CDP

What is Contextual MDM?

Henrik Gabs LiliendahlLeave a comment

The term “contextual Master Data Management” has been floating around in a couple of years as for example when tool vendors want to emphasize on a speciality that they are very good at. One example is from the Data Quality Management leader Precisely in the August 2020 article with the title How Contextual MDM Drives True Results in the Age of Data Democratization. Another example is from the Product Information/Experience Management leader Contentserv in the 2017 article with the title Contentserv Expands its Portfolio with Innovative Contextual MDM.

We can see contextual MDM as smaller pieces of MDM with a given flavour as for example focussing on sub/overlapping disciplines as:

The focus can also be at:

  • A given locality
  • A given master data domain as customer, supplier, employee, other/all party, product (beyond PIM), location or asset
  • A given business unit

You must eat an elephant one bite at a time. Therefore, contextual MDM makes a good concept for getting achievable wins.   

However, in an organization with high level of data management maturity the range of contextual MDM use cases, and the solutions for them, will be encompassed by a common enterprise-wide, global, multidomain MDM framework – either as one solution or a well-orchestrated set of solutions.

One example with dependencies is when working with personalization as part of Product Experience Management (PXM). Here you need customer personas. The elephant in the room, so to speak, is that you have to get the actual personas from Customer MDM and/or the Customer Data Platform (CDP).

In having that common MDM solution/framework there are some challenges to be solved in order to cater for all the contextual MDM use cases. One such challenge, being context-aware customer views, was touched upon in the post There is No Single Customer 360 View.

Customer Data Platform (CDP) vs Master Data Management (MDM)

Henrik Gabs LiliendahlLeave a comment

A recent Gartner report states that: “Organizations that fail to understand their use cases, desired business outcomes and customer data governance requirements have difficulty choosing between CDPs and MDM solutions, because of overlapping capabilities.”

Indeed. This topic was examined here on the blog last year in the post CDP: Is that part of CRM or MDM?

Gartner compare the two breeds of solutions this way:

  • CDPs are marketing-managed tools designed for the creation, segmentation and activation of customer profiles. … These platforms have less governance functionality than MDM solutions and tend to focus on delivering a complete view through the amalgamation of data generated by digital customer interactions.
  • MDM solutions are more mature technology that also enable customer 360 insights by creating and managing a central, persisted system or index of record for master customer records. They enable governance and management of the core data that uniquely identifies one customer as distinct from another. They were built to support enterprisewide sources and applications of customer data.

CDP platforms (via CRM applications) seems to hit from outside in without getting to the core of customer centrecity. MDM solutions are hitting the bullseye and some of the MDM solutions are moving inside out in the direction of extended MDM, where all customer data, not just customer master data, is encompassed under the same data governance umbrella.

CDP vs MDM

Get the Gartner report Choose Between Customer Data Platforms and MDM Solutions for 360-Degree Customer Insights through Reltio here.

10 MDMish TLAs You Should Know

Henrik Gabs LiliendahlLeave a comment

TLA stands for Three Letter Acronym. The world is full of TLAs. The IT world is indeed full of TLAs. The Data Management world is also full of TLAs. Here are 10 TLAs from the data management space that surrounds Master Data Management:

Def MDM

MDM: Master Data Management can be defined as a comprehensive method of enabling an enterprise to link all of its critical data to a common point of reference. When properly done, MDM improves data quality, while streamlining data sharing across personnel and departments. In addition, MDM can facilitate computing in multiple system architectures, platforms and applications. You can find the source of this definition and 3 other – somewhat similar – definitions in the post 4 MDM Definitions: Which One is the Best?

The most addressed master data domains are parties encompassing customer, supplier and employee roles, things as products and assets as well as location.

Def PIM

PIM: Product Information Management is a discipline that overlaps MDM. In PIM you focus on product master data and a long tail of specific product information – often called attributes – that is needed for a given classification of products.

Furthermore, PIM deals with how products are related as for example accessories, replacements and spare parts as well as the cross-sell and up-sell opportunities there are between products.

PIM also handles how products have digital assets attached.

This data is used in omni-channel scenarios to ensure that the products you sell are presented with consistent, complete and accurate data. Learn more in the post Five Product Information Management Core Aspects.

Def DAM

DAM: Digital Asset Management is about handling extended features of digital assets often related to master data and especially product information. The digital assets can be photos of people and places, product images, line drawings, certificates, brochures, videos and much more.

