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.
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 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 vendor consolidation and simplification (fewer systems to administer, manage and integrate, combined with higher chance of successful user adoption). 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 core data to support a number of Business Intelligence initiatives, for example, can be made available.
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 vendor consolidation and simplification, 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, for example).
However, the ability to build function-led data input workflows has been forfeited in favour of IT-led data 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.
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 data-driven, IT-led solution – 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.
- Centralization of data into a single location outside of transactional systems
- Allows for good data governance and control / maintenance of inputed data
- A single, consistent, authoritative version of the truth for core data is achievable. It provides the ability to consolidate and clean data.
- Helps to improve data quality across core data elements
- Offers a high degree of internal workflow capabilities and flexibility for data modeling
- Strong technical integration capabilities. Data can be made available across multiple systems and can be used for BI projects
- In many cases, you still need multiple multi-domain MDMs in order to achieve all functionalities required
- It is an IT-led solution to a data problem and, as such, tends to have a narrow focus which does not always consider wider business use cases for the data
- It runs counter to data democratization as ownership of the data should sit with those who understand the data
- Domain expertise is still required to fully realize the benefits of data integration and make them available to end users
- There is often no supplier portal; the solution is internally focused. This means there is no workflow to allow for collaboration with the suppliers. A solution is to buy a workflow tool to overlay on top of the MDM platform
- While offering strong technical integration capabilities, generic MDM solutions lack the detailed context of integrating supplier data, particularly with the ERP(s), in the real-world. While theoretically possible, this is a big driver of cost in practice.
- It is faster to implement and provides quicker time to value due to its alignment with business requirements, such as the need for a supplier onboarding portal and ongoing collaboration with suppliers
- Data quality can be controlled by the domain experts
- Data can be checked and verified at creation, ensuring a golden record for master supplier data
- It integrates easily with other systems, such as ERP, as part of a Master Data Management (MDM) approach
- It gives ownership of the data – and more autonomy – to the business unit(s) to drive accurate insights and reports
- It supports the workflows of domain experts and can be configured to match bespoke requirements of the enterprise through drag-and-drop low-code customization
- By combining the four key elements (portal, MDM, workflow and integration) with domain expertise, dedicated SIM offers the fastest route to true automation.
- It provides pre-built access to third-party data sources (or punch-outs) which can be used to validate data
- SIM provides the best return at the lowest cost over the length of the project
- Where the IT department has vendor consolidation as a goal, an additional solution for supplier data may run counter and so require its own business case
- It requires broader stakeholder support and cross-functional collaboration (although this collaboration is the best outcome for the enterprise)
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.