How Bosch is Aiming for Unified Partner Master Data Management

A recurrent theme on this blog is the way organizations should handle party master data management as examined in the post What is Best Practice: Customer- and Vendor- or Unified Party Master Data Management?

What I advise my clients to do, is to have a common party (or business partner) structure for identification, names, addresses and contact data. This should be supported by data quality capabilities strongly build on external reference data (third party data). Besides this common structure, there should be specific structures for customer, vendor/supplier and other party roles.

This week I attended the MDM event arranged by Marcus Evans in Barcelona. The presentation by Udo Couto Klütz of the industrial giant Robert Bosch highlighted the clever way of handling customer master data, by having a partner master data concept.

Bosch

At Bosch they have reached the conclusion, that unified partner master data management is the way to achieve:

  • A single source of truth
  • Transparency
  • Standardized processes
  • Worldwide applicability
  • One compliance standard
  • Increased efficiency

I absolutely agree.

Welcome Semarchy xDM on The Disruptive MDM List

I am happy to welcome Semarchy xDM as the first disruptive Master Data Management Solution on the disruptive MDM list. You can learn more about, and review, Semarchy xDM here.

xDM Capabilities (002)

Semarchy has been a part of developing Product Data Lake, as the first prototype of this service was made using the Semarchy platform. I owe Salah Kamel, the Semarchy CEO, big thanks for his support in doing that.

By making that prototype, I can confirm that Semarchy caters for a fast track, when it comes to setting up a Master Data Management solution.

The Disruptive MDM List

As reported in the previous post on this blog, Gartner (the analyst firm) has stopped having a list of smaller and potential disruptive MDM solutions in their Magic Quadrant for Master Data Management Solutions.

I think it is time to have an alternative list of MDM solutions with room for the disruptive ones.

Therefore, I have created a new site for a list of MDM and similar solutions. 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

You can use this site as an alternative to the likes of Gartner, Forrester, MDM Institute and others when selecting a MDM / CDI / PIM / DAM solution, not at least because this site will also include smaller and disruptive solutions.

Vendors can register their solutions here and the crowd, being processional users, can review the solutions.

I will welcome vendors of all sizes, at all stages and from all geographies to register your solution at the disruptive MDM list.

Master Data or

Please have a look at the current stage of The Disruptive MDM List

Disruptive Forces in MDM Land

MDM 2017 disruptionFor the second time this year there is a Gartner Magic Quadrant for Master Data Management Solutions out. The two leaders, Orchestra Networks and Informatica, have released their free copies here and here.

Now Gartner have stopped having a list of vendors on the market too small to be in the actual quadrant. So, if you are looking for new thinking, you will have to read the section about disruptive forces in the MDM market.

Gartner says that every market experiences disruptive forces that influence its overall shape and trajectory over time, and that inspire innovation, both transformational and incremental. According to Gartner, those most prominent in the MDM market appear diametrically opposed.

The current market is dominated by vendors who have predominantly taken a platform-centric approach involving robust technology stacks categorized as application-neutral hub-based solutions. Thus, the business value of the resulting master data is realized through utilization of that data within business applications or suites, or analytics platforms, external to the MDM solution — such as CRM, ERP and e-commerce systems, and data warehouses.

One disruptive force against that is an increase in business applications or suites with embedded ADM (Application Data Management) capabilities that address organizational needs for data management, including MDM (to varying degrees), while also managing nonmaster data for the pertinent application. Gartner states that application-centric approaches for some organizations can return greater value than platform-centric approaches in the short term and do so at reduced cost.

The opposing disruptive force stems from the emergence of more generalized data management solutions. These provide for unified execution logic on top of what is effectively an integrated technology stack. Vendors envision the primary consumption model to be cloud-based subscription. As such, these solutions will also provide a means for midmarket organizations and SMBs to procure advanced data management capabilities (such as MDM) using this model of consumption. Executed crisply, cloud-based subscriptions to these solutions may even moderate the rise of cloud-based MDM offerings.