Within DAM you are able to apply tags to digital assets, you can convert between the various file formats and you can keep track of the different format variants – like sizes – of a digital asset.

You can learn more about how these first 3 mentioned TLAs are connected in the post How MDM, PIM and DAM Stick Together.

Def DQM

DQM: Data Quality Management is dealing with assessing and improving the quality of data in order to make your business more competitive. It is about making data fit for the intended (multiple) purpose(s) of use which most often is best to achieved by real-world alignment. It is about people, processes and technology. When it comes to technology there are different implementations as told in the post DQM Tools In and Around MDM Tools.

The most used technologies in data quality management are data profiling, that measures what the data stored looks like, and data matching, that links data records that do not have the same values, but describes the same real world entity.

Def RDM

RDM: Reference Data Management encompass those typically smaller lists of data records that are referenced by master data and transaction data. These lists do not change often. They tend to be externally defined but can also be internally defined within each organization.

Examples of reference data are hierarchies of location references as countries, states/provinces and postal codes, different industry code systems and how they map and the many product classification systems to choose from.

Learn more in the post What is Reference Data Management (RDM)?

Def CDI

CDI: Customer Data Integration is considered as the predecessor to MDM, as the first MDMish solutions focused on federating customer master data handled in multiple applications across the IT landscape within an enterprise.

The most addressed sources with customer master data are CRM applications and ERP applications, however most enterprises have several of other applications where customer master data are captured.

You may ask: What Happened to CDI?

Def CDP

CDP: Customer Data Platform is an emerging kind of solution that provides a centralized registry of all data related to parties regarded as (prospective) customers at an enterprise.

In that way CDP goes far beyond customer master data by encompassing traditional transaction data related to customers and the emerging big data sources too.

Right now, we see such solutions coming both from MDM solution vendors and CRM vendors as reported in the post CDP: Is that part of CRM or MDM?

Def ADM

ADM: Application Data Management is about not just master data, but all critical data that is somehow shared between personel and departments. In that sense MDM covers all master within an organization and ADM covers all (critical) data in a given application and the intersection is looking at master data in a given application.

ADM is an emerging term and we still do not have a well-defined market – if there ever will be one – as examined in the post Who are the ADM Solution Providers?

Def PXM

PXM: Product eXperience Management is another emerging term that describes a trend to distance some PIM solutions from the MDM flavour and more towards digital experience / customer experience themes.

In PXM the focus is on personalization of product information, Search Engine Optimization and exploiting Artificial Intelligence (AI) in those quests.

Read more about it in the post What is PxM?

Def PDS

PDS: Product Data Syndication connects MDM, PIM (and other) solutions at each trading partner with each other within business ecosystems. As this is an area where we can expect future growth along with the digital transformation theme, you can get the details in the post What is Product Data Syndication (PDS)?

One example of a PDS service is the Product Data Lake solution I have been working with during the last couple of year. Learn why this PDS service is needed here.

10 Data Management TLAs You Should Know

Henrik Gabs LiliendahlLeave a comment

TLA stands for Three Letter Acronym. The world is full of TLAs. The IT world is full of TLAs. The Data Management world is full of TLAs. Here are 10 TLAs from the data management world that have been mentioned a lot of times on this blog and the sister blog over at The Disruptive MDM / PIM / DQM List:

MDM = Master Data Management can be defined as a comprehensive method of enabling an enterprise to link all of its critical data to a common point of reference. When properly done, MDM improves data quality, while streamlining data sharing across personnel and departments. In addition, MDM can facilitate computing in multiple system architectures, platforms and applications. You can find the source of this definition and 3 other – somewhat similar – definitions in the post 4 MDM Definitions: Which One is the Best?

PIM = Product Information Management is a discipline that overlaps MDM. In PIM you focus on product master data and a long tail of specific product information related to each given classification of products. This data is used in omni-channel scenarios to ensure that the products you sell are presented with consistent, complete and accurate data. Learn more in the post Five Product Information Management Core Aspects.

DAM = Digital Asset Management is about handling rich media files often related to master data and especially product information. The digital assets can be photos of people and places, product images, line drawings, brochures, videos and much more. You can learn more about how these first 3 mentioned TLAs are connected in the post How MDM, PIM and DAM Stick Together.

