IT/OT convergence is essential for digital transformation in industrial settings. Fortunately, technology innovations over the last several years help make such convergence possible.
For many years, industrial manufacturing organizations have focused on integrating Information Technology (IT) and Operational Technology (OT) to improve efficiency, drive innovation, and increase their competitiveness. At the heart of most IT/OT convergence efforts is the desire to enable data-centric operations facilitated by seamless data exchange, real-time analytics, and integrated control systems, leading to enhanced informed decision-making.
According to IoT Analytics’ “IT/OT Convergence Insights Report 2024,” the combined market for IT software, OT software, and OT hardware was valued at $720 billion in 2023. The market research firm estimates that the market will have a growth rate of approximately 8.5% per year, with expectations to surpass $1 trillion by 2027 and approach $1.3 trillion by 2030. Such growth underscores the increasing importance of IT/OT convergence in driving industrial innovation.
Drivers of IT/OT Integration
One factor that makes IT/OT integration increasingly possible is technology innovations that have occurred in the last several years. For example, organizations are able to take advantage of new enterprise industrial connectivity solutions that allow OT data to be more easily accessible.
Additionally, there has been a broader adoption of data management and analytics platforms that help organizations collect and make sense of that data. Those platforms also ensure that the OT data can be used by traditional IT enterprise systems.
All of these developments help move organizations closer to achieving the objectives and goals of Industry 4.0. To that point, there are several high-level reasons driving most IT/OT convergence efforts. According to IoT Analytics, they include:
Scaling Digital Transformation Initiatives: As operational demands grow, scalable and flexible OT infrastructure powered by advanced computing, cloud applications, and alignment with IT practices enables organizations to address these needs. It also unlocks greater potential for AI and improved collaboration, driving smarter operations and increased agility.
Robust Data Exchange: OT network protocols are often proprietary or differ from those used by an organization’s IT systems, and the OT data may be unstructured and lack device context, creating challenges for seamless IT–OT data exchange. Protocol converters, DataOps, and IoT data integration platforms help organizations’ IT and OT systems communicate and ensure OT data is usable for downstream applications.
Enhanced Security: More and more OT systems are coming online, exposing organizations to more avenues for cyber threats. With cybersecurity ranking first in enterprise technology priorities, applying industry cybersecurity standards (e.g., IEC-62443, influenced by IT cybersecurity practices) helps organizations defend against such threats.
See also: The Future of IT/OT Integration in Industrial Manufacturing
Obstacles to IT/OT Integration Success
Industrial organizations face several key obstacles when integrating IT and OT. These challenges stem from cultural, technical, and security-related factors. Here are some of the main hurdles:
Cultural and Organizational Differences: IT teams prioritize agility, frequent updates, and scalability, while OT teams focus on stability, uptime, and safety. Additionally, IT and OT teams often operate independently, using different terminologies, methodologies, and leadership structures. Another factor is that many OT engineers lack IT cybersecurity and networking knowledge, while IT professionals often have limited experience with industrial control systems.
Legacy and Proprietary Systems: Many OT devices use proprietary protocols that do not easily communicate with modern IT infrastructure. Some industrial systems are decades old and not designed to interface with IT networks or cloud-based solutions. Retrofitting or replacing legacy OT systems with IT-compatible solutions is expensive and may disrupt operations.
Data Integration and Management Challenges: IT and OT systems often use different communication protocols (e.g., MQTT, OPC UA for OT; TCP/IP for IT), requiring protocol conversion solutions. Furthermore,OT data can be unstructured, inconsistent, or lack proper context, making it difficult for IT systems to analyze. Plus, traditional OT infrastructure may not be able to handle large volumes of data needed for IT-driven analytics and AI.
Resistance to Change: Many OT environments run critical processes that cannot afford downtime, making integration risky. Some OT personnel worry that automation and IT-driven analytics will replace human roles. Without strong executive support, IT/OT convergence projects may stall due to funding or prioritization issues.
A Final Word on IT/OT Convergence
Despite these challenges, IT/OT convergence is essential for digital transformation in industrial settings. Overcoming these obstacles can lead to greater efficiency, improved decision-making, and stronger security in industrial operations.
