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.
This survey points to that the main reason why this does that take place is that manufacturers need to mature in handling and consolidating product information internally, before they are confident in sharing the detailed data elements (in an automated way) with their downstream partners. This subject was elaborated in the post Product Information Sharing Issue No 1: We Need to Mature Internally.
Issue no 3 is the apparent absence of a good solution for sharing product information with trading partners that suites the whole business ecosystem. I guess it is needless to say to regular readers of this blog that, besides being able to support issue no 1 and issue no 2, that solution is Product Data Lake.
“Organisations need architectural thinking beyond their organisational boundaries” and “The days of Enterprise Architecture taking a castle and moat approach are over”.
The end of the castle and moat thinking in Enterprise Architecture (and Business Information Architecture) is also closely related to the diminished importance of the brick and mortar ways of selling, being increasingly overtaken by eCommerce.
However, some figures I have noticed that cause the brick and mortar way to resist the decline by still having a castle and moat thinking is:
Retailers, distributors and manufacturers need to move on from the castle and moat thinking in Enterprise Architecture and Business Information Architecture and start interacting effectively in their business ecosystems with product information.
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.
One, perhaps shocking, number mentioned in the report is that there is “room for improvement, as only 5 percent of organizations share all their product data electronically with supply chain partners”.
However, this resonates very well with my experience, as it has been hard to find a good way to share all kind of product information electronically with all your trading partners, as:
The most common used way today is exchanging spreadsheets, which is cumbersome and error prone and therefore many companies experience that it simply is not done or only done partly and certainly not timely.
Using consensus data pools (eg GS1 GDSN) only covers a fraction of product groups and product data elements with varying penetration and coverage in different geographies
Product Information Management (PIM) is a fast-growing discipline enabled by PIM platforms. While the current market for PIM platforms is much about supporting a consistent in-house management of the information related to product models we make, buy and sell, there are new opportunities arising. Three of them on my radar are:
The recent buzzword in the chain starting with “supply chain” and going over “value chain” is “value web”. Learn about the arrival of continuously evolving business ecosystems and value webs in this article from Deloitte University Press. Product information management encompassing business ecosystems will be imperative in value webs.
Product Data Lake
This is in all humbleness my venture by having launched a PIM-2-PIM platform that deals with the current main pain in product information management, being exchanging product information between trading partners. We do that in an agile and automated way by supporting partnerships in value webs and are soon adding things to Product Data Lake.
Hundreds of years ago the geocentric model was replaced by heliocentrism, meaning that we recognize that the earth travels around the sun and not the other way around.
When it comes to Product Information Management (PIM), we also need a Copernican Revolution, meaning that it is good to manage product information consistently inside a given company, but it is better to manage product information in the light of the business ecosystem where we participate.
Exchanging product information in the business ecosystems of manufacturers, distributors and retailers cannot work properly by asking all your trading partners to use your version of a spreadsheet – if they don’t get to you first with their version. Nor will self-centered supplier / customer product data portals work as examined in the post PIM Supplier Portals: Are They Good or Bad?
Your company is not a lonely planet. You are part of a business ecosystem, where you may be:
Upstream as the maker of goods and services. For that you need to buy raw materials and indirect goods from the parties being your vendors. In a data driven world you also to need to receive product information for these items. You need to sell your finished products to the midstream and downstream parties being your B2B customers. For that you need to provide product information to those parties.
Midstream as a distributor (wholesaler) of products. You need to receive product information from upstream parties being your vendors, perhaps enrich and adapt the product information and provide this information to the parties being your downstream B2B customers.
Downstream as a retailer or large end user of product information. You need to receive product information from upstream parties being your vendors and enrich and adapt the product information so you will be the preferred seller to the parties being your B2B customers and/or B2C customers.
At Product Data Lake we support business ecosystems in Product Information Management (PIM). And this is not just a nice model. There are concrete business benefits too. 5 for you and 5 for your trading partner: Check our 10 business benefits.