Industrial Internet of Things (IIoT) connects sensor equipped machines and systems, derives intelligent insights from sensor data and analytics for better market and operational strategy, and controls operation of machines and other assets for better business outcomes. IoT applications in industries ranging from manufacturing and transportation to retail, travel and healthcare, to name a few, have promising benefits in terms of increased revenue and operational efficiencies and delivering new services.
Gartner predicts that 20.8 billion connected things will be in use worldwide by 2020. Predictions for the value created by IIoT range as high as $15 trillion of global GDP by 2030. Despite the increased adoption in IoT, enterprises face significant challenges in managing, securing and optimizing their IoT initiatives and investments. The key to unlocking the value of IIOT is to remove silos and integrate with enterprise eco-systems for better business outcomes. Data-driven decisions play a vital role in transforming the operation models of industries by optimizing the performance of systems and processes significantly.
CSS Corp continues to invest in machine-learning technologies and analytics to deliver cutting edge IIoT solutions for their customers by partnering with IoT pioneers like GE Digital on their Predix platform and other startups. The connected world needs a data driven technology solution for actionable insights and CSS Corp’s offerings are well positioned to address the key needs of enterprises that deploy IIoT.
Key Drivers of IIoT solutions
Business outcome definition and alignment
Defining the desired business outcome whether it is operational efficiency by reducing costs or defects, or increasing revenue is key to designing the right IoT solution. Aggregate the data and align your project with the business objective in mind.
Key questions to ponder for designing the IIoT solution are:
- What devices, endpoints and hubs are the source of usage for my product or service?
- How are my customers and partners interacting with these touch points and what does the usage data tell me?
For example, think about a household appliance or a HVAC or a machine in an industrial setting being used over a period of time. By collecting usage data through sensors, manufacturers can gain tremendous insight about usage patterns and even have the ability to detect wear and tear from the sensor data and offer proactive and predictive maintenance services to the end-user and stay engaged throughout the product lifecycle with service add-ons and upgrades.
Increase in customer and business engagement
Enterprises have a window into customer usage patterns of their products, and they can provide better service if there was a service request during the warranty period and have the opportunity to proactively address future issues.
Analytics and Machine Learning algorithms in smart connected products can improve output, utilization and overall efficiencies of the product. Improved first-time fix rates and reduced service calls are a few key benefits of an analytics driven, algorithmic approach to addressing issues.
They can offer Product-as-a-service model with subscription based services, and have better insights about usage patterns and potentially address new market segments. A well designed IoT solution can result in creation of additional value-added services as well as sales opportunities for recurring revenue, such as equipment uptime guarantees that can be sold to customers.
Manufacturers can gain insights into product or equipment usage, which can be used for additional insights into product design of future versions. Usage data monitoring for example could provide valuable insights and reduce over engineering costs for example. The underlying principles of solution design should support product upgrades, extensions and customizations that allow quick turnaround of a batch production to selectively enable new features in specific markets. These could be enabled by software or even small incremental hardware modules designed to provide features, gleaned from insights of product usage.
Expand the Ecosystem
Asset tracking can be enabled with sensors and supply chain and inventory data can be shared with suppliers and partners to enable a nimbler digital supply chain that tracks high value assets and movement of finished goods and components. Manufacturers and other players in the value chain are in a unique position to leverage the aggregate data of their products and see if their partners can benefit from them by improving the components that go into the product , be it software or hardware and see what incremental efficiencies can be achieved . By knowing the wear and tear and usage pattern of each component through sensor data, products can be efficiently engineered with the goal of maximizing performance and the component suppliers can build better components.
IoT technology has had a major impact in enterprises on improved equipment uptime and availability, remote diagnostics, reduced operational costs and new channels of revenue spurred by product as service models. A whole range of benefits can be realized leveraging IoT solutions, resulting in new business models and services.
Here is a whitepaper that has interesting insights into supporting the IoT world. Internet of Things Support. What does the future hold?