So far, the Internet of Things (IoT) has mostly been considered as a technology challenge, leaving CIOs with the responsibility to define investments and lead implementation plans. However, it’s now clear that this technology can have a disruptive effect on key business processes – from production to logistics, from marketing to sales –, so it shouldn’t be taken from a technological perspective only.
Let’s consider a straightforward case. Key equipment of a chemical plant has a series of sensors to monitor and control operations and possible failures. If resulting data are not properly stored and analysed, if maintenance processes are not quickly aligned, benefits from this IoT efforts would be irrelevant.
Discussing the most interesting trends that are shaping the IoT business landscape, industry analyst McKinsey highlighted that IoT projects nowadays require a more disciplined execution. Businesses should compare multiple use cases before selecting the one to be piloted, implement it carefully and examine the lessons learned to move forward.
The Industrial IoT is gaining much traction, specifically in industries such as oil and gas, mining, utilities, and agriculture, while quickly progressing in automotive, complex machinery, and discrete manufacturing. One of the critical success factors in industrial projects is the effective management of IoT data and events. As McKinsey reports, data-centric businesses are getting significant value from their IoT investments: a leading global power company managed to reduce unit production costs by 33% over five years and save more than USD 9 billion in capital costs.
Moreover, organisations need to define whether to host the IoT environment in the cloud or on edge. In remote industrial facilities, or in situations with many mobile assets (think of aviation or transportation), data transmission costs are still high, thus performing some analytics at the edge – that is, adjacent to where data are generated – might be a cost-effective option. Autonomous vehicles face a similar challenge, and edge-based solutions are still to be preferred, at least until the broad availability of enhanced data-transport technologies such as 5G.
Last but not least, decisions around the IoT should consider two additional relevant elements: cybersecurity, that should not be a barrier to IoT adoption but needs to be cautiously scrutinised, and Artificial Intelligence, now being used in about 60% of new IoT implementations to take advantage of algorithmic advances and tackle data proliferation and increasing complexity.
The IoT is flagged among the most transformative technologies for businesses and consumers, but its landscape is changing quite rapidly, so we’d better keep up with emerging trends to leverage it in our organisations successfully.