Industrial IoT: From Data Capture to Real‑Time Decision Making

Industrial operators today generate vast amounts of data—yet only a fraction is actually leveraged. A recent GE and Accenture study revealed that 80‑90% of companies list Big Data analytics among their top three priorities, and 76% anticipate increasing their investment next year.

Data can unlock new efficiencies across sectors—from energy to healthcare to transportation—by boosting productivity, enhancing customer experience, and opening new revenue streams. But data alone isn’t enough; the key lies in turning it into actionable insight, fast.

The Industrial Internet is the Nervous System of Modern Factories

In a healthy body, the nervous system constantly monitors the environment and responds instantaneously, often without conscious thought. Machine controls are the industrial equivalent, yet traditional closed‑loop systems are limited: they run on fixed schedules, react to only a handful of variables, and operate in isolation. As a result, companies using legacy controls tap into merely about 3% of the data available on their assets.

Achieving the next wave of productivity requires controls that are both smart—capable of local data collection and processing—and connected, so they can feed that data into cloud‑based analytics and receive real‑time decisions. These controls must maintain the reliability and determinism that operators expect while unlocking new intelligence.

Turning Data Into Automated, Insight‑Driven Operations

GE’s Industrial Internet Controls System (IICS) exemplifies this approach. IICS seamlessly connects thousands of machines to GE’s Predix platform, a purpose‑built operating system for industry, and brings computing to the edge.

The system integrates intelligent controllers, I/O modules, secure cloud connectivity, advanced analytics, and industry‑specific apps. For instance, a turbine’s connected controller could query electricity prices in real time and adjust its output to match peak demand, a capability that traditional controls simply cannot provide.

In a gas‑fired power plant, automated controls would continuously monitor every unit’s performance, market conditions, and supply‑demand dynamics. They could forecast pricing, weigh potential revenue against wear and maintenance costs, and adjust output accordingly—all while leveraging digital twin models that give precise health data for each asset.

By balancing processing between the cloud and the edge, connected controls enable assets to communicate, coordinate, and respond to both physical and economic stimuli. The result is a dramatic shift toward predictive maintenance, reduced downtime, higher efficiency, and increased profitability.

The author is president and CEO of GE Automation & Controls.