How to Connect Legacy Systems Without Halting Production

Key takeaways:

• Most food manufacturers don’t need to replace their older systems to modernize. Connecting them to newer tools through phased integration tends to be faster, less disruptive, and more cost-effective than starting over.
• The biggest obstacles to system connectivity are complexity and a lack of clear starting points, not the age of the equipment itself.
• Starting small with one data-rich process or one production line gives teams a working proof of concept before broader rollout.

Somewhere on most food manufacturing floors, there’s a machine that has been running reliably for fifteen years. It does exactly what it was built to do. But it doesn’t talk to anything else. Data from that machine lives in a silo. It may be on a paper log, in a spreadsheet, or in no permanent record at all.

That gap between older operational equipment and newer digital infrastructure is one of the defining challenges for food manufacturers right now. And it’s more common than most people realize.

According to TraceGains’ 2024 Digital Drag report, which surveyed 165 senior leaders in food safety, quality, and innovation, 69% of food and beverage companies still rely on manual systems to manage critical processes, even though most (82%) are prioritizing new technology implementation. That gap between intention and execution is what researchers call “digital drag,” and complexity is the most commonly cited reason it persists.

The good news is that connecting legacy systems doesn’t require a full operational overhaul. Many manufacturers are finding practical, lower-disruption ways to bridge the gap without shutting down the line.

Why integration is on the table now

The pressure to connect systems isn’t coming from one direction. It’s regulatory, competitive, and operational all at once.

On the regulatory side, the FDA’s Food Safety Modernization Act (FSMA), specifically its traceability requirements taking effect in 2028, is pushing manufacturers to have better, faster access to production data. If that data is scattered across disconnected systems, pulling it together when it matters most becomes a manual scramble.

On the operational side, disconnected systems make it harder to catch quality issues early, forecast maintenance needs, or understand where inefficiencies are concentrated on the floor. Manufacturers who can pull data from across their operations into a single view tend to have more options when something goes wrong.

And competitively, buyers, retailers, and food service partners are increasingly asking for documentation that requires clean, accessible data — on sourcing, allergen controls, environmental conditions, and more.

None of this means every manufacturer needs to move at the same pace. But it does explain why the topic keeps rising on executive agendas.

The case for integration over replacement

When older systems become a bottleneck, the instinct is sometimes to replace them entirely. That approach, often called “rip and replace,” can work, but it tends to be expensive, time-consuming, and risky when production continuity is the priority.

Industry experience increasingly points toward integration as the more practical path for most manufacturers. Rather than retiring equipment that still performs its core function well, integration connects it to newer platforms using middleware, application programming interfaces (APIs), or purpose-built industrial connectors. 

So the older system keeps doing its job, while a data bridge carries the information it generates into wherever the team needs it. This phased integration approach allows teams to build toward connectivity incrementally, validating each step before expanding.

Common starting points to consider

One of the most useful questions a leadership team can ask is: where does disconnected data create the most friction right now?

That question often surfaces a handful of high-value entry points:

• Quality data collection: Manual quality checks recorded on paper or in standalone spreadsheets are one of the most common integration starting points. Connecting quality checkpoints to a central system doesn’t require replacing the measurement tools. It often just requires a way to capture and route the data digitally.
• Supplier and ingredient data: TraceGains’ research points to supplier and ingredient information as one of the most practical early integration targets. This data is compliance-critical, frequently updated, and often managed in fragmented ways across teams. Centralizing it tends to deliver visible value relatively quickly.
• Predictive maintenance on high-value equipment: Adding sensor connectivity to critical machinery, such as packaging lines, cookers, and mixing systems, can enable teams to monitor equipment health over time. This doesn’t require replacing the machinery; it requires adding the ability to capture and analyze its operational data.
• Production reporting: If operators are still manually entering shift production data into a separate system, there’s usually an integration opportunity. Automated data capture from production systems into enterprise resource planning (ERP) software or reporting dashboards reduces entry errors and saves time.

The Institute of Food Technologists’ (IFT’s) 2024 Technology Trends Survey found that roughly half of food industry professionals are planning investments in artificial intelligence and supply chain tracking systems as part of their digital strategies for 2025. Meanwhile one-third are prioritizing real-time analytics and cloud computing. These technology categories all rely on having connected data sources. Integration is what makes them possible.

An example phased approach plan

There’s no single integration roadmap that fits every facility. But the manufacturers who tend to make the most progress choose a bounded, well-understood process to start with, demonstrate that the connection works, and build from there.

Phase 1: Identify the data gap

Before connecting anything, it helps to understand what data currently exists, where it lives, and where it’s missing. A process audit, even an informal one, can surface the most consequential disconnects.

Phase 2: Start with one process or one line

Picking a single, well-defined integration target (one production line, one quality checkpoint, or one supplier data workflow) gives the team a manageable scope. A successful small integration builds institutional confidence and technical understanding before the work expands.

