When working with Party Master Data Management one approach to ensure accuracy, completeness and other data quality dimensions is to onboard new business-to-business (B2B) entities and enrich such current entities via a business directory.
While this could seem to be a straight forward mechanism, unfortunately it usually is not that easy peasy.
Let us take an example featuring the most widely used business directory around the world: The Dun & Bradstreet Worldbase. And let us take my latest registered company: Product Data Lake.
On this screen showing the basic data elements, there are a few obstacles:
The address is not formatted well
The country code system is not a widely used one
The industry sector code system shown is one among others
In our address D&B has put the word “sal”, which is Danish for floor. This is not incorrect, but addresses in Denmark are usually not written with that word, as the number following a house number in the addressing standard is the floor.
D&B has their own 3-digit country code. You may convert to the more widely used ISO 2-character country code. I do however remember a lot of fun from my data matching days when dealing with United Kingdom where D&B uses 4 different codes for England, Wales, Scotland and Northern Ireland as well as mapping back and forth with United States and Puerto Rico. Had to be made very despacito.
Industry Sector Codes
The screen shows a SIC code: 7374 = Computer Processing and Data Preparation and Processing Services
This must have been converted from the NACE code by which the company has been registered: 63.11:(00) = Data processing, hosting and related activities.
The two codes do by the way correspond to the NAICS Code518210 = Data processing, hosting and related activities.
During the last couple years social media have been floating with an image and a silly explanation about how a pack of wolves are organized on the go. Some claims are that the three in the front should be the old and sick who sets the pace so everyone are able to stay in the pack and the leader is the one at the back.
This leadership learning lesson, that I have seen liked and shared by many intelligent people, is made up and does not at all correspond to what scientists know about a pack of wolves.
This is like when you look at master data (wolves) without the right reference data and commonly understood metadata. In order to make your interpretation trustworthy you have to know: ¿Who is the alpha male (if that designation exists), who is the alpha female (if that designation exists) and who is old and sick (and what does that mean)?
PS: For those of you who like me are interested in Tour de France, I think this is like the peloton. In front are the riders breaking the wind (snow), who will eventually fall to the back of the standings, and at the back you see Chris Froome having yet a mechanical problem when the going gets tough and thereby making sure that the entire pack stays together.
With the rise of the Internet of Things (IoT) you may regard the Master Data Management (MDM) discipline as yet a bit more complicated.
The most addressed part of MDM has traditionally been achieving a 360 degree view of customers.
Also, a 360 degree view of products within your organization has been a good old chestnut to deal with. The way we have managed products has mostly been by looking at product models, meaning things made up by the same ingredients in the same way under the same brand.
When entering the IoT era MDM now needs to take care of each physical instance of a product model: Each smartphone, each intelligent refrigerator, each big data producing drilling machine.
In here Prash states: “The IoT plays an ever-increasing role in CX across a variety of industries, and MDM delivers the context it requires to deliver value.”
I agree with that – with an important amendment: In order not to over complicate every-thing, you have to implement a MDM landscape, where you are able to collaborate closely with your business partners as exemplified in the concept of Master Data Share.
Block 8 proposed herein, based on a presentation by former Gartner analyst John Radcliffe, is data. I have no problem with that. I think data has been there always as the foundation for information leading to knowledge and topped by wisdom.
Yep, let’s include data in Master Data Management.
Having a 360 degree of something is a recurring subject within Master Data Management (MDM). “Customer 360” is probably the most used term. “Product 360” is promoted from time to time too and occasionally we also stumble upon “Supplier 360” (or “Vendor 360”).
The Buy Side Oval is a combination of Product 360 and Supplier 360
Within (Multi-Domain) Master Data Management (MDM) and Product Information Management (PIM) we must be able to provide solutions that enables the buy side to effectively and consistently handle the core entities involved.
When it comes to mastering product data there are these three kinds of data and supporting managing disciplines and solutions:
Master data and the supporting Master Data Management (MDM) discipline and a choice of MDM solutions for the technology part
Product information and the supporting Product Information Management (PIM) discipline and a choice of PIM solutions for the technology part
Digital assets and the supporting Digital Asset Management (DAM) discipline and a choice of DAM solutions for the technology part
What these disciplines are and how the available solutions relate was examined in the post How MDM, PIM and DAM Sticks Together. This post includes a model for that proposed by Simon Walker of Gartner (the analyst firm).
The right mix for your company depends on your business model and you will also have the choice of using a best of breed technology solution for your focus, that being MDM, PIM or DAM, as well as there are choices for a same branded solution, and in some cases also actually integrated solution, that supports MDM, PIM and DAM.
When selecting a (product) data management platform today you also must consider how this platform supports taking part in digital ecosystems, here meaning how you share product data with your trading partners in business ecosystems.
For the digital platform part supporting interacting with master data, product information and digital assets with your trading partners, who might have another focus than you, the solution is Product Data Lake.