Product information is the data a potential buyer of a product needs to make a purchasing decision. Today purchasing is more and more made by self-services as in e-commerce. The product information is usually obtained through a supply chain between trading partners stretching from the manufacturer to the end merchant.
The most common way of exchanging product information between trading partners is using spreadsheets. Spreadsheets are marvellous, because you can do almost anything you want with them. However, spreadsheets are also horrendous, because you can do almost anything you want with them. Therefore, trading partners are often stuck with manual, cumbersome and error prone processes on both the providing and receiving end.
At Product Data Lake we have developed a new mechanism that enables a whole new process for exchanging product information between trading partners. We have kept the flexibility of spreadsheets when it comes to choosing the data standards on the providing and receiving end but at the same time introduced automation and correctness when it comes to transferring, translating and transforming the data.
When telling about our service I am often asked if we have a nice feature for on-boarding spreadsheets. We don’t. Because the process is designed to omit the spreadsheets and transfer directly from the providers in-house product information data store(s) to the receiving in-house product information data store.
This reminds me of when we talk about using robots to substitute human labor. Then we often think about a machine that looks like a human. But effective industrial robots do not look like humans. They a designed to do a specific process much more effective than a human and will therefore not look like a human. The same is true in digitalization. When we redesign business processes to be much more effective they should not include spreadsheets.
Video on demand has become a popular way to watch television series, films and other entertainment and Netflix is probably the most known brand for delivering that.
The great thing about watching video on demand is that you do not have to enjoy the service at the exact same time as everyone else, as it was the case back in the days when watching TV or going to the movies were the options available.
At Product Data Lake we will bring that convenience to business ecosystems, as the situation today with broadcasting product information in supply chains very much resembles the situation we had before video on demand came around in the TV/Movie world.
As a provider of product information (being a manufacturer or upstream distributor), you will push your product information into Product Data lake, when you have the information available. Moreover, you will only do that once for each product and piece of information. No more coming to each theatre near your audience and extensive reruns of old stuff.
As a receiver of product information (being a downstream distributor, reseller or large end user), you will pull product information when you need it. That will be when you take a new product into your range or do a special product sale as well as when you start to deal with a new piece of information. No more having to be home at a certain time when your supplier does the show or waiting in ages for a rerun when you missed it.
Learn more about how Product Data Lake makes your life in Product Information Management (PIM) easier by following us here on LinkedIn.
When working with Product Information Management (PIM) and not at least with product information exchange between trading partners, I have noticed three major sectors where the requirements and means differs quite a bit.
These sectors are:
- Food, beverage at pharmaceuticals: These are highly regulated sectors where the rules for taxonomy, completeness and exchange formats are advanced. Exchange standards and underpinning services as GS1/GDSN are well penetrated at least for basic data elements among major players. This sector counts for circa 1/6 of the world trade.
- Fashion, books and mainstream electronics: The products within this sector can be described with common accepted taxonomies and do not differ that much though there certainly are room for more common adhered standards in some areas. The trade here is becoming more penetrated by marketplaces with their specific product information requirements. This sector counts for circa 1/6 of the world trade.
- The rest (including building materials, special electronics, machinery, homeware): This is a diverse segment of products groups and the product groups themselves are diverse. The requirements for product information completeness and other data quality dimensions are overwhelming and the choice of standards are many, so most often two trading partners will be on different pages. This sector counts for circa 2/3 of the world trade.
Note: Automotive (vehicles) is a special vertical, where the main products (for example cars) resembles mainstream electronics and all the spare parts resembles special electronics. Some retailers (like department stores) covers all sectors and therefore need hybrid solutions to their product information exchange handling challenges.
The main drivers for better product information handling are compliance – not at least within food, beverage and pharmaceuticals – and self-service purchasing (as in ecommerce), where the latter has raged many years within fashion, books and mainstream electronics and now also is raising in more B2B (business-to-business) biased product groups as building materials, special electronics and machinery.
Learn more about how to tackle these diverse needs in product information exchange in the article and discussion about Product Data Lake.
The term End-to-End is used a lot in marketing jargon. Now, I will jump on that wagon too.
In reality, no solution will be an End-to-End solution for all your business needs. Therefore, my take will merely be to cast some light on an End-to-End need for which there are only very scattered solutions today.
If we look at Product Information Management (PIM) there are many good solutions for taking care of the End-to-End needs within your organisation. The aim is to gather the product information that exist within your organisation in various silos, have one trusted place for all this information and being able to publish this information in a consistent way across all sales channels – the omnichannel theme.
However, product information does in many cases not live just within your organization. In most cases, it lives in a business ecosystem of manufacturers, distributors, merchants and large end users.
Therefore we need an End-to-End solution for product information that encompasses the path from manufacturers over distributors to merchants and large end users and in some cases the way back.
Whether you are a manufacturer, distributor, merchant, large end user or a provider of tools and services for product information you can join the business ecosystem oriented End-to-End solution for product information. Please find some more information about Product Data Lake here.
As a manufacturer, you can find your benefits on the Product Data Push site here.
As a merchant, you can find your benefits on the Product Data Pull site here.
If you are a vendor in the Product Information Management space, you can join forces with us a explained here.
Product Information Management (PIM) is challenged by the fact that product data is the kind of data that usually flows cross company. The most common route starts with that the hard facts about a product originates at the manufacturer. Then the information may be used on the brand’s own website, propagated to a marketplace (online shop-in-shop) and propagated downstream to distributors and merchants.
The challenge to the manufacturer is that this represent many ways of providing product information, not at least when it comes to distributors and merchants, as these will require different structurers and formats using various standards and not being on the same maturity level.
