I am pleased to welcome Viamedici on The Disruptive MDM/PIM/DQM List and thus also one of the innovative solutions to be on the 2022 version.
During the recent years I have followed Viamedici as a very interesting solution among those Product Information Management (PIM) vendors who are developing into multidomain Master Data Management (MDM) vendors.
Their PIM solution has some unique capabilities around managing complex products and real-time handling of large numbers of products, attributes, relations, and digital assets. These capabilities can be utilized to cover extended MDM where multidomain MDM goes beyond traditional customer, supplier, and product MDM.
Since the emerge of Master Data Management (MDM) back in 00’s this discipline has taken on more and more parts of the also evolving data management space.
The past
It started with Customer Data Integration (CDI) being addressing the common problem among many enterprises of having multiple data stores for customer master data leading to providing an inconsistent face to the customer and lack of oversight of customer interactions and insights.
In parallel a similar topic for product master data was addressed by Product Information Management (PIM). Along with the pains of having multiple data stores for product data the rise of ecommerce lead to a demand for handling much more detailed product data in structural way than before.
While PIM still exist as an adjacent discipline to MDM, CDI mutated into customer MDM covering more aspects than the pure integration and consolidation of customer master data as for example data enrichment, data stewardship and workflows. PIM has thrived either within, besides – or without – product MDM while supplier MDM also emerged as the third main master data domain.
The present
Today many organizations – and the solution providers – either grow their MDM capabilities into a multidomain MDM concept or start the MDM journey with a multidomain MDM approach. Multidomain Master Data Management is usually perceived as the union of Customer MDM, Supplier MDM and Product MDM. It is. And it is much more than that as explained in the post What is Multidomain MDM?
As part of a cross-domain thinking some organizations – and solution providers – are already preparing for the inevitable business partner domain as pondered in the post The Intersection of Supplier MDM and Customer MDM.
The PIM discipline has got a subdiscipline called Product Data Syndication (PDS). While PIM basically is about how to collect, enrich, store, and publish product information within a given organization, PDS is about how to share product information between manufacturers, merchants, and marketplaces.
The future
Interenterprise MDM will be the inflated next stage of the business partner MDM and Product Data Syndication (PDS) theme. This is about how organizations can collaborate by sharing master data with business partners in order to optimize own master data and create new data driven revenue models together with business partners.
It is in my eyes one of the most promising trends in the MDM world. However, it is not going to happen tomorrow. The quest of breaking down internal data and knowledge silos within organizations around is still not completed in most enterprises. Nevertheless, there is a huge business opportunity to pursue for the enterprises who will be in the first wave of interenterprise data sharing through interenterprise MDM.
Extended MDM is the inflated next scope of taking other data domains than customer, supplier, and product under the MDM umbrella.
Also, we will see handling of locations, assets, business essential objects and other digital twins being much more intensive within the MDM discipline. Which entities that will be is industry specific. Examples from retail are warehouses, stores, and the equipment within those. Examples from pharma are own and affiliated plants, hospitals and other served medical facilities. Examples from manufacturing are plants, warehouses as well as the products, equipment and facilities where their produced products are used within.
The handling of all these kind of master data on the radar of a given organization will require interenterprise MDM collaboration with the involved business partners.
Organizations who succeed in extending the coverage of MDM approaches will be on the forefront in digital transformation.
Augmented MDM is the inflated next level of capabilities utilized in MDM as touched in the post The Gartner MDM MQ of December 2021 and Augmented MDM. It is a compilation of utilizing several trending technologies as Machine Learning (ML), Artificial Intelligence (AI), graph approaches as knowledge graph with the aim of automating MDM related processes.
Metadata management will play a wider and more essential role here not at least when augmented MDM and extended MDM is combined.
Mastering this will play a crucial role in the future ability to launch competitive new digital services.
The latest Gartner Magic Quadrant for Master Data Management Solutions is out.
If we look at the vendor positioning not much has happened since the January 2021 quadrant. Tamr is a new solution in the quadrant while Cluedin and Pimcore are now listed under honorable mentions. Informatica is as always closest to the top-right corner.
Augmented data management and augmented MDM are the new main buzzwords as seen in the strategic planning assumptions. Also, the vendors capabilities for doing the augmented stuff are stated as strengths and cautions.
So, what is this augmented data management and augmented MDM by the way? It is in short a compilation of utilizing several trending technologies as Machine Learning (ML), Artificial Intelligence (AI), graph approaches (as examined in the post MDM and Knowledge Graph) with the aim of automating and scaling data management including MDM.
If this will be the final shape of whatever augmented MDM is though in my eyes a bit unsure and even Gartner has doomed augmented MDM to be obsolete before reaching the plateau of productivity in their latest hype cycle for Data and Analytics Governance and Master Data Management. Anyway, I am sure we will see some form of extended MDM covering more domains than customer, supplier and product and utilizing the emerging technologies.
If you want to read the full Gartner report for free, you can get it from Informatica here.
Today it is time to present the fourth vendor to be on The Disruptive MDM / PIM / DQM List in 2022. That is Reltio.
I have been following Reltio here on the blog since 2013 as this MDM vendor has grown from an entrepreneur to a recognized solution provider recently manifested as being a leader in the Forrester MDM Wave and receiving 120 M USD in funding last month.
Reltio is a multi-domain cloud-native MDM solution covering a broad range of MDM capabilities.
