The Three MDM Ages

Master Data Management (MDM) is relatively new discipline. The future will prove what is was, but standing here in mid-2018 I see that we already had 2 ages and are now slowly proceeding into a 3rd age. These ages can be coined as:

  • Pre MDM,
  • Middle MDM and
  • High MDM

Pre MDM

In these dark ages the term Master Data Management may have been used, but there were not any established discipline, methodologies, frameworks and technology solutions around that truly could count as MDM.

We had Customer Data Integration (CDI) around, we had Product Information Management (PIM) in the making and some of us were talking Data Quality Management – and that in practice being namely deduplication / data matching.

Middle MDM

MDM as Three Letter Acronym (TLA) emerged in the mid 00’s as told in the post Happy 10 Years Birthday MDM Solutions.

It was at that time Aaron Zornes changed his stage name from The Customer Data Integration Institute to The MDM Institute.

During this age many MDM solutions slowly but steadily have developed into multi-domain MDM solutions as reported over at the Disruptive MDM List in the blog post called 4 Vendor Paths to Multidomain MDM covering the road travelled by 10 vendors on the MDM market.

Most MDM solutions in the Middle MDM Age have been deployed on-premise

High MDM

We are now cruising into the High MDM Age. First and foremost a lot more organizations are now implementing MDM. Many new deployments are cloud based. New ways are tried out like encompassing more than master data in the same platform.

The jury is of course still out about what will be some main trends of the High MDM Age. My money is placed on what Gartner, the analyst firm, calls Multienterprise MDM as elaborated in the post Ecosystem Wide MDM.

MDM Ages.png

How MDM Solutions are Changing

When Gartner, the analyst firm, today evaluates MDM solutions they measure their strengths within these use cases:

  • MDM of B2C Customer Data, which is about handling master data related to individuals within households acting as buyers (and users) of the products offered by an organisation
  • MDM of B2B Customer Data, which is about handling master data related to other organizations acting as buyers (and users) of the products offered by an organisation.
  • MDM of Buy-Side Product Data, which is about handling product master data as they are received from other organisations.
  • MDM of Sell-Side Product Data, which is about handling product master data as they are provided to other organisations and individuals.
  • Multidomain MDM, where all the above master data are handled in conjunction with other party roles than customer (eg supplier) and further core objects as locations, assets and more.
  • Multivector MDM, where Gartner adds industries, scenarios, structures and styles to the lingo.

QuadrantThe core party and product picture could look like examined in the post An Alternative Multi-Domain MDM Quadrant. Compared to the Gartner Magic Quadrant lingo (and the underlying critical capabilities) this picture is different because:

  • The distinction between B2B and B2C in customer MDM is diminishing and does not today make any significant differentiation between the solutions on the market.
  • Handling customer as one of several party roles will be the norm as told in the post Gravitational Waves in the MDM World.
  • We need (at least) one good MDMish solution to connect the buy-sides and the sell-sides in business ecosystems as pondered in the post Gravitational Collapse in the PIM Space.

Building a MDM Solution Using Best-in-Class Modules

Sometimes keeping it simple is the shortcut to getting it all wrong. While I am a believer in mastering all master data domains under the same vision and strategy, there are still best-in-class options when it comes to orchestrating processes and applying technology in the right chunks.

Customer Data Integration (CDI)

A recent post on this blog was called What Happened to CDI? This post examines the two overlapping disciplines Master Data Management (MDM) and Customer Data Integration (CDI). In a comment Jeff Jones argues that MDM vendors have forgotten about proper CDI workflows. Jeff says: “It seems the industry wants to go from Source to Match/Merge, instead of Source to Match/Identify and finally to Merge.” Please find and jump into the discussion here.

Also, this question was touched some years ago in the post The Place for Data Matching in and around MDM.

Product Information Management (PIM)

The product domain within Multi-Domain MDM also holds some risks of forgetting the proper ways of handling product information. In this domain we must also avoid being blinded by the promise of a single source of master data with surrounding processes and applied technology.

There are many end-to-ends to cover properly as exemplified in the post A Different End-to-End Solution for Product Information Management (PIM).

 

Master Data or

What Happened to CDI?

CDI is a Three Letter Acronym which in the data management world stands for Customer Data Integration.

Today CDI is usually wrapped into Master Data Management (MDM) as examined in the post CDI, PIM, MDM and Beyond. As mentioned in this post, a well-known analyst, Aaron Zornes, runs a business called the MDM Institute, which was originally called the The Customer Data Integration Institute and still has this website: http://www.tcdii.com/.

Many Master Data Management (MDM) vendors today emphasizes on being multidomain, meaning their solutions can manage customer, supplier employee and other party master data as well as product, asset, location and other core business entity types.

