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.
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?
A 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?
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.
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.
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.
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.
“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.
While 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.