Top 5 Reasons Why PIM Deployments Fail
A properly functional PIM will easily manage complex product data, ensuring consistency and streamlining operations across sales, marketing, and supply chains. This enables faster time-to-market, better customer experiences, compliance, and scalability by providing a single source of truth for all product details. It will automate data distribution, reduce errors, and power digital commerce by feeding accurate information to websites, marketplaces, and partners.
Product Information Management (PIM) systems are crucial in manufacturing for centralizing and enriching product data, but implementations often fail due to organizational, technical, and planning issues. Although a PIM deployment can lead to various benefits, industry reports and expert analyses from 2024–2025 highlight recurring pitfalls, with data quality problems alone sabotaging up to 85% of projects.
If your PIM deployment failed, it is likely due to some, if not all, of these top reasons.
5. Low User Adoption and Resistance to New Workflows
When a PIM system is introduced without clear context or practical training, it can feel like an extra layer of complexity rather than a solution. Users may think, “Why should I enter data here when I already have it in Excel?” or “This slows me down instead of helping me ship products faster.” As a result, teams revert to old habits, and the PIM becomes a passive repository instead of a living system of record.
This is where thoughtful onboarding and role-based workflows matter. For manufacturers, PIM adoption improves when users see the value to them: how it reduces manual efforts and rework, prevents errors in specs, and speeds up downstream processes like channel syndication, service documentation, or regional product launches. Without that connection to real, day-to-day value, even a technically successful rollout can quietly fail.
4. Overlooked or Complex System Integrations
In large manufacturing environments, PIM doesn’t live in isolation—it sits at the center of a complex ecosystem. ERP systems manage pricing and inventory, PLM systems handle engineering data, and digital commerce, content management systems and/or distributor portals depend on clean, accurate, and complete product information.
When integration requirements are underestimated or postponed, problems surface quickly. Data doesn’t sync correctly, leading teams to create manual workarounds while IT spends time maintaining fragile custom scripts. Suddenly, the PIM that was meant to simplify product data operations becomes another system to manage.
3. Insufficient Stakeholder Engagement and Change Management
Failing to fully involve cross-functional teams (marketing, sales, IT, etc.) early creates resistance, fear of job changes, and poor implementation. If stakeholders feel a PIM is being “done to them” instead of built with them, resistance grows. Some worry about losing ownership of data. Others fear the implementation will disrupt productivity or redefine roles without their input. By not having open communication, training, and shared goals, implementation stalls and return on investment (ROI) erodes.
2. Lack of Clear Planning and Requirements Definition
Rushing into implementation without defined objectives, scope, roadmap, or thorough requirements gathering results in misalignment, scope creep, and a system that doesn't fit business needs. This can lead to frustration amongst the team and inefficient processes. The technical experts at Convergence Data include a project manager who will lead your team's implementation.
And the most common reason for a PIM deployment failure is...
1. Poor Data Quality and Migration Issues
For most manufacturers, existing product data is frequently incomplete (40–60% of records), inconsistent, outdated, or duplicated. Underestimating the complexity of cleanup and migration leads to "garbage in, garbage out," resulting in ongoing errors and project delays or abandonment. Convergence Data's PIM can validate data in bulk to expose the items that require improved data. It's critical that your PIM can do data validation and enrichment at scale, as well as handle process flows that align with the right stakeholders that own technical and marketing attributes to manage the changes required to make data right.
To mitigate these aforementioned issues, prioritize data audits, executive sponsorship, phased rollouts, and expert partnerships early. Successful PIM deployments require treating the process as a business transformation program, not just a software install project. When dealing with the most common pain points for product data, it is important to work with a team like ours that knows how to find the right solution.
With over two decades of experience handling large data sets for some of the biggest manufacturers in the HVAC, aerospace, and electronics industries, the team at Convergence Data is ready to help your team find success with our PIM.
Ready to migrate? Your future sales will thank you! Contact us today to get started with a free discovery call.