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 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 syndication 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 special products 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 products where product information is needed when the surrounding processes should be automated.

At 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 Product Data Push site.

Materials

New Routes for Products. New Routes for Product Information

One of the news this week was that Maersk for the first time is taking a large container ship from East Asia to Europe using a Northern Route through the Arctic waters as told in this Financial Times article.

Arctic route

The purpose of this trip is to explore the possibility of avoiding the longer Southern Route including shoehorning the sea traffic through the narrow Suez Canal. A similar opportunity exists around North America as an alternative to going through The Panama Canal.

Similar to moving products and finding new routes for that we may also explore new routes when it comes to moving information about products. Until now the possibilities, besides cumbersome exchange of spreadsheets, have been to shoehorn product information from the manufacturer into a consensus-based data portal or data pool from where the merchant can fetch the information in accurate the same shape as his competitors does.

At Product Data Lake we have explored shorter, more agile and diverse new routes for that. We call it Product Data Syndication Freedom.

Product Data Syndication Freedom

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 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.

As a merchant you will have hundreds of suppliers 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 manufacturer push product information using your data standards and your preferred exchange method and letting you as a merchant pull product information using your data standards and your preferred exchange method.

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

Ecosystem Wide Product Information Management

The concept of doing Master Data Management (MDM) not only enterprise wide but ecosystem wide was examined in the post Ecosystem Wide MDM.

As mentioned, product master data is an obvious domain where business outcomes may occur first when stretching your digital transformation to encompass business ecosystems.

The figure below shows the core delegates in the ecosystem wide Product Information Management (PIM) landscape we support at Product Data Lake:

Ecosystem Wide PIM.png

Your enterprise is in the centre. You may have or need an in-house PIM solution where you manipulate and make product information more competitive as elaborated in the post Using Internal and External Product Information to Win.

At Product Data Lake we collaborate with providers of Artificial Intelligence (AI) capabilities and similar technologies in order to improve data quality and analyse product information.

As shown in the top, there may be a relevant data pool with a consensus structure for your industry available, where you exchange some of product information with trading partners. At Product Data Lake we embrace that scenario with our reservoir concept.

Else, you will need to make partnerships with individual trading partners. At Product Data Lake we make that happen with a win-win approach. This means, that providers can push their product information in a uniform way with the structure and with the taxonomy they have. Receivers can pull the product information in a uniform way with the structure and with the taxonomy they have. This product data syndication concept is outlined in the post Sell more. Reduce costs.

Product Data Lake Version 1.7 is Live

Win-Win

The good thing about providing Software-as-a-Service is that you do not have to ship the software to all your users and the good thing about using Software-as-a-Service is that program updates are immediately available to the users without that an IT department has to schedule, plan, test and go live with a new version of an application.  This is also true for Product Data Lake, the cloud service also being a win-win application by providing business benefits to both manufacturers and merchants of goods.

Using Application Programming Interfaces (APIs)

Already existing means to feed to and consume product information from Product Data Lake include FTP file drops, traditional file upload from your desktop or network drives or actually entering data into Product Data Lake. With version 1.7, that went live this week, you can now also use our APIs for system to system data exchange by both pushing (put) data into the lake and pulling (get) data from the lake.

Get the Overview

Get the full Product Data Lake Overview here (opens a PDF file).

Get

What is Interenterprise Data Sharing?

The term “Interenterprise Data Sharing” has been used a couple of times by Gartner, the analyst firm, during the last two decades.

Lately it has been part of the picturing in conjunction with a recent research document with the title Fundamentals for Data Integration Initiatives.

Data Integration.png
Source: Gartner Inc with red ovals added

The term was also used back in 2001 in the piece about that Data Ownership Extends Outside the Enterprise. Here on the blog it was included in the title of the post about Interenterprise Data Sharing and the 2016 Data Quality Magic Quadrant.

In my eyes interenterprise data sharing is closely related to how you can achieve business benefits from taking part in the ecosystem flavor of a digital business platform. Some of the data types where we will see such business ecosystem platform flourish will be around sharing product model master data and data about and coming from things related to the Internet of Things (IoT) theme. This is further explained in the blog page about Master Data Share.

Seven Flavors of MDM

Master Data Management (MDM) can take many forms. An exciting side of being involved in MDM implementations is that every implementation is a little bit different which also makes room for a lot of different technology options. There is no best MDM solution out there. There are a lot of options where some will be the best fit for a given MDM implementation.

