PIM vs. MDM – 10 Key Pointers to Help You Decide

A single data repository, integrated data applications, one view of information, data governance, operational efficiency, automation, and an omnichannel customer experience: These all sound related to both product information management (PIM) and master data management (MDM) to you? And thus useful for your business? Then you’re not alone! For a lot of decision-makers, a cloud of confusion often hangs over what’s the difference between the two.

The truth is: There are wide variations between PIM and MDM regarding the purposes they serve and their advantages to fit the needs and aspirations of businesses. Here’s a 10-point attempt at untangling the puzzle by addressing the timeless PIM vs. MDM question.

What is Product Information Management (PIM), but not MDM?

PIM, as the name suggests, is a business application to manage product information. Its job is to gather information from every possible data source that stores product information. It serves to consolidate, enrich, and turn this product information into accurate, use-worthy, consistent, and complete datasets. A PIM is mainly required for the marketing and selling of products on enterprise sales channels. Typically, it is needed by manufacturers, retailers, CPG businesses, and distributors. PIM also facilitates collaboration across functions, while streamlining critical workflows.

Needless to say, product information can be as wide-ranging as:

• product SKUs (consisting of size, color, model, style, etc.)
• technical specifications (in case of automobile parts, medical equipment, computer hardware, etc.)
• translations
• information on the product’s lifecycle
• details provided by suppliers
• metadata
• price
• labels
• and lot more … 

To manage this product information, a PIM is needed, and not a master data management (MDM) platform. MDM covers a much broader range of deployment areas. It centralizes all enterprise data of customers, locations, suppliers, financials, and even product information. 

Main Motive to use PIM and not MDM: catching up with the extraordinary growth in omnichannel selling and speeding up the time-to-market. A PIM has the ability to scale and syndicate product information quickly and simultaneously to various customer touchpoints. PIM can carry out product customization on a global level, optimize efficiency while keeping a laser-sharp focus on improving the customer experience. 

What is Master data management (MDM), but not PIM?

To put it plainly, MDM is for company-wide data what PIM is for product data. But MDM’s ambit is much broader than that. It is an IT-led initiative that focuses on centralizing all enterprise data entities in a “golden record” to make it consistently available across the enterprise. Master data refers to the essential business information associated with the analytical and transactional operations within an enterprise. Master data points to the business-oriented properties of data objects used in applications across the enterprise alongside their connected attributes, metadata, roles, associations, taxonomies, and descriptions.

MDM involves technologies, applications, business clients, partners, and stakeholders. It cleans up, centralizes, and syncs corporate master data to execute processes, workflows, and operations. An essential piece of MDM is master data governance, which is steered by the enterprise Data Governance Council. And it charts out data definitions, access rights, controls, implementation policies, and procedures. 

Main Motive to use MDM and not PIM: A PIM cannot do what MDM can. Master data management system aims to improve enterprise business intelligence, speed up decision making, boost relations with customers, enhance agility and outcomes of business processes, build operational efficiencies, and provide smarter data governance. All this is done for the larger purpose of enterprise growth, which goes way beyond the scope of PIM.

What is Product MDM? How does it differ from PIM?

Whenever product data is managed inside of an MDM system, as all other essential business data, it is referred to as Product MDM. The system serves the primary purpose of developing associations among customers, employees, products, vendors, locations, and households in order to fulfill the analytical and operational needs of the business. The goal then is to get real-time knowledge by associating product data to several other data domains in many hierarchies, apart from product-to-product associations. 
In other words, the scope of Product MDM is broader than supporting a few departments such as sales and marketing. Its need often arises from several different domains from inside the enterprise. It supports the operational, inventory forecasting, and supply chain side of the business. The request for a product MDM is mostly raised by the IT when product data discrepancies are flagged by various departments.  

How PIM is different from a Product MDM: Ideally, an enterprise PIM system is built upon a data management platform for collaboration on product content. It has predefined features like data modeling, workflow management, data semantics, and data integration & delivery, along with a user-friendly UI. Its benefits include consolidating data from silos, digitalization, automation, omnichannel enablement. And it is aimed at decreasing time-to-market, building engaging product experiences, and revenue growth. 

Can PIM and Product MDM go hand in hand?
Organizations can go for both systems if their use case allows for it. When combined, they can unlock an entire ecosystem. PIM can consolidate product data for distribution to several customer touchpoints, while product master data can be used to develop relationships among customers, products, and vendors. The latter can also be sent to business apps. Product MDM will bring along advantages like better reporting, analytics, and forecasting for supply chain efficiency.  