Looking at this from the downstream side as a merchant you have the opposite challenge. Manufacturers provide product information in different structurers and formats using various standards and are not on the same maturity level.
Supply chain participants can challenge this in a passive or an active way. Unfortunately, many have chosen – or are about to choose – the passive way. It goes like this:
- As a manufacturer, we have a product data portal where trading partners who wants to do business with us, who obviously is the best manufacturer in our field, can download the product information we have in our structure and format using the standards we have found best.
- As a merchant we have a supplier product data portal where trading partners who wants to do business with us, the leading player in our field, can upload the product information we for the time being will require in our structure and format using the standard(s) we have found best.
- As a distributor, you could take both these standpoints.
This approach seems to work if you are bigger than your trading partner. And many times, one will be bigger than the other. But unless you are very big, you will in many cases not be the biggest. And in all cases where you are the biggest, you will not be a company being easy to do business with, which eventually will decide how big you will stay.
Using (often local) industry product data hubs is a workaround, but the challenges shines through and often it leads to that everyone will only benefit from what anyone can do and still calls for many touch points when doing business internationally and across several product data groups.
The better way is the active way creating a win-win situation for all trading partners as described in the article about Product Data Lake Business Benefits.
Our February 2018 version of the Product Data Lake cloud service is live. New capabilities include:
- Subscriber clusters
- Put APIs
As a Product Data Lake customer, you can be a subscriber to our public cloud (www.productdatalake.com) or install the Product Data Lake software on your private cloud.
Now there is a hybrid option: Being a member of a subscriber cluster. A subscriber cluster is an option for example for an affiliated group of companies, where you can share product data internally while at the same time you can share product data with trading partners from outside your group using the same account.
Already existing means to feed Product Data Lake include FTP file drops, traditional file upload from your desktop or network drives or actually entering data into Product Data Lake. Now you can also use our APIs for system to system data exchange.
Get the Overview
Get the full Product Data Lake Overview here (opens a PDF file).
Sometimes keeping it simple is the shortcut to getting it all wrong. While I am a believer in mastering all master data domains under the same vision and strategy, there are still best-in-class options when it comes to orchestrating processes and applying technology in the right chunks.
Customer Data Integration (CDI)
A recent post on this blog was called What Happened to CDI? This post examines the two overlapping disciplines Master Data Management (MDM) and Customer Data Integration (CDI). In a comment Jeff Jones argues that MDM vendors have forgotten about proper CDI workflows. Jeff says: “It seems the industry wants to go from Source to Match/Merge, instead of Source to Match/Identify and finally to Merge.” Please find and jump into the discussion here.
Also, this question was touched some years ago in the post The Place for Data Matching in and around MDM.
Product Information Management (PIM)
The product domain within Multi-Domain MDM also holds some risks of forgetting the proper ways of handling product information. In this domain we must also avoid being blinded by the promise of a single source of master data with surrounding processes and applied technology.
There are many end-to-ends to cover properly as exemplified in the post A Different End-to-End Solution for Product Information Management (PIM).
Merchants sells the goods produced by manufacturers. In that game merchants and manufacturers are basically allies. Then of course the merchant’s profit may depend on the margin he can get between the manufacturers price to him and the merchant’s price to his customer. In that game, merchants and manufacturers are kind of enemies.
When it comes to providing product information to the end customers, merchants and manufacturers are allies too. The more complete product information placed in front of the end customer, the better. This is increasingly important today with more and more goods sold in self-service scenarios as in ecommerce.
But again, there seems to be an enemy angle here too. Who should have the burden of lifting product information as the manufacturers have it to the way it is presented at the point-of-sales provided by the merchant? Often this seems to be stalled in a standoff as described in the post Passive vs Active Product Information Exchange.
At Product Data Lake we offer merchants and manufacturers an honorable way out of this standoff:
The title of this blog post is the title of, in my rapid eye movements, one the best albums ever: Automatic for the People by R.E.M., which came out 25 years ago in 1992.
It began in manufacturing
Automation began in the manufacturing industry. Since then automation has been part of most other industries. Not at least within Information Technology, automation is part of the promise in almost every initiative.
When automating stuff, we should always be aware of not just automating old bad processes. To the most extreme, as Michael Hammer said back in 1990: Don’t Automate, Obliterate.
However, some of the most successful companies today are companies born in the information age and delivering services that in a high degree automates processes of value to their customers based on working intensively with information technology.
How can we close the loop and bring that kind of modern automation back to where it began: In the manufacturing industry? The challenges of doing that was examined by Harri Juntunen in a guest blog post called Data Born Companies and the Rest of Us.
IT will come back to manufacturing
In all humbleness we want to be part of that endeavor at Product Data Lake. Therefore, we are setting up a Product Data Push solution for manufacturers, in order to solve one of most severe issues for manufacturers today, being a dysfunctional flow of product information out to whoever is managing the point of sales for the produced goods.
Automation is the end goal. But in order to get started, we accept upload of product information in whatever format, structure and state it is available in. We will then get it in shape to be pulled by retailers, etailers and other trading partners. We will use manual workforce for that and we will use Artificial Intelligence for that too. And in the end, it will be automatic for the people.
In a recent poll on this blog we had this question about how to share product information with trading partners:
As a manufacturer: What is Your Toughest Product Information Sharing Issue?
The result turned out as seen below:
Product information flow in supply chains will typically start with that manufacturers shares the detailed hard facts about products to the benefit of downstream partners as examined in the post Using Internal and External Product Information to Win.
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.
Another obstacle is the lack of a common standard for product information in the business ecosystem where the manufacturer is a part as further examined in the post Product Information Sharing Issue No 2: No Viable Standard.
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.