July 8, 2020

Multi-domain Master Data Management Won’t Fix Your Data Problems – Here’s Why

multi-domain mdm single domain mdm master data 600px

Getting to grips with digital transformation and multi-domain MDM

Digital transformation relies on the effective application of digital technologies. However, as far as procurement is concerned, adoption of technology is hindered. The recent Deloitte CPO survey showed that quality of data was the most cited obstacle to adoption, with 57% of respondents stating it was one of the top three main barriers.

Deloitte CPO Survey 2019

Enterprises have embarked on multi-domain MDM initiatives in order to resolve the issue and many are in various stages of implementation. The idea of multi-domain MDM is to have one centralised, trusted repository for all master data records that can be used by any other domain, enterprise-wide, as required.

In reality, however, it has not delivered on the trusted level of data quality that multi-domain MDM vendors suggested it might. Consequently enterprises are having to re-assess their strategies as they learn first-hand that multi-domain MDM is not the silver bullet to fix their problems.

Additionally, in a recent HICX survey on procurement data, 82% of respondents agreed that the procurement function not owning the supplier data problem end-to-end makes it more difficult to address.

This does not mean master data management is the wrong strategy, on the contrary. However, it does warrant an understanding of why specifically multi-domain MDM may fall short. In this article, we’ll examine the reasons why an enterprise-wide data initiative is an enterprise-wide issue that requires domain-specific input and collaboration – including the resolution of some conflicts – in order to attain a truly successful master data management strategy that incorporates the requirements of the procurement function.

Without this, the headache experienced by the 57% of CPO respondents to the Deloitte study will only continue and intensify. Worse still, procurement will not be able to benefit from the wider advantages of digital transformation, nor will the business use cases for procurement be addressed.

We recommend the following approach:

  • Gain an understanding of the IT point of view
  • Formulate the arguments for a domain-specific approach and be able to articulate the benefits
  • Collaborate to drive an enterprise-wide solution that is a balance between a purely technical solution led by IT and a business use case led solution with wider advantages

Understanding IT’s point of view on multi-domain MDM

Just as procurement is tasked with driving down costs while mitigating risk, IT’s goals will be focused on rationalising software (to reduce cost) and simplification (fewer systems to administer, manage and integrate, combined with higher chance of successful user adoption, including all features that provide value). Superficially, multi-domain MDM appears to achieve these IT targets and, as such, resonates well at C-level.

From a data perspective, it means that information that needs to be shared across the business is captured in fewer systems – and fewer systems should yield greater enterprise-wide trust when the information is used.

However, there is a trade-off for business users. Data models tend to require different levels of complexity, based on hierarchies, relationships and dependencies. No more so than in procurement, where the complexities – and therefore the required governance – go far beyond even those seen in some of the most intricate product and customer databases.

While IT has met its objective of rationalisation, simplification and democratisation of already-created data, the solution does nothing to fix the problems of inadequate data entering the system in the first instance. This has to be fixed by function-led workflows that manage data at point of creation (such as supplier onboarding) or, for example, within transactional systems.

However, the ability to build function-led data input workflows has been forfeited in favour of IT-led goals. Simplification in one area has created enormous inefficiencies and deficiencies elsewhere throughout the enterprise, while data can only be ‘fixed’ after it has entered the enterprise, not captured and qualified at point of entry.

Benefits of single-domain, or domain-specific, MDM

On the other hand, single-domain, or domain-specific, MDM, means that workflows can be implemented that ensure good quality data capture at the point of entry into the enterprise data ecosystem. It is imperative that a single-domain solution has this at the core of its offering and is able to integrate, for example, into the ERP or ERP systems.

While it lends greater autonomy to procurement there are benefits for IT as well. Capturing ‘bad data’ at source removes the need to conduct endless data cleansing exercises that need to be administered centrally and that require cross-functional collaboration, but without the workflows to support them.

It also means that functions are able to better self-serve when it comes to creating workflows specific to their domain expertise. Management of supplier data involves complex scenarios and considerations, some of which can be unforeseen due to the nature of the supplier ecosystem and many of which are known to the domain experts only. The burden of ‘building around’ these cases should necessarily be placed into the area of domain expertise, which can be facilitated by a domain-specific solution.

Further, the volume of data being created both internally and by external parties that needs to be integrated into processes, such as validation processes, is growing exponentially. In particular, supplier information requires punch-outs to specific external databases, such as tax ID verification, in order to support domain-specific activities. Multi-domain MDM vendors will struggle to achieve any kind of ‘one-size-fits-all’ for these circumstances, which change regularly based on domain-specific events. This underlines another reason why bad quality data can often circulate within multi-domain MDM configurations.

In fact, rather than attempting to implement and enforce some kind of ‘one-size-fits-all’ solution across the enterprise and make it the repository for all master data, it is becoming increasingly clear to business users that the key to consistently high-quality data and effective governance is having a model that encourages and facilitates function-led data input.

Procurement needs to be able to formulate the arguments for a domain-specific approach, and also be able to clearly articulate these benefits in cross-functional conversations involving multiple stakeholders.


Collaboration is required to drive an enterprise-wide solution that achieves this balance between a purely technical solution led by IT – while being sympathetic to their position – and a business use case led solution with these wider advantages.

For this reason, it is worth being highly familiar with a summary of the arguments for both types of approach, while understanding that, provided integration is robust, the ‘multi’ versus ‘single’ debate is really a technical one, rather than an ‘either-or’ strategic discussion.

It is a matter of determining the best solution (regardless of technology definitions) for the business objectives identified.

To summarise:

Multi-domain MDM

multi domain mdm master data management pros cons 2

Single-domain MDM

single domain mdm master data management pros cons

Conclusion: focus on the end goal and the wider picture

The end goal, whether multi-domain MDM or domain-specific MDM, is the same – a ‘golden master data record’, which can be relied upon to support the needs of the function (procurement), as well as the needs of the broader business.

Procurement needs to position itself as a proactive advocate of a balanced decision that continues to incorporate the data-driven goal, as well as being the champion of (and experts in) what is required to reach a truly successful digital transformation strategy.

If you found this blog useful, then you may want to check out our other detailed resources as well, covering different aspects of master data management, data cleansing, data governance and more.


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