The need for a platform approach to the Industrial Internet of Things (IIoT) is about speed and agility. Few organizations have the wherewithal to start from scratch – particularly when it comes to the industrial demands of IIoT. Supporting the services, integration, and data management needed to make IIoT a success, a platform can speed ramp-up for IIoT deployments and help manage these deployments for ongoing value.
Compare “commercial” IoT (think smart coffee machines and the like) to its industrial cousin, IIoT. Commercial IoT focuses on convenience for customers and better customer engagement. IIoT more often focuses on cost, efficiency, and safety in industrial environments.
IIoT deployments are highly controlled. The environment is purpose-built for industrial ends. It is closely managed and often regulated. Data streams are heavy and constant.
This data, in fact, is where almost all of the value lives. In the context of IIoT, the “things” deployed in industrial plants and warehouses are important to the degree that they share their data for greater insight and control. IIoT, ultimately, is about managing data to make better decisions about business processes.
So, if speed and agility are the goal, what are some of the core attributes to think about when considering an IIoT platform? Interest in platforms that support the IIoT is growing. Recently, two leading analyst firms – Gartner and Forrester – have released reports that evaluate the market. Here’s a quick run-down.
When an IIoT deployment goes down in an industrial environment, at stake are cost overruns and even the safety of workers. Your IIoT platform, therefore, should be able to pass a stress-test for demanding industrial situations. The connection between IT and operational technology (OT) should be built into the platform from the ground up. A resilient platform with the ability to monitor and manage connected devices and support 100% availability is a must.
As value chains grow more complex, organizations need the agility to quickly collaborate with new technology and partners – such as third-party data sources. Look for robust ecosystem partnerships. And look for a wide spectrum of expertise – from system integration, data management, and connectivity services to specializations in application management, data management, and security. Particularly important: competency with edge computing scenarios.
On its own, IIoT data is of little use. To yield relevant insights, you need to mix it with business systems and data – which requires integration. Some organizations mix IIoT data with customer records to detect demand signals. Others feed it to compliance systems to meet regulatory obligations at lower cost. Look for platforms that take the integration challenge seriously. Particularly helpful are accelerators such as preconfigured integration packages and flexible workbenches that help speed integration tasks.
With IIoT data, organizations want the ability to run analyses in real time – and monitor it all with intuitive dashboards. Speed is critical, which is why many organizations are moving to in-memory data processing where transaction data and historical business data live side by side. Leading organizations are also jumping into digital twin technology, creating asset intelligence networks (AIN) that maintain a real-time digital mirror of the IIoT deployment – with opportunities to evaluate data at the macro level and generate predictive insights regarding maintenance needs and potential process disruptions. Look for in-platform support for AIN – and fast analytical processing as well.
IIoT deployments are challenging for organizations. When they connect to external partners and data sources, the challenge grows. No wonder the protocols for connecting to all the systems involved are varied. One popular choice across industries is OPC Unified Architecture (OPC UA) – but depending on the industry and specifics of the deployment, protocols will vary. To avoid building connectors from scratch, look for an IIoT platform with comprehensive protocol support. It’s always best to be prepared.
Across these categories and more, many organizations seek the support of a platform to move forward with their IIoT initiatives. Some platforms provide a step up when it comes to building out an IIoT deployment – with support for emerging technologies such as Big Data analytics, machine learning, and blockchain. Others support specific use cases out of the box with preconfigured solutions that streamline edge processing, backend integration, analytics, and more.
With the cost of sensors dropping and pressure growing to increase efficiency and agility, effective IIoT is becoming a business differentiator. The platform you choose is critical. Make sure it fits all your needs for today and into the future.