About Henrik Gabs Liliendahl

Data Quality and Master Data Management professional

Five Product Information Management (PIM) Essential Aspects

A Product Information Management (PIM) solution must encompass some core aspects of handling product data in a digitalized world where products are exchanged online in self-service scenarios. Here are five essential aspects:

Product Identification

PIM id

Usually a product is identified uniquely within each organization using a number or a code that follows the product in all the applications that handles product data. But as products are exchanged between trading partners, an external product identifier is essential in many business processes.

The most common external identifier of a product is a GTIN (Global Trade Identification Number) which has those three most common formats:

  • 12-digit UPC – Universal Product Code, which is popular in North America
  • 13- digit EAN – European/International Article Number, which is popular in Europe
  • 14-digit GTIN, which is meant to replace among others the two above

We know these numbers from the barcodes on goods in physical shops.

It is worth noticing that a GTIN is applied to each packing level for a product model. So, if we for example have a given model of a magic wand, there could be three GTINs applied:

  • One for a single magic wand
  • One for a box of 25 magic wands
  • One for a pallet of 50 boxes of magic wands

Also, the GTIN is applied to a specific variant of a product model. So, if we have a given model of a pair of trousers, there will be a GTIN for each size and colour variant.

This level of product is also referred to as a SKU – Stock Keeping Unit.

Besides the GTIN (UPC/EAN) system there are plenty of industry and national number and code systems in play.

Product Classification

PIM class

There are many reasons for why you need to classify your range of products. Therefore, there are also many ways of doing so. You can either use an external classification system or your homegrown classification tailored to your organizations view of the world.

Here are five examples of an external standard you can use in order to meet the classification standards required by your trading partners:

  • UNSPSC (United Nations Standard Products and Services Code) is managed by GS1 US™ for the UN Development Programme (UNDP). This is an open, global, multi-sector standard for classification of products and services. This standard is often used in public tenders and at some marketplaces.
  • GPC (Global Product Classification) is created by GS1 as a separate standard classification within its network synchronization called the Global Data Synchronization Network (GDSN).
  • Harmonized System (HS) codes are commodity codes lately being worldwide harmonized to represent the key classifier in international trade. They determine customs duties, import and export rules and restrictions as well as documentation requirements. National statistical bureaus may require these codes from businesses doing foreign trade.
  • eCl@ss is a cross-industry product data standard for classification and description of products and services emphasizing on being a ISO/IEC compliant industry standard nationally and internationally. The classification guides the eCl@ss standard for product attributes (in eClass called properties) that are needed for a product with a given classification.
  • ETIM develops and manages a worldwide uniform classification for technical products. This classification guides the ETIM standard for product attributes (in ETIM called features) that are needed for a product with a given classification.

Within each organization you can have one – and often several – homegrown classification schemes that exist besides the external ones relevant in each organization. One example is how you arrange your range of products on a webshop similar to how you would arrange the goods in aisles in a physical shop.

Specific product attributes

PIM attributes

When selling products in self-service scenarios a main challenge is that each classification of products needs a specific set of attributes (sometimes called properties and features) in order to provide the set of information needed to support a buying decision.

So, while some attributes are common for all products there will be a set of attributes needed to be populated to have data completeness for this product while these attributes are irrelevant for another product belonging to another classification.

External standards as eClass and ETIM includes a scheme that names and states the attributes needed for a product belonging to a certain classification and also the value lists that goes with it as for example which terms for colours that are valid and can be exchanged consistently between trading partners.

Related products

PIM relation

A core challenge in self-service selling is that you have to mimic what a salesman does: If you enter a shop to buy an intended product, the salesman will like you to walk away with a better (and more expensive) choice along with some other products you would need to fulfil the intended purpose of use.

A common trick in a webshop is to present what other users also bought or looked at. That is the crowdsourcing approach. But it does not stop there. You must also present precisely what accessories that goes with a given product model. You must be able to present a replacement if the intended product is not available anymore (or temporarily out of stock). You can present up-sell options based on the features in question. You can present x-sell options based on the intended purpose of use.

Digital Assets

PIM asset

When your prospective customer can’t see and feel a product online you must present product images of high quality that shows the product (and not a lot of other things too). It can be product images taken from a range of different angles. You can also provide video clips with the given product.

Besides that, there may be many other types of digital assets related to each product model. This can be installation guides, line drawings, certificates and more.

Tools That Can Help

This site has a list of innovative Master Data Management (MDM) and PIM solutions that can help you mastering the core aspects of products information management. Check out the list here.

