My youngest son used to say that our fridge should be able to send a message to the supermarket to deliver milk when a carton is almost empty. This certainly shows that the Internet of Things (IoT) meets the expectations and demands of the young generation, and it also raises a question: if the fridge can order milk from the supermarket, it has to hold data about the groceries we want to buy… so what happens to that information?
The smart answer is: IoT data monetization
For telecommunication operators, the IoT – from smart fridges in smart homes, to smart healthcare and even smart cities – is a huge opportunity. CSPs, with their technology, access to data and software, and experience in delivering sophisticated solutions, are ideally placed to cooperate with vertical enterprises already using the IoT to become more competitive, attract new customers, improve business efficiency and lower operational costs. Not only that, there are possibilities to combine data from different IoT verticals – for example in a smart car that tells a smart home to turn on the heating when its almost home.
The vast amount of data generated by IoT devices, systems and software can certainly help organizations manage production, marketing and business operations so they respond better to customer expectations and thus become more profitable. And from that, it’s a short step to IoT data monetization. But, for this to work, a business case first needs to be developed. What kind of data should be collected? What will the information be used for? What value will data analytics add? And what kind of business intelligence tools will be used to mine data? Once these questions have been answered and raw data collected, actionable analytics tools can be used to collate, compare and store the information – even triggering pre-defined actions if certain parameters are exceeded. It is crucial that IoT actionable analytics tools operate on data from within the company and from outside – from partners, resellers and customers – as this increases opportunities for additional revenue.
Different verticals have different requirements for data analytics, depending on how they answer the questions above. But it can be said that all of them fall into one of three broad categories – those that focus on improving operational efficiency, those that are focused on customer-centric issues, and those concerned with new business models. What’s more, the best way of selling data analytics for every vertical in all three of these categories is in the analytics as a service model. As long as a service provider truly understands and is able to define how analytics provides business value to a particular vertical, both parties will benefit. To this end, the service provider should meet the vertical company’s need for a true partner, selling analytics as a service to help the organization develop and compete in the multi-faceted and technologically advanced IoT world.
Read more on IoT Data Monetization in our White Paper.