Regular readers of this blog may guess, that I see a coming third disruptive force in MDM land, being specialized data management services for business ecosystems as explored in the post Ecosystems are The Future of Digital and MDM.

The Product Data Domain and the 2017 Gartner Data Quality Magic Quadrant

data-quality-magic-quadrant-2017The Gartner Magic Quadrant for Data Quality Tools 2017 is out. One place to get it for free is at the Informatica site.

As data quality for product data is high on my agenda right now, I did a search for the word product in the report. There are 123 occurrences of the word product, but the far majority is about the data quality tool as a product with a strategy and a roadmap.

The right context saying about the product domain is, as I could distil it based on word mentioning, as follows:

Product data is part of multidomain

Gartner says that the product domain is a part of multidomain support, being packaged capabilities for specific data subject areas, such as customer, product, asset and location.

Some vendors were given thumbs up for including product data in the offering. These were:

  • BackOffice Associates has this strength: Multidomain support across a wide range of use cases: BackOffice Associates’ data quality tools provide good support for all data domains, with particular depth in the product data domain.
  • Information Builders has this strength: Multidomain support and diverse use cases: Deployments by Information Builders’ reference customers indicate a diversity of usage scenarios and data domains, such as customer, product and financial data.
  • SAS (Institute, not the airline) has this strength: Strong knowledge base for the contact and product data domains.

One should of course be aware, that other vendors also may have support for product data, but this is overshadowed by other strengths.

Effect on positioning

Multidomain brings vendors to the top right. Gartner’s metrics means that leaders address all industries, geographies, data domains and use cases. Their products support multidomain and alternative deployment options such as SaaS.

Product data focus can make a vendor a challenger. Gartner tells that challengers may not have the same breadth of offering as Leaders, and/or in some areas they may not demonstrate as much thought-leadership and innovation. For example, they may focus on a limited number of data domains (customer, product and location data, for example). This also means, that missing product data focus keeps vendors away from the top right positioning, which seems to be hitting Pitney Bowes and Experian Data Quality.

Product data will become more important, but is currently behind other domains

Gartner emphasizes that data and analytics leaders including Chief Data Officers and CIOs must, to achieve CEOs’ business priorities, ensure that the quality of their data about customers, employees, products, suppliers and assets is “fit for purpose” and trusted by users.

Organizations are increasingly curating external data to enrich and augment their internal data. Finally, they are expanding their data quality domains from traditional party domains (such as customer and organization data) to other domains (such as product, location and financial data).

According to Gartner, data quality initiatives address a wide variety of data domains. However, party data (for existing customers, prospective customers, citizens or patients, for example) remains the No. 1 priority: 80% of reference customers considered it the top priority among their three most important domains. Transactional data came second highest, with 45% of reference customers naming it among their top three. Financial/quantitative data was third, with 39% of reference customers naming it. The figure for product data was 34%.

In my view, the 34% figure is because not all organizations have high numbers of product data and have major business pains related to product data. But those who have are looking at data quality tool and service vendors for suitable solutions.

Sell more. Reduce costs.

Business outcome is the end goal of any data management activity may that be data governance, data quality management, Master Data Management (MDM) and Product Information Management (PIM).

Business outcome comes from selling more and reducing costs.

At Product Data Lake we have a simple scheme for achieving business outcome through selling more goods and reducing costs of sharing product information between trading partners in business ecosystems:

Sell more Reduce costs

Interested? Get in touch:

Neutron Star Collision and Data Quality

The scientific news of the day is the observed collision of two neutron stars resulting in gravitational waves, an extremely bright flash – and gold.

The connection between gravitational waves and Master Data Management (MDM) was celebrated here on the blog when those waves were detected for the first time as told in the post Gravitational Waves in the MDM World.

The ties to Product Information Management (PIM) was examined in the post Gravitational Collapse in the PIM Space.

Now we have seen a bright flash resembling what happens when two trading partners collide, as in makes business together encompassing sharing master data and product information. Seen from my telescope this improves data quality and thereby business outcome (gold, you know) as explained in the post Data Quality and Business Outcome.

Neutron Star Collide