15-year-olds are showing us the way forward
My children expect the world to be centered around their technology needs. They expect to receive services how and when they want them. Transport is their own car or Uber, and products come to them when they want them. They see everything as a service highly connected to their needs. This is a radically different view of the world than previous generations held, amplified by events of 2020 and the shift to millennials—and those even younger—as the core of the world’s workforce. We expect our systems to sense and measure everything, from taking blood oxygen levels from the wrist to predicting when you should refill your refrigerator.
Your car may be able to drive itself and, in near real time, deliver ongoing data from the driver and vehicle to the manufacturer, who then updates settings—based on feedback from your most recent drive—about best adjustments to the suspension or handling. This won’t make you the Formula One driver and world champion Lewis Hamilton, but it does show where the synthesis of human and machine learning and near real-time updates can take us. Driving will soon be a different activity than our parents engaged in. The car, the human, the manufacturer, other cars and even highway infrastructure will interact in a seamless experience. Roads will be safer and most of what you care about while driving will be enhanced by the customization of your whole-car experience.
Auto manufacturers, according to McKinsey, will see 20% or more of their profits coming from software customization services in the vehicle. The same will be true for commercial trucking, with self-driving trucks trains in Australia reducing human workloads and also increasing safety and the volume of cargo carried. Telematics technologies and other connected devices and sensors will make sure the vehicle is performing as expected and connect to various drop points on the journey to check whether the inventory on the trucks is needed. Imagine a virtual, moving supply chain, crossing a continent for near real-time matching of supply and demand.
Intelligent systems at the edge become the expected, not the unexpected
The idea that products will increasingly need to be intelligent to be useful, not just intelligent as a value-added experience, is the catalyst to an intelligent systems world. These systems are a pathway to build digital scale and competitiveness for organizations where embedded machines, software, and intelligence work together in near real time to do tasks, pass information or deliver services through the cloud. And these systems are found at the intelligent edge where data is being collected, analyzed, or sensed – rather than at a centralized server.
To seamlessly connect the driver, the vehicle and the manufacturer in near real time has obvious and exciting possibilities for the user, the vendor and the completely revised set of expectations that this new generation will have for transportation. This is as true for personal autonomous vehicles as for autonomous transportation—for each of us as well as for those truck trains in Australia.
And it’s true across industries. Just imagine being in the elevator business and recognizing that the elevator is a sensor, gathering data on usage and movement patterns of people in the building, and that it is even a potential addition to the building’s security capabilities. If sensors can monitor and prevent expensive and highly inconvenient repairs by anticipating possible parts failures and conducting predictive maintenance, then the economics of the elevator business and the nature of conversations about the value of the elevator go far beyond the past 100 years of highly focused expectations. Imagine connecting that data securely from one elevator to others in the city (or other cities). Then imagine being able to look for similar patterns in near real time to enhance knowledge for new product or service design, or even to lower ownership costs for users across tens of thousands of similar elevators. Turning this from a capital cost for a user to an operating expense, with the promise that the application of that intelligence will be used to lower ongoing costs and that perpetual updates will be deployed over time, is going to be the norm.
By making the elevator a service (transport, security and insights), by focusing on machine and software to deliver services never before imagined possible, we enter the world of intelligent systems at the edge. Now think about your industry and how you can turn your company into a thriving intelligent-systems business.
- What outcomes could your intelligent systems at the edge (human, machine and software code with near real-time analytics and automation) radically optimize for your customers right now?
- What other outcomes does the customer need you to deliver on in an intelligent systems approach?
- How could intelligent systems at the edge reengineer the dynamics of your industry?
Since KPMG’s 2017 research into CEO mindsets, we’ve known that 65% of company leaders believe that disruptions to their industry sectors present opportunity.
Intelligent systems allow leaders to go beyond choosing one of the tenets of Michael Porter’s five-forces model of strategy frameworks, giving you the potential to address all of them: You can compete by changing the nature of your relationships with existing customers and suppliers, protect against substitutes, and enhance components or experiences you might have relied on for decades.
Whereas digital transformation has been a steady process since 2013, the growth of intelligent systems at the edge is likely to be faster and deeper, because as enterprises become software driven to deliver on the needs of systems and customers, the intelligent systems world becomes the expected norm. We could call this the Teslafication of industry.
SOURCE : www.forbes.com
BY: Kevin Dallas
ILLUSTRATION : GETTY
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