PIM for Manufacturing

Industrial manufacturing leads all sectors in technology investment. Yet, KPMG’s Global Tech Report identifies it as the most likely to cite immature data management as the top drag on digital progress. Product data scattered across ERPs, supplier spreadsheets, and shared drives that no one fully trusts is a big part of that problem. 

A PIM for manufacturing addresses that directly, and this guide covers what it does, the specific challenges it solves for manufacturers, how it connects your existing tech stack, and what features actually matter when you’re evaluating platforms.

What challenges do manufacturers face today?

If you’re a manufacturer today, pressure is coming from every direction, from shrinking lead times and fragmenting supply chains to tightening regulations and a talent pool that can’t keep pace with the complexity of modern operations. 

AI has moved from a long-term ambition to an immediate operational priority, with 92% of executives planning to increase investment and 78% of organizations already deploying it in at least one business function.

However, almost 70% of manufacturers say data quality and integration problems are their biggest obstacle to making it work, according to Deloitte’s 2025 report, Manufacturing Industry Outlook. That problem traces back to product data that is scattered, inconsistent, and difficult to act on across systems.

1. Shrinking lead times and rising product complexity

Customer expectations for delivery speed are tightening faster than most production environments can absorb. According to KPMG’s report, lead-time expectations are getting shorter by the day while production specifications are simultaneously becoming more complex and bespoke, meaning your teams are expected to deliver more customization, faster, without compromising on accuracy or quality.

Manufacturers responding to this pressure are turning to digital interventions across production cycles, supply chain, procurement, and sales functions to bring the speed and reliability customers now expect as standard.

2. Talent and skills shortages

The manufacturing talent shortage is not a future risk. Deloitte and the Manufacturing Institute project that 1.9 million manufacturing jobs could go unfilled over the next decade if the problem isn’t addressed. 

The pressure extends well beyond the factory floor, with KPMG noting that four in five manufacturing executives say technology is now filling knowledge gaps that previously required dedicated headcount across data management, analytics, and digital operations throughout the organization.

3. Supply chain disruption and geopolitical pressure

Today’s supply chain planning is under strain from multiple directions: geopolitical tensions, elevated costs, climate volatility, trade-impeding tariff policies, and labor shortages are all compressing margins and creating instability across sourcing and distribution networks, according to Deloitte. 

Manufacturers are responding, with 78% saying they have or are planning to invest in supply chain planning software, but the effectiveness of those investments depends heavily on having accurate, accessible product data across every node of the chain.

4. Regulatory and compliance pressure

Meeting regulatory requirements across different regions requires maintaining product information that is accurate, up to date, and formatted to each market’s standards. The EU’s digital product passports are raising the bar further, requiring manufacturers to attach structured sustainability and lifecycle data to individual products, a requirement that most current systems are not built to support.

Maintaining compliance across multiple markets means a single outdated or incorrectly formatted data point can create downstream errors that are costly and time-consuming to correct at scale.

5. Fragmented data and poor systems integration

Three-quarters of manufacturers are already increasing investments in data lifecycle management, according to Deloitte, indicating how acute the problem has become. Product and operational data living across disconnected ERPs, PLM systems, supplier portals, and spreadsheets creates errors that compound at every stage of the product journey, and without a unified strategy to integrate and analyze that data across platforms, your teams miss efficiency gains, slow down time-to-market, and limit what every other technology investment can deliver.

How does a PIM system help manufacturers solve these challenges?  

Most of the challenges outlined above share a common thread: decisions being made on incomplete, inconsistent, or inaccessible product data. A PIM system addresses that directly by giving your teams a single, structured source of product information that connects to every system, channel, and market you operate in. Here is what that looks like in practice.

Manufacturing product data spans systems, teams, and markets, making consistency difficult to maintain. Use the ebook to see how PIM creates a single, reliable source of truth.

Get the guide

How PIM integration connects your manufacturing tech stack

Most manufacturers have already made significant investments in AI-powered tools across their operations; however, only 1% of organizations are fully mature in their AI deployment, according to McKinsey. 

