Product Information Management

2022 Data Management Predictions

Henrik Gabs Liliendahl2 Comments

On the second last day of the year it is time to predict about next year. My predictions for the year gone were in the post Annus Horribilis 2020, Annus Mirabilis 2021?. These predictions were fortunately fluffy enough to claim that they were right.

There is no reason not to believe that the wave of digitalization will go on and even intensify. Also, it seems obvious that data management will be a sweet spot of digitalization.

The three disciplines within data management focussed on at this blog are:

  • MDM: Master Data Management
  • PIM: Product Information Management
  • DQM: Data Quality Management

So, let`s look at what might happen next year within these overlapping disciplines.

MDM in 2022

MDM will keep inflating as explained in the post How MDM inflates. 

More organizations will go for enterprise wide MDM implementations and those who accomplish that will continue to do interenterprise MDM.

More business objects will be handled within the MDM discipline. Multidomain MDM will in more and more cases extend beyond the traditional customer, supplier and product domain.

Intelligent capabilities as Machine Learning (ML) and Artificial Intelligence (AI) will augment the basic IT capabilities currently used within MDM.

PIM in 2022

As with MDM also PIM will go more interenterprise wide. As organizations get a grip on internal product data stores the focus will move to collaborating with external suppliers of product data and external consumers of product data through Product Data Syndication.

In some industries PIM will start extending from the handling the product model to also handling each instance of each product as examined in the post Product Model vs Product Instance.

There will also be a term called augmented PIM meaning using Machine Learning and Artificial Intelligence to improve product data quality. In fact, classification of products using AI has been an early use case of AI in data management. This use case will be utilized more and more besides other product information use cases for AI and ML.

DQM in 2022

Data quality management will also go wider as data quality requirements increasingly will be a topic in business partnerships. More and more contracts between trading partners will besides pricing and timing also emphasize on data quality.

Data quality improvement has for many years been focused on the quality of customer data. This is now extending to other business objects where we will see data quality tools will get better support for other data domains and the data quality dimensions that are essential here.

ML and AI data quality use cases will continue to be implemented and go beyond the current trial stage to be part of operational business processes though still at only a minority of organizations.  

Happy New Year.

Welcome Viamedici on The Disruptive MDM/PIM/DQM List

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I am pleased to welcome Viamedici on The Disruptive MDM/PIM/DQM List and thus also one of the innovative solutions to be on the 2022 version.

During the recent years I have followed Viamedici as a very interesting solution among those Product Information Management (PIM) vendors who are developing into multidomain Master Data Management (MDM) vendors.

Their PIM solution has some unique capabilities around managing complex products and real-time handling of large numbers of products, attributes, relations, and digital assets. These capabilities can be utilized to cover extended MDM where multidomain MDM goes beyond traditional customer, supplier, and product MDM.

You can learn more about Viamedici here.

How MDM Inflates

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Since the emerge of Master Data Management (MDM) back in 00’s this discipline has taken on more and more parts of the also evolving data management space.

The past

It started with Customer Data Integration (CDI) being addressing the common problem among many enterprises of having multiple data stores for customer master data leading to providing an inconsistent face to the customer and lack of oversight of customer interactions and insights.

In parallel a similar topic for product master data was addressed by Product Information Management (PIM). Along with the pains of having multiple data stores for product data the rise of ecommerce lead to a demand for handling much more detailed product data in structural way than before.

While PIM still exist as an adjacent discipline to MDM, CDI mutated into customer MDM covering more aspects than the pure integration and consolidation of customer master data as for example data enrichment, data stewardship and workflows. PIM has thrived either within, besides – or without – product MDM while supplier MDM also emerged as the third main master data domain.   

The present

Today many organizations – and the solution providers – either grow their MDM capabilities into a multidomain MDM concept or start the MDM journey with a multidomain MDM approach. Multidomain 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 as explained in the post What is Multidomain MDM?

As part of a cross-domain thinking some organizations – and solution providers – are already preparing for the inevitable business partner domain as pondered in the post The Intersection of Supplier MDM and Customer MDM.

The PIM discipline has got a subdiscipline called Product Data Syndication (PDS). While PIM basically is about how to collect, enrich, store, and publish product information within a given organization, PDS is about how to share product information between manufacturers, merchants, and marketplaces.

