When it comes to IoT data, one thing is certain: analysing it continues to accelerate as companies get better results by including sensor-based / IoT device data in their decision-making process - and there is no slowing down in sight. We see this in particular on the IT side - as IT spending increases, so will the investment in IoT. Organisations will build on hardware and connectivity layers supporting IoT as well as the services and analytics software to integrate IT, security, transactional and IoT data.
And this makes sense - for organisations looking to expand their existing data footprint, IoT is the logical next step. Companies that are successfully integrating their IT, operations and transactional data are now looking to ingest and correlate IoT data into existing infrastructure.
The risk is real
On the security side, IoT brings a tangible risk. As we continue to entrench our daily lives with more ‘connected things’, we drive both new levels of innovation, and at the same time, open ourselves up to a security minefield. In 2018, security for IoT isunder heavy scrutiny. Cyber security risk is increasing exponentially as people, processes and businesses continue to connect every part of our daily lives and our economy. Each ‘connected thing’ opens new doors into personal intelligence, corporate intelligence and public safety. Through these doors we open ourselves up - as individuals and organisations - to new weaknesses hackers could exploit. We are looking into a future where attacks can be orchestrated not just from public networks, but from private devices such as a smartphone or a smart home. So, while the IoT revolution is exciting, consumers and businesses should be thinking of the tradeoffs. This will be particularly relevant to businesses where a breach will lead to a potentially fatal loss of consumer trust. Gartner predicts that by 2020, more than 25 percent of identified attacks in enterprises will involve IoT, although IoT will account for less than 10 percent of IT security budgets. This gives businesses something to think about.
industry adoption first?
The most value from IoT comes from solving complex logistics, manufacturing and public sector problems. That means there are some industries that will see tangible benefits faster than others:
- Public Sector - with increasing connectivity between people, data and things - the sector is embracing smart technology, using sensors and automation to enhance the reliability of services, especially in the areas of safety and environment. IoT sensor data enables use cases including improved air quality, optimized traffic patterns, reduced safety incidents, traffic fire incident prediction, and improved citizen identity.
- Manufacturing holds the position as the leading IoT industry, with predictive maintenance use cases driving the transformation. Organisations are continue to invest in improving operations and driving predictability in equipment downtime.
- The transportation industry, airlines and airports in particular are pushing the boundaries in adopting IoT data. This industry is now using real-time airport, aircraft, weather-sensor and passenger information to improve operations and deliver better customer experiences.
Cloud & digital transformation: the great enablers
Cloud spending enables new flexible business models making it easier for small and medium businesses to adopt IoT. For larger organisations, cloud investments orchestrate global-data integration. AWS IoT for example, serves as a central platform for devices, assets and sensors wherever they happen to be located. When you couple this with security and data ingestion, the cloud makes IoT successful.
Digital transformation initiatives - especially those centered around customer experience - will drive IoT expansion velocity. Building a technology infrastructure is relatively easy. The challenge is operationalising data-driven decision-making that impacts the health of the business. Traditionally companies have invested heavily in the infrastructure, and then into solving for IT and security data-driven use cases. Organisations that are only beginning to integrate IoT data will begin asking the questions - how do I innovate; how do I drive revenue and better customer experiences with the new information I have available?
Machine learning
Machine learning and artificial intelligence represent a tremendous opportunity to IoT. The increasing commoditisation and scale of sensor devices will drive a new wave of smart industries and have significant impacts on existing ones. Being able to predict when machinery will need to be repaired, self-optimising production, and demand response are only a few application examples.
With existing network infrastructure likely to be used for ‘connected things’, the investment spend on analytics technology will be higher as companies find new ways to make sense of the vast amounts of smart device-generated data. Industrial asset management, fleet management in transportation, inventory management and government security are the current hottest areas for IoT growth.