The gap between investment and impact almost always traces back to data that lives in disconnected systems, unable to be synthesized across platforms where it would do the most good. The AI capabilities built into modern PIM platforms become more effective when the underlying data is clean, centralized, and consistently structured. 

PIM integration addresses this by sitting at the center of your tech stack, connecting the systems that generate product data with the channels and platforms that consume it.

Here’s how PIM connects to the core systems manufacturers typically run:

ERP systems

Your ERP is where product master data originates: SKUs, pricing, inventory levels, and supplier information. Without a direct connection to your PIM, that data has to be manually transferred, reformatted, and redistributed every time something changes.

PIM integration with your ERP creates an automated data flow that keeps product information accurate across both platforms, reducing errors and the time your teams spend reconciling conflicting records.

PLM systems

Product lifecycle management systems hold the engineering and design data behind every product: specifications, materials, component relationships, and revision histories. That information rarely reaches sales and marketing teams in a usable format, which means your engineering teams become bottlenecks every time product content needs to go to market. 

A PIM connected to your PLM system pulls that upstream data into a centralized repository where it can be enriched, formatted, and prepared for market without that dependency.

Digital Asset Management (DAM)

Technical documentation, product images, CAD drawings, and installation guides are as important to B2B buyers as written specifications, and managing those assets separately from your product data creates version-control issues and gaps in your channel content.

PIM integration with a DAM system keeps your digital assets linked directly to the products they belong to, so every channel automatically receives the right asset alongside the right product information.

E-commerce and channel platforms

Every channel your products reach, whether your own website, third-party distributors, or global marketplaces, has its own content requirements and formatting standards.

A PIM connected to your e-commerce platforms and syndication channels automates that adaptation, distributing channel-ready product content at scale without your teams having to rebuild the same information multiple times for different destinations.

CRM and sales enablement tools

Sales teams working from outdated specs or chasing other departments for current product information lose credibility in buyer conversations and slow down the commercial cycle. Connecting your PIM to your CRM and sales tools gives your commercial teams direct access to current, complete product information without adding steps to their workflow.

What PIM features should manufacturers look for?

Manufacturers who choose the wrong PIM typically find out the hard way, building workarounds to handle parts relationships their platform cannot model, paying for custom development every time a workflow needs to change, and hitting catalog or channel limits at the worst possible moment.

The features below are what set a PIM built for manufacturing complexity apart from one that creates more work than it solves.

1. Extensible data model

A single product in your catalog can have hundreds of variants, components, accessories, and related parts, each with its own attributes and relationships. 

Your PIM needs a data model flexible enough to support that complexity without requiring workarounds, one that scales as your catalog grows rather than forcing you to restructure every time you add a new product line or market.

2. AI-powered content generation

Manually creating and adapting product content across markets, languages, and channels is one of the most resource-intensive tasks in product data management. 

Look for a platform with built-in AI content generation that can use your existing technical documentation, including PDFs, compliance files, and installation guides, as inputs rather than relying on text fields alone, producing more accurate, compliant content at scale with less manual effort.

3. Automated workflows without custom development

Product information workflows in manufacturing typically involve multiple teams, approval stages, and data validation steps before content is ready to publish. 

A PIM that lets you build those workflows visually, with automated checks, conditional logic, and field population rules, removes the need for custom development every time your processes change, and gives your operations teams the visibility to identify bottlenecks before they cause launch delays.

4. Seamless tech stack integration

Manufacturing environments run on multiple systems simultaneously, and your PIM needs to connect cleanly to your ERP, PLM, DAM, and e-commerce platforms without requiring significant custom development to maintain those connections. The tighter the integration, the less time your teams spend reconciling data between systems.

5. Digital asset management

Technical documentation, CAD drawings, product images, and installation guides are as important to B2B buyers as written specifications, and a PIM with integrated DAM capabilities keeps those assets directly linked to the products they belong to, ensuring every channel receives accurate, up-to-date assets alongside the correct product information.

6. Channel syndication with pre-publish validation

Every retail and B2B platform your products reach has its own formatting and content requirements, and a PIM with direct syndication capabilities and built-in validation lets your teams test submissions against a channel’s own rules before anything goes live, catching issues early rather than troubleshooting rejections after the fact. 

