In my last post, I wrote about the progress Glassbeam has made this year, leveraging the increasing interest in IoT analytics in a wide range of industries. It is now clear that IoT analytics can dramatically improve business efficiency in everything from operations to product development and customer service. Here, I’d like to look forward at where Glassbeam sees IoT advancing in the coming year.
In a recent release, GARTNER PREDICTS that 6.4 Billion things will be in use in 2016, up 30% from this year. We believe that a significant chunk of the value derived from these connected things will be through analytics; and the biggest potential for IoT analytics in 2016 lies in industries like medical, industrial, data centers, that have millions of machines increasingly getting connected to the internet. The installed base of existing machines in medical, industrial and data center provides a very compelling business ROI to product manufacturers and services providers to connect, transport, analyze and create actionable information to reduce service costs, increase new product revenues and provide differentiation in an increasingly commoditized product hardware business.
Emerging industries like smart grids, smart cities, smart homes and smart buildings will gain new levels of efficiency and resultant revenues and profits if the manufacturers and service providers collaborate to standardize on data format, security issues, and data ownership issues. These industries have a disparate set of end points that are connected together to form a solution for end users.
IoT analytics will be successful in any application that brings new levels of customer intimacy and business intelligence through better customer service and support. Businesses buy high technology products to provide them year around 24x7x265 services without any downtime. The old paradigm has been that these products are prone to significant unplanned downtime due to hardware and software glitches and that has a significant negative productivity impact on the economy. If IoT analytics can provide proactive, predictive and prescriptive analytics to its user base, then these issues are significantly mitigated.
Just as consumers expect immediate gratification when seeking out information, ordering products online and in many day-to-day situations, those involved in analytics increasingly expect new insights in real time, despite the volumes of big data involved and the complexity of integrating different types of data sets. As the quality of analytics engines improve, speeding the integration of new types of data and production of new insights, IoT analytics will be relevant to an increasing number of industries and in an increasing range of functions within businesses.
Happy 2016 to all of you!