The future

Interenterprise MDM will be the inflated next stage of the business partner MDM and Product Data Syndication (PDS) theme. This is about how organizations can collaborate by sharing master data with business partners in order to optimize own master data and create new data driven revenue models together with business partners.

It is in my eyes one of the most promising trends in the MDM world. However, it is not going to happen tomorrow. The quest of breaking down internal data and knowledge silos within organizations around is still not completed in most enterprises. Nevertheless, there is a huge business opportunity to pursue for the enterprises who will be in the first wave of interenterprise data sharing through interenterprise MDM.

Extended MDM is the inflated next scope of taking other data domains than customer, supplier, and product under the MDM umbrella.

Reference Data Management (RDM) is increasingly covered by or adjacent to MDM solutions.

Also, we will see handling of locations, assets, business essential objects and other digital twins being much more intensive within the MDM discipline. Which entities that will be is industry specific. Examples from retail are warehouses, stores, and the equipment within those. Examples from pharma are own and affiliated plants, hospitals and other served medical facilities. Examples from manufacturing are plants, warehouses as well as the products, equipment and facilities where their produced products are used within.

The handling of all these kind of master data on the radar of a given organization will require interenterprise MDM collaboration with the involved business partners.

Organizations who succeed in extending the coverage of MDM approaches will be on the forefront in digital transformation.

Augmented MDM is the inflated next level of capabilities utilized in MDM as touched in the post The Gartner MDM MQ of December 2021 and Augmented MDM. It is a compilation of utilizing several trending technologies as Machine Learning (ML), Artificial Intelligence (AI), graph approaches as knowledge graph with the aim of automating MDM related processes.

Metadata management will play a wider and more essential role here not at least when augmented MDM and extended MDM is combined.    

Mastering this will play a crucial role in the future ability to launch competitive new digital services.

The Disruptive MDM/PIM/DQM List 2022: Magnitude Software

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In the round of presenting the solutions for The Disruptive MDM / PIM / DQM List 2022 the next vendor is Magnitude Software.

Magnitude Software has two solutions on the list:

  • Kalido MDM where you can define and model critical business information from any domain – customer, product, financial, vendor, supplier, location and more – to create and manage accurate, integrated, and governed data that business users trust.
  • Agility Multichannel PIM which has the capabilities to get products to market faster with a simple-to-use, comprehensive Product Information Management solution that makes it easy to support commerce across digital and traditional channels.

Learn more about Kalido MDM here and Agility Multichannel PIM here.

The Disruptive MDM/PIM/DQM List 2022: Contentserv

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One of the recurring entries on The Disruptive MDM/PIM/DQM List is Contentserv.

Contentserv operates under the slogan: Futurize your customers’ product experience.

Using Contentserv, you will be able to develop the groundbreaking product experiences your customers expect — across multiple channels. Contentserv help you unleash the potential of your product information, using our unique combination of advanced technologies.

Contetserv has combined multiple data management technologies in a single platform for controlling the total product experience. The platform facilitates collecting data from suppliers, enriching it into high-grade content, and then personalizing it for use in targeted marketing and promotions.

Learn more about the Contentserv Product Experience Platform here.

PS: You can also find some compelling success stories from Contentserv on the Case Study List here.

Conflicting Analyst Views on the PIM Market

Henrik Gabs Liliendahl2 Comments

As reported in the previous post here on this blog Forrester published their Product Information Management (PIM) 2021 Q2 Wave last week.

Practically simultaneously Ventana Research published their 2021 Vendor and Product Assessment for Product Information Management (PIM).

The two vendor rankings are here:

The methodology and lingo differ a bit, however the ranking is, as with all these kinds of analyst rankings, based on that the vendors are assessed more positive the closer they are to the top right corner.

The two analyst firms are in more or less agreement about some vendors while some vendors are assessed quite different. These are in particular:

  • Informatica, who is assessed much more negative by Forrester than by Ventana. It is a part of the story that Informatica for a long time has declined to participate in Forrester’s PIM assessments.
  • Akeneo, who is a new vendor among the major players, and has a better debut at Ventana than at Forrester.
  • Stibo Systems, who has been a leader at Forrester for some years but has moved down to a modest position at Ventana in the latest ranking.

Looking at assessing the vendors against the others is close to me as part of the Select Your Solution service on The Disruptive MDM / PIM / DQM List. Here the assessment is based on the actual context, scope and requirements for you as a potential buyer (or someone who is helping a potential buyer). When doing that it is natural that a given vendor can be closest to the top right corner in some cases and not in other cases.

