When blueprinting a Master Data Management (MDM) solution one aspect is if – or in what degree – you should unify customer MDM and supplier MDM.
In theory, you should unify the concept for these two master domains in some degree. The reasons are:
There is always an overlap of the real-world entities that has both a customer and a supplier role to your organization. The overlap is often bigger than you think not at least if you include the overlap of company family trees that have members in one of these roles.
The basic master data for these master data domains are the same: Identification numbers, names, addresses, means of communication and more.
The third-party enrichment opportunities are the same. The most predominant possibilities are integration with business directories (as Dun & Bradstreet and national registries) and address validation (as Loqate and national postal services).
In practice, the problem is that the business case for customer MDM and supplier MDM may not be realized at the same time. So, one domain will typically be implemented before the other depending on your organization’s business model.
Most MDM solutions must coexist with an – or several – ERP solutions. Many popular enterprise grade ERP solutions have adapted the business partner view with a common data model for basic customer and supplier data. This is the case with SAP S/4HANA and for example the address book in Microsoft Dynamics AX and Oracle JD Edwards.
MDM solutions themselves does also provide for a common structure. If you model one domain before the other, it is imperative that you consider all business partner roles in that model.
Data Governance Considerations
A data governance framework may typically be rolled out one master data domain at the time or in parallel. It is here essential that the data policies, data standards and business glossary for basic customer master data and basic supplier master data is coordinated.
Business Case Considerations
The business case for customer MDM will be stronger if the joint advantages with supplier MDM is incorporated – and vice versa.
This includes improvement in customer/supplier engagement and the derived supply/value chain effectiveness, cost sharing of third-party data enrichment service expenses and shared gains in risk assessment.
Check the list of innovative solutions in the MDM space here.
“By 2023, organizations with shared ontology, semantics, governance and stewardship processes to enable interenterprise data sharing will outperform those that don’t.“
Interenterprise data sharing must be leveraged through interenterprise MDM, where master data are shared between many companies as for example in supply chains. The evolution of interenterprise MDM and the current state of the discipline was touched in the post MDM Terms In and Out of The Gartner 2020 Hype Cycle.
In the 00’s the evolution of Master Data Management (MDM) started with single domain / departmental solutions dominated by Customer Data Integration (CDI) and Product Information Management (PIM) implementations. These solutions were in best cases underpinned by third party data sources as business directories as for example the Dun & Bradstreet (D&B) world base and second party product information sources as for example the GS1 Global Data Syndication Network (GDSN).
In the previous decade multidomain MDM with enterprise-wide coverage became the norm. Here the solution typically encompasses customer-, vendor/supplier-, product- and asset master data. Increasingly GDSN is supplemented by other forms of Product Data Syndication (PDS). Third party and second party sources are delivered in the form of Data as a Service that comes with each MDM solution.
In this decade we will see the rise of interenterprise MDM where the solutions to some extend become business ecosystem wide, meaning that you will increasingly share master data and possibly the MDM solutions with your business partners – or else you will fade in the wake of the overwhelming data load you will have to handle yourself.
The latest Gartner Hype Cycle for Data and Analytics Governance and Master Data Management includes some of the MDM trends that have been touched here on the blog.
If we look at the post peak side, there are these five MDM terms in motion:
Single domain MDM represented by the two most common domains being MDM of Product Data and MDM of Customer Data. Doing Customer MDM and Product MDM is according to Gartner still going up the slope of enslightment towards the plateau of productivity.
Multidomain MDM solutions as examined here on this blog in the post What is Multidomain MDM?.According to Gartner there are still desillusions to be made for these solutions.
Interenterprise MDM, which before was coined Multienterprise MDM by Gartner and I like to coin Ecosystem Wide MDM. An example of a kind of solution with this theme will be PDS as explained in the post What is Product Data Syndication (PDS)? This trend has, estimated by Gartner, just passed the peak and have more than 5 years before reaching the plateau of productivity.
It is also worth noticing that Gartner has dropped the term Multivector MDM from the hype cycle. This term never penetrated the market lingo.
Another term that is related to- or opposed to– MDM and that is almost only used by Gartner is Application Data Management (ADM). That term is still in there making the under most radars progress near the final uphill climb.
The Master Data Management (MDM) market has traditionally been divided into Customer MDM and Product MDM – with Vendor/Supplier MDM as a rarer third option.
However, from being an academic notion we see more and more implementations where the MDM solution is build as a Party MDM solution, where the party entity encompass customer, vendor/supplier, other business partners, internal business units and any other party entity that matters to the sell, buy and make side of the enterprise.
The party MDM concept will also encompass the employees (and contractors) in the business units – which can be seen as Human Resource MDM – as well as the contacts at B2B customers, vendors/suppliers and other business partners.
Then there is the good old question: “What is a customer?”. In many business scenarios there are more than direct customers that matters in marketing and selling. In manufacturing, including life science, there are B2B2C chains. In these and other industries there are influencers that matters. In life science that is healthcare professionals. In building materials that is for example architects and other construction professionals.
In banking the term counterparty is used to cover both direct customers and other parties that are referred to in the service delivery. In education there are teachers and students. In public administration there are citizens.
Practically all organizations have more parties than customers and vendors/suppliers involved in the operating model and therefore their descriptions must sooner or later be handled as master data in a unified Party MDM model. This will underpin the digital transformation that is on the agenda in every organization these days.
One challenge here is how to extend the capabilities in MDM / PIM / DQM solutions that are build for Business-to-Business (B2B) and Business-to-Consumer (B2C) use cases. Doing B2B2C requires a Multidomain MDM approach with solid PIM and DQM elements either as one solution, a suite of solutions or as a wisely assembled set of best-of-breed solutions.
In the MDM sphere a key challenge with B2B2C is that you probably must encompass more surrounding applications and ensure a 360-degree view of party, location and product entities as they have varying roles with varying purposes at varying times tracked by these applications. You will also need to cover a broader range of data types that goes beyond what is traditionally seen as master data.
In DQM you need data matching capabilities that can identify and compare both real-world persons, organizations and the grey zone of persons in professional roles. You need DQM of a deep hierarchy of location data and you need to profile product data completeness for both professional use cases and consumer use cases.
In PIM the content must be suitable for both the professional audience and the end consumers. The issues in achieving this stretch over having a flexible in-house PIM solution and a comprehensive outbound Product Data Syndication (PDS) setup.
As the middle B in B2B2C supply chains you must have a strategic partnership with your suppliers/vendors with a comprehensive inbound Product Data Syndication (PDS) setup and increasingly also a framework for sharing customer master data taking into account the privacy and confidentiality aspects of this.