Here is a recap on Internet of Things (IoT) : First, in the simplest terms, IoT deals with physical devices that generate data from sensors and send the streams of data via the Internet to some kind of “hub” for data collection, visualization, and analytics. Second, IoT deals with multiple types of sensors and data formats. Third, IoT solutions might deal with thousands and millions of connected devices and huge amount of data.
Now, Billions of Internet-connected ‘things’ will, by definition, generate massive amounts of data of varying complexity, formats and timeliness. This is just a swamp, especially if all you do is collect data and don’t do anything with it. For example, Insurers pay more than $1 billion in claims in the United States for cars and trucks damaged by hail. Can Weather Company’s weather data make it possible for insurers to send text-message alerts to policy holders, warning them of an imminent hailstorm and advising them of safe locations nearby? Note IoT will make it possible to identify the exact location of these cars /trucks and identify the owner to send the text message!
Therefore while many people focus on the devices themselves— how they function, how they perform and how they look—the real opportunity is in the data these devices are consuming and generating and the value it provides for businesses and even entire connected cities. Retailers will piggyback on Analytics, and use IoT to pull consumers into one of their channels, where they will entice them with products that have been contextualized and personalized for the customers’ gratification. And there will be similar usecases for manufacturers, servicing organizations, public utilities, industrial, telecommunications, healthcare providers and more—to serve their customers in new, personalized ways. Using predictive, prescriptive, cognitive and investigative analytics will make it possible for organizations to discover new relationships and correlations that bring together broader and deeper insights that lead to smarter business decisions in terms of risks, costs, growth, customer service and other things.
What all will be required for organizations to harness the power of Analytics and what will be the challenges? Stay tuned.
Disclaimer: The postings on this site are my own and don’t necessarily represent IBM’s positions, strategies or opinions