It must always be kept in mind that fulfilling the need for a PIM with a Product MDM may not be the right thing to do, as some product data will always remain outside of the Product MDM. This means, it would have to be fetched from other systems every time. Hence, it wouldn’t sufficiently meet the requirements of the sales and marketing departments, where speed, accuracy, and control over product data is non-negotiable. 

Common misconceptions regarding PIM and MDM

1. MDM covers product data, so there’s no need for PIM.
   Yes, MDM covers product data, but as explained above, not in the same in-depth way that PIM does, which creates a golden repository exclusively for product data. 
    
2. If you have a PIM, you don’t need an MDM.
   MDM fulfills a different purpose than PIM. While PIM is solely for product information, MDM’s scope covers customers, vendors, distributors, partners, products, suppliers, locations as well as employees’ data. 
    
3. If you have an ERP (Enterprise Resource Planning) software, why do you need a PIM or MDM?
   An ERP software is usually a centralized repository for a vast amount of financial, back-office, and front-office business data. It caters to the needs of a variety of systems like customer relationship management (CRM), business intelligence (BI), supply chain management (SCM), and more. Its purpose, however, is very different from that of MDM and PIM, and it also lacks their capabilities. For instance, ERPs are not designed for enterprise master data governance, data workflows, data enrichment, or for providing up-to-date data at all times. It also cannot store digital assets. 
    
4. Every MDM is a multi-domain, multi-vector system.
   ‘MDM,’ which in common parlance is often used interchangeably with multi-domain MDM, can turn out to be a single-domain MDM. Single-domain MDM platforms emphasize product or customer data and are programmed to collect data for one domain only. They have predefined data-model templates and other domain-specific features. Getting separate single-domain MDMs for customer and product data can not only become very costly. It can also threaten achieving the very objectives of the organization, such as data integration, data governance, and data enrichment. 
   
   Only a multi-domain MDM helps organizations attain the appropriate business intelligence for sound decision-making, nudging them towards becoming a digital business. A multi-vector MDM is the one that is suitable for any organizational structure, industry, or implementation style.
    
5. MDM implementation is a one-time thing. Once done, chapter closed!
   MDM and even PIM must be understood as a business philosophy. They thrive on accommodating new processes, business requirements, mergers, and acquisitions. Sometimes even a new business scope emerges. However, the basics always remain the same. MDM must – at all times – facilitate cross-departmental, cross-functional collaboration and analysis. It must always promote the common good of the enterprise, which is accepted across the board.
   
   

Why do you need a PIM solution? vs. Why do you need an MDM solution?

The fundamental difference between a PIM solution and an MDM solution lies in the needs that they meet. 

A PIM solution is typically needed to deal with product data accuracy issues. To live up to the requirements of an explosion of customer touchpoints, enterprises strive for a faster time-to-market, omnichannel enablement, quick new product introductions, faster growth, and a higher ROI. PIM is needed when traditional product data management systems can’t cope with the rising number of product SKUs. And when data collection and collaboration with vendors and suppliers face setbacks due to dependence on manual means of managing data. 

An MDM solution caters to the operational and analytical needs and requirements of an enterprise. Operational needs have to do with the integration of technologies that improve enterprise-wide efficiency, streamline supply chain operations, and boost processes. Analytical needs refer to better business intelligence, forecasting, analysis, and insights. Of course, both analytical and operational requirements aim towards decreasing the time-to-market, reduce costs, achieve a higher ROI, and improve the customer experience.     

How do you decide if you need a PIM or MDM for your business?

It entirely depends on your use case; you will need to analyze it thoroughly. Some examples:

1. You need a Product Catalog. 
   This would fall under the need for a PIM system, as a centralized product data repository is fundamental to product catalog management needs. A PIM offers your staff scalable, real-time access for creating catalogs. It would help you decrease your time-to-market, simplify management of your product attributes, enable quick updates, and offer a single product data view.  
    
2. You need better business analytics and reporting.
   An MDM is what you need here. It can offer advanced analytics and insights for managing master data to your best advantage. It will aid business scenario predictions, reporting, and improved resource management. And thus, it also improves planning, which will further encourage better business growth.
    
