MDM vs ADM

Henrik Gabs Liliendahl4 Comments

The term Application Data Management (ADM) has recently been circulating in the Master Data Management (MDM) world as touched in The Disruptive MDM List blog post MDM Fact or Fiction: Who Knows?

Not at least Gartner, the analyst firm, has touted this as one of two Disruptive Forces in MDM Land. However, Gartner is not always your friend when it comes to short, crisp and easy digestible definitions and explanations of the terms they promote.

In my mind the two terms MDM and ADM relates as seen below:

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So, ADM takes care of a lot of data that we do not usually consider being master data within a given application while MDM takes care of master data across multiple applications.

The big question is how we handle the intersection (and sum of intersections in the IT landscape) when it comes to applying technology.

If you have an IT landscape with a dominant application like for example SAP ECC you are tempted to handle the master data within that application as your master data hub or using a vendor provided tightly integrated tool as for example SAP MDG. For specific master data domains, you might for example regard your CRM application as your customer master data hub. Here MDM and ADM melts into one process and technology platform.

If you have an IT landscape with multiple applications, you should consider implementing a specific MDM platform that receives master data from and provides master data to applications that takes care of all the other data used for specific business objectives. Here MDM and ADM will be in separated processes using best-of-breed technology.

Product Data Completeness

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Completeness is one of the most frequently mentioned data quality dimensions as touched in the post How to Improve Completeness of Data.

ChecklistWhile every data quality dimension applies to all domains of Master Data Management (MDM), some different dimensions apply a bit more to one of the domains or the intersections of the domains as explained in the post Multi-Domain MDM and Data Quality Dimensions.

With product master data (or product information if you like) completeness is often a big pain. One reason is that completeness means different requirements for different categories of products as pondered in the post Hierarchical Completeness within Product Information Management.

At Product Data Lake we develop a range of cloud service offerings that will help you improve completeness of product data. These are namely:

  • Measuring completeness against these industry standards that have attribute requirements such as eClass and ETIM
  • For manufacturers measuring completeness against downstream trading partner requirements (if not fully governed by an industry standard).
  • For merchants measuring incoming completeness when pulling from merchants.
  • Measuring against completeness required by marketplaces.
  • Transforming product information to meet conformity and thereby ability to populate according to requirements
  • Translating product information in order to populate attributes in more languages
  • Transferring product information by letting manufacturers push it in their way and letting merchants pull it their way as described in the post Using Pull or Push to Get to the Next Level in Product Information Management.

The Lesser Known GDPR Article 101 (Right to Indulgence)

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While a lot have been written about the original 99 articles in the EU General Data Protection Regulation (GDPR) perhaps we have seen less focus on the additional articles that have been added since the first approval of 14th April 2016, but that will as well apply on 25th May 2018.

The original articles are mainly emphasizing on the rights of the data subject. But later additions also take care of the right of data controllers. Not at least article 101 about the right to indulgence for data controllers (and data processors) falls into that category.

A representative of the EU, Don Par, explains it this way: “You can escape the heavy fines if you are about to be caught by confessing your sins and pay a more modest purification fee which eventually by subscribing to an annual scheme may allow you to continue business as usual”.

13indulgences.large (1).jpgThe consultancy industry also has had a low profile on article 101. Max Hagnaður of The GDPR Advisory Institute puts it this way: “First we wanted to make money on advising on how to comply with GDPR. When it shows up, that only a very few companies will do so, we will redirect our hailstorms of power-point decks to article 101 and how to apply for indulgence”.

Indeed, the costs of indulgence may very well be lesser than the costs of compliance (not to say fines because you will fail anyway).

Product Information on Demand

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Video on demand has become a popular way to watch television series, films and other entertainment and Netflix is probably the most known brand for delivering that.

The great thing about watching video on demand is that you do not have to enjoy the service at the exact same time as everyone else, as it was the case back in the days when watching TV or going to the movies were the options available.

At Product Data Lake we will bring that convenience to business ecosystems, as the situation today with broadcasting product information in supply chains very much resembles the situation we had before video on demand came around in the TV/Movie world.

As a provider of product information (being a manufacturer or upstream distributor), you will push your product information into Product Data lake, when you have the information available. Moreover, you will only do that once for each product and piece of information. No more coming to each theatre near your audience and extensive reruns of old stuff.