The available solutions also change over the years – typically by spreading to cover more land in the MDM space.

In the following I will shortly introduce the basic stuff with seven flavours of MDM. A given MDM implementation will typically be focused on one of these flavours with some elements of the other flavors and a given piece of technology will have an origin in one of these flavours and in more or less degree encompass some more flavors.

7 flavours

The traditional MDM platform

A traditional MDM solution is a hub for master data aiming at delivering a single source of truth (or trust) for master data within a given organization either enterprise wide or within a portion of an enterprise. The first MDM solutions were aimed at Customer Data Integration (CDI), because having multiple and inconsistent data stores for customer data with varying data quality is a well-known pain point almost everywhere. Besides that, similar pain points exist around vendor data and other party roles, product data, assets, locations and other master data domains and dedicated solutions for that are available.

Product Information Management (PIM)

Special breed of solutions for Product Information Management aimed at having consistent product specifications across the enterprise to be published in multiple sales channels have been around for years and we have seen a continuously integration of the market for such solutions into the traditional MDM space as many of these solutions have morphed into being a kind of MDM solution.

Digital Asset Management (DAM)

Not at least in relation to PIM we have a distinct discipline around handling digital assets as text documents, audio files, video and other rich media data that are different from the structured and granular data we can manage in data models in common database technologies. A post on this blog examines How MDM, PIM and DAM Stick Together.

Big Data Integration

The rise of big data is having a considerable influence on how MDM solutions will look like in the future. You may handle big data directly inside MDM og link to big data outside MDM as told in the post about The Intersection of MDM and Big Data.

Application Data Management (ADM)

Another area where you have to decide where master data stops and handling other data starts is when it comes to transactional data and other forms data handled in dedicated applications as ERP, CRM, PLM (Product Lifecycle Management) and plenty of other industry specific applications. This conundrum was touched in a recent post called MDM vs ADM.

Multi-Domain MDM

Many MDM implementations focus on a single master data domain as customer, vendor or product or you see MDM programs that have a multi-domain vision, overall project management but quite separate tracks for each domain. We have though seen many technology vendors preparing for the multi-domain future either by:

  • Being born in the multi-domain age as for example Semarchy
  • Acquiring the stuff as for example Informatica and IBM
  • Extend from PIM as for example Riversand and Stibo Systems

MDM in the cloud

MDM follows the source applications up into the cloud. New MDM solutions naturally come as a cloud solution. The traditional vendors introduce cloud alternatives to or based on their proven on-promise solutions. There is only one direction here: More and more cloud MDM – also as customer as business partner engagement will take place in the cloud.

Ecosystem wide MDM

Doing MDM enterprise wide is hard enough. But it does not stop there. Increasingly every organization will be an integrated part of a business ecosystem where collaboration with business partners will be a part of digitalization and thus we will have a need for working on the same foundation around master data as reported in the post Ecosystem Wide MDM.

Ecosystem Wide MDM

Doing Master Data Management (MDM) enterprise wide is hard enough. The ability to control master data across your organization is essential to enable digitalization initiatives and ensure the competitiveness of your organization in the future.

But it does not stop there. Increasingly every organization will be an integrated part of a business ecosystem where collaboration with business partners will be a part of digitalization and thus we will have a need for working on the same foundation around master data.

The different master data domains will have different roles to play in such endeavors. Party master will be shared in some degree but there are both competitive factors, data protection and privacy factors to be observed as well. However, privacy regulations as GDPR article 20 on data portability will make data sharing a must too.

MDM Ecosystem

Product master data – or product information if you like – is an obvious master data domain where you can gain business benefits from extending master data management to be ecosystem wide. This includes:

  • Working with the same product classifications or being able to continuously map between different classifications used by trading partners
  • Utilizing the same attribute definitions (metadata around products) or being able to continuously map between different attribute taxonomies in use by trading partners
  • Sharing data on product relationships (available accessories, relevant spare parts, updated succession for products, cross-sell information and up-sell opportunities)
  • Having access to latest versions of digital assets (text, audio, video) associated with products

The concept of ecosystem wide Multi-Domain MDM is explored further is the article about Master Data Share.

(PS: Ecosystem wide MDM is coined by Gartner, the analyst firm, as multienterprise MDM).

Product Information on Demand

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.

Product Data Lake