3. You are expanding into a new location.
   A PIM would be the right fit in this case. Because what you’ll need are ready-to-use catalogs, marketing and sales collaterals as well as digital assets in newer languages. A centralized PIM helps you not waste any time on launching products in multiple regions, marketplaces, and storefronts.
    
4. You want to establish policies and guidelines for data usage.
   That’s a clear-cut case for MDM, as you’ll require data governance measures to decide roles, responsibilities, access rights, stakeholders, data ownership, clearances, and controls across the organization.
    
5. You want to sell more of your product – faster.
   A definite case for PIM, as it will enable omnichannel engagement for superior buying experiences, and help you maintain continuity across all customer touchpoints. Besides, PIM helps you quickly create price rules (having conditions such as discounts) for specific markets, time-periods, and locations.
   
   

VII. How different are Product Data Management (PDM) and Digital Asset Management (DAM) from PIM, MDM?

Although sometimes used interchangeably with PIM, Product Data Management (PDM) fulfills a very distinct need for enterprises. It is used to manage computer-aided design (CAD) data, technical specifications, models, manufacturing instructions, drawings, engineering documentation, and information on parts in one specific location. In other words, it is mostly used by engineering teams to revise, track, collaborate, manage orders, or generate bills of materials. A PDM is considered a subcategory of Product Lifecycle Management (PLM).    

A Digital Asset Management (DAM) platform centralizes all sorts of product media assets, including images, videos, graphics, music, videos, animations, podcasts, and other media content. It falls under the ambit of PIM.

Also read-

PIM strategy vs. MDM strategy – an overview

PIM strategy

• The idea is to achieve product information excellence to boost customer experience, facilitate growth, grow market share, speed up the time-to-market and thus increase revenue.
• It must start with collecting, consolidating, and enriching data.  
• Automation must replace manual work to boost efficiency.
• Interoperability issues must be fixed with legacy or homegrown software using APIs.
• Enterprise omnichannel needs must be met to provide a seamless customer experience on growing output channels.
• The idea is not just to support marketing and sales, but also suppliers, procurement, the R&D department and customer care, as well as offer customers the best possible experience.

MDM strategy

• The idea is first to have a vision around MDM. 
• Secure buy-in from the top C-suite executives, decision-makers, and stakeholders.
• Institutionalize this vision across the board and identify what constitutes master data for your organization. 
• Tie your key business objectives to your vision for desired business growth.
• Come to a census about attributes regarding customers, assets, employees, suppliers, products, services, and locations.
• A collaboration-led approach where breaking up information silos, rejecting legacy practices, and creating and maintaining high-quality data, is needed.
• Assess your technological requirements.
• Finally, focus on your analytical and/or operational MDM needs.
  
  

PIM Implementation vs. MDM Implementation – the main differences

PIM Implementation

• Assess the existing product data management lifecycle.
• Retrieve and consolidate data into a single repository.
• Prioritize output channels essential for your business, whether that’s physical stores, websites, call centers, marketplaces, mobile devices, point of sale systems, or social platforms.
• Create the right data model for scalability and growth.
• Develop business-centric workflows and functions.
• Create user interfaces for data import and export with various source systems.
• Leverage API-led connectivity to integrate with various existing systems.

MDM Implementation

• First, you must decide whether you want to go for a single domain or multi-domain MDM depending on what your priorities are.
• Depending on what’s your use case, decide on operational and/or analytical MDM.
• You may adopt any one of the implementation styles suggested by Gartner:
  • Consolidation 
  • Registry 
  • Co-existence 
  • Centralized

*For more information, read about MDM implementation styles in detail. 

PIM/MDM — Proprietary vs. Open Source vs. Open Core

If you’re scouting for PIM/MDM systems for your enterprise, Pimcore can be a viable option for you!

Pimcore comes with features such as Data Modeling, Data Quality, Data Management, Data Integration, and Workflow Management. No matter what your PIM/MDM needs are, Pimcore can consolidate and integrate any size, any type, and any format of digital data for organizations of any size or belonging to any industry. 

Pimcore has helped scores of clients by:

• significantly improving data quality 
• greatly decreasing time-to-market 
• enhancing the customer experience 
• accelerating new product introduction 
• reducing manual effort by automating workflows
• boosting operational efficiency 
• ameliorating accessibility of assets across countries 
• simplifying the management of assets globally
• increasing sales and marketing performance 
• offering greater flexibility to internal teams
• and much more…