Disciplines come and go in the data management world. Here is a mind map of the disciplines on top of my mind today. Some of the disciplines goes back to the emerge of IT in the previous millennium and some have risen during the latest years.
Today the 11th January 2021 we should, according to the Gartner publishing schedule, expect a refreshed Gartner Magic Quadrant for Master Data Management (MDM) Solutions.
Historically these quadrants have been delayed possibly due to fighting with vendors objecting to the results herein.
An observation is that the thorough process applied by Gartner makes the results in here a bit behind what is currently happening on the market as touched in the post Why are Analyst Rankings Behind the MDM Market Dynamics? If say the information used in a fresh published quadrant is between a half to a full year old, the latest quadrant to be used in a given tool assessment can be founded on up to 2 years old data.
The last Magic Quadrant for MDM was mentioned in this post.
As touched in the post the two advancing vendors in here were Informatica, who extended their lead, and Semarchy, who became top challenger.
With Informatica it is hard to confirm their position in other analyst reports. Informatica has a dysfunctional relationship with Forrester, so they are not included in their latest MDM reports. Information Difference did not assess Informatica that favourable in their ranking as seen in the post Who is in the MDM Landscape Q2 2020? Will be interesting to see if Gartner keeps having a view on Informatica MDM which is different from most other sources.
Semarchy seems to keep up their momentum from what I hear from the market. Let us see if Gartner reflects that too.
The fastest growing vendor last time was Reltio as reported in the post What has Changed with the Gartner MDM Magic Quadrant? I hope Gartner keeps publishing these revenue estimates, so we can see who has grown the most and who has grown not so much or even shrunk as it happened with IBM and Riversand in the previous check.
Stay tuned for a summary of and link to first free reprints of the refreshed MDM Magic Quadrant.
I am running a service where organizations on the look for a Master Data Management (MDM), Product Information Management (PIM) and/or Data Quality Management (DQM) solution can get a list of the best fit solutions for their context, scope and requirements. The service is explained in more details in the post Get Your Free Bespoke MDM / PIM / DQM Solution Ranking.
2020 was a busy year for this service. There were 176 requests for a list. About half of them came, as far as I can tell, from end user organizations and the other half came from consultancies who are helping end user organizations with finding the right tool vendor. Requests came from all continents (except Antarctica) with North America and Europe as the big chunks. There were requests from most industries thus representing a huge span in context.
Also, there where requests from a variety in organization sizes which has given insights beyond what the prominent analyst firms obtain.
It has been a pleasure also to receive feedback from requesters which has helped calibrating the selection model and verifying the insights derived from the context, scope and requirements given.
The variety in context, scope and requirements resulted in having 8 different vendor logos in top-right position and 25 different logos in all included in the 7 to 9 sized best fit extended longlists in the dispatched Your Solution Lists during 2020.
If you are on the look for a solution, you can use the service here.
If you are a vendor in the MDM / PIM / DQM space, you can register your solution here.
A given master data domain as customer, supplier, employee, other/all party, product (beyond PIM), location or asset
A given business unit
You must eat an elephant one bite at a time. Therefore, contextual MDM makes a good concept for getting achievable wins.
However, in an organization with high level of data management maturity the range of contextual MDM use cases, and the solutions for them, will be encompassed by a common enterprise-wide, global, multidomain MDM framework – either as one solution or a well-orchestrated set of solutions.
One example with dependencies is when working with personalization as part of Product Experience Management (PXM). Here you need customer personas. The elephant in the room, so to speak, is that you have to get the actual personas from Customer MDM and/or the Customer Data Platform (CDP).
In having that common MDM solution/framework there are some challenges to be solved in order to cater for all the contextual MDM use cases. One such challenge, being context-aware customer views, was touched upon in the post There is No Single Customer 360 View.
Talend is not in the landscape this year, which is natural as Talend do not promote MDM anymore. Viamedici and Veeva is not in there as they were last year. This may, as discussed under the 2019 MDM Landscape with other vendors, be because they have declined to participate.
Recurring vendors are positioned quite like last year. As the vertical axis is technology, including customer satisfaction, and the horizontal axis is market strength, there still seems to be two main groups of vendors. Best-of-breed MDM with higher customer satisfaction and mega-vendors with not so high customer satisfaction.
Stibo Systems sits between these two groups according to this report. In my current work at the consultancy firm Astrocytia we have some engagements where we assist our clients in getting much more business benefit from MDM and thereby with these cases we strive to push Stibo Systems towards the top-right corner.
Gaining customer satisfaction, not at least with larger market strength, is dependent on both the capabilities of the MDM vendor and the approach from the consultancy firm that assist with the wider MDM strategy and implement the solutions.
In the recent Gartner Top 10 Trends in Data and Analytics for 2020 trend number 8 is about data marketplaces and exchanges. As stated by Gartner: “By 2022, 35% of large organizations will be either sellers or buyers of data via formal online data marketplaces, up from 25% in 2020.”
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 multienterprise 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 data sharing will be facilitated by data marketplaces and exchanges.
On July 23rd I will, as a representative of The Disruptive MDM/PIM/DQM List, present in the webinar How to Sustain Digital Ecosystems with Multi-Enterprise MDM. The webinar is brought to you by Winshuttle / Enterworks. It is a part of their everything MDM & PIM virtual conference. Get the details and make your free registration here.