From Data Silos to Unified Insights: Best Practices for Converging IT and OT in Manufacturing

 Learn how to eliminate the invisible barriers that keep your manufacturing data locked in silos.

Today’s manufacturing systems capture more data than ever before. But even with all that data, it’s often challenging for companies to answer questions about equipment efficiency or quality issues across their operations. Two primary obstacles hinder the connection between IT and OT: persistent data silos and the complexity of integrating legacy systems. The stakes are high — in the grand scheme of things, businesses lose an average of $3.1 trillion each year due to the high costs of data silos. So, how can manufacturers converge IT and OT to start seeing the benefits of predictive, optimized systems?

IT vs. OT: A Side-by-Side Comparison

The modern factory operates on two parallel tracks: Information Technology (IT) and Operational Technology (OT). IT encompasses the business systems that manage data across resources, finances, and logistics. Relying on platforms such as ERP and CRM, IT safeguards data availability, cybersecurity, and integrity to support business planning.

By contrast, OT governs physical processes and machinery on the factory floor. It includes systems such as Supervisory Control and Data Acquisition (SCADA), Manufacturing Execution Systems (MES), and Programmable Logic Controllers (PLCs). The primary goal of OT is to maximize machine uptime, production output, and overall operational reliability.

Let’s take a closer look at the difference between IT/OT:

 In this article, we’ll explore how to break down data silos, connect your legacy equipment to modern systems, and create data flows that turn your manufacturing data into new knowledge.

The Primary Obstacles to IT/OT Convergence

Bridging the gap between IT and OT has been challenging for several reasons, with data silos representing one of the most persistent barriers.

Many legacy OT systems were built to operate reliably for years but lack modern security features or network connectivity. They often rely on proprietary protocols incompatible with standard IT networks. This incompatibility has resulted in pockets of valuable operational intelligence that remain isolated within specific systems, departments, or even individual machines.

 Data silos appear at multiple levels across the organization:

• Equipment-level silos. Individual machines that collect performance metrics, quality data, and maintenance indicators in proprietary formats.
• System-level silos. MES, SCADA systems, and historian databases that operate in isolation.
• Departmental silos. Production, quality, maintenance, and planning OT teams each maintaining their own datasets without cross-functional visibility.
• Enterprise-level silos. The fundamental disconnect between operational technology that generates real-time data and enterprise systems that require the same data for strategic decision-making.

 When ERP systems lack real-time production data, inventory counts become unreliable, resulting in costly overstocking or disruptive stockouts.

Without clear visibility into the factory floor, companies frequently miss production targets and struggle to identify the root causes. The insights they need remain hidden within siloed IT and OT systems.

Perhaps most critically, this disconnect makes it nearly impossible to accurately calculate the true profitability of a single production run, as the actual material consumption, energy usage, and labor time recorded on the floor never fully reconcile with the standard costs estimated in the ERP.

As a result, manufacturers with fragmented data architectures cannot fully leverage advanced analytics, AI, or digital twin technologies — all of which depend on integrated, high-quality datasets.

So, what are the options to turn things around?

Step 1: Integrating Legacy Systems Without “Ripping and Replacing”

One of the biggest challenges in modernizing a factory floor is the presence of reliable, decades-old machines that represent significant capital investments. The mindset of “if it ain’t broke, don’t fix it” remains strong, making the replacement of functional equipment both financially and operationally impractical.

The core principle of a successful integration strategy is not to “rip and replace” but to enable existing equipment to “talk.” This means implementing cost-effective, targeted upgrades that extract data from legacy assets and integrate it into the modern data ecosystem.

One effective tool for achieving this is edge computing. Edge devices act as universal translators for industrial machinery. These small, industrial-grade computers are installed directly on or near a machine, where they connect to its native controller or PLC. The edge device captures raw, proprietary data, converts it into a standard format such as MQTT or OPC-UA, and securely transmits it to higher-level systems.

This approach eliminates the need for costly and complex PLC reprogramming, enabling businesses to access data from equipment that was never designed to be networked. It’s a minimally invasive solution that gives even the oldest machines a voice in the digital conversation.

For older or simpler machines without digital controllers, retrofitting with Industrial Internet of Things (IIoT) sensors offers a practical solution. These sensors can be mounted on almost any piece of equipment to measure key performance and health indicators such as vibration, temperature, power consumption, or cycle counts.

