Industrial firms need IoT use cases to tap big data

May 4, 2015

Driven by the expanding Internet of Things (IoT)—connecting billions of physical things to the Internet—big data hype and trillions in spending are shifting from banks, retailers, and telecoms to farmers, manufacturers, and oilfield operators. But big data vendors’ current offerings don’t fit with complex equipment, tons of materials, and moving machines in ways that can drive profits. Companies offering sensors, cloud computing, and analytics tools are beginning from the wrong end, if the goal is to create an ideal platform for the industrial Internet, according to Lux Research.

“Big data products and services have had an easy time so far, with existing data from point-of-sale systems and online stores basically handed over from one computer to another. But starting with available data won’t work in material-centric industries trying to implement big data visions like precision agriculture, ‘Industry 4.0’ in manufacturing, digital oilfields, and intelligent cities—because the important data isn’t captured anywhere yet. Instead, these industries need to start with the business problems to be solved, and deploy new networks, sensors, protocols, and analytics to capture and crunch that data,” said Mark Bünger, Lux Research director and the lead author of the report titled, “Information Meets Matter: Devising Big Data Strategies for Real-World Industries.”

Lux Research analysts evaluated how industrial firms can tap the potential of big data to transform themselves in the Internet era. Among their findings:

IoT will disrupt physical industries—in time. PCs, the Web, and smartphones created the first waves of disruption using big data for consumers, finance, and retail. The Internet of Things will similarly transform material industries, from the intelligent oilfield to personalized medicine. Still, the disruption has been slow in coming because of longer lifecycles of physical equipment, the higher risks to humans and environment, and high up-front capital costs.

Companies must establish a business case. In the case of big data, the costs of hardware, software, and implementation can run into the millions or billions—before any payoff comes. Consequently, even the most apparently beneficial use case needs a business case to significantly reduce process costs, increase product/service revenue, or tilt competitive dynamics in one’s favor.

Big data enables big goals. The strategic opportunities stemming from big data in a particular industry boil down to two things: new sensors feeding the big data, and new kinds of analytics one can run on that data. Precision agriculture, for example, aims to provide more food at lower cost to people and the planet; intelligent buildings and cities need energy efficiency and security and smarter water management. Integrating IoT and big data is key to all these goals.

The report, titled “Information Meets Matter: Devising Big Data Strategies for Real-World Industries,” is part of the Lux Research Big Data Intelligence service.

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