However, some vendors still focus on customer master data and the topic of integrating customer data by excelling in the special pain points here, not at least identity resolution and sustainable merge/purge of duplicates. One example is Uniserv Smart Customer MDM.

In my recent little venture called The Disruptive Master Data Management Solution List the aim is to cover all kinds of MDM solutions: Small or big. New (start-up) or old. Multidomain MDM, Customer Data Integration (CDI), Product Information Management (PIM) or even Digital Asset Management (DAM). As a potential buyer, you can browse all these solutions and select your choice of one-stop-shopping candidates or combine best-of-breed solution candidates that matches your requirements in your industry and geography.

First thing that must happen is that vendors register their solutions on the site here.

MDM

The Evolution of MDM

Master Data Management (MDM) is a bit more than 10 years old as told in the post from last year called Happy 10 Years Birthday MDM Solutions. MDM has developed from the two disciplines called Customer Data Integration (CDI) and Product Information Management (PIM). For example, the MDM Institute was originally called the The Customer Data Integration Institute and still have this website:http://www.tcdii.com/.

Today Multi-Domain MDM is about managing customer, or rather party, master data together with product master data and other master data domains as visualized in the post A Master Data Mind Map.

You may argue that PIM (Product Information Management) is not the same as Product MDM. This question was examined in the post PIM, Product MDM and Multi-Domain MDM. In my eyes the benefits of keeping PIM as part of Multi-Domain MDM are bigger than the benefits of separating PIM and MDM. It is about expanding MDM across the sell-side and the buy-side of the business eventually by enabling wide use of customer self-service and supplier self-service.

MDM

The external self-service theme will in my eyes be at the centre of where MDM is going in the future. In going down that path there will be consequences for how we see data governance as discussed in the post Data Governance in the Self-Service Age. Another aspect of how MDM is going to be seen from the outside and in is the increased use of third party reference data and the link between big data and MDM as touched in the post Adding 180 Degrees to MDM.

Besides Multi-Domain MDM and the links between MDM and big data a much mentioned future trend in MDM is doing MDM in the cloud. The latter is in my eyes a natural consequence of the external self-service themes and increased use of third party reference data.

If you happen to be around Copenhagen in the late January I can offer you the full story at a late afternoon event taking place in the trendy meatpacking district and arranged by the local IT frontrunner company ChangeGroup. The event is called Master Data Management: Before, now and in the future.

MDM and SCM: Inside and outside the corporate walls

QuadrantIn my journey through the Master Data Management (MDM) landscape, I am currently working from a Supply Chain Management (SCM) perspective. SCM is very exciting as it connects the buy-side and the sell-side of a company. In that connection we will be able to understand some basic features of multi-domain MDM as touched in a recent post about the MDM ancestors called Customer Data Integration (CDI) and Product Information Management (PIM). The post is called CDI, PIM, MDM and Beyond.

MDM and SCM 1.0: Inside the corporate walls

Traditional Supply Chain Management deals with what goes on from when a product is received from a supplier, or vendor if you like, to it ends up at the customer.

In the distribution and retail world, the product physically usually stays the same, but from a data management perspective we struggle with having buying views and selling views on the data.

In the manufacturing world, we sees the products we are going to sell transforming from raw materials over semi-finished products to finished goods. One challenge here is when companies grow through acquisitions, then a given real world product might be seen as a raw material in one plant but a finished good in another plant.

Regardless of the position of our company in the ecosystem, we also have to deal with the buy side of products as machinery, spare parts, supplies and other goods, which stays in the company.

MDM and SCM 2.0: Outside the corporate walls

SCM 2.0 is often used to describe handling the extended supply chain that is a reality for many businesses today due to business process outsourcing and other ways of collaboration within ecosystems of manufacturers, distributors, retailers, end users and service providers.

From a master data management perspective the ways of handling supplier/vendor master data and customer master data here melts into handling business-partner master data or simply party master data.

For product master data there are huge opportunities in sharing most of these master data within the ecosystems. Usually you will do that in the cloud.

In such environments, we have to rethink our approach to data / information governance. This challenge was, with set out in cloud computing, examined by Andrew White of Gartner (the analyst firm) in a blog post called “Thoughts on The Gathering Storm: Information Governance in the Cloud”.

CDI, PIM, MDM and Beyond

The TLAs (Three Letter Acronyms) in the title of this blog post stands for:

  • Customer Data Integration
  • Product Information Management
  • Master Data Management

CDI and PIM are commonly seen as predecessors to MDM. For example, the MDM Institute was originally called the The Customer Data Integration Institute and still have this website: http://www.tcdii.com/.