Although this data is less detailed than that captured by a PLC, it can still reveal critical insights into a machine’s status, performance, and health. For instance, a sudden increase in vibration may serve as an early warning of mechanical failure, enabling a shift from reactive to predictive maintenance. By streaming this sensor data to a central platform, manufacturers can effectively give analog assets a digital reflection.

 To manage the influx of data from newly connected sources, it is essential to establish a data abstraction layer. This middleware platform acts as a universal connector, capable of communicating with a wide range of machine protocols and data formats.

The abstraction layer consolidates data from all machines — old and new, digital and analog — and delivers it in a single, standardized format. Higher-level systems such as MES and ERP can then consume this data seamlessly, without needing to account for the complexity or diversity of factory-floor sources. In effect, the abstraction layer creates a single source of truth for all machine data, regardless of origin.

Step 2:  Creating an IT/OT Data Flow

Once you have a strategy for making your legacy equipment “talk,” the next step is to orchestrate the software convergence. Integrated industrial operations rely on an automated data flow between SCADA, MES, and ERP systems, where each system plays a distinct role. For example, the SCADA system functions as the real-time “data collector.” It uses a network of PLCs and sensors to gather raw, high-speed data like cycle counts, machine speeds, temperatures, pressures, and fault codes. It provides the granular, moment-to-moment visibility essential for operators and line supervisors.

 Building on this foundation, the MES serves as the factory floor brain. Its core role is to take the raw, high-volume data from SCADA and enrich it with operational context. The MES manages digital work orders, tracks material genealogy, enforces quality control checks, and provides operators with step-by-step instructions. Most importantly, it leverages SCADA data to calculate key performance metrics such as Overall Equipment Effectiveness (OEE). In doing so, the MES answers critical questions: What is happening on the factory floor right now? Why is it happening? And how does it compare to the plan?

Finally, the ERP serves as the “business command center.” It takes the contextualized, aggregated data from the MES to manage the big-picture business workflow. The ERP is concerned with financials, long-term capacity planning, customer order fulfilment, supply chain logistics, and inventory management. It does not need to know the temperature of a specific machine, but it needs to know how many Grade A units were produced, how much raw material was consumed, and what the actual labor cost was for a specific production order. This information, which can only be accurately provided by the MES, is essential for precise financial reporting and strategic business planning.

The ideal data handshake between these three systems creates a closed-loop, self-correcting operational cycle. It begins when a sales order is entered into the ERP, which automatically triggers the creation of a production order. This production order is then passed down to the MES, which schedules it for a specific line and time, and delivers the digital work instructions and quality parameters to the operator’s terminal.

 As the machine executes the order, the SCADA system continuously monitors performance in real time and feeds the data to the MES. The MES analyzes this input to track progress against the schedule, identify quality deviations, and calculate the run’s real-time OEE. Once the order is complete, the MES sends a confirmation signal to the ERP. The ERP then automatically updates finished goods inventory, deducts consumed raw materials, and calculates the actual cost of production — effectively closing the loop.

 Ultimately, the goal of IT/OT integration is to equip teams with timely, accurate, and actionable information. Static, manually compiled spreadsheets — still common on many factory floors — cannot achieve this. The true value of integration emerges through real-time, automated dashboards that serve as the operational hub. These dashboards transform the torrent of data from newly connected systems into clear, accessible insights that drive informed decision-making at every level of the organization.

System Overview

Aligning IT and OT for Operational Excellence

The cumulative impact of data silos costs manufacturers millions in delayed responses, manual reconciliation, and missed opportunities for improvement. However, the solution does not require abandoning decades of operational investment. Legacy systems do not need to be replaced entirely — middleware solutions and phased integration approaches can preserve existing investments and simultaneously enable the connectivity necessary for digital transformation.

At the end of the day, integrating IT and OT is a strategic initiative to be aspired to, not merely a technical project. It demands organizational commitment, cultural change, and a clear vision of how unified data will drive competitive advantage.

Avenga’s expertise in enterprise IT systems and industrial OT environment helps manufacturers bridge the critical gap between their business and production floor systems. If you’re interested in learning more about improved equipment effectiveness, predictive maintenance capabilities, and real-time operational visibility, contact us.