MDM Terms In and Out of The Gartner 2020 Hype Cycle

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 MDM terms in motion:

  • Single domain MDM represented by the two most common domains being MDM of Product Data and MDM of Customer Data. Doing Customer MDM and Product MDM is according to Gartner still going up the slope of enslightment towards the plateau of productivity.
  • Multidomain MDM solutions as examined here on this blog in the post What is Multidomain MDM?.According to Gartner there are still desillusions to be made for these solutions.
  • Cloud MDM as for example pondered in a guest blog post on this blog. The post is called Cloud multi-domain MDM as the foundation for Digital Transformation. There is still a long downhill journey for cloud MDM in the eyes of the Gartner folks.
  • Data Hub Strategy which my also be coined Extended MDM as a data hub covers more data than master data as reported in the post Master Data, Product Information, Reference Data and Other Data. This trend is trailing cloud MDM on the Gartner Hype Cycle.
  • Interenterprise MDM, which before was coined Multienterprise MDM by Gartner and I like to coin Ecosystem Wide MDM. An example of a kind of solution with this theme will be PDS as explained in the post What is Product Data Syndication (PDS)? This trend has, estimated by Gartner, just passed the peak and have more than 5 years before reaching the plateau of productivity.

It is also worth noticing that Gartner has dropped the term Multivector MDM from the hype cycle. This term never penetrated the market lingo.

Another term that is related to- or opposed to– MDM and that is almost only used by Gartner is Application Data Management (ADM). That term is still in there making the under most radars progress near the final uphill climb.

Learn more about how solution providers cover these terms on The Resource List.

What is Data Matching and Deduplication?

The two terms data matching and deduplication are often used synonymously.

In the data quality world deduplication is used to describe a process where two or more data records, that describes the same real-world entity, are merged into one golden record. This can be executed in different ways as told in the post Three Master Data Survivorship Approaches.

Data matching can be seen as an overarching discipline to deduplication. Data matching is used to identify the duplicate candidates in deduplication. Data matching can also be used to identify matching data records between internal and external data sources as examined in the post Third-Party Data Enrichment in MDM and DQM.

As an end-user organization you can implement data matching / deduplication technology from either pure play Data Quality Management (DQM) solution providers or through data management suites and Master Data Management (MDM) solutions as reported in the post DQM Tools In and Around MDM Tools.

When matching internal data records against external sources one often used approach is utilizing the data matching capabilities at the third-party data provider. Such providers as Dun & Bradstreet (D&B), Experian and others offer this service in addition to offering the third-party data.

To close the circle, end-user organizations can use the external data matching result to improve the internal deduplication and more. One example is to apply a matched duns-numbers from D&B for company records as a strong deduplication candidate selection criterium. In addition, such data matching results may often result not in a deduplication, but in building hierarchies of master data.

Data Matching and Deduplication

This site has a list of the most innovative providers of data matching and deduplication tools stretching from best-of-breed solutions for Articficial Intelligence (AI) underpinned data matching and deduplication specialists to Master Data Management (MDM) solutions that include data matching and deduplication capabilities. Check the list here.

What is a Golden Record within Data Management?

The term golden record is a core concept within Master Data Management (MDM) and Data Quality Management (DQM). A golden record is a representation of a real world entity. This representation may be compiled from multiple different representations of that entity in a single or in multiple different databases within the enterprise system landscape.

A golden record is optimized towards meeting data quality dimensions as:

  • Being a unique representation of the real world entity described
  • Having a complete description of that entity covering all purposes of use in the enterprise
  • Holding the most current and accurate data values for the entity described

In Multidomain MDM we work with a range of different entity types as party (with customer, supplier, employee and other roles), location, product and asset. The golden record concept applies to all of these entity types, but in slightly different ways.

Party Golden Record

Having a golden record that facilitates a single view of a customer is probably the most known example of using the golden record concept. Managing customer records and dealing with duplicates of those is the most frequent data quality issue around.

If you are not able to prevent duplicate records from entering your MDM world, which is the best approach, then you have to apply data matching capabilities. When identifying a duplicate you must be able to intelligently merge any conflicting views into a golden record as examined in the post Three Master Data Survivorship Approaches.

In lesser degree we see the same challenges in getting a single view of suppliers and you ultimately will want to have a single view on any business partner, also where the same real world entity have both customer, supplier and other roles to your organization.

There are party identification systems available. Most countries have national ID systems for both citizens (however in most countries mostly restricted to public administration) and organizations. There is Legal Entity Identifier (LEI) concept slowly penetrating in financial services. Also, there are commercial organization identifiers as the Duns Number available.

Location Golden Record

Having the same location only represented once in a golden record and applying any party, product and asset record, and ultimately golden record, to that record may be seen as quite academic. Nevertheless, striving for that concept will solve many data quality conundrums.

Location management have different meanings and importance for different industries. One example is that a brewery makes business with the legal entity (party) that owns a bar, café, restaurant. However, even though the owner of that place changes, which happens a lot, the brewery is still interested in being the brand served at that place. Also, the brewery wants to keep records of logistics around that place and the historic volumes delivered to that place. Utility and insurance are other examples of industries where the location golden record (should) matter a lot.

