Early in 2017, it would seem that the internet of things is poised to have a large impact on the business world in the upcoming years. While it seems that in the realm of consumer products IoT has yet to present a compelling value proposition for most buyers, businesses are already seeing the benefits of collecting data from a myriad of connected devices and sensors, and then using this data to optimize ongoing processes.
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This is particularly true in industries such as energy, transportation and manufacturing — with Business Insider predicting that global manufacturers will invest $70 billion in IoT solutions in 2020. Other industries such as healthcare and telecom are also introducing wearables, smart devices and sensor data to gain unprecedented real-time understanding of their operations.
What do with all this data?
This wealth of new data sources naturally leads the business world to think of ways to introduce IoT to another growing IT trend, which has already gained mainstream traction — namely the world of business intelligence (BI) and data analytics. Obviously the sophisticated tools and technologies developed to rapidly query and visualize large, disparate datasets could prove useful when trying to drive insights from the massive streams of data generated by IoT devices.
The need for such technologies become even more acute considering the findings of a recent report by Verizon (requires registration), which states that “despite the huge revenue potential that data monetization presents, our Oxford Economics study found that today only 8% of businesses are actually using more than 25% of their IoT data.”
The BI industry could offer solutions for companies that work with IoT technologies by providing them with the same visual techniques employed by business analysts to create dashboards and analyses from traditional databases. IoT data is often different in that it is less structured and more volatile than most sources, but as business analytics matures and grows capable of tackling increased data complexity, modern BI tools will undoubtedly present benefits for driving increased business benefits from IoT.
In this model, the relationship is one-way: Data is pulled from IoT devices into an existing data mart or data warehouse, and BI provides a layer for visual analytics based on the massive datasets being generated. And while this use case is definitely viable, there is another often overlooked potential for combining the worlds of BI and IoT: namely, using IoT devices as a means to consume and interact with business intelligence insights.
A two-way relationship
In this model, IoT devices are more than mere data sources; they are a way for the business to communicate the results of data analysis to line-of-business business employees and to create more data-driven organizations by bringing the data physically closer to the people in the organization, and to represent it in new audio-visual ways.
While there is a lot of hype around the term “data-driven,” the fact of the matter is that for most business workers — i.e., those without an IT or data analysis background — access to data is often far from immediate or obvious. Some departments, such as marketing, have grown more accustomed to using analytical tools in their daily work; others, such as human resources and sales, are often less familiar with the various digital systems used to generate reports, mash-up data or create dashboards.
These types of less-technical users might want to adopt a more data-oriented strategy and work based on measurable KPIs — but they don’t necessarily want to log into a dashboard application every few hours and learn how to use this new and powerful digital system merely to know that they are on track in terms of a handful of KPIs. They need simpler, more streamlined ways to interact with the data, one that would actually correspond to their use case.
This is where the IoT comes in: The beauty of all of these connected devices is not merely their ability to transmit data, but also to receive data through the World Wide Web and change their behavior accordingly. By connecting IoT devices such as smart lamps and wearables to business intelligence systems, end users can receive instant notifications for important changes in their data — through a change in light, sound or vibration of a wearable device. This gives them a cue to interact with changes in their KPIs by taking an appropriate response (e.g., a retail store manager sees a contextual light switch from red to green, indicating a drop in sales).
Further potential lies in the use of personal assistant tools (such as Amazon’s Alexa or Apple’s Siri) within smart BI applications, to enable users to have a voiced, natural-language conversation regarding their data and KPIs. This again serves to make data analytics more accessible by removing the dashboard — which in this case is a somewhat unnecessary “middleman” — and connecting the business worker directly with the data.
More to come… soon
We are now at the tip of the iceberg when it comes to IoT. While BI technology is reasonably mature, we are yet to see exactly where the IoT train is headed and the ways in which it will manifest itself in the business world. However, the growth trajectories of these two industries — alongside other emerging technologies such as machine learning and natural language processing — is sure to introduce new intersections and combinations, as well as new data-driven methodologies within the business world.
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