Utilizing a knowledge graph has an overlap with Master Data Management (MDM).
If we go back 10 years MDM and Data Quality Management had a small niche discipline that was called (among other things) entity resolution as explored in the post Non-Obvious Entity Relationship Awareness. The aim of this was the same that today can be delivered in a much larger scale using knowledge graph technology.
During the past decade there have been examples of using graph technology for MDM as for example mentioned in the post Takeaways from MDM Summit Europe 2016. However, most attempts to combine MDM and graph have been to visualize the relationships in MDM using a graph presentation.
When utilizing knowledge graph approaches you will be able to detect many more relationships than those that are currently managed in MDM. This fact is the foundation for a successful co-existence between MDM and knowledge graph with these synergies:
MDM hubs can enrich knowledge graph with proven descriptions of the entities that are the nodes (vertices) in the knowledge graph.
Additional detected relationships (edges) and entities (nodes) from the knowledge graph that are of operational and/or general analytic interest enterprise wide can be proven and managed in MDM.
In this way you can create new business benefits from both MDM and knowledge graph.
In the round of presenting the solutions for The Disruptive MDM / PIM / DQM List 2022 the next vendor is Magnitude Software.
Magnitude Software has two solutions on the list:
Kalido MDM where you can define and model critical business information from any domain – customer, product, financial, vendor, supplier, location and more – to create and manage accurate, integrated, and governed data that business users trust.
Agility Multichannel PIM which has the capabilities to get products to market faster with a simple-to-use, comprehensive Product Information Management solution that makes it easy to support commerce across digital and traditional channels.
Data fabric has been named a key strategic technology trend in 2022 by Gartner, the analyst firm.
According to Gartner, “by 2024, data fabric deployments will quadruple efficiency in data utilization while cutting human-driven data management tasks in half”.
Master Data Management (MDM) and data fabric are overlapping disciplines as examined in the post Data Fabric vs MDM. I have seen data strategies where MDM is put as a subset to data fabric and data strategies where they are separate tracks.
In my head, there is a common theme being data sharing.
Then there is a different focus, where data fabric seems to be focusing on data integration. MDM is also about data integration, but more about data quality. Data fabric takes care of all data while MDM obviously is about master data, though the coverage of business entities within MDM seems to be broadening.
Another term closely tied to data fabric – and increasingly with MDM as well – is knowledge graph. Knowledge graph is usually considered a mean to achieve a good state of data fabric. In the same way you can use a knowledge graph approach to achieve a good state of MDM when it comes to managing relationships – if you include a data quality facet.
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 terms in motion:
Single domain MDM represented by the two most common domains being MDM of Product Data and MDM of Customer Data.
Multidomain MDM has moved on from the Trough of Disillusionment to climbing up the Slope of Enlightenment. I have been waiting for this to happen for 10 years – both in the hype cycle and in the real-world – since I founded the Multi-Domain MDM Group on LinkedIn back then.
Interinterprise MDM has swapped place with Cloud MDM, so this term is now ahead of Cloud MDM. It is though hard to imagine Interenterprise MDM without Cloud MDM, and MDM in the cloud will also according Gartner reach the the Plateau of Productivity before ecosystem wide MDM. The promise of this is also in accordance with a poll I made as told in the post Interenterprise MDM Will be Hot.
You can get the full report from the MDM consultancy parsionate here.
One of the most addressed domains in Master Data Management (MDM) is the vendor domain – or is it called the supplier domain?
I have seen the terms vendor and supplier used synonymously many times at different MDM end user organizations, by MDM system integrators and by MDM platform vendors where I have been engaged. This ambiguity exists in English, the most used corporate language, whereas in other languages the distinction seems to be much clearer.
In a recent post by Jignesh Patel of Stibo Systems it is suggested that supplier and vendor are two opposite terms. The post is called What Vendor Data Is and Why It Matters to Manufacturers. I remember to have read the similar post before, probably in a previous version, and commented that this interpretation, in an MDM context, confuses me.
The linguistic issue is to me that a supplier is someone you buy from, and a vendor is someone who sells to you. But as interpreted in the above post, a vendor could also be someone who sells for you. In the latter case I however have mostly seen terms as dealer and reseller used.
Another possible distinction will be that a supplier is someone who deliver goods and services. A vendor will be someone who deliver the bill. So, in an MDM implementation supplier will be used if the MDM implementation is product oriented and vendor will be used if the MDM implementation is procurement and/or financial oriented or dominated.
This distinction reveals an interesting MDMish observation which is that usually the one who deliver the goods and services and the one who deliver the bill is the same entity – but not always.
What is your stance? Is vendor and supplier the same, a bit different or opposite?
The previous acquisitions have strengthened the Precisely offerings around data quality for the customer master data domain and the adjacent location domain.
The Winshuttle take over will make Precisely a multidomain vendor adding cross domain capabilities and specific product domain capabilities.
The original Winshuttle capabilities revolves around process automation for predominately SAP environments covering all master data domains and further Application Data Management (ADM).
As Winshuttle recently took over the Product Information Management (PIM) solution provider Enterworks, this will bring capabilities around product master data management and thus make Precisely a provider for a broad spectrum of master data domains.
The interesting question will be in what degree Precisely over the time will be willing to and able to integrate these different solutions so a one-stop-shopping experience will become a one-stop digital experience for their clients.
Liliendahl on Data Quality 