Today Multi-Domain MDM is about managing customer, or rather party, master data together with product master data and other master data domains as visualized in the post A Master Data Mind Map. Some of the most frequent other master domains are location master data and asset master data, where the latter one was explored in the post Where is the Asset? A less frequent master data domain is The Calendar MDM Domain.

QuadrantYou may argue that PIM (Product Information Management) is not the same as Product MDM. This question was examined in the post PIM, Product MDM and Multi-Domain MDM. In my eyes the benefits of keeping PIM as part of Multi-Domain MDM are bigger than the benefits of separating PIM and MDM. It is about expanding MDM across the sell-side and the buy-side of the business eventually by enabling wide use of customer self-service and supplier self-service.

The external self-service theme will in my eyes be at the centre of where MDM is going in the future. In going down that path there will be consequences for how we see data governance as discussed in the post Data Governance in the Self-Service Age. Another aspect of how MDM is going to be seen from the outside and in is the increased use of third party reference data and the link between big data and MDM as touched in the post Adding 180 Degrees to MDM.

Besides Multi-Domain MDM and the links between MDM and big data a much mentioned future trend in MDM is doing MDM in the cloud. The latter is in my eyes a natural consequence of the external self-service themes and increased use of third party reference data which all together with the general benefits of the SaaS (Software as a Service) and DaaS (Data as a Service) concepts will make MDM morph into something like MDaaS (Master Data as a Service) – an at least nearly ten year old idea by the way, as seen in this BeyeNetwork article by Dan E Linstedt.

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An Alternative Multi-Domain MDM Quadrant

No, this is not an(other) attempt to challenge Gartner, the analyst firm, in making quadrants about vendors in the Master Data Management (MDM) realm.

This an attempt to highlight some capabilities of Multi-Domain MDM solutions here focusing on party and product master data and the sell-side and the buy-side of MDM as discussed some years ago in the post Sell-side vs Buy-side Master Data Quality.

A simple quadrant will look like this:

Quadrant

  • The upper right corner is where MDM started, being with solutions back then called Customer Data Integration (CDI).
  • The Product Information Management (PIM) side is quite diverse and depending on the industry vertical where implemented:
    • Retailers and distributors have their challenges with sometimes high numbers of products that goes in and comes out as the same but with data reflecting different viewing points.
    • Manufacturers have other issues managing raw materials, semi-finished products, finish products and products and services used to facilitate the processes.
    • Everyone have supplies.
  • The supplier master data management has more or less also been part of the PIM space but looks more like customer master data and should be part of a party master data discipline also embracing other party roles as employee.

Also, this quadrant is by the way without other important domains as location (as discussed in the post Bringing the Location to Multi-Domain MDM) and asset (as discussed in the post Where is the Asset?)

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Slicing the MDM Space

Master DataThese days I am attending the Gartner MDM summit in London.

MDM (Master Data Management) initiatives and MDM solutions are not created equal and different ways of slicing the MDM world were put forward on the first day.

Gartner is famous for the magic quadrants and during the customer master data quadrant presentation I heard Bill O’Kane explain why this is a separate quadrant from the product master data quadrant and why there are no challengers and no visionaries.

In another session about MDM milestones Bill O’Kane for this context sliced the MDM world a bit differently based on moving between MDM styles. Here we had:

  • Business-to-consumer (B2C) Customer Data Integration (CDI)
  • Business-to-business (B2B) customer MDM, Product Information Management (PIM) and other domains.

The vendors in general seems to want to do everything MDM.

Stibo Systems, a traditional PIM vendor, presented the case for multidomain MDM based on how things have developed within eCommerce. Stibo even smuggled the term omnidomain MDM into the slides. A marketing gig in the making perhaps.

The megavendors has bought who ever they need to be multidomain.

Some new solutions are born in the multidomain age. Semarchy is an interesting example as they are so the evolutionary way.

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Data Entry by Employees

A recent infographic prepared by Trillium Software highlights a fact about data quality I personally have been preaching about a lot:

Trillium 75 percent

This number is (roughly) sourced from a study by Wayne W. Eckerson of The Data Warehouse Institute made in 2002:

TDWI 76 percent

So, in the fight against bad data quality, a good place to start will be helping data entry personnel doing it right the first time.

One way of achieving that is to cut down on the data being entered. This may be done by picking the data from sources already available out there instead of retyping things and making those annoying flaws.

If we look at the two most prominent master data domains, some ideas will be:

  • In the product domain I have seen my share of product descriptions and specifications being reentered when flowing down in the supply chain of manufacturers, distributors, re-sellers, retailers and end users. Better batch interfaces with data quality controls is one way of coping with that. Social collaboration is another one as told in the post Social PIM.
  • In the customer, or rather party, domain we have seen an uptake of using address validation. That is good. However, it is not good enough as discussed in the post Beyond Address Validation.

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