Voices | How fast can you deliver an MDM MVP?

Can an MVP be ready in just 60 days? Catherine Cherry, MDM Practice Lead, explores how rapid implementation is possible, what compromises are involved, and how to ensure an MVP is a solid foundation for long-term success.

As AI tools and systems are embedded into the world’s working environment, there’s been a focus on efficiency. Even before AI, there’s been a constant focus on delivering quicker, faster, better. Unsurprisingly, this includes rollout times of minimum viable products (MVPs). Gartner highlighted this in their Market Guide for Master Data Management Solutions (Dec 2024) , saying “The average implementation time has dropped from nine months to having a minimum viable product (MVP) ready in under 60 days.” I wanted to explore the how an MVP could be implemented this quickly, and what would be delivered.

It’s important to remember that master data management is still a marathon not a sprint. Just like preparing for a real marathon, the groundwork and training before you hit the starting line are a must. If you skip or rush that preparation, you risk a haphazard result that falls short of your goals.

Messaging that is frequently vendor-led might have you believe that master data management is becoming a plug-and-play solution, but the reality on the ground tells a different story. Working directly with clients, it’s clear that successful implementation still depends on careful planning, collaboration, and long-term strategy. A quick rollout might mean you’ve got something working on paper, but that doesn’t guarantee it’s set up for real-world success, or that it achieves the expected business benefits.

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So, what is an MVP? And what can you realistically achieve in 60 days?

What does MVP mean?

A minimum viable product is just that. Minimal. It’s not fully-fledged. There will be compromises. It may not include all third-party data sources, it may only cover a single data domain, or it may lack some automation or integration that will come later. Despite these compromises it’s crucial that an MVP is not something disposable.

A successful minimum viable product should be the foundation for something bigger. Rather than a trial run or a throwaway project, it’s the starting point that you can build on, one that will evolve and grow as it becomes a core part of the business.

MVP is not synonymous with a short time frame. What is ‘viable’ for one organisation and achievable in three months may look entirely different for another, requiring 18 months. It’s not about getting something live quickly to say you can. The key is in the name, it needs to be viable for its intended purpose. This means considering who will use it and how.

  • Business Users: Can they use it effectively in their daily operations?
  • Analytics Teams: Does it provide the necessary data for reporting and analysis?
  • Suppliers: Is it fit for their requirements and interactions?

Adopting a lean approach

A lean approach to master data management prioritises the most impactful data, delivering real business value without tackling everything at once.

  • Focus on master data that drives key outcomes.
  • Identify the smallest, most valuable data set influencing those outcomes.

Don’t aim to cover every requirement immediately. Focus on the "most valuable fruit", i.e. the data that will deliver the greatest business impact first.

Defining the right MVP for your organisation

Understanding what you’re trying to solve with your master data management solution is key to forming your MVP. The scope of an MVP should align with these answers:

  • What’s the minimum needed to prove the solution’s value?
  • What are you not willing to compromise on?
  • What challenges does it need to resolve?
  • What business case justifies the investment?
  • What’s the least complex version that will be approved?
  • What changes will this MVP drive, and what impact will they have?

The scope and timing will depend on your business goals, the challenges you’re facing and what needs to be demonstrated before scaling. There’s no fixed timeline for an MDM MVP, as each one is bespoke to your organisation. We’ve delivered well-scoped MVPs quickly, some in full in three months, others in phased implementations over several months.

While speed is impressive, quality matters more. An MVP must prove value, but that doesn’t mean rushing at the expense of substance. It must be functional and have solid foundations so that the MVP can evolve into what your business need it to be.

What is a full MDM implementation?

The key difference between a minimum viable product and a full implementation is scope and flexibility:

Feature

Minimum Viable Product (MVP)

Full Implementation

Scope

| Defined, limited to key priorities

| Expansive, evolving over time

Domains

| Usually 1-2 critical domains

| Need not be limited to 1-2 data domains

Integrations

| Essential systems only (if any)

| Full integration across enterprise

Governance

| Basic controls to ensure usability

| Comprehensive policies and automation

Phasing

| Delivered within a single phase

| Delivered in multiple phases

Flexibility

| Rigid scope to maintain viability

| Solution may adapt with business needs

Business Value

| Proves concept and initial value

| Delivers long-term transformation

With a minimum viable product, you must constantly challenge the scope to ensure it remains viable and delivers value within defined constraints. In contrast, a full implementation allows for a broader, more adaptable roadmap, making room for new priorities and requirements as they emerge but still making sure that incremental phases are clearly scoped to ensure continued delivery.

