If you haven’t heard the “data is the new oil” metaphor yet, you’re out of the loop. It dates back to at least 2006, when mathematician Clive Humby used it at a conference for British marketers. It’s been referenced repeatedly ever since. The analogy has its drawbacks. Oil is a finite resource, data is not. Data can be reused, oil cannot. Data has more variety than oil and so on. But bottom line: Like oil, data is a hot commodity.
But as Humby noted, oil out of the ground is useless unless processed R12; just like raw data. He continued, “It’s valuable, but if unrefined it cannot really be used. It has to be changed R12; into gas, plastic, chemicals or something else R12; to create a valuable entity that drives profitable activity. So must data be broken down, analyzed for it to have value.”
Instead of an oil refinery, analytics in IoT is the key to processing and putting that connected data to work. Whether it’s to improve routing in a smart supply chain, create better relationships with customers in a connected retail environment or monitor machinery with sensors in industrial plants across the globe, analytics in IoT — descriptive, diagnostic, predictive and prescriptive alike — has the potential to help organizations optimize processes, improve decision-making, automate tasks and increase business value.
There’s a lot to say about it — from building an IoT analytics strategy to considering edge analytics in IoT to solving the challenges of data waste. And while it may not happen overnight, with some planning and the proper resources, IoT analytics applications will help organizations get the most out of connected data, creating insights and wisdom, sometimes in ways never before imagined.