As you likely know, the Internet of Things (IoT) is the network of physical devices embedded with sensors, actuators, electronics and software that enables vehicles, home appliances, industrial machines and many other items to connect and exchange data. IoT holds many promises for data-driven innovation: improved operational efficiency, a shift from products to services, smart and autonomous systems and entirely new business models.
While it’s true that IoT continues to hold great promise – for example, Forbes reported in July 2017 that nearly 3,000 IoT-focused businesses in the US alone have raised US$125 billion in funding – progress with IoT has not happened as quickly as expected. Many companies are still in the proof-of-concept stage on their IoT initiatives, driven in large part because they lack the knowledge to analyze the vast amount of data collected by IoT sensors. Much of what is being done with IoT is relatively simple, such as tracking product movement through a company’s distribution network.
The more data generated, the bigger the gap becomes between the promise of IoT and the reality. The solution is not to cut back on collecting data, but to create means for experts from fields other than data science to contribute to interpreting IoT and other field-generated data. Any time a problem is solved virtually or physically, those insights must be made available to others throughout the enterprise to be capitalized on for future iterations.
IoE – the Internet of Experiences – is the next step beyond IoT.
We are in the Age of Experience where virtual worlds allow people to imagine, map, model and engineer collaboratively new environments and experiences. This is bringing new ways – real and virtual – of inventing, learning, producing and trading. This is also triggering businesses to shift from selling products to selling services, with success contingent on their capability to design and deliver differentiated experiences to customers, employees and partners.
The value of IoE is that it links data, knowledge and experts from each step of a product or system lifecycle in a single-data-model digital experience platform that supports interaction between the virtual and the real. It enables multidisciplinary teams to quickly interpret data and make informed decisions in support of an ultimate goal of discovering, evaluating and designing opportunities for new services and new business models. IoE leverages a massive repository of knowledge and know-how that most companies already have at the ready: their virtual models. These models, developed in the design phases of a project, are largely unused outside of engineering. IoE can change that.
Designing, operating and continuously improving intelligent systems such as self-reprogramming and self-optimizing factories, self-driving vehicles or even outcome-based services all require tight collaboration among experts and knowledge from a broader innovation loop within organizations. IoE projects build understanding of users’ and products’ behaviors in the real world. They allow companies to engineer the right services and deliver the right experiences, and while also accelerating the rate at of scaling proof-of-concept projects to full implementation by iterating with applicability at scale from the beginning. IoE is not mutually exclusive of IoT: in fact, done well an IoE approach should accelerate IoT initiatives, enabling optimized, long-term innovation at tremendous speed.
This post originally appears in Dassault Systèmes corporate blog, 3DPerspectives