What can you realistically achieve within 60 days?

Referring back to the 60-day delivery time, it’s essential to define where that clock starts. Are we saying its:

  • 60 days to build a solution?
  • 60 days to design and build a solution?
  • 60 days starting from scratch, with no existing requirements or understanding of value?

Each scenario is vastly different, and without clear scope expectations can become misaligned.

Clearing up misconceptions

There’s no single “60-day fix” for an MDM MVP because every organisation starts from a different place. Some have strong foundations, while others need time for data preparation, governance, or stakeholder alignment. Every business moves at its own pace, and that’s okay.

An MVP is about proving value efficiently, not delivering everything at once. The best approach is the one that balances speed with substance, ensuring the result is meaningful and sets the stage for future growth.

Case studies: what’s possible in a limited timeframe?

Here are two different projects which show how scope influences what can be delivered within a short timeframe:

Client one (17-week project, 85 days):

  • The goal was to provide product master data for an existing reporting solution.
  • Data was to be moved from current sources to a more mature master data management platform.
  • The scope was clearly defined from the outset.
  • We knew what the existing solution did, what it didn’t do, and what data was provided.
  • Because of this clear ring-fenced scope, we could focus on execution.

Client two (18-week project, 90 days inc. 2 weeks of knowledge transfer):

  • A different scenario - rather than recreating an existing system, we were building on their out-of-the-box CMDM configuration.
  • This accelerated delivery by leveraging a pre-existing design rather than building from scratch.
  • Some MDM use cases are universally applicable, allowing for the transfer of best practices across projects. However, some specific contexts may require tailored approaches.
  • It demonstrated that using a pre-configured system can deliver value more efficiently when aligned with business needs.

Both projects were buildable within a clear scope and delivered results that aligned with expectations.

Be realistic on your starting point

If you’re starting from scratch, you need to have a different mindset. When there’s no pre-defined scope, no clear understanding of business value, and no existing system to reference, jumping straight into a 60-day build isn’t realistic. Without a clear, aligned definition of ‘viable,’ measuring the success of an MVP becomes challenging. Instead, the priority should be establishing a strong foundation for long-term success.

In these situations, the focus should be on assessing the current state and defining clear requirements before developing an MVP. Investing those 60 days upfront helps establish a solid foundation, reducing the risk of delays, costly rework, and potential project setbacks.

Value of an implementation partner

We know the challenges that come with implementing MDM, and proving value quickly in an MVP only makes them more apparent. Configuration mistakes, unrealistic expectations, and overlooked dependencies can quickly cause delays. Even experienced teams may struggle to configure MDM effectively for their specific needs.

Delivering an MDM MVP in 60 days is ambitious, even with expert support. Expert guidance ensures that critical design decisions, particularly data model design, are carefully established from the outset, regardless of time constraints. Once implemented, these elements are difficult to revise.

Beyond the technical setup, a partner like Amplifi helps keep the project on track, flagging risks early and managing expectations. We provide structure and authority, making it easier to stay focused on delivering value without distractions or scope creep.

If you’re wanting an MVP that will prove value, or in need of a full MDM implementation, then Amplifi is your trusted data and AI partner. With our collective expertise across multiple data disciplines, we work to solve your most complex challenges.

Read our Modern MDM guide to explore how to use modern data strategies, such as data mesh, data fabric, and emerging technologies such as artificial intelligence, can help overcome some of the common challenges that MDM projects often face.

Download Guide | How not to fail an MDM Implementation

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About the Author

Catherine Cherry is MDM Practice Lead at Amplifi.

Catherine possesses a wealth of experience across different industries, specialising in several aspects of data management including Data Analysis, Data Modelling, Data Architecture, Data Governance, MDM Design & Implementation and Data Quality. To get in touch with Catherine, reach out here.

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