If you’ve ever consulted your fitness tracker, or conferred with Alexa or Siri, you know that it’s impossible to deny the proliferation of the Internet of Things (IoT). With so many “smart” devices on the market, it almost feels as if the science fiction scenes of the silver screen are on the brink of reality. (OK, fine. Uber’s flying taxi concept might not fall within these exact parameters, but the notion sure seems reminiscent of The Jetsons.) But, as connected IoT devices become integrated across the enterprise, these increasingly popular tools promise to provide important insights into how organizations operate.
IoT-enabled devices are on the rise, as Forbes indicates that the global IoT market will expand from $157 billion to $457 billion between the year 2016 and 2020. Manufacturing, logistics, and transportation will lead the way where investment and adoption are concerned. Gartner agrees, noting that, by 2020, more than 65 percent of enterprises will have taken up IoT to help grow their businesses.
Bringing Insight into Action
Connected devices have the capacity to collect an array of information that could prove critical to internal operations for companies. However, without machine learning technology, this insight falls into the same trap as the so-called Big Data of yesteryear because it can’t aid the decision process without the proper analysis. Forbes’ Insights survey supports the notion that, when analyzed properly by the right team, data from IoT can be useful in many ways. Among respondents operating IoT programs to generate incremental revenue, 55 percent said they were using connected data to create new services they could offer customers, while 44 percent said IoT was creating data and analytics they could sell outright.
“IoT-enabled devices are already being used for many different applications,” Forbes explains. “In some cases, the data they collect is used to communicate status, such as whether a device is running properly. In other cases, data is used to provide actionable intelligence that helps people (and machines) change their behaviors, or to provide a feedback loop that companies can leverage to improve the functionality and user experience of their products.”
When combined with machine learning, IoT data allows companies to take predictive analytics to the next level because actionable insight drives progress. Without backend systems to guide IoT data, this information becomes nothing more than noise or clutter. But, when paired with ML, IoT data can help these systems decipher patterns and determine where improvements are needed, thereby empowering companies to engage in proactive outreach or repairs.
Just as employees must collaborate effectively to achieve companywide goals, backend technologies must work together to create seamless experiences across the enterprise. IoT data cannot be brought to action without machine learning, and ML cannot succeed without this stream of insight.
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