The Need for Data in Master Data Management

For nearly a decade we have lived with the Gartner 7 building blocks of MDM.

The 7 blocks encompassing vision, strategy, metrics, governance, organization, processes and technology was recently touched here on the blog in the post The Need for a MDM Vision.

Yesterday Justine Rodian of Stibo Systems wrote Why 7 Master Data Management Building Blocks Aren’t Enough Anymore: Revisiting Gartner’s Best Practice Model.

Block 8 proposed herein, based on a presentation by former Gartner analyst John Radcliffe, is data. I have no problem with that. I think data has been there always as the foundation for information leading to knowledge and topped by wisdom.

Yep, let’s include data in Master Data Management.

MDMDG 2013 wordle

The Need for a MDM Vision

Many of the MDM programs we see are increasingly tactical rather than enterprise in nature. This observation was examined in the previous post on this blog as well as in the comments. If you missed it, check out Do we need better business decisions about MDM?

MDM BlocksA crucial point is that organizations have a MDM vision. The need for a MDM vision was also the top block in the seven building blocks of MDM proposed by John Radcliffe, when John worked at Gartner (the analyst firm).

In here, John advised that there should be one unifying, strategic MDM vision that needs to reflect the organization’s business vision. However, due to internal politics and entrenched working practices a pragmatic, step-by-step approach is necessary for the entire organization to embrace the vision.

Does your organization have a MDM vision? What is included in the MDM vision? How is the vision embraced by various organizational entities?

MDM / PIM Platform Vendors Need to Grow Up Too

Participating in digital ecosystems is the way forward for enterprises who wants to be tomorrow’s winners through digital transformation.

Some figures from Gartner, the analyst firm, tells this about digital transformation:

  • 79% of top performing companies indicate that they participate in a digital ecosystem
  • 49% of typical companies indicate the same
  • 24% of trailing companies does it

These figures were lately examined by Bryan Kirschner of Apigee (now part of Google) in a Cio.com article called Ecosystems: when digital transformation grows up.

Master Data Share
Master Data Share for Business Ecosystems

As a Master Data Management (MDM) and/or Product Information Management (PIM) platform vendor you should support your current and prospective clients with means to participate in digital ecosystems.

Current offerings from MDM and PIM platforms vendors have become quite mature in supporting inhouse (enterprise wide) handling of master data and product information. Next step is supporting sharing within business ecosystems. A concept for that is introduced in Master Data Share.

Master Data or Shared Data or Critical Data or What?

What is master data and what is Master Data Management (MDM) is a recurring subject on this blog as well as the question about if we need the term master data and the concept of MDM. Recently I read two interesting articles on this subject.

Andrew White of Gartner wrote the post Don’t You Need to Understand Your Business Information Architecture?

In here, Andrew mentions this segmentation of data:

  • Master data – widely referenced, widely shared across core business processes, defined initially and only from a business perspective
  • Shared application data – less widely but still shared data, between several business systems, that links to master data
  • Local application data – not shared at all outside the boundary of the application in mind, that links to shared application and master data

Teemu Laakso of Kone Corporation has just changed his title from Head of Master Data Management to Head of Data Design and published an article called Master Data Management vs. Data Design?

In here, Teemu asks?

What’s wrong in the MDM angle? Well, it does not make any business process to work and therefore doesn’t create a direct business case. What if we removed the academic borderline between Master Data and other Business Critical data?

The shared sentiment, as I read it, between the two pieces is that you should design your “business information architecture” and the surrounding information governance so that “Data Design Equals Business Design”.

My take is that you must look from one level up to get the full picture. That will be considering how your business information architecture fits into the business ecosystem where your enterprise is a part, and thereby have the same master data, shares the same critical data and then operates your own data that links to the shared critical data and business ecosystem wide master data.

Master Data or

Three Ways of Embracing Digital Ecosystem Platforms

Gartner, the analyst firm, has recently promoted their take on the five kinds of digital platforms you will need to consider in your digital transformation journey.

Gartner Digital Platforms 2The top right kind of platform is the ecosystem one. This kind of platform will facilitate how you interact with business partners.

I my eyes, there are three kind of ways you can do that:

  1. You provide and own an ecosystem digital platform for your business partners
  2. You participate in an ecosystem digital platform provided and owned by one of your business partners
  3. You participate in a neutral provided and owned ecosystem digital platform for a given purpose

Currently I am working with Product Data Lake, which is the third kind of platform. In this ecosystem digital platform you can exchange product information with your trading partners. There are alternatives of the other kinds as discussed in the post PIM Supplier Portals: Are They Good or Bad?

Ecosystems are The Future of Digital and MDM

A recent blog post by Dan Bieler of Forrester ponders that you should Power Your Digital Ecosystems with Business Platforms.

In his post, Dan Bieler explains that such business platforms support:

·      The infrastructure that connect ecosystem participants. Business platforms help organizations transform from local and linear ways of doing business toward virtual and exponential operations.

·      A single source of truth for ecosystem participants. Business platforms become a single source of truth for ecosystems by providing all ecosystem participants with access to the same data.

·      Business model and process transformation across industries. Platforms support agile reconfiguration of business models and processes through information exchange inside and between ecosystems.

A single source of truth (or trust) for ecosystem participants is something that rings a bell for every Master Data Management (MDM) practitioner. The news is that the single source will not be a single source within a given enterprise, but a single source that encompasses the business ecosystem of trading partners.

Gartner Digital Platforms.png

Gartner, the other analyst firm, has also recently been advocating about digital platforms where the ecosystem type is the top right one. As stated by Gartner: Ecosystems are the future of digital.

I certainly agree. This is why all of you should get involved at Master Data Share.

 

I am afraid that Gartner does not help

“The average financial impact of poor data quality on organizations is $9.7 million per year.” This is a quote from Gartner, the analyst firm, used by them to promote their services in building a business case for data quality.

AverageWhile this quote rightfully emphasizes on that a lot of money is at stake, the quote itself holds a full load of data and information quality issues.

On the pedantic side, the use of the $ sign in international communication is problematic. The $ sign represents a lot of different currencies as CAD, AUD, HKD and of course also USD.

Then it is unclear on what basis this average is measured. Is it among the +200 million organizations in the Dun & Bradstreet Worldbase? Is it among organizations on a certain fortune list? In what year?

Even if you knew that this is an average in a given year for the likes of your organization, such an average would not help you justify allocation of resources for a data quality improvement quest in your organization.

I know the methodology provided by Gartner actually is designed to help you with specific return on investment for your organization. I also know from being involved in several business cases for data quality (as well as Master Data Management and data governance) that accurately stating how any one element of your data may affect your business is fiendishly difficult.

I am afraid that there is no magic around as told in the post Miracle Food for Thought.