Five Manufacturing Trends to Watch in 2025

Understanding Manufacturing Trends Can Prepare You for a More Successful Year.

Though the manufacturing sector has experienced several consecutive hard years, data from our recent CRO Survey shows improvement. Manufacturers reported fewer challenges from supply chains and other structural issues, not to mention a growing sense of optimism that they’ll hit their revenue goals. If manufacturing trends in a positive direction in 2025, manufacturers will need to be ready for a growth market.

Any manufacturer looking for a competitive advantage should look to their technology, and specifically to how they’re using data. As you start the year off, here are a few trends in manufacturing technology that might help you hit your goals.

1. Enriching ERP Systems with IoT Streaming Data

Too often, manufacturers’ ERP systems are static, transactional platforms, instead of the dynamic, real-time decision-making tools that they could be. Integrating Internet of Things (IoT) data into ERPs can change that. An ERP continuously refreshed with relevant data from factory floors can give you a better understanding of equipment performance (uptime/downtime), equipment maintenance, environmental conditions, and more.

Beyond data from the factory floor, an ERP on its own usually isn’t powerful enough to handle the large volumes of information that a modern IoT-enabled factory puts out. Many manufacturers are turning to advanced data platforms to make sense of the data and synthesize them into real decision-making tools. Once the data is all in one place, manufacturers can use it to align on operational needs. This can include core elements such as demand and supply signals with real-time data, reducing defects on the production line and improving the overall accuracy of the information in your ERP for future trend and scenario analysis. Integrating a modern data platform with your ERP has other benefits too: a data platform will enable the ability to further utilize cutting-edge AI tools to analyze the data coming in for more actionable insights.

2. Predictive Maintenance Powered by AI and Machine Learning

It’s not exactly news that manufacturers want to maximize the productivity and lifespan of their equipment. Avoiding unplanned equipment maintenance means less downtime, giving manufacturers the ability to keep up with supply demands and decrease OpEx spending on major repairs. It’s also not a secret that better equipment data can deliver better results—many companies have already begun using internet of things (IoT)-enabled equipment to understand the status of their production line. However, two factors have been reshaping how manufacturers have addressed predictive maintenance.

First: The rapid expansion of data applications. With more powerful tools, manufacturers can monitor more data points and analyze equipment health in real time, giving them better information on how and when to conduct preventive maintenance.

Second: AI. With the growing amount of equipment data that new data applications can use, manufacturers are turning to machine learning algorithms to analyze historical and real-time data from sensors embedded in machinery. These algorithms detect patterns and anomalies that identify potential issues at a faster rate with greater reliability than a human analyst, allowing maintenance teams to intervene proactively.

Together, these factors are allowing manufacturers to further reduce downtime by preventing unexpected halts in production, to reduce labor and operational costs by scheduling maintenance during non-peak hours, and by performing smarter and proactive upkeep to extend machinery life.

3. Inventory Management Optimization

Effective inventory management remains crucial for operational efficiency and customer satisfaction—no customer likes hearing that the product they ordered isn’t actually in stock and won’t be shipped for two weeks. Today, manufacturers are getting closer than ever to eliminating inventory management errors. Through real-time tracking with IoT sensors and RFID technology, manufacturers can provide up-to-the-minute inventory data, reducing stockouts and overstock situations.

Predictive analytics can provide additional options for inventory management. Manufacturers are turning to machine learning models to forecast demand trends and seasonality, helping them adjust inventory levels proactively. And by adopting more advanced planning processes and applications, companies can integrate data from various sources, enhancing inventory management and decision-making processes, thus leading to greater cost savings with fewer expedited raw material purchases. This can include integration with supply chain partners, ensuring better visibility into snags up or down the chain that could affect manufacturing operations.

4. Digital Twin Technology

Manufacturers frequently have “what if?” questions about their production processes, but most of these questions are too expensive or too risky to test on their actual equipment. To get around this challenge, manufacturers have adopted digital twins: virtual replicas of physical assets, systems, or processes. Digital twins allow manufacturers to test processes and optimize operations in a risk-free virtual environment.

By mirroring physical processes in a digital format, companies can test scenarios, forecast nuances in the production process, and identify bottlenecks without disrupting actual production lines. They also facilitate better communication between design, engineering, and production teams by providing a unified model to reference and test before, during, and after construction. And by integrating the digital twin with IoT and AI capabilities, companies can further enhance their predictive capabilities and operational efficiency.

Finally, digital twin technology can catalyze a faster research & development lifecycle as well as eliminate costs from product recalls. With the ability to have digital versions of the current product(s), engineers and data analysts can better predict design defects and production shortcomings of an existing and/or upcoming product iteration. Thus, in future launches of a product, product teams can be more confident that the new models are less recall prone.

5. Consolidating Data from Multiple ERPs

Following a wave of mergers and acquisitions, many manufacturers have accumulated multiple ERP systems to manage. While each ERP might work fine for its individual role, trying to consolidate data from multiple ERPs can lead to data harmonization challenges. ERPs managed by different teams for different purposes could have inconsistent definitions, where a data field labeled as “delivery date” might refer to the original scheduled date in one system, versus the actual delivery date in another. Heavy customization can also dilute the effectiveness of standard reporting and complicate data consolidation and result in more data transformation efforts.

As manufacturers increasingly need total visibility into their production process, they’re establishing consistent data standards and definitions across all their ERPs. This isn’t just a data process—it means agreeing on a common set of objectives and making sure all team members and systems are aligned. But by successfully creating alignment, companies can achieve a single source of truth, reduce redundancy, and increase data accuracy, leading to better decisions.

Power Up Your Manufacturing Company.

While even in a strong year, manufacturing is no easy business, embracing these trends will help manufacturers thrive in 2025 and beyond. Harnessing the power of AI, machine learning, and real-time data integration will give companies an advantage in everything they need to succeed: optimizing operations, reducing costs, and staying agile as the market changes. The rapid expansion of data applications provides manufacturers with new tools to leverage these technologies effectively—but a strategic partner to navigate these tools can also help. Spaulding Ridge is a partner to numerous manufacturers on issues from finance to supply chain to data management and more. Reach out to learn about how we can help.