As a receiver of product information (being a downstream distributor, reseller or large end user), you will pull product information when you need it. That will be when you take a new product into your range or do a special product sale as well as when you start to deal with a new piece of information. No more having to be home at a certain time when your supplier does the show or waiting in ages for a rerun when you missed it.

Learn more about how Product Data Lake makes your life in Product Information Management (PIM) easier by following us here on LinkedIn.

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Three Major Sectors within Product Information Exchange

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When working with Product Information Management (PIM) and not at least with product information exchange (product data syndication) between trading partners, I have noticed three major sectors where the requirements and means differs quite a bit.

These sectors are:

  • Food, beverage at pharmaceuticals: These are highly regulated sectors where the rules for taxonomy, completeness and exchange formats are advanced. Exchange standards and underpinning services as GS1/GDSN are well penetrated at least for basic data elements among major players. This sector counts for circa 1/6 of the world trade.
  • Fashion, books and mainstream electronics: The products within this sector can be described with common accepted taxonomies and do not differ that much though there certainly are room for more common adhered standards in some areas. The trade here is becoming more penetrated by marketplaces with their specific product information requirements. This sector counts for circa 1/6 of the world trade.
  • The rest (including building materials, special electronics, machinery, homeware): This is a diverse segment of products groups and the product groups themselves are diverse. The requirements for product information completeness and other data quality dimensions are overwhelming and the choice of standards are many, so most often two trading partners will be on different pages. This sector counts for circa 2/3 of the world trade.

Note: Automotive (vehicles) is a special vertical, where the main products (for example cars) resembles mainstream electronics and all the spare parts resembles special electronics. Some retailers (like department stores) covers all sectors and therefore need hybrid solutions to their product information exchange handling challenges.

The main drivers for better product information handling are compliance – not at least within food, beverage and pharmaceuticals – and self-service purchasing (as in ecommerce), where the latter has raged many years within fashion, books and mainstream electronics and now also is raising in more B2B (business-to-business) biased product groups as building materials, special electronics and machinery.

Learn more about how to tackle these diverse needs in product information exchange in the article and discussion about Product Data Lake.

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Welcome Enterworks, Contentserv and SyncForce on The Disruptive MDM List

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I am happy to welcome three new entries on The Disruptive Master Data Management Solutions List.

This site is meant to be a list of available:

  • Master Data Management (MDM) solutions
  • Customer Data Integration (CDI) solutions
  • Product Information Management (PIM) solutions
  • Digital Asset Management (DAM) solutions

Organizations on the look for a solution of the above kind can use this site as an alternative to the likes of Gartner, Forrester, MDM Institute and others, not at least because this site will include the market leaders as well as smaller and disruptive solutions with specific use case, geographical, industry or other best of breed capabilities.

The new entries are:

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  • EnterWorks who is among the market leaders in multi-domain master data solutions for acquiring, managing and transforming a company’s multi-domain master data into persuasive and personalized content for marketing, sales, digital commerce and new market opportunities.
  • Contentserv thumbCONTENTSERV who offers a real-time Product Experience Platform. This integrated and product centric solution seamlessly combines the functionalities of multi domain Master Data Management, Product Information Management & Marketing Content Management.
  • SyncForce-plus-iconSyncForce who makes your product portfolio digitally available with a click of a button, in every shape and form, both internal and external, so you can shift your attention from fire fighting to building successful business with your trading partners.

You can visit the list here.

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 If you are a vendor, you can register your solution here.

Embracing Standards versus Imposing Standards

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When working with Product Information Management (PIM) and the recurring challenges in exchanging product information between trading partners the idea about everyone adhering to the same standard is a tempting idea.

This idea is also governing the many product data pools around. However, there are some serious considerations against this idea, namely:

  • Being on the same standard and not to say on the same version within your business ecosystem is quite utopic (being that within your own organization is hard enough).
  • It is not desirable to have the same product information as your competitors if you are going to compete on other factors than price.
In my eyes it is a better idea to forget about imposing a rigid standard for everyone and instead embrace the many available standards for product information where your organization utilize those being best for you at the given time and your various trading partners utilize those being best for them at a given time.

The solution for that is Product Data Lake.

