There are RFID sensors that can fit on bees.
Is it any wonder that Cisco estimates that the Internet of Things (IoT) is expected to generate $19 trillion in value?
The question isn’t whether companies will embrace IoT technology, but rather whether organizations will be able to make money from it, Capgemini Consultant Jerome Buvat warns in “Monetizing the Machine: Business Models for the Internet of Things.”
“Most organizations are yet to derive significant commercial value from IoT,” Buvat writes. “Our recent research shows that 70 percent of organizations do not generate service revenues from their IoT solutions.”
Buvat proposes four emerging business models that could lead to IoT payouts. If you regularly read this blog, you won’t be surprised to see “Harvesting data” as one of the IoT business models. Sensors are a bit like cicadas — they chatter constantly, with the chief difference being that sensors don’t stop when you get closer. Capturing, aggregating, anonymizing and selling that data will be a moneymaker for some companies. The idea is that companies or even customers will pay for that data if it provides insights or even advertising benefits.
Buvat points to Michelin Solutions, which generates data from sensors placed inside customer vehicles. Customers subscribe to the data because it gives them insights about reducing costs or their carbon footprint.
Other promising business models he identifies:
Profit models aren’t the only details that need to be worked out for the IoT; those include energy, bandwidth and security concerns.
And then there’s the data. The IoT will create new data challenges, including the question of where you process the data. One theory is that the sensors or network edge should handle most of the data, so that only the exceptions or particular data samples are sent to enterprise systems.
That may be a particularly useful idea for the Industrial Internet of things. In a recent Forbes column, logistics and supply chain writer Steve Banker looks at how either option might play out within a supply chain.
"IIoT implementations often quickly become Big Data projects as well. But in many cases, not all of this data really needs to be stored,” Banker writes. “An alert is a notification that indicates a parameter – for example, the minimum threshold for replenishment – has moved outside of the desired range. Unless that minimum quantity level has been violated, and an alert is generated, does this data really need to be transferred to a corporate database and stored? Maybe, maybe not.”
Pushing some intelligence out to the device will help reduce database bloat, he adds.
Loraine Lawson is a veteran technology reporter and blogger. She currently writes the Integration blog for IT Business Edge, which covers all aspects of integration technology, including data governance and best practices. She has also covered IT/Business Alignment and IT Security for IT Business Edge. Before becoming a freelance writer, Lawson worked at TechRepublic as a site editor and writer, covering mobile, IT management, IT security and other technology trends. Previously, she was a webmaster at the Kentucky Transportation Cabinet and a newspaper journalist. Follow Lawson at Google+ and on Twitter.