The gap between OT and IT is where the money leaks
Machines predict their own failures. Business systems decide what to do about them. In most enterprises, those two never speak, and the cost is enormous.
Walk any plant and you'll find two worlds that don't talk. On one side, operational technology (OT): sensors, PLCs, SCADA, historians, a live stream of what the machines are actually doing. On the other, information technology (IT): the ERP, the CMMS, the CRM, the systems that run the business. Between them sits a gap, and the gap is expensive.
How big is the gap?
Unplanned downtime is the clearest tax. Siemens' True Cost of Downtime 2024 study put the aggregate loss for the world's 500 largest companies at roughly $1.4 trillion a year, with a single hour of unplanned downtime at a heavy-industry plant costing on the order of $2.3 million (Siemens, 2024). Predictive maintenance can move uptime by a well-documented 10–20% (Deloitte), but only if the prediction actually reaches the system that acts on it.
That last clause is the whole problem. A machine-health tool can raise a perfect alert and still change nothing, because the alert lands as a PDF in someone's inbox instead of a work order in the CMMS.
Why the tools you're sold don't close it
IT platforms, process mining, RPA, copilots, stop at the ERP. They never see the sensor data that predicts the failure. OT platforms, machine health, historians, MES, stop at the plant boundary. They raise the alert but don't reach the business systems that would act on it.
So the loop stays open: sense on one side, act on the other, and a human ferrying context across the gap in between.
Closing it is a governance problem, not just an integration problem
Bridging OT and IT technically is necessary but not sufficient. The moment a signal from a machine can trigger an action in a business system, or on the plant floor, you've created an autonomous pathway that needs to be governed: approved by the right human, scoped to the right authority, and recorded in a way that survives an audit. And it has to respect a hard safety line that no prompt can cross.
The value isn't in seeing the machine or running the business system. It's in the governed path between them.
What good looks like
A closed loop: sense the condition, diagnose the real root cause, propose a specific action, get human approval at the right risk tier, execute through the proper channel, never a direct PLC or safety-system write, then verify the outcome and learn from it. That's the thread Tokoaido was built to run.