In our previous post, we discussed customization overload and the integration pitfalls that hinder scalable IIoT deployments. But there’s another, arguably even more critical barrier to IIoT success: the organizational disconnect between IT and OT.
In many industrial companies, information technology (IT) and operational technology (OT) exist side-by-side—but not together. One team handles networks, cybersecurity, and cloud systems. The other oversees production lines, sensors, and control systems. When these two worlds don’t align, the result is inefficiency, miscommunication, and missed opportunities.
IT and OT have traditionally evolved with different goals, systems, and cultures:
| IT (Information Technology) | OT (Operational Technology) |
| Data, analytics, infrastructure | Machines, sensors, automation |
| Cloud services and apps | PLCs, SCADA, DCS |
| Fast tech cycles | Long equipment lifespans |
| Flexibility and scalability | Reliability and stability |
| Cybersecurity and access control | Process safety and uptime |
When perspectives between IT and OT don’t align, the consequences can quickly become tangible. An IIoT project, for example, may fail to meet the practical needs of production because the chosen technical solutions don’t reflect the realities on the ground. Cybersecurity policies designed for IT environments may block access to critical operational data, delaying or even derailing project progress. At the same time, IT architecture might depend on solutions that aren’t built for the 24/7 reliability demanded by production. Hardware purchases made without a shared strategy or mutual support can result in fragmented systems that are difficult to integrate or maintain.
The disconnect between IT and OT often shows up in daily operations. Projects run late because data access or interface issues are discovered too late. Production teams may not know what data is being collected—or why—while IT teams might lack insight into what information is actually needed on the factory floor. This can create mutual frustration: OT sees IT as bureaucratic and out of touch with real operations, while IT perceives OT as independent and prone to risk, often bypassing agreed procedures.
We’ve seen that “better communication” isn’t enough. Real integration between IT and OT requires intentional structure, shared goals, and trust. Here are some of the proven methods:
1. Use Case First
When everyone aligns around a clearly defined use case—like automated quality checks or energy optimization—it’s easier to find common ground and prioritize decisions.
2. Clear Roles and Responsibilities
Define who owns what. IT manages access, security, and infrastructure; OT owns process continuity and safety. Don’t leave it vague—create a working model.
3. Interface Standardization
Avoid vendor lock-in and integration chaos by using open industrial protocols (e.g., OPC UA, MQTT) that both IT and OT can rely on.
4. Shared Data Platform
A centralized but flexible data layer, like our Owl platform, ensures both teams have access to the right data, with proper context and control.
5. Collaborative Development
Bring both IT and OT into the project from day one. Involve them in requirements, testing, and iteration—not just in delivery. This fosters ownership and trust.
Without effective collaboration between IT and OT, Industrial Internet of Things (IIoT) systems risk becoming fragmented, with disconnected components that fail to support each other. This lack of cohesion can lead to low trust from production teams, who may view new tools as unreliable or irrelevant. Security can also be compromised if systems are built without shared principles or oversight. Ultimately, the return on investment (ROI) remains below expectations, as the solutions fail to deliver real, integrated value in day-to-day operations.
But when collaboration works:
The next post “Clarity Before Connectivity: How Undefined Use Cases Sabotage IIoT Projects” will explore why so many industrial digitalization efforts fail before the first sensor is even connected.