Phase 3: Choose integration-friendly tools

Modern integration platforms, sometimes called middleware or industrial Internet of Things (IoT) gateways, are designed specifically to bridge older operational technology and newer information systems. Many don’t require modifying or reprogramming the legacy equipment itself. They sit alongside it and translate its outputs.

Phase 4: Validate before scaling

Once the first integration is live, it’s worth letting it run long enough to confirm that the data is accurate, the connection is stable, and the team knows how to use what it’s now seeing. Then the scope can expand.

Phase 5: Build toward a unified data environment

Over time, connecting multiple processes into a shared platform, whether that’s an ERP system, a manufacturing execution system (MES), or a quality management platform, creates the visibility that makes advanced analytics and AI tools useful.

What to watch out for

There are a few common friction points that slow integration projects down, and it’s worth looking out for them.

• Protocol mismatches: Older equipment often communicates using industrial protocols that newer software doesn’t natively understand. This is a solvable technical problem (most industrial integration platforms handle it), but it requires knowing what protocols the legacy equipment uses before selecting a connection method.
• Data quality issues: Connecting systems sometimes surfaces the fact that data has been inconsistently recorded. Inconsistent product codes, duplicate supplier records, or missing fields can create headaches downstream. Cleaning up data before or during an integration project is often time well spent.
• Change management: The operational and technical elements of integration tend to get more attention than the human element. Operators who have managed a process manually for years sometimes meet new data capture tools with skepticism, especially if they don’t understand why the change is happening or what will be done with the information. Involving floor-level staff early in the process tends to produce better outcomes.
• Cybersecurity. Connecting previously isolated operational technology to networks that touch the broader internet creates new exposure. This is manageable (IT/OT security has its own established practices), but it needs to be part of the integration conversation from the beginning, not an afterthought.

FAQ for food manufacturing leaders

Q: What does “legacy system” actually mean in this context? 

A: In food manufacturing, a legacy system is typically any piece of equipment or software that is still functional and in active use but wasn’t designed to share data with other systems. This might be a production line controller from ten years ago, a standalone quality database, or an older ERP platform that predates modern API connectivity. The age of the system matters less than whether it can exchange data.

Q: Do we need to stop production to integrate our systems? 

A: Not necessarily. And in most cases, the goal is to avoid exactly that. Many integration approaches are additive: they layer new data connectivity on top of existing equipment without modifying how that equipment operates. The specific answer depends on the system and the integration method, but most manufacturers explore options that avoid production downtime.

Q: How long does a typical integration project take? 

A: It varies widely based on scope. A focused, single-process integration can be completed in weeks. Broader integrations across multiple facilities and systems may take months to years. The TraceGains report notes that 60% of food and beverage companies get stuck in implementation, often because projects are scoped too broadly at the start. Starting smaller tends to produce faster results.

Q: What’s the difference between an API, middleware, and an IoT gateway? 

A: These are three different tools that can each help connect systems. Which one is appropriate depends on what you’re connecting.

• An API is a set of rules that allows two software applications to communicate. It’s primarily useful when both systems are software-based and relatively modern.
• Middleware is software that sits between two systems and translates between them, often used when the systems speak different technical languages. 
• An IoT gateway is a hardware or software device that collects data from physical equipment on the plant floor and forwards it to a software system. 

Q: We have dozens of systems across multiple facilities. Where should we start? 

A: Focus on wherever disconnected data is creating the most visible friction: compliance documentation that requires manual assembly, quality issues that are hard to trace back to their source, or production reporting that takes staff hours to compile. Supplier and ingredient data is one widely recommended starting point because it’s compliance-relevant and manageable in scope.

Q: What does this cost, and how do we make the business case? 

A: Integration costs vary significantly based on complexity, the number of systems involved, and whether you’re using off-the-shelf tools or custom development. The business case typically rests on labor savings (less manual data entry and reporting), reduced quality-related losses, better regulatory documentation, and faster response to disruptions. Comparing the cost of a targeted integration project against the ongoing cost of manual workarounds (in staff time, error rates, and compliance exposure) often makes the numbers clearer.

Q: Is there a risk that integrating our systems creates cybersecurity vulnerabilities?

A: Connecting operational technology to broader networks does introduce new security considerations. Most manufacturers address this through network segmentation (keeping operational systems on separate network segments from business systems), access controls, and working with vendors who specialize in industrial cybersecurity. The risk is real but manageable when addressed proactively.

Q: What if our team doesn’t have the technical expertise to do this internally? 

A: Many manufacturers work with systems integrators or technology vendors who specialize in food and beverage industry applications. The TraceGains report notes a growing availability of implementation models that can deliver initial results in weeks rather than the multi-year timelines associated with older consulting approaches. It’s worth asking vendors specifically about implementation timelines and what internal resources will be required before committing.