Sell more Reduce costs

The Wide End-to-End Solution for Product Information Management (PIM)

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The term End-to-End is used a lot in marketing jargon. Now, I will jump on that wagon too.

In reality, no solution will be an End-to-End solution for all your business needs. Therefore, my take will merely be to cast some light on an End-to-End need for which there are only very scattered solutions today.

If we look at Product Information Management (PIM) there are many good solutions for taking care of the End-to-End needs within your organisation. The aim is to gather the product information that exist within your organisation in various silos, have one trusted place for all this information and being able to publish this information in a consistent way across all sales channels – the omnichannel theme.

However, product information does in many cases not live just within your organization. In most cases, it lives in a business ecosystem of manufacturers, distributors, merchants and large end users.

Therefore we need an End-to-End solution for product information exchange (product data syndication) that encompasses the path from manufacturers over distributors to merchants and large end users and in some cases the way back.

Whether you are a manufacturer, distributor, merchant, large end user or a provider of tools and services for product information you can join the business ecosystem oriented End-to-End solution for product information. Please find some more information about Product Data Lake here.

As a manufacturer, you can find your benefits on the Product Data Push site here.

As a merchant, you can find your benefits on the Product Data Pull site here.

If you are a vendor in the Product Information Management space, you can join forces with us as explained here.

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Why it is not a Product Data Warehouse, but a Product Data Lake

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There is a need for a new solution to sharing product information between trading partners. Product Data Lake is that new solution. Using the term data lake as a part of the name for the solution is very deliberate. Here is why:

Volume

When setting up a warehouse, and a data warehouse, you have to estimate the storing size and the throughput. There will be a limit to how much data you can store and how much data you can upload and download within a given period.

Our vision is that Product Data Lake will be the process driven key service for exchanging any sort of product information within business ecosystems all over the world, with the aim of optimally assist self-service purchase of every kind of product.

In order to achieve that vision, we need to be able to scale up drastically. Therefore, we use a document-oriented database called MongoDB to store product information.

Even if you choose to implement a Product Data Lake instance for a single business ecosystem, you will benefit from the high scalability.

Velocity

Business ecosystems changes all the time. You need to rapidly be able to adapt your data management, not at least when it comes to exchanging product information.

Swapping trading partners is one thing. That often means dealing with other product information requirements and opportunities and adhering to other standards.

We will also see business ecosystems in new shapes in the future. There will be fewer nodes between manufacturers and point-of-sales and point-of-sales will more likely be online marketplaces.

However, the changes will not happen as a big bang but in varying pace for each industry, geography and organization.

The rigid consensus structure of a data warehouse, and product information exchange solutions that resembles a data warehouse, will not cope with that change. The data lake concept, in the form of Product Data Lake, will.

In Product Data Lake you as a provider upload product information in your structure and format and you as a receiver download in your structure and format. The linking and transformation takes place inside Product Data Lake using linked metadata.

Variety

While everyone agrees that a common standard for all product information is the best answer we must on the other hand accept, that using a common standard for every kind of product and every piece of information needed is quite utopic. We haven’t even a common uniquely spelled term in English for standardization/standarisation.

Also, we must foresee that one organization will mature in a different pace than another organisation in the same business ecosystem.

These observations are the reasons behind the launch of Product Data Lake. In Product Data Lake we encompass the use of (in prioritized order):

  • The same standard in the same version
  • The same standard in different versions
  • Different standards
  • No standards
Learn about some of these standards in the post Five Product Classification Standards.
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Which MDM and/or PIM Solution to Choose?

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More and more organizations are implementing Master Data Management (MDM) and Product Information Management (PIM) solutions.

When the implementation comes to the phase where you must choose one or more solutions and you go for the buy option (which is recommended), it can be hard to get a view on the available solutions. You can turn to the Gartner option, but their Quadrant only shows the more expensive options and Gartner is a bit old school as reported here.

An additional option will be to see how the vendors themselves present their solutions in a crisp way. This is what is going on at The Disruptive Master Data Management Solutions List.

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As a solution provider you can register your solution on this site in order to be a solution considered by organizations looking for a:

  • Master Data Management (MDM) solution
  • Customer Data Integration (CDI) solution
  • Product Information Management (PIM) solution
  • Digital Asset Management (DAM) solution

Registration takes place here.

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