Analyst firm IDC believes that 75-80% of intelligent industry solutions will be data intensive, leveraging massive amounts of sensor data for real-time monitoring and predictive analysis of critical assets and industrial operations. According to IDC, that data intensity goes beyond what traditional IT systems (such as for ERP-centric systems and data warehouses) are able to deliver. Hence the need for an Operational Technology (OT) – optimized "3rd generation platform" to enable Industrial Internet “IoT” applications.

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Driver 1: OT / IT Convergence

With more machines connected to the internet and more data generated every minute, traditional means for managing OT systems and their data are no longer sustainable. Rather there is an imperative to apply IT disciplines like security, data governance, and central remove management to the realm of industrial environments.  Essentially, OT systems (controllers, gateways, PTC’s, SCADA systems, etc.) need to be managed like IT systems. And, another important aspect of OT / IT convergence is integration of business processes and the underlying systems, such as as SAP or Oracle for supply chain management. Once early warnings are detected off a critical asset, a customer may intervene with a proactive asset repair, expecting the correct spare parts to be delivered “just in time.”

Driver 2: Data-Driven Discovery

Some 75-80% of intelligent industry solutions will be data intensive. As a result, effective industrial data management is moving to the forefront of business looking to “digitalize” their operations. Another statistic is concerning: Per IDC, 80% of a typical analytics project involves simply gathering and preparing data. That is lots of time and money spent without a clear return. This approach is not viable for a business that wants to be data-driven, with diverse users including data scientists and maintenance staff, operational planners, and business executives. An industrial software platform must allow for cost-effective and highly efficient data collection, discovery, and analysis. Technologies for consideration, per IDC, should include (possibly alongside traditional historians): Hadoop, NoSQL and STREAMS / complex event processing (CEP), and in-memory computing.

Driver 3: Measurable Return on Investment

In the past, IT investment into analytics and BI systems sometimes had a questionable ROI. Not so, thinks IDC, in the area of industrial applications for asset performance management (APM) and operations optimization: Research over nearly 20 years has shown that analytics on operations yields a higher ROI than any other category - more than customer-facing (CRM) projects and more than financial analysis. Reduction of unplanned asset downtime, extended asset life, improved output, lower maintenance / repair cost, and reduced risks – those results are proven and real. Accurate, timely predictions can easily equate to millions of dollars annually, concludes IDC.

In a nutshell, an “IoT” platform for operational technology must bring together broad capabilities in support of operational roles and connected decisions from planning to real-time operations to discovery. The task is not easy and demands a “3rdgeneration platform,” but the payoffs can be handsome.

About the author

GE Digital

Driving Digital Transformation

GE Digital connects streams of machine data to powerful analytics and people, providing industrial companies with valuable insights to manage assets and operations more efficiently. World-class talent and software capabilities help drive digital industrial transformation for big gains in productivity, availability and longevity. We do this by leveraging Predix, our cloud-based operating system, purpose built for the unique needs of industry.