IoT at the edge of business transformation

Why IoT at the edge could be key to transforming your business model  

IoT at the edge enables a step change in the services offered by equipment makers to their customers. The old model of processing all IoT data in the cloud limited IoT’s role primarily to monitoring and reporting. Processing data at the edge, with computing close to assets and equipment, allows for higher frequency monitoring, local control and automation that can be used to significantly enhance efficiency, performance and reliability. 

Pioneering equipment makers are already seeing the ways edge computing can help them transform their operations and pivot to new Equipment-as-a-Service business models. 

Beecham Research recently explored how IoT at the edge is enabling the real-time enterprise. Highlights of its findings, in our new guide IoT at the edge: Enabling Equipment-as-a-Service business models, show how IoT edge is a key enabler for offering new services and is already creating strong competitive advantage for first-mover enterprises.  

What is IoT at the edge? 

Edge computing moves data processing resources close to the source of the data, reducing the need to transfer everything for processing in the cloud or in data centers. This reduces latency, enhances local control for semi- or fully-autonomous operation, improves security and greatly reduces networking costs.  

It also enables manufacturers to connect remote assets that have limited connectivity, produce too much data to cost-effectively send to the cloud , or need millisecond response times from analytics—think wind turbines in far-flung locations. 

Edge computing is a continuum, stretching from cloud-native fog services closer to cloud-hubs on one end of the spectrum, to microcontroller powered micro-edges in embedded in products on the other. Typical deployments combine local computing in tandem with centralized data centers or the cloud. In industrial IoT, the first edges were thick edges based on industrial PCs, which are ideal for applications and devices that generate lots of data or require significant computing capabilities. More recently, the continuous increase of compute power in low-cost devices is driving the rapid growth of thin edge, the category of resource-constrained devices that run general purpose operating systems such as Linux. 

Overcoming industrial IoT challenges with edge 

Equipment makers are eager to apply advances in IoT to deliver improved service performance to customers, gather actionable insights for continuous product development, offer new digitally-powered services to customers. In short, they’re able to make smarter products and generate value faster.  

For these innovative equipment makers, edge overcomes six typical challenges in industrial IoT: 

1. Real-time performance with fast response times to take actions that help avoid machine downtime, reduce repair costs and enhance product quality 

2. More reliable connectivity to remotely manage critical industrial equipment with predictable, continuous monitoring 

3. Greater security and confidentiality by using computing capabilities embedded in secure environments 

4. Lower connectivity costs by reducing the volume of transferred data from remote assets 

5. Local autonomy with on-site execution of sophisticated condition monitoring or predictive analytics 

6. Anomaly detection with solutions that integrate machine learning models to continuously analyze machine data  

Edge + IoT for business model transformation 

Edge computing is not only a tactical differentiator—it’s a strategic asset for equipment makers that want to transform their business model away from one-time equipment sales and toward an EaaS model.  

Maintaining a connection to products in the field generates value for both the equipment makers and their manufacturing customers.  

With a connected product, equipment makers can offer new value-added services that help their customers operate more reliably and efficiently. Services such as remote monitoring and smart field services are only possible with reliable connectivity; performance management requires both connectivity and precise, low-latency control. For equipment makers, these as-a-service business models unlock new opportunities to generate subscription revenue which is more consistent and usually higher-margin than one-time sales.  

No matter where you are on the IoT maturity journey—whether you’re just starting to connect equipment or already on your way to an EaaS business model—edge computing is a key enabler to deliver higher-value services. Read our guide on IoT at the edge by clicking the link below.