Scaling Up the List

This site was launched in the late 2017.

Here the first innovative Master Data Management (MDM) and Product Information Management (PIM) tool vendors joined the list with a presentation page showcasing the unique capabilities offered to the market.

The blog was launched at the same time. Since then, a lot of blog posts – including guest blog posts – have been posted. The topics covered have been about the list, the analysts and their market reports as well as the capabilities that are essential in solutions and their implementation.

In 2019 the MDM and PIM tool vendors were joined by some of the forward-looking best-of-breed Data Quality Management (DQM) tool vendors.

The Select Your Solution service was launched at the same time. Here organizations – and their consultants – who are on the look for a MDM / PIM / DQM solution can jumpstart the selection process by getting a list of the best solutions based on their individual context, scope and requirements. More than 100 hundred end user organizations or their consultants have received such a list.

MDMlist timeline

Going into the 20es the site is ready to be scaled up. The new sections being launched are:

  • The Service List: In parallel with the solution providers it is possible for service providers – like implementation partners – to register on The Service List. This list will run besides The Solution List. For an organization on the look for an MDM / PIM / DQM solution it is equally important to select the right solution and the right implementation partner.
  • The Resource List: This is a list – going live soon – with white papers, webinars and other content from potentially all the registered tool vendors and service providers divided into sections of topics. Here end user organizations can get a quick overview of the content available within the themes that matters right now.
  • The Case Study List: The next planned list is a list of case studies from potentially all the registered tool vendors and service providers. The list will be divided into industry sectors. Here end user organizations can get a quick overview of studies from similar organizations.

If you have questions and/or suggestions for valuable online content, make a comment or get in contact here:

What’s in a Product Name?

Within Master Data Management (MDM), Product Information Management (PIM) and Data Quality Management (DQM) one of the critical data elements that needs to be governed is the product name (product description).

Usually the product name is held in two forms:

  • A short form as it appears internally in an organization and is held in an ERP application. Everyone working with SAP knows about the challenge of keeping the product description in SAP within 40 characters. The short form is typically governed within the MDM discipline and is kept in the single one official language in the organization.
  • A long and customer friendly form as it is used when presenting the product in sales channels as for example on a web shop. The long form is typically governed within the PIM discipline and is kept in all languages in use in the organization.

The data quality dimensions that applies to the product name are namely:

  • Uniqueness, meaning that:
    • The product name must be the same (in short or long language form) across data stores in order to avoid duplicates.
    • Each product most have a distinct name, so you are able to distinguish one from the other.
  • Consistency, meaning that you must build the product name by sub elements that are sequenced the same way and have a common vocabulary.

The most common sub elements in a product name are:

  • Brand name or product line
  • Model number
  • Kind of product
  • Size
  • Color
  • Product classification (group) specific characteristics
  • Country

What is in a product name

It is a challenge to implement data governance around product names within a single organization. Even more it is a challenge to rely on / be depended on your trading partners when governing product names in business ecosystems as told in the post Toilet Seats and Data Quality.

Fashion vs Work Clothes: A PIM Perspective

In data management disciplines as Master Data Management (MDM), Product Information Management (PIM and Data Quality Management (DQM) the context has a lot say for data that fundamentally are the same. One example is fashion vs work clothes as it applies to PIM and data quality measures required .

Clothes for private (and white collar) use and work clothes are as products quite similar. You have the same product groups as shoes, trousers, belts, shirts, jackets, hats and so on.

However, the sales channels have different structures and the product information needed in sales, not at least self-service sales as in ecommerce, are as Venus and Mars.

Online fashion sales are driven by nice images – nice clothes on nice models. The information communicated is often fluffy with only sparse hard facts on data like fabrics, composition, certificates, origin. Many sales channel nodes only deal with fashion.

Selling work clothes, including doing it on the emerging online channels, does include images. But they should be strict to presenting the product as is. There is a huge demand for complete and stringent product information as we know it in B2B (online) sales.

Work clothes are often sold in conjunction with very different products as building materials, where the requirements for product information attributes are not the same. Work clothes comes, as fashion, in variants in sizes and colors. This is not so often used, or used quite differently, when selling for example building materials.

