In today’s fast paced business environment there is no time, money, or people to waste on reinventing anything you’ve already invented. Whether it is a US-based engineer looking for relevant CAD files created by a colleague in India, a product marketer hunting for material for a promotional campaign, or a customer browsing your online catalog – all the information about the products you sell should be readily available to whoever needs it, when and where they need it.
Product Data Management (PDM) is the process of sourcing and organizing data about your products—accurate and complete descriptions, technical specifications, images, related content, and more.
Within an organization there may be multiple systems associated with this process including ERP, MDM, PLM, PIM, and more. Too frequently, these systems are disconnected, slowing down the flow of information. Top performing brands understand that within these systems resides their most valuable company assets – the information about their products and the corporate knowledge related to their inner workings. To be competitive they find ways to leverage that information and make it work harder by investing in the information architecture that support seamless processes.
Keep reading to learn more about:
- The Definition of PDM
- Metadata Management
- Data Governance
- Product Data Management Services
- Get Ready For Digital Transformation
What is Product Data Management?
PDM software is closely related to Product Lifecycle Management (PLM) software and some consider PDM to be a subset of PLM. Some providers of PDM software include Dassault Systèmes, Synergis, and Stratasys. Other providers include PDM capabilities within PLM tools, such as AutoDesk. A PDM system is a beneficial tool that can help you create better designs, reduce errors and costs, and use resources effectively. It helps ensure there is a common understanding about a product through its lifecycle.
PDM also relates to master data management (MDM), which controls the usage of information throughout the enterprise. One of the main applications of MDM is in supporting a 360-degree-view of the customer as part of a strategic plan. This view provides insight into what customers are buying, which channels they’re purchasing from, and their household or relationships with other customers and prospects.
Another aspect of the PDM ecosystem is Product Information Management (PIM) which focuses on managing the product information needed to market and sell products through distribution channels. Providers of PIM software include Informatica, Agility Multichannel, Salsify, and Enterworks. Product information that is used in these distribution channels
What is Metadata Management?
Metadata is “data about data”. Metadata allows you to describe a digital asset in a predefined and structured way.
There are three main types of metadata:
- Descriptive metadata: Descriptive metadata describes a resource for purposes, such as discovery and identification. For example, the title, abstract, author and keywords.
- Structural metadata: Indicates how compound objects are put together like how pages are ordered to form chapters.
- Administrative metadata: Provides information to help manage a resource, such as when and how it was created, file type and other technical information, and who can access it.
In a PIM system this product data metadata is referred to as attributes. Product data attributes are commonly exposed on web sites in the form of search filters. If you are looking for a lawn mower, the filters offered might include power type, cutting width, and engine make, among others. This metadata also enables associations with other products such as replacement parts or accessories. The same principles apply for internal knowledgebases when the item being searched for is a statement of work or a CAD drawing.
Problems will arise when product data is incomplete or inconsistent. If your customer can’t find the product he is looking for because it isn’t coming up in search results, he may go to your competitor. With the right product data management process in place you ensure that your products are easily found, descriptions are always complete and accurate, images display consistently, related content helps guide buying decisions, and suggestions are always relevant.
What is Data Governance?
These days, no matter what industry you operate in, your competitive advantage depends on the quality of the data that is flowing through your information systems. Many companies are undergoing transformational initiatives because their customers are demanding it. B2B customers who have grown accustomed to buying on Amazon now expect the same level of shopping ease when buying for their company.
What is often overlooked is the fact that a digital transformation is not just new technology -- it is first and foremost a data transformation. If your data is wrong, incomplete, and/or disconnected from other systems it won't matter what technology you install. You need a plan for cleaning, harmonizing, and processing all the various information/data sources that will power your transformation.
But it isn't enough to do it and call it done. Ongoing oversight and governance are crucial to long term success. The challenge is that governance, while important, can seem like mundane work. But, it is possible to build a sustainable governance program that delivers results over the long term by using a metrics-driven approach.
Governance is different for every company, but there are some common steps to creating a strong data governance program:
- Establish a governance team. Data governance is a team effort from all sides of the business. Assign various roles, including the taxonomist, data steward, and product manager, from different departments to ensure organization-wide adoption.
- Create a list of enterprise processes. No data governance program will succeed without agreed-upon and thoughtful processes for handling institutional data.
- Identify metrics to measure success. The goals you set will determine the right performance metrics and guide the selection of analytics.
- Develop a RACI (Responsible, Accountable, Consulted, Informed) chart. The RACI chart will help identify who has what role for each process. They are Responsible, Accountable, Consulted, and Informed.
- Design process maps. Process maps lay out each task in the data governance process, who owns them, and what systems to use—all in a visual format.
Data governance means better, cleaner and more efficient data—which means better analytics, business decisions, and business outcomes.
Product Data Management Services
Product data management services can help your organization succeed and win more business by ensuring your data is well prepared to support your business goals.
Earley Information Science’s approach to product data management can prepare your data for any technology by making it more adaptable, intuitive, findable and usable. Data can be messy, information can be incomplete, and errors will be found. However, a strategic approach to product data management will help your organization fix all of that.
We help at key points of the product data journey
- We bring behind-the-scenes order to your product through taxonomy and attribute design so you can intelligently design digital experiences that reflect the wants and needs of your customers. We help you personalize their experience by tuning attributes to delight them no matter the season, channel, device or regional market.
- A PIM system connects your internal and external product data sources to your various digital sales and marketing channels. Choosing the right PIM system is a critical decision because it will help you get your product data right and - just as important - keep it right. This is a decision you want to get right and we can help you select the right PIM software.
- We help make your online product catalog become fast and easy to navigate through product catalog optimization. Each item must be findable in onsite search as well as optimized for Internet search engines. With a well organized taxonomy and a rational top down attribute inheritance model, you can get there.
This case study for a multinational conglomerate is a perfect example of how EIS's approach has been successful.
Are You Ready For a Digital Transformation?
Getting your product data management in order is one important step to an overarching digital transformation. Do you have a roadmap to guide your digital transformation? Does it lay a solid foundation for the successful transition to your vision of a future digital business?
If you want to see success in your company’s product data management process, download our Digital Transformation Roadmap to get started.