Knowing the properties of a location also supports the party deduplication process. For example, if you have two records with the name “John Smith” on the same address, the probability of that John Smith being the same real world entity is dependent on whether that location is a single-family house or a nursing home.

Location identification concepts revolves around postal adresses, which are fluffy and varies in format by country, and geocoding systems as latitude/longitude, UTM coordinates, WGS coordinates and more.

Golden Records

Product Golden Record

Product Information Management (PIM) solutions became popular with the raise of multi-channel where having the same representation of a product in offline and online channels is essential. The self-service approach in online sales also drew the requirements of managing a lot more product attributes than seen before, which again points to a solution of handling the product entity centralized.

In large organizations that have many business units around the world you struggle with having a local view and a global view of products. A given product may be a finished product to one unit but a raw material to another unit. Even a global SAP rollout will usually not clarify this – rather the contrary.

While third party reference data helps a lot with handling golden records for party and location, this is lesser the case for product master data. Classification systems and data pools do exist, but will certainly not take you all the way. With product master data you must rely more on second party master data meaning sharing product master data within the business ecosystems where you operate.

The none-profit organization GS1 has done a lot in implementing the Global Trade Item Number (GTIN) based on the Universal Product Code (UPC) and the European Article Number (EAN) concept. However there are still some challenges in this concept around packaging levels and more.

Asset (or Thing) Golden Record

In asset master data management you also have different purposes where having a single view of a real world asset helps a lot. There are namely financial purposes and logistic purposes that have to aligned, but also a lot of others purposes depending on the industry and the type of asset.

With the raise of the Internet of Things (IoT) we will have to manage a lot more assets (or things) than we usually have considered. When a thing (a machine, a vehicle, an appliance) becomes intelligent and now produces big data, master data management and indeed multi-domain master data management becomes imperative.

You will want to know a lot about the product model of the thing in order to make sense of the produced big data. For that, you need the product (model) golden record. You will want to have deep knowledge of the location in time of the thing. You cannot do that without the location golden records. You will want to know the different party roles in time related to the thing. The owner, the operator, the maintainer. If you want to avoid chaos, you need party golden records.

Tools That Can Help

This site has a list of innovative MDM and DQM solution that can help you mastering golden records. Check out the list here.

What is Multi-Domain MDM?

Multi-domain 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.

Customer MDM is typically about federating the accounts receivable in the ERP system(s) and the direct and prospective accounts in the CRM system(s). Golden records are formed through deduplication of multiple representations of the same real-world entity.

Supplier (or vendor) MDM is typically about federating the accounts payable in the ERP system(s) and the existing and prospective accounts in the SRM system(s). A main focus is on the golden records and the company family tree they are in.

Product MDM has a buy-side and a sell-side.

On the buy-side MDM is taking care of trading data for products to resell, in manufacturing environments also the trading data for raw materials and in some cases also for parts to be used in Maintenance, Repair and Operation (MRO). The additional long tail of product specifications may in resell scenarios be onboarded in an embedded/supplementary Product Information Management (PIM) solution.

On the sell-side the trading data are handled for resell products and in manufacturing environments the finished products. The additional long tail of product specifications may be handled in an embedded/supplementary Product Information Management (PIM) solution.

What is multidomain MDM

Multidomain MDM does this in a single solution / suite of solutions. And much more as for example:

  • Supplier contacts can be handled in a generic party master data structure.
  • Customer contacts can be handled in a generic party master data structure
  • Besides the direct accounts in CRM the indirect accounts and contacts can in the party master data structure too. Examples of such parties are:
    • Influencers in the form of heath care professionals in life science.
    • Influencers in the form of architects and other construction professionals in building material manufacturing.
    • End consumers in many supply chain B2B2C scenarios.
  • Employee records can be handled in a generic party master data structure. The roles of sales representatives and their relation to customers, influencers, product hierarchies and location hierarchies can be handled as well as purchase responsibles and their relation to suppliers, influencers, product hierarchies and location hierarchies can be handled.
  • The relation between suppliers and product hierarchies and location hierarchies cand be handled.
  • The relation between customers and end consumers and the product hierarchies and location hierarchies can be handled.
  • Inbound product information feeds from suppliers can be organized and optimized through Product Data Syndication (PDS) solutions.
  • The relation between customer preferences and product information can be handled in Product eXperience Management (PXM) solutions.
  • Outbound product information feeds to resellers can be organized and optimized through Product Data Syndication (PDS) solutions.

This site has a list of the most innovative solutions that can either be your multi-domain solution or supplement other solutions as a best-of-breed component. Check the list here.