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:
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.
“Black Friday & Christmas: 5 Retail Strategies for Providing a Wonderful Shopping Experience” is the title of a recent blog post by Antonia Renner on the Informatica blog.
This blog post revolves around how Master Data Management (MDM) and Product Information Management (PIM) can be the foundation of a better shopping experience and how to do this within driving digital transformation, being agile, and streamlining internal and external collaboration and workflows.
I agree with that. My only concern around the means mentioned relates to the section about how great customer experience starts with great supplier product data. The proposed approach for that is a self-service supplier data portal.
From what I have experienced, the concept of a supplier data portal for product data has limited chances of success. The problem for you as retailer or other form of downstream trading partner is your supplier. They will eventually have to deal with hundreds of supplier portals with different format and structure by the choice of their downstream trading partners, whereof you are just one. If you are a big one to them, it might work. Else probably not.
In the same way, your supplier could offer their customer data portal, build with their choice of format and structure. If they are a big one to you, you might go with that. Else, you probably would object to dealing with hundreds of different upstream data portals for you to go-to.
My Christmas present to you – suppliers, retailers, other supply chain nodes / PIM-MDM solution vendors – is a free trial / ambassadorship on Product Data Lake.
Product Data Lake is a cloud service for sharing product data in business ecosystems. Product Data Lake ensures:
- Completeness of product information by enabling trading partners to exchange product data in a uniform way
- Timeliness of product information by connecting trading partners in a process driven way
- Conformity of product information by encompassing various international standards for product information
- Consistency of product information by allowing upstream trading partners and downstream trading partners to interact with in-house structure of product information
- Accuracy of product information by ensuring transparency of product information across the supply chain
It’s in your hands. See you on Product Data Lake.
Sharing product data within business ecosystems of manufacturers, distributors, retailers and end users has grown dramatically during the last years driven by the increased use of e-commerce and other customer self-service sales approaches.
At Product Data Lake we recently had a survey about how companies shares product data today. The figures were as seen below:
The result shows that there are different approaches out there. Spreadsheets still rules the world though closely, in this survey, followed by external data portals. Direct system to system approaches are also present while supplier portals seems to be not that common.
At the Product Data Lake we aim to embrace those different approaches. Well, regarding use of spreadsheets and digital asset files via eMail our embracement is meant to be that of a constrictor snake. The Product Data Lake is the solution to end the hailstorms of spreadsheets with product data within cross company supply chains.
For external data portals, the Product Data Lake offers the concept of a data reservoir. A data reservoir in the Product Data Lake can be with an industry focus or with a special focus on certain data elements as for example sustainability data as described in the post Sustainability Data in PIM.
Direct systems to system exchange can be orchestrated through the Product Data Lake and supplier portals can served by the Product Data Lake. In that way existing investments in those approaches, that typically are implemented to serve basic data elements shared with your top trading partners, can be supplemented by a method that caters for exchange with all your trading partners and covering all data elements and digital assets.
The launch of the Product Data Lake is 24 days away. Hope to see you either in London Olympia or on the internet then.
The increased use of self-service based sales approaches as in ecommerce has put a lot of pressure on cross company supply chains. Besides handling the logistics and controlling pricing, you also have to take care of a huge amount of product data and digital assets describing the goods.
You may divide product information into these five levels:
Please learn more about the five levels of product information, including how hierarchies, pricing and logistics fits in, by visiting the product information castle.
Level 4 in this model is self-service product data being:
- Product attributes, also sometimes called product properties or product features. These are up to thousands of different data elements that describes a product. Some are very common for most products like height, length, weight and colour. Some are very specific to the product category. This challenge is actually the reason of being for dedicated Product Information Management (PIM) solutions.
- Basic product relations are the links between a product and other products like a product that have several different accessories that goes with the product or a product being a successor of another now decommissioned product.
- Standard digital assets are documents like installation guides, line drawings and data sheets.
These are the product data that helps the end customer comparing products and making an objective choice when buying a product for a specific purpose of use. These data are also helpful in answering the questions a buyer may have when making a purchase.
Every piece of data belonging to any level of product information may be forwarded through the cross company supply chain from the manufacturer to the end seller. Self-service product data are however the data that most obviously will do so.
In order to support end customer self-service when producing, distributing and selling goods you must establish a process driven service that automates the introduction of new products with extensive product data, the inclusion of new kinds of product data and updates to those data. You must be a digitalized member of your business ecosystem. The modern solution for that is the Product Data Lake.