How Manufacturers of Building Materials Can Improve Product Information Efficiency

Building materials is a very diverse product group. Even within a manufacturing enterprise there may be considerable variances in what kind of product information you need for different product groups. If production is taking place on plants around the world, then local demands and cultural differences is another source of diversity in how product information is handled.

In many cases building materials are not sold directly to end users, but are forwarded in the supply chain to re-sellers being distributors/wholesalers, merchants/dealers and marketplaces. These trading partners each have their range of products and specific requirements for product information which makes it very hard for you as the manufacturer to prepare product information that fits all.

The IT enabled discipline aimed at solving such challenges is called product data syndication. There are namely these three kinds of product data syndication relevant to manufacturers:

  • Enterprise wide product data sharing aiming at linking, transforming and consolidating product information created by various business units and production sites around the world. The goal is to have consistent, accurate and timely information ending up in one place, often being an in-house Product Information Management (PIM) or Master Data Management (MDM) solution.
  • Ecosystem wide product data syndication push aiming at providing product information to re-sellers in a uniform way. On the other hand, it should be possible for the diverse crowd of re-sellers to pull that information adhering to each one’s requirements for format, completeness and conformity at a certain time.
  • Ecosystem wide product data syndication pull also in many cases applies to a manufacturer. It is not unusual that a manufacturer complements the own produced product range with trading goods supplied from other manufacturers, where product information must be provided by those. In addition to that manufacturers buys raw materials, spare parts for machinery and other MRO (Maintenance, Repair, Operation) products where product information is needed when the surrounding processes must be automated.

Through emerging technology in Product Data Lake we offer a solution to these challenges. We emphasize on these capabilities:

  • Product Data Quality aiming at improvements of completeness of product data, as well as the accuracy, timeliness, consistency and conformity of the product information shared with trading partners and end users.
  • Product Data Syndication Freedom, as the solution is suited for consolidating enterprise wide diversities and pushing information to trading partners in a uniform way while making it possible for trading partners to pull the product information in their many ways.

Learn more about the solution and the benefits for manufacturers of building materials on the About Product Data Push page.

Materials

Product Data Syndication Freedom for Manufacturers

When working with product data syndication in supply chains the big pain is that data standards in use and the preferred exchange methods differ between supply chain participants.

As a manufacturer or brand owner you will have hundreds of re-sellers who probably have data standards different from you and most likely wants to exchange data in a different way than you do.

The aim of Product Data Lake is to take that pain away from both the manufacturer side and the merchant side. We offer product data syndication freedom by letting you as a manufacturer or brand owner push product information using your data standards and your preferred exchange method and letting your merchants pull product information using their data standards and their preferred exchange method.

This concept will free you from applying many different solutions to providing product information to your re-sellers. You will avoid errors. You will be able to automate the processes and you will be easy to do business with in the eyes of your trading partners.

The people who will use your products want to get complete product information when making the buying decision wherever they are in the supply chain.

Product Data SyndicationIf you want to know more: Get in contact here:

 

 

How to end the standoff with your merchants

Who should have the burden of lifting product information as you as a manufacturer have it to the way it is presented at the digital point-of-sales provided by your merchants? Often this seems to be stalled in a standoff as described in the post Passive vs Active Product Information Exchange.

Using spreadsheets

Most companies participating in cross company supply chains use spreadsheets for exchanging product data. Doing that is very cumbersome, error-prone and does in most cases not provide the needed data quality for providing self-service ready product data to your re-sellers.

The most common way of using spreadsheets for this is that a merchant gives each of his suppliers a spreadsheet with columns of attributes based on the merchants taxonomy to be filled out. As a supplier, you will typically be tasked with filling in a different spreadsheet from each of your downstream re-seller. This is very inefficient seen from a supplier perspective.

Deploying customer (and supplier) portals for product information

There is a tendency when deploying Product Information Management (PIM) solutions, that you may want to add a portal for your trading partners:

  • If you are a manufacturer, you could have a customer portal where your downstream re-sellers can fetch the nicely arranged product information that is the result of your PIM implementation.
  • If you are a merchant, you could have a supplier portal where your upstream suppliers can deliver their information nicely arranged according to your product information standards in your PIM implementation.