That analysts in a generic ranking reaches a different result only underpins that solution selection is not easy and requires a substantial knowledge about the available solutions, where they come from and where they are heading.

If you need help navigating in this jungle, ping me here:

Forrester PIM Wave Q2 2021

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The Forrester Wave™ Product Information Management Q2 2021 is out.

In here, Forrester has identified the in their eyes 10 most significant solutions — Akeneo, Contentserv, IBM, Informatica, inRiver, Riversand, Salsify, Stibo Systems, Syndigo, and Winshuttle — and researched, analyzed, and scored them.

The previous PIM wave from 2018 was examined here on the blog in the post There is no PIM quadrant, but there is a PIM wave.

Here is the new one and the old one:

So, what is status quo and what has changed?

Status Quo

Stibo Systems is still close to the right top corner and thereby cementing their role as a leader in PIM.

Informatica still has a dysfunctional relationship with Forrester and has not participated in this report either. This has not helped with their positioning in the ranking.

IBM is still in the lower rankings.

Changed

Salsify has moved up and grown.

Riversand has moved up and grown a bit – and has been accompanied by Syndigo who by the way just bought them today.

Enterworks, now as part of Winshuttle, has moved down – but grown.

Contentserv has moved down and shrunk. So has inRiver.

Akeneo has entered the PIM wave.

SAP and Agility Multichannel (now part of Magnitude) has been dropped from this report.

Missing

Compared to Gartner, who only has a Master Data Management (MDM) Quadrant, Via Medici is a major MDM/PIM player missing in this report.

Get Your Free Bespoke MDM / PIM / DQM Solution List

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Many analyst market reports in the Master Data Management (MDM), Product Information Management (PIM) and Data Quality Management (DQM) space have a generic ranking of the vendors.

The trouble with generic ranking is that one size does not fit all.

On the sister site to this blog, The Disruptive MDM / PIM / DQM 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 data domains to be covered and organizational scale stretching from specific business units over enterprise-wide to business ecosystem wide (interenterprise).
  • Your specific requirements covering the main capabilities that differentiate the vendors on market.
  • 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.
The vendors included are both the major players on the market as well as emerging solutions with innovative offerings.

You can get your free solution list here.

10 Kinds of Product Information Needed Within Customization and Personalization

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When working with Product Information Management (PIM) I usually divide the different kinds of information to be managed into some levels and groups as elaborated in the post 5 Product Data Levels to Consider.

The 10 groups of data in this 5-level scheme are all relevant for personalization of product data in the following way:

  1. A (prospective) customer may have some preferred brands which are recognized either by collection of preferences or identified through previous behaviour.
  2. The shopping context may dictate that some product codes like GTIN/UPC/EAN and industry specific product codes are relevant as part of the product presentation or if these codes will only be noise.
  3. The shopping context may guide the use of variant product descriptions as touched in the post What’s in a Product Name?
  4. The shopping context may guide the use of various product image styles.
  5. The shopping context may guide the range of product features (attributes) to be presented typically either on a primary product presentation screen and on a detailed specification screen.
  6. The shopping context and occasion may decide the additional product description assets (as certificates, line drawings, installation guides and more) to be presented.
  7. The shopping occasion may decide the product story to be told.
  8. The shopping occasion may decide the supplementary products as accessories and spare parts to be presented along with the product in focus.
  9. The shopping occasion may decide the complementary products as x-sell and up-sell candidates to be presented along with the product in focus.
  10. The shopping occasion may decide the advanced digital assets as brochures and videos to be presented.   

The data collection track that can enable customization and personalization of product information is examined in the post The Roles of MDM in The Data Supply Chain.

Analyst MDM / PIM / DQM Solution Reports Update March 2021

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Analyst firms occasionally publish market reports with a generic solution overview for Master Data Management (MDM), Product Information Management (PIM) and Data Quality Management (DQM).

Here is an overview of the latest major reports:

MDM PIM DQM solutions analyst firms

3 ways to learn more:

  • You can check out many of the included solutions on The Disruptive MDM / PIM / DQM List.
  • You can get a free ranking that also include the rising stars on the solution market and is based on your context, scope and requirements here.
  • You can book a free short online meeting with me for further discussion on your business case as part of my engagement at the consultancy firm Astrocytia here.