Smart: An intelligent approach to IoT data


By Luc Vidal-Madjar, head of mobility innovation at BICS

The rapidly expanding Internet of Things (IoT) is engulfing every industry and every object in its path. Its embrace is turning dumb devices into smart gadgets and opening new insight-based revenue streams for businesses. Consumers too are getting clever to the IoT, driving connected device sales and a culture of data sharing.

Yet the IoT is somewhat of a misnomer; the current landscape would more accurately be described as the ‘Intelligence of Things’. Yes, like Cerf’s internet, the IoT does encompass interconnected networks via which information is exchanged and accessed. And yes, the hardware and products which make up this network do play a key role.

However, the terminology does not do justice to the new experiences, customer service, societal benefits and sheer untapped intellect of the ecosystem. Indeed, the proliferation of ‘smart’ objects we’ve seen in recent years have been bestowed that titled not solely based on their technological capabilities, but because of the intelligence and insight which can be mined from them.

Flooding the market

Devices continue to flood the market. IHS Markit [IoT Trend Watch 2017] has predicted that the rise in the number of smart objects in 2017 will jump 15% year over year, reaching 20 billion. Device designers and manufacturers, as well as those producing the associated software and components, have no doubt seen profits soar as a result of these devices entering the IoT. Yet it is the smart analysis and utilisation of data gathered from these gadgets which will really drive profit.

Companies are rightly buying into the IoT; almost a third of businesses worldwide had live IoT projects last year and 76% said that IoT will be ‘critical’ to future success, according to a Vodafone report [The IoT Barometer 2016]. Yet it is vital that these companies’ data gathering and analytics strategies keep pace with device development and deployment, or this success will never come to fruition. Deploying such a strategy requires a collaborative, business-wide approach and for many companies a shift in outlook.

Even with knowledge and expertise in data analytics, all companies looking to profit from the IoT – and improve customer experience – will need to re-examine their approach in this area. IoT data really is Big Data; collected from a huge number of sensors, geographies, devices and the cloud, it is unstructured, with streams of information available from an array of sources in real time. The success of any IoT project, to drive revenue on the business side, and to provide new, better and personalised services on the consumer side, therefore lies in a company’s ability to intelligently harness and capitalise on data.

Currently, only one third of organisations in Europe are analysing data generated by their IoT initiatives [IoT & the Data Analytics Challenge, Telefonica 2017], meaning the majority remain ignorant to its potential, and are failing to make the most of their investments in this area. This lack of IoT data insight means consumers too are missing out. New business models must be adopted to address this, supported by tools to assist companies in monetising data.

Factors for success

There are number of factors which are crucial to successful IoT data analytics. Continuous, 24/7 visibility of data is a must, with insights available in real time across the entire spectrum of a company’s IoT project. This encompasses the potentially vast array of devices and sensors, networks and interconnections. A company must have a clear view of current data, as well as of historical network and business intelligence across all technologies. A platform must provide data collection about asset performance and customer behaviour, helping companies to understand the customer journey in granular detail, and manage quality of service (QoS). This will facilitate improvements to existing services and the launch of new ones.

The impact of a disruption on an IoT network can be severe and wide-ranging. Whilst building a connected environment of devices, people and services can be beneficial, on the flip side, any negative activity can rapidly filter network-wide, causing disturbance across the entire IoT infrastructure. Data traffic irregularities on IoT networks need to be spotted immediately, varying from anomalies identified by physical operating equipment, to shifts in consumer behaviour or traffic.

Over a quarter of companies admitted that security and privacy concerns were a chief obstacle to investment in the IoT, according to The Economist’s Intelligence Unit [2017]. A tool which highlights potential problems in a company’s IoT network is therefore crucial to ensure a network, and all associated data and devices, are reliable, safe and performing at optimal levels at all times.

We are at an exciting time in the development of the IoT. Early investors in devices and services have been reaping the rewards of consumer and enterprise adoption. What is now required is an intelligent approach to the IoT. This will involve companies adopting the analytics tools and methodologies to capitalise on this new era of (very) big data.

BICS is a global voice carrier and the provider of mobile data services.


About Author

Comments are closed.