DQM = Data Quality Management is dealing with assessing and improving the quality of data in order to make your business more competitive. It is about making data fit for the intended (multiple) purpose(s) of use which most often is best to achieved by real-world alignment. It is about people, processes and technology. When it comes to technology there are different implementations as told in the post DQM Tools In and Around MDM Tools.

RDM = Reference Data Management encompass those typically smaller lists of data records that are referenced by master data and transaction data. These lists do not change often. They tend to be externally defined but can also be internally defined within each organization. Learn more in the post What is Reference Data Management (RDM)?

10 TLA show

CDI = Customer Data Integration, which is considered as the predecessor to MDM, as the first MDMish solutions focussed on federating customer master data handled in multiple applications across the IT landscape within an enterprise. You may ask: What Happened to CDI?

CDP = Customer Data Platform is an emerging kind of solution that provides a centralized registry of all data related to parties regarded as (prospective) customers at an enterprise. Right now, we see such solutions coming both from MDM solution vendors and CRM vendors as reported in the post CDP: Is that part of CRM or MDM?

ADM = Application Data Management, which is about not just master data, but all critical data however limited to a single (suite of) application(s) at the time. ADM is an emerging term and we still do not have a well-defined market as examined in the post Who are the ADM Solution Providers?

PXM = Product eXperience Management is another emerging term that describes a trend to distance some PIM solutions from the MDM flavour and more towards digital experience / customer experience themes. Read more about it in the post What is PxM?

PDS = Product Data Syndication, which connects MDM, PIM (and other) solutions at each trading partner with each other within business ecosystems. As this is an area where we can expect future growth along with the digital transformation theme, you can get the details in the post What is Product Data Syndication (PDS)?

Three Not So Easy Steps to a 360-Degree Customer View

Henrik Gabs Liliendahl2 Comments

Getting a 360-degree view (or single view) of your customers has been a quest in data management as long as I can remember.

This has been the (unfulfilled) promise of CRM applications since they emerged 25 years ago. Data quality tools has been very much about deduplication of customer records. Customer Data Integration (CDI) and the first Master Data Management (MDM) platforms were aimed at that conundrum. Now we see the notion of a Customer Data Platform (CDP) getting traction.

There are three basic steps in getting a 360-degree view of those parties that have a customer role within your organization – and these steps are not at all easy ones:

360 Degree Customer View

  • Step 1 is identifying those customer records that typically are scattered around in the multiple systems that make up your system landscape. You can do that (endlessly) by hand, using the very different deduplication functionality that comes with ERP, CRM and other applications, using a best-of-breed data quality tool or the data matching capabilities built into MDM platforms. Doing this with adequate results takes a lot as pondered in the post Data Matching and Real-World Alignment.
  • Step 2 is finding out which data records and data elements that survives as the single source of truth. This is something a data quality tool can help with but best done within an MDM platform. The three main options for that are examined in the post Three Master Data Survivorship Approaches.
  • Step 3 is gathering all data besides the master data and relate those data to the master data entity that identifies and describes the real-world entity with a customer role. Today we see both CRM solution vendors and MDM solution vendors offering the technology to enable that as told in the post CDP: Is that part of CRM or MDM?

CDP: Is that part of CRM or MDM?

Henrik Gabs Liliendahl2 Comments

The notion of a data centred application type called a Customer Data Platform (CDP) seems to be trending these days. A CDP solution is a centralized registry of all data related to parties regarded as (prospective) customers at an enterprise.

This kind of solution comes from two solution markets:

  • Customer Relationship Management (CRM)
  • Master Data Management (MDM)

The CRM track was recently covered in a Venture Beat article telling that Salesforce announces a Customer Data Platform to unify all marketing data. In this article it is also stated that Oracle just announced a similar solution named CX Unity and Adobe announced triggered journeys based on a rich pool of centralized data.

Add to that last year´s announcement from Microsoft, Adobe and SAP on their Open Data Initiative as told in the LinkedIn article Using a Data Lake for Data Sharing.

Some MDM solution providers are also on that track. Reltio Cloud embraces all customer data and Informatica Customer 360 Insights, formerly known as Allsight, is also going there as reported in the post Extended MDM Platforms.

Will be interesting to follow how CDP solutions evolve and if it is CRM or MDM vendors who will do best in this discipline. One guess could be that MDM vendors will provide “the best” solutions but CRM vendors will sell most licenses. We will see.

CDP CRM MDM