What if you could establish that specific air temperature, pressure, humidity, and wind-speed readings were correlated with increases in ice cream sales?
Creating business value from the Internet of Things (IoT) is not just about the data, as the Big Data refrain often has it. It’s about creating actionable intelligence for employees and customers alike. It’s about possessing the understanding that a shopper standing in front of a product on a store shelf is of little or no value without layers of contextualised knowledge.
With location-aware services, retail operators and product manufacturers can collaborate in offering customers onetime discounts or special offers. To have the greatest impact, these offers must be personalised by utilising accurate data describing the customer’s current position and past buying behaviours.
Being effectively productive in the IoT realm means going beyond simply reacting to data. It means being able to tease out cause-and-effect patterns in data so the enterprise can respond to events before they happen. It means boosting organisational agility.
When Smart Cars Go Dumb
Consider the sensor-laden autonomous vehicle. Today these vehicles are essentially siloed devices. A single vehicle measures everything around it and leverages the data almost exclusively for its own use. But what if that data was actively published, networked, and shared? What if the sensors in these vehicles interacted with sensors in other vehicles?
That same siloed vehicle data is suddenly transformed into an intelligence network for a traffic flow ecosystem. Proximities to traffic events could be communicated. Engine operations could be altered. Speeds could be adjusted. Traffic signals could be re-calibrated. Travel paths could be rerouted. And all of this could be executed on the fly.
Turning Data Streams into Revenue Streams
Turning IoT insights into productivity means leveraging new contextualised information to automate business processes and drive predictive capabilities. When used in this way, data essentially becomes magic, predicting future behaviours and outcomes. Rolls-Royce does this by monitoring a broad range of jet engine parameters while an aircraft is in flight.
When engine performance measurements transposed over data-generated cause-and-effect patterns indicate potential problems, the company arranges to have maintenance crews waiting for the aircraft when it lands. These potential problems can then be proactively repaired before they result in downtime and safety hazards.
Savvy use of data generated by the sensors could be used to create value directly. For example, what if you could establish that specific air temperature, pressure, humidity, and wind-speed readings were correlated with increases in ice cream sales? You could collect real-time weather measurements combined with crowd densities for specific urban micro-climates, package them as spot reports, and sell them through an iTunes-type platform. These spot reports could be used to make just-in-time inventory, price, and location adjustments.
Your Next Offering: Using IoT to Drive New Services
With contextualised data generated from IoT networks, enterprises can make staffing, product, inventory, and price adjustments based on correlations with, and anomalies in, data sets from external environments. From an enterprise perspective, everything feels predictive, fluid, and dynamic. From a user perspective, everything feels a bit more personal. And that’s where the true value comes in.