewardship roles, and enforcing data quality standards. This is where Master Data Management (MDM) tools come in – tools that bring together information across different applications to manage, leverage, and integrate across the enterprise without the burden and expense of managing multiple, siloed systems. 

Selecting a solution that will fit the scope, context, and identified MDM requirements can be challenging. A few considerations you will need to review include: 

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  • Master Data Management business requirements 
  • Master Data Management functional requirements
  • Integration needs
  • Data quality and governance
  • Deployment models

There are many solutions available in the MDM market for any business use case. The challenge is selecting the right one for your context, scope, and requirements. But you first need to assess your current state by conducting a data audit. This involves identifying the data sources and stakeholders and evaluating the data quality, governance, and integration aspects.   

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Once you have a clear picture of your current state, you can start planning your MDM strategy. Here are the seven key areas to review:  

1. Master data management scope and context

The first place to start is with 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 scope, capabilities, and ongoing support.
  • Does the solution fit into your master data management functional requirements? Determining the track record for the solution in your industry is vital. 
  • 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? 
  • Multidomain Master Data Management software 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 at your fingertips, so you can connect functions and teams to improve your performance and business continuity.

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2. Master data management functional requirements

A handful of general capabilities must be prioritized within the solution selection for master data management (MDM) and the adjacent product information management (PIM) discipline. These can include prioritizing functionality for: 

  • Hierarchy management
  • Workflow management
  • Versioning of master data/product information
  • Flexible data models
  • Data import/export 
  • Integration/API
  • Data governance/analytics/reporting
  • Legacy systems and applications to include: SAP, Salesforce, Microsoft, etc. 

The right MDM strategy involves flexible data integration and access to improve business outcomes, create operational efficiencies, and reduce operational costs. Consider projects that serve your current business use case and support additional use cases for other departments and projects down the road.   

3. Master data management quality requirements

Ensuring data quality is often the main reason for implementing an MDM solution. The key criteria 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

The right MDM strategy enables businesses to reduce risk with complete control over all data, 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 the enterprise.

4. Master data management 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 meets not only your current requirements but also your future considerations is critical. To prevent costly change management programs and embrace intelligent, informed growth and expansion, enterprises large and small need increased traceability and transparency. This is to initiate and sustain business continuity and profitability, unlocking maximum business value while controlling data infrastructure costs.

5. Master data management 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 master data management software, as well as hybrid solutions, the cloud platform also matters. Some prefer Microsoft Azure, Amazon AWS, or Google.

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 data access with an easy, fast, and agile data integration implementation.  

6. 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 all of the most promising solutions in the selection. The response will give you a detailed understanding of the capabilities offered, and a price indication including license price and model required consultancy costs, and internal resources needed.
  • You may issue a detailed Request for Proposal (RFP) and invite the providers to give a demo and answer specific concerns. 
  • From there your organization can award the best-fit solution provider with a contract and you can commence the implementation, possibly assisted by an implementation partner.
  • Your organization may also ask the best-fit solution provider for a Proof of Concept (POC), possibly with the assistance of a consultancy firm. If the result is successful and the total cost of ownership (TCO) matches your business case, you can begin the implementation based on a contract with the solution provider and possibly an implementation partner. 

7. Plan for MDM results

With an improved MDM strategy, everything from geographic, facilities, and supply chain data to schedules, customer and product information is centrally stored, allowing you to connect and standardize your data across the enterprise for improved business continuity and agility. 

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. With an MDM 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 fast time to value using a single software platform for governance, master data, reference data, data quality, enrichment, and workflows. 

Today’s MDM tools and technologies are agile, adaptable, and easy to deploy. 

Book a demo of the Semarchy Unified Data Platform today and see measurable value in just a few weeks.  

Get Your Free Master Data Management Solution Buyer’s Guide eBook

Solutions available on the MDM market are both similar and different. Therefore, you may spend time comparing capabilities that in fact are fulfilled by any solution on the market but miss comparing capabilities that will make a difference to you. Download the independent guide to read Henrik Liliendahl’s assessment of Master Data Management Solutions.

What are your MDM requirements? 

The Semarchy Unified Data Platform is your integrated MDM and reference data management software. It’s the one-stop shop for business-centric data management, powerful data integration, and intelligent data governance. With Semarchy, any sized business can build trust in a single source of truth.

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