Some new capabilities have been included in the Product Data Lake service.
As a manufacturer you can now utilize Product Data Lake even more as a cloud based lightweight Product Information Management (PIM) system. We have added better views of uploaded product information and better means of managing product data within the service. This will be of benefit for manufacturers who already handles product data in ERP and Product Lifecycle Management (PLM) solutions and needs a cost-effective solution to share these data with trading partners. Learn more about this option here.
Also, independent providers of hubs of product information within a given industry and/or geography can now self-register as a reservoir inside Product Data Lake and thus ad a modern and generic way of collecting and distributing product information to existing specialized product data pools.
But we do not stop there. The next version 1.4 will be live just before our far east development team takes some time off for the Lunar New Year. This version adds new possibilities for pushing product information through Product Data Lake. We already support file drops via FTP domains, traditional interactive upload from network drives and direct data entry. Next option is APIs.
Further versions during the coming months covers deeper integration of popular product information standards such as ETIM, eClass and UNSPSC. Learn more about these standards in the post Five Product Classification Standards.
The importance of having a viable Product Information Management (PIM) solution has become well understood for companies who participates in supply chains.
The next step towards excellence in PIM is to handle product information in close collaboration with your trading partners. Product Data Lake is the solution for that. Here upstream providers of product information (manufacturers and upstream distributors) and downstream receivers of product information (downstream distributors and retailers) connect their choice of in-house PIM solution or other product master data solution as PLM (Product Lifecycle Management) or ERP.
The PIM-2-PIM solution resembles a social network where you request and accept partnerships with your trading partners from the real world.
After connecting the next to set up is how your product attributes and digital asset types links with the one used by your trading partner. In Product Data Lake we encompass the use of these different scenarios (in prioritized order):
- You and your trading partner uses the same standard in the same version
- You and your trading partners uses the same standard in different versions
- You and your trading partner uses different standards
- You and/or your trading partners don’t use a public standard
Read more about that and the needed data governance in the post Approaches to Sharing Product Information in Business Ecosystems.
Then it is time to link your common products. This can be done automatically if you both use a GTIN (or the older implementations as EAN number or UPC) as explained in the post Connecting Product Information. Alternatively, model numbers can be used for matching or, as a last option, the linking can be done in the interactive user interface.
Now you and your trading partner are set to start automating the process of sharing product information. In Product Data Lake upstream providers of product information can push new products, attribute values and digital assets from the in-house PIM solution to a hot folder, where from the information is uploaded by Product Data Lake. Downstream receivers can set up pull requests, where the linked product information is downloaded, so it is ready to be consumed by the in-house PIM solution.
This process can now be repeated with all your other trading partners, where you reuse the elements that are common between trading partners and build new linking where required.
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.
There is a game called Chinese Whispers or Broken Telephone or some other names. In that game, one person whispers a message to another person. The message is passed through a line of people until the last player announces the message to the entire group. At that point the message is often quite different or very shortened. The reasons for that is human unreliability including how we put our own perceptions and filters into a message.
When working with data quality you often see the same phenomenon when data is passed through a chain. One area I have observed in recent years is within Product Information Management (PIM). Here the chain is not just the data chain within a given company but the whole data chain in ecosystems of manufacturers, distributors, retailers and end users.
While Product Information Management (PIM) solutions and Product Master Data Management (Product MDM) solutions – if there is a difference – address the issues within a given company, we haven’t seen adequate solutions for solving the problem in the exchange zones between trading partners.
From what I have seen the solutions that upstream providers of product data work with and the solutions that downstream receivers of product data work with will not go well together.
Consequently, I am right now working with a solution to end Chinese whispers in product data supply chains. Check out the Product Data Lake.