The term infonomics does not yet run unmarked through my English spellchecker, but there are some information available on Wikipedia about infonomics. Infonomics is closely related to the often-mentioned phrases in data management about seeing data / information as an asset.
Much of what I have read about infonomics and seeing data / information as an asset is related to what we call first party data. That is data that is stored and managed within your own company.
Some information is also available in relation to third party data. That is data we buy from external parties in order to validate, enrich or even replace our own first party data. An example is a recent paper from among others infonomic guru Doug Laney of Gartner (the analyst firm). This paper has a high value if you want to buy it as seen here.
Anyway, the relationship between data as an asset and the value of data is obvious when it comes to third party data, as we pay a given amount of money for data when acquiring third party data.
Second party data is data we exchange with our trading and other business partners. One example that has been close to me during the recent years is product information that follows exchange of goods in cross company supply chains. Here the value of the goods is increasingly depending on the quality (completeness and other data quality dimensions) of the product information that follows the goods.
In my eyes, we will see an increasing focus on infonomics when it comes to exchanging goods – and the related second party data – in the future. Two basic factors will be:
Product Data Lake is the new solution to sharing product information between trading partners. While we see many viable in-house solutions to Product Information Management (PIM), there is a need for a solution to exchange product information within cross company supply chains between manufacturers, distributors and retailers.
Completeness of product information is a huge issue for self-service sales approaches as seen in ecommerce. 81 % of e-shoppers will leave a webshop with lacking product information. The root cause of missing product information is often an ineffective cross company data supply chain, where exchange of product data is based on sending spreadsheets back and forth via email or based on biased solutions as PIM Supplier Portals.
However, due to the volume of product data, the velocity required to get data through and the variety of product data needed today, these solutions are in no way adequate or will work for everyone. Having a not working environment for cross company product data exchange is hindering true digital transformation at many organizations within trade.
As a Product Information Management professional or as a vendor company in this space, you can help manufacturers, distributors and retailers in being successful with product information completeness by becoming a Product Data Lake ambassador.
The Product Data Lake encompasses some of the most pressing issues in world-wide sharing of product data:
The first forward looking professionals and vendors in the Product Information Management realm have already joined. I would love to see you as well as our next ambassador.
Interested? Get in contact:
A recent discussion on the LinkedIn Multi-Domain MDM group is about vendor / supplier portals as a part of Product Information Management implementations.
A supplier portal (or vendor portal if you like) is usually an extension to a Product Information Management (PIM) solution. The idea is that the suppliers of products, and thus providers of product information, to you as a downstream participant (distributor or retailer) in a supply chain, can upload their product information into your PIM solution and thus relieving you of doing that. This process usually replace the work of receiving spreadsheets from suppliers in the many situations where data pools are not relevant.
In my opinion and experience, this is a flawed concept, because it is hostile to the supplier. The supplier will have hundreds of downstream receivers of products and thus product information. If all of them introduced their own supplier portal, they will have to learn and maintain hundreds of them. Only if you are bigger than your supplier is and is a substantial part of their business, they will go with you.
Another concept, which is the opposite, is also emerging. This is manufacturers and upstream distributors establishing PIM customer portals, where suppliers can fetch product information. This concept is in my eyes flawed exactly the opposite way.
And then let us imagine that every provider of product information had their PIM customer portal and every receiver had their PIM supplier portal. Then no data would flow at all.
What is your opinion and experience?
The below figure shows the cross border data flows on this planet. There are inter-regional data flows and there are flows between the worldwide regions:
Now, a small part of this data will be product data exchanged between trading partners participating in global business ecosystems. While I have no data on if product data are distributed by the same proportions as data in general, it will be a qualified guess, that the picture will look somewhat the same.
Exchanging product data across borders has some challenges:
- Language is an issue. Product data will eventually have to be translated into the language of the end buyer, if this is not the language in which the product data originally are provided. The definitions (metadata) of product data will also be subject to translation. Even the language of the transmission tools would not be in English all over.
- Regulations around product data are different from country to country.
- The cultural content of the optimal data describing a product in structured data elements and related digital assets are different between countries and regions.
At Product Data Lake, we are, from the center of the largest green bubble, looking for ambassadors around the world who are able to link the in-house product information management solutions at trading partners.
Interested? Get in contact:
In the Master Data Management (MDM) realm we have some common notions, being
- 360 degree Customer Master Data Management, meaning how different views on customers in a company’s various business units and sales channels can be handled as a shared single view.
- 360 degree Vendor (or Supplier) Master Data Management, meaning how different views on vendors/suppliers in a company’s various business units and supply chains can be handled as a shared single view.
- 360 degree Vendor Product Master Data Management, meaning how different views on products in a company’s various business units, sales channels and supply chains can be handled as a shared single view.
Multi-Domain Master Data Management (MDM) is the discipline that brings all these views together. Here it is not enough that the same brand of technology is used for all three domains. Handling the intersections is the important part.
The intersection of Vendor/supplier and Customer is known as the Party Master Data domain. My recommendation 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.
The Vendor/supplier and Product Master Data intersection is related to buying products, namely how to on-board data about the vendor/supplier as a party, in the vendor role (financial stuff), the supplier role (logistic stuff) and then on-boarding his product information. My recommendation for on-boarding product information from suppliers being manufacturers is to make this a Win-Win solution for both parties as described in the post How a PLM-2-PIM Solution Becomes a WIN-WIN Solution.
The Customer and Product Master Data intersection is about supporting how you sell products. The term omnichannel is popular for that these days. Again, Product Information Management (PIM) plays a crucial role here and my recommendations for that is expressed in the post Adding Business Ecosystems to Omnichannel.
Yesterday Gautam Sood of Riversand blogged about that One Size doesn’t fit all – The Complexities of a Global PIM.
In this blog post Gautam examines the challenges, the key questions and the concept options an organization have when embarking on a journey to go from a national (or regional) scale to an international scale in Product Information Management.
A recent blog post here on the blog also had that theme for the Master Data Management (MDM) realm. This post is about Cross Border Master Data Management.
In his post Gautam states: “A Global PIM is not a consolidation exercise. Variance is the reality, and it has to be supported.”
This resonates very well with my findings. Very low practical this means that you will not win by translating all product descriptions into English. Even the metadata has to be multilingual, as you will interact with trading partners using different languages. While one public standard for product information may be king in one region, this will most likely not be the case in another region, which again effects how you collaborate with trading partners in different geographies.
In my eyes the global PIM journey does not end with consensus and a common platform of either concept inside your organization. You have to embrace your business ecosystem of trading partners. How to do that is explained in the post What a PIM-2-PIM Solution Looks Like.
Ben Rund of Informatica has a Youtube video running these days with the title/question: Enough Heard on Digital Transformation by Uber & AirBnB?
I share this sentiment with Ben. You don’t have to disrupt the whole world to take part in digital transformation and you don’t have to start something completely new. As an established enterprise you can transform your current business and combine the good things from the past with the new opportunities aroused from the digital evolution.
Forrester, the other analyst firm, some years ago devided digital transformation into a loop of:
- Digital Customer Experience
- Digital Operational Excellence
The below figure visualizes this landscape:
What I would like to elaborate on related to this picture is the business ecosystem of your enterprise, which must be included in the everyday digital transformation.
Let’s take the example of product information management:
However, connect is better than collect. If you are dependent on receiving spreadsheets with product information from your trading partners or you let them put their spreadsheets into your supplier product data portal, you have an everyday digital transformation in front of you.
The solution for that is Product Data Lake.