One challenging area here is where we have work clothes and building materials in the same data pool or in other means of Product Data Syndication (PDS).

Work Clothes versus Fashion

Are These Familiar Hierarchies in Your MDM / PIM / DQM Solution?

The term family is used in different contexts within Master Data Management (MDM),  Product Information Management (PIM) and Data Quality Management (DQM) when working with hierarchy management and entity resolution.

Here are three frequent examples:

Consumer / citizen family

Family consumer citizenWhen handling party master data about consumers / citizens we can deal with the basic definition of a family, being a group consisting of two parents and their children living together as a unit.

This is used when the business scenario does not only target each individual person but also a household with a shared economy. When identifying a household, a common parameter is that the persons live on the same postal address (at the same time) while observing constellations as:

  • Nuclear families consisting of a female and a male adult (and their children)
  • Rainbow families where the gender is not an issue
  • Extended families consisting of more than two generations
  • Persons who happen to live on the same postal address

There are multicultural aspects of these constellations including the different family name constructions around the world and the various frequency and acceptance of rainbow families as well of frequency of extended families.

Company family tree

When handling party master data about companies / organizations a valuable information is how the companies / organizations are related most commonly pictured as a company family tree with mothers and sisters. This can in theory be in infinite levels. The basic levels are:

  • A global ultimate mother being the company that ultimately owns (fully or partly) a range of companies in several countries.
  • A national ultimate mother being the company that owns (fully or partly) a range of companies in a given country.
  • A legal entity being the basic registered company within a country having some form of a business entity identifier.
  • A branch operated by a legal entity from a given postal / visiting address.

Family companyYou can build your own company tree describing your customers, suppliers and other business partners. Alternatively or supplementary, you can rely on third party business directories. It is here worth noticing that a national source will only go to the ultimate national mother level while a global source can include the global ultimate mother and thus form larger families.

Having a company family view in your master data repository is a valuable information asset within credit risk, supply risk, discount opportunities, cross-selling and more.

Product family

The term “product family” is often used to define a level in a homegrown product classification / product grouping scheme. It is used to define a level that can have levels above and levels below with other terms as “product line”, “product category”, “product class”, “product group”, “product type” and more.

Family productSometimes it is also used as a term to define a product with a family of variants below, where variants are the same product produced and kept in stock in different colours, sizes and more.

Read more about Stock Keeping Units (SKUs), product variants, product identification and product classification in the post Five Product Information Management Core Aspects.

Generic Ranking of Vendors versus an Individual Selection Service

Many analysts market reports in the Master Data Management (MDM), Product Information Management (PIM) and Data Quality Management (DQM) space has a generic ranking of the vendors. Some of these reports were back in December last year mentioned in the post Major Generic MDM / PIM / DQM Solution Rankings. (Since then a new Gartner MDM Magic Quadrant has been published).

The trouble with generic ranking is that one size does not fit all. Therefore organizations on the look for a solution need to examine the market anyway and spend a lot of time and/or money with consultants in doing that.

On this list there is no generic ranking. Instead there is a service where you can provide your organization’s context, scope and requirements and within 2 to 48 hours get your solution list.

The selection model includes these elements:

  • Your context in terms of geographical reach and industry sector.
  • Your scope in terms of domains to be covered and organizational scale stretching from specific departments over enterprise wide to business ecosystem wide (multi-enterprise).
  • Your specific requirements.
  • Vendor capabilities.
  • A model that combines those facts into a rectangle where you can choose to:
    • Go ahead with a Proof of Concept with the best fit vendor
    • Make an RFP with the best fit vendors in a shortlist
    • Examine a longlist of best fit vendors and other alternatives like combining more than one solution.

Selection Model

You can get your free solution list here.

Note that the solution vendors considered are those who are:

  • On this Disruptive MDM / PIM / DQM Solutions List or
  • Gartner MDM Magic Quadrant or
  • Forrester MDM Wave or Forrester PIM Wave or
  • Information Difference MDM Landscape