Data Analytics for IoT: Business Transformation through Connected Products

The era of big data is upon us. With the advent of the Internet of Things (IoT), companies have access to more information than ever before. Employees sit in Internet-connected chairs in rooms with remotely monitored HVAC systems. Industrial buildings, built by cranes with pumps whose IoT performance monitoring can be seen on an iPad, feature Internet-connected pest-control traps that send text messages to sanitation workers when rodents have been caught. Employees go home to Internet-connected garage doors, lights, and thermostats that can all be controlled from a smartphone.

Although a staggering amount of information is gathered every day from IoT connected products just like these, the companies that have access to it are not necessarily using that data effectively. As Tim Harford of the Financial Times notes, “Big data has arrived, but big insights have not.” Useful data analysis requires much more than the simple collection and summary of data. Companies must have a long-term IoT analytics strategy in place to provide significant, actionable insights that will fuel their business transformation from a product company to a connected product company. That strategy must begin with a solid IoT product deployment foundation and include the purposeful creation of a data pipeline, from the developing processes for data gathering to leveraging algorithmic predictions to inform business decisions.

Analytics within the context of connected products can be broken down into stages of analytics maturity, introducing machine learning and the prospect of automating device behavior along the way. Enterprises building connected products can realize the full potential of IoT by turning data into action that produces business results.