As a technological turning point, the Internet of Things ranks with the advent of the Internet itself and mobile computing. Even in its nascent form today, IoT is changing the way we interact with our physical environment and how we learn from it too. Besides bringing us Internet-enabled light bulbs and self-driving cars, the IoT will bring to the physical world the kind of behavioral modeling and analytics that have been embedded in the digital world for years. Businesses are already able to apply lessons from the data they gather from IoT-enabled sensors to their own operations, and early adopters stand to reap rewards from this data approach, using it to guide development of next-generation consumer devices and even open up entirely new market segments.
Analysts predict there will be somewhere between 20 billion and 30 billion digitally connected devices by 2020, equating to a multi-trillion-dollar economic impact. Fueling much of that growth will be data—so much, in fact, that the torrent of data generated by the IoT will make big data look like a trickle in comparison. And if that data is to be useful in unlocking potential economic impact, then it needs to be mined for patterns and insights through the appropriate analytics. Fortunately, data science has matured to the point where we have the kinds of advanced analytics needed to answer the kinds of questions organizations want to ask of the data. Not just “what has happened?” but “what does this mean?” and “what should we do next?” And we can begin delegating some of that decision making to machines.
Through interviews with industry experts and analysts and examination of real-world use cases, a recent Forbes Insights report, “Harnessing the Internet of Things: How to Derive Big Business Benefits From the Connected World,” sponsored by Pitney Bowes, explores some of the potential opportunities and challenges inherent within the IoT—with a particular focus on data and analytics, the fuel the IoT runs on—as well as some recommendations for organizations considering the possible impacts on their own industries.
Bear in mind, the IoT may experience growing pains for some time yet. The Internet itself has been in widespread use (beyond academia) for around 25 years, and we’re still sorting out its implications. Regardless, businesses that are slow to plan for the IoT will quickly find themselves left behind.
Technology market intelligence firm IDC suggests that every business needs an IoT plan now, and that within five years all industries will have rolled out IoT initiatives. This is probably accurate at least with respect to businesses that depend on physical assets, meaning, at the very least, the conversations and strategizing for IoT disruption need to begin sooner rather than later.
Besides, the data generated by the IoT is a treasure trove of insights for any business. Analyzing this data will not only allow businesses to automate routine decision making—such as scheduling maintenance calls—but will support more complex decision making through prescriptive and predictive analytics.
And in a market where price is relatively structured, the pressure is on businesses to eke out larger margins by lowering costs and optimizing business processes on the back end—tasks to which the Industrial IoT is particularly suited. By collecting and analyzing data from equipment and machines, businesses can increase productivity, minimize or eliminate downtime, and better manage uptime.
The Internet of Things is a source of huge potential for businesses that move to capitalize upon it. That potential will be manifested in several ways: in businesses optimizing their own operations, in creating consumer-facing products and in the eventual monetization and learning from the data these generate. And, thanks to a burgeoning IoT ecosystem of platforms, developer tools and APIs, there’s no need to go it alone. Expertise can be plugged in, rather than developed internally, allowing many product development steps to be leapfrogged. But businesses should approach the available tools with a discerning eye and partner wisely with those that have the strengths and analytics robustness that will serve them into the future.