7. Digital Shelf Analytics (DSA)

Publishing product content is only half the job because understanding how that content performs across channels, where it falls short of competitor listings, and where buyer behavior signals gaps in your product information requires visibility beyond your own systems, and a PIM with integrated DSA gives you that view in real time rather than waiting for sales reports to surface problems.

5 Best PIM software for manufacturers

Manufacturing operations vary too much in catalog size, system complexity, and channel requirements for any single PIM to be the right fit across the board.

The platforms below represent a range of approaches, from enterprise-grade solutions built for industrial complexity to more focused tools designed around aftermarket operations or composable architecture.

PIM for manufacturing in action: Real results from real teams

The operational impact of centralizing product data shows up quickly and measurably. Here is what two manufacturers achieved when they got their product data in order.

Rust-Oleum: 90% reduction in product management time across 6,000+ SKUs

Rust-Oleum, a century-old specialty coatings manufacturer, was managing 5,000 to 6,000 SKUs using Excel spreadsheets, local network files, and tribal knowledge spread across teams, resulting in duplicated work, inconsistent data, and a lean e-commerce team of 10 spending hours on tasks that should have taken minutes. 

After centralizing all product data into a single source of truth and automating syndication to retail partners, processes that previously took 10 to 30 hours were completed in 30 minutes or less, and the team could meet the unique data requirements of every retail partner without adding headcount.

“Now we no longer need to hire a separate headcount to manage each customer’s data requirements—Inriver gives us that scalability with fewer heads, less effort, and less time.”

– Jon Ahn

Account Manager, E-commerce at Rust-Oleum

Read the full case study

Vertiv: Single source of truth across 130 countries and 22 languages

Vertiv operates in over 130 countries, selling a portfolio of highly configurable products through direct, indirect, and digital commerce channels. Disconnected systems were creating bottlenecks across engineering, marketing, and sales, while manual updates led to data inconsistencies and channel errors at scale. 

By connecting PLM and ERP data directly into a centralized PIM and embedding AI into daily enrichment workflows, Vertiv consistently reduced time-to-market, dramatically cut manual work, and now syndicates accurate, localized product content to global marketplaces, including Amazon, Lazada, Shopee, and Alibaba.

“AI is part of our daily process. We use it to enrich, personalize, and optimize continuously. With Inriver, we’re confident that we can scale wherever our business goes next.”

– Alexandru Radavoi

Global Director, Digital Commerce & Product Catalog, Vertiv

Read the full case study

What is the ROI of PIM for manufacturers?

The true cost of poor product data management rarely shows up as a line item anyone is tracking, but it compounds across every product, market, and channel your business operates in. Hours spent pulling specs from multiple systems before a product can go live, headcount reformatting data for different retail partners, and launches delayed waiting on compliance documentation are all real costs that accumulate quietly across your operation. 

Rust-Oleum reduced processes that previously took 10 to 30 hours to 30 minutes or less, while Vertiv consistently reduced time-to-market across 130 countries by centralizing product data and embedding AI into daily enrichment workflows.

The return on that investment typically shows up across four areas: time recovered from manual data work, headcount efficiency across a growing catalog, faster product launches, and fewer downstream errors reaching retail partners and marketplaces. 

To build your own case, start by quantifying what your teams currently spend on manual product data tasks and how many launches are delayed as a result, because in most manufacturing environments, those two numbers make the investment decision straightforward.

Get your product data working as hard as your manufacturing operation

Most manufacturers are already investing in the technology to compete, but the returns on those investments are limited when the product data feeding those systems is fragmented, inconsistent, and difficult to act on at scale.

The manufacturers pulling ahead are the ones treating product data as a core operational asset, not an IT problem, and building the infrastructure to govern, enrich, and distribute it across every market and channel they operate in.

If you want to see how leading manufacturers govern their product data and scale without adding headcount, the PIM for manufacturers ebook covers the strategies and frameworks that drive those results.

And if you’re ready to see what that looks like for your specific operation, you can schedule a personalized demo with Inriver.