By Elvira Wallis, Senior Vice President, Global Head of Internet of Things at SAP
With the price of sensor technology dropping, manufacturers are designing and delivering more Internet of Things (IoT) enabled smart products and assets than ever before. As the technology moves its way further along the adoption curve, IoT hype is giving way to real-world IoT implementations. Today we are well past the proof of concept stage. The time for IoT is NOW.
The backbone of Industry 4.0
IoT has long been seen as the backbone technology behind Industry 4.0 – and with real-world IoT implementations proceeding apace, we can now see the vision of Industry 4.0 staring to take shape in the form of smart factories and digital supply chains powered by data, insight, and automation.
Adoption is starting to snowball. Here at SAP, we see IoT implementations picking up steam in 2020 as the technology increasingly goes mainstream. As Gartner sees it, at least 50% of enterprise applications in production will be IoT enabled by 2024.
Indeed, organizations all over the world are now using IoT at scale and with a level of sophistication that enables them to increase efficiency, meet growing demand, and drive better customer experiences. The result is that the traditional production stack is evolving into a digital manufacturing platform that supports fully automated plants, high-volume production, mass customizations, and the profitable production of personalized products.
With IoT driving Industry 4.0 forward, machines and business processes are now interacting without human intervention – freeing enterprises to focus on business outcomes. This is enabling organizations to increase business automation, improve business agility, and enhance the customer experience.
The way humans work in production settings is changing as well. Increasingly, workers get tailored information and decision support delivered to them on their smart devices at the point of work. To further facilitate this shift, the systems that support production are moving from a focus on transactional production execution to data-driven business process execution and optimization.
Context-rich data processed at the edge
Indeed, raw telemetry data collected from machines is of little value on its own. To make IoT a business reality, what companies need is a way to put that data into business context. Sensor data, in other words, needs to be augmented with business semantics stored in systems of record for materials, products, customers, inventory, assets, and more. This can give meaning to raw data – enabling organizations to build insights that lead to improved business outcomes and better decision making.
The rise of applications and platforms capable of bringing in vast amounts of big data from connected devices via the cloud is a major step forward in this regard. But what about cases in which no connection is available? And what about cases where low latency is key?
Here the solution lies in edge computing. Think of edge computing as a new form of distributed computing where data, applications, and business processes are run near the source of generated data. The ability to extend and run business processes at the edge, enables organizations with factories and plants to fully automate and run their operations independently – even in situations of low bandwidth or where specific security and regulatory requirements stipulate that data must be processed locally rather than in the cloud.
Like IoT itself, edge computing is catching on. According to IDC, “70% of IoT deployments by 2023 will include edge-based decision making to support organizations’ operational and strategic agendas”. The report also states that by “2023, 70% of enterprises will run varying levels of data processing at the IoT edge. In tandem, organizations will spend over $16 billion on IoT edge infrastructure in that time.”
New business models
The upshot of all this means that organizations are now starting to follow through on one of the key imperatives of the Industry 4.0 vision: to use data in smart ways to drive better business outcomes.
With IoT data coming from assets in the field, for example, companies using augmented analytics and machine learning can predict machine maintenance requirements and take action to prevent downtime – otherwise known as predictive maintenance.
But this is just a starting point. Incoming data can yield valuable information on how customers use the assets, and what they expect moving forward. Leading companies are using this data to dramatically improve the customer experience.
This is typified in the move toward product-as-a-service business models. With so much data on hand to evaluate asset performance and customer experiences, companies can more precisely calculate operating costs for, say, an HVAC machine deployment designed to cool a data center. Based on this insight, companies can move from selling HVAC machines to selling the service of temperature-controlled facilities.
This model, of course, puts the onus on the manufacturer to ensure uptime. If assets go down in a way that violates a service-level agreement, then the manufacturer is on the hook. But for many companies, the benefits outweigh the risks. With constant sensor data streaming in, the manufacturer can predict maintenance needs, avoid downtime situations, and confidently offer and end-to-end service based on a subscription model. And this helps to generate sustainable long-term revenues. That’s the power of IoT.
To learn more about how IOT is driving smart manufacturing and the factory of the future, download the recent IDC whitepaper.
Elvira Wallis is a Senior Vice President, Global Head of Internet of Things at SAP. She is a thought leader in the use of intelligent technologies in business systems and has recently been shortlisted as a finalist in the Internet of Things World “IoT Leader of the Year” Awards for a second year in a row.