This is a death trap for both manufacturers and merchants, because:

  • As a trading manufacturer and merchant, you probably follow different standards, so one must obey to the other. The result is that one side will have a lot of manual and costly work to do to obey the strongest trading partner. Only a few will be the strongest all time.
  • If all manufacturers have a customer portal and all merchants have a supplier portal everyone will be waiting for the other and no product information will flow in the supply chains.

Standoff as upstream

The solution

At Product Data Lake we offer manufacturers and merchants an honorable way out of this standoff by offering Product Data Syndication Freedom.

 

How Manufacturers Can Sell More and Reduce Costs

In a data driven world being the best at sharing product information with your trading partners is a winning formula.

You will sell more if your re-sellers will have the most complete, accurate and timely product information about your products in front of their customers.

You will reduce costs if you can push your product information in one uniform way and let your re-sellers pull it in their many ways. This will free you from applying many different solutions to providing product information to your re-sellers. You will avoid errors and you will be able to automate the processes.

Our solution using emerging technologies within Product Data Lake will make you “easy to do business with” in the eyes of your re-sellers and make your product information a powerful weapon.

The people who will use your products want to get complete product information when making the buying decision wherever they are in the supply chain.

Would you like to know more? Get in contact here:

Upstream sell more reduce costs

Automatic for the People

R.E.M._-_Automatic_for_the_PeopleThe 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.

Passive vs Active Product Information Exchange

Product information is the kind of data that usually flows cross company. The most common routes start with that the hard facts about a product originates at the manufacturer. Then the information may be used on the brands own website, propagated to a marketplace (online shop-in-shop) and also propagated downstream to distributors and retailers.

The challenge to the manufacturer is that this represent many different ways of providing product information, not at least when it comes to distributors and retailers, 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, the distributors and retailers, we 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 distributor/retailer 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.

Passive vs ActiveThis 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 seen as a company being easy to do business with, which eventually will decide how big you will stay.

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.

Five Product Classification Standards

When working with Product Master Data Management (MDM) and Product Information Management (PIM) one important facet is classification of products. You can use your own internal classification(s), being product grouping and hierarchy management, within your organization and/or you can use one or several external classification standards.

Five External Standards

Some of the external standards I have come across are:

UNSPSC

The United Nations Standard Products and Services Code® (UNSPSC®), managed by GS1 US™ for the UN Development Programme (UNDP), is an open, global, multi-sector standard for classification of products and services. This standard is often used in public tenders and at some marketplaces.

GPC

GS1 has created a separate standard classification named GPC (Global Product Classification) within its network synchronization called the Global Data Synchronization Network (GDSN).

Commodity Codes / Harmonized System (HS) Codes

Commodity codes, lately being worldwide harmonized and harmonised, represent the key classifier in international trade. They determine customs duties, import and export rules and restrictions as well as documentation requirements. National statistical bureaus may require these codes from businesses doing foreign trade.

eClass

eCl@ss is a cross-industry product data standard for classification and description of products and services emphasizing on being a ISO/IEC compliant industry standard nationally and internationally. The classification guides the eCl@ss standard for product attributes (in eClass called properties) that are needed for a product with a given classification.

ETIM

ETIM develops and manages a worldwide uniform classification for technical products. This classification guides the ETIM standard for product attributes (in ETIM called features) that are needed for a product with a given classification.

pdl-whyThe Competition and The Neutral Hub

If you click on the links to some of these standards you may notice that they are actually competing against each other in the way they represent themselves.

At Product Data Lake we are the neutral hub in the middle of everyone. We cover your internal grouping and tagging to any external standard. Our roadmap includes more close integration to the various external standards embracing both product classification and product attribute requirements in multiple languages where provided. We do that with the aim of letting you exchange product information with your trading partners, who probably do the classification differently from you.

What a PIM-2-PIM Solution Looks Like

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.

pdl-how-1

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.

pdl-how-2

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.

pdl-how-3

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.

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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.

pdl-how-5

Self-service Ready Product Data

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:

Product Information 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.

Chinese Whispers and Data Quality

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.

Broken data supply chain

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.