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 should look 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.
The most votes in the current standing has gone to this answer:
We must first mature in handling our product information internally
Solving this issue is one of the things we do at Liliendahl.com. Besides being an advisory service in the Master Data Management (MDM) and Product Information Management (PIM) space, we have a developing collaboration with companies providing consultancy, cleansing and, when you come to that step, specialized technology for inhouse MDM and PIM. Take a look at Our Business Ecosystem.
If you are a manufacturer with a limited need for scaling the PIM technology part and already have much of your needs covered by an ERP and/or Product Lifecycle Management (PLM) solution, you may also fulfill your inhouse PIM capabilities and the external sharing needs in one go by joining Product Data Lake.
Internet of Things (IoT) is a hot topic in the data management world and yours truly is also among those who sees IoT as a theme that will have a tremendous impact on data management including data quality, data governance and Master Data Management (MDM).
However, I think the flavour of IoT called Industrial Internet of Things (IIoT) or Industry 4.0 will mature, and already have matured, before the general IoT theme.
IIoT / Industry 4.0 is about how manufacturers use connected intelligent devices to improve manufacturing processes where the general IoT theme extends the reach out in the consumer world – with all the security and privacy concerns related to that.
In this article, Justin Hester of automotive part manufacturer Hirotec tells about their approach to embracing IIoT. Justin Hester states that “…we can finally harness the data coming in from all of these different sources, whether they are machines, humans, parts – but I think the real challenge is the next step – how do I execute? That’s the challenge.”
Indeed, how to execute and take (near) real-time action on data will be the scenario where Return on Investment (ROI) will show up. This means, as explained in the article, that you should make incremental implementations.
It also means, that you must be able to maintain master data that can support (near) real-time execution. As IIoT/Industry 4.0 is about connected devices in business ecosystems, my suggestion is a data architecture as described on Master Data Share.
The use of graph technology in Master Data Management (MDM) has been a recurring topic on this blog as the question about how graph approaches fits with MDM keeps being discussed in the MDM world.
Recently Salah Kamel, the CEO at the agile MDM solution provider Semarchy, wrote a blog post called Does MDM Need Graph?
In here Salah states: “A meaningful graph query language and visualization of graph relationships is an emerging requirement and best practice for empowering business users with MDM; however, this does not require the massive redesign, development, and integration effort associated with moving to a graph database for MDM functionality”.
In his blog post Salah discusses how relationships in the multi-domain MDM world can be handled by graph approaches not necessarily needing a graph database.
At Product Data Lake, which is a business ecosystem wide product information sharing service that works very well besides Semarchy MDM inhouse solutions, we are on the same page.
Currently we are evaluating how graph approaches are best delivered on top of our document database technology (using MongoDB). The current use cases in scope are exploiting related products in business ecosystems and how to find a given product with certain capabilities in a business ecosystem as examined in the post Three Ways of Finding a Product.
When working with Master Data Management (MDM) it is always valuable to follow the analyst firms that are active on this subject and the related subjects as data quality, data governance and data management in general. You can learn from their insights – and disagreements – on the matters. Here are 10 analyst firms I follow:
Gartner, the large analyst firm known for their magic quadrants, hype cycles and cool vendor lists. There is a lot of brain power in this firm and they have never been caught in admitting a mistake. Quite a lot of posts on this blog mentions Gartner.
Forrester, another firm with heaps of analysts. Forrester has though been less prominent in the MDM world since Robert Karel left for Informatica. However, there are lots of wider insights to gain from as mentioned in the post Ecosystems are The Future of Digital and MDM.
The MDM Institute, which basically is Aaron Zornes, known as the Father Christmas of MDM. Aaron Zornes was the inspirational source in my recent post called MDM as Managed Service.
In his article, Aaron Zornes looks at the slow intake of multi-domain MDM, proactive data governance, graph technology and Microsoft stuff ending with stating that MDM as MANAGED SERVICE = HOT:
“Just as business users increasingly gave up on IT to deliver modest CRM in a timely, cost effective fashion (remember all the Siebel CRM debacles), so too are marketing and sales teams especially looking to improve the quality of their customer data… and pay for it as a “service” rather than as a complex, long-time-to-value capital expenditure that IT manages”.
I second that, having been working with the iDQ™ service years ago, and will add, that the same will be true for product data as well and then eventually also multi-domain MDM.