Why PIM Solutions Fall Short in B2B: Nine Common Challenges

Inflexible data model

💔 Legacy PIM solutions typically underperform when it comes to data model management. This is due to their rigid structures, making critical edits to master attribution hierarchies a convoluted and time-consuming process when substantial data model changes are needed, such as during major transformation initiatives. The lack of ability to make sweeping data model adjustments can ultimately impact product launches, slowing down speed to market.

Inability to manipulate data and manage quality at scale

📉 Most PIMs cannot support data staging, cleansing, or validating data and implementing governance decisions to transform data at scale. While many solutions in the market today claim to offer data quality and change management options, it can require heavy customization and even scripting. This functionality is critical to establishing and maintaining data cleanliness, accuracy, and completeness. Without that ability, most teams will be constrained by manual, "one-off" edits, or have to work in spreadsheets outside of the PIM entirely.

Difficulty implementing product data governance frameworks

📦 This is another common challenge for legacy PIMs. PIM users need functionality for many governance capabilities, such as:

• Managing data changes by assigning and isolating user-specific permissions for attributes, attribute groups and categories
• Enabling team-level permissions, such as a Marketing team, to work together on marketing descriptions and feature bullets, which helps cope with changing team members over time
• Designating attributes to be dispatched to (or hidden from) specific downstream publication targets such as a data sheets, marketing websites, eCommerce platforms or syndication channels

Industry mismatch and technical complexity

👚 The majority of legacy PIMs were born out of the retail sector to handle fast-moving SKUs with light attribution. As a result, many industrial manufacturers who have adopted them received a solution that was not an inherent fit for their sector. Many PIMs are simply not equipped to handle the technical complexity across products required by industrial manufacturers, including normalizing units of measure to specific standards or handling unit conversions.

Requires heavy custom coding and scripting to enable basic functionality

💻 Some PIMs are not user-friendly and come with a heavy reliance on SQL scripting and coding to get simple functions, such as importing and exporting data, to be operational. In addition to their daily roles, many product marketing teams find themselves having to learn how to create scripts to manipulate the data and make it available and consumable for downstream channels, distributors, and other key business partners.

⚙️ Attribution management should be consistent across an enterprise. One critical area that most manufacturers need is integrating technical attribute data directly from Engineering, which is often seen as the point of origination of a part or product. The lifecycle (and, by proxy, the PIM) should be capable of supporting the end-to-end attribution of both parts and products from Engineering through Marketing and eCommerce.

🔎 Searching and filtering is often greatly hindered, leaving frustrated end users with constraints around global item findability. Legacy PIM users may find themselves needing to create manual "work arounds" to search, prompting them to work offline in spreadsheets and other data siloes.

↘️ Without robust publication and export capabilities, a traditional PIM becomes just another legacy data silo. Many customers with outdated PIM solutions struggle with delivering their data to distributors, retail channels, and to the website. Ideally, the PIM should deliver the data to:

• Websites to enable self-service and a D2C experience 
• Syndication channels to allow for listing products and finished goods on different marketplaces and retail channels, serving the data up in a way that aligns to how those channels require the data to be structured
  
• Publication points such as product specification sheets and catalogs

😡 After the initial purchase of a legacy PIM license, many customers find themselves in limbo between the software vendor and a systems integrator for configuration, custom development, code changes, and other critical activities to ensure the PIM is operational and will meet business objectives. This model is problematic in that there is often unclear services and support ownership. In addition, this means that customers in this scenario purchase technical expertise to solve problems and are not advised properly, leaving them with unresolved issues and limited functionality.

Other customers rely heavily on their internal IT departments for software development, system maintenance, and support, resulting in significant overhead and internal costs. This model is also suboptimal, in that the business is not empowered or able to make key changes to their data model, categories, or attribution in a timely manner and are dependent on the IT division to sustain and (hopefully) optimize the solution over time.

Ideally, a PIM software team will offer flexible infrastructure and hosting options, dedicated engineering support, and taxonomy services under one unified model to drive transparency around ownership, overall reliability and follow-through in support.