Tapping data reserves to extract value

Modern businesses are swimming in an ocean of data thanks to the Internet of Things, but they are still coming to terms with how to distil all that data into actionable insight that delivers tangible business outcomes.

Smart home IoT devices might be the hot new thing in consumer electronics, but it is wrong to assume that IoT’s practical applications are mostly consumer-focused. There are valuable use cases for IoT across every sector and vertical, from manufacturing and healthcare to retail and facilities management.

By the end of 2020, 5.8 billion automotive and enterprise gadgets were expected to be connected as IoT devices, according to Gartner. By 2023, the average chief information officer will be responsible for more than three times the endpoints they managed in 2018.

With this IoT boom comes a torrent of raw data, with the data generated by IoT devices globally predicted to reach 73.1 million petabytes by 2025, according to IDC. Most of this will consist of security and video surveillance, but industrial IoT applications will also make up a significant portion.

Furthermore, IoT has the potential to generate more than $4 trillion in economic value by 2025, according to McKinsey.

Extracting this economic value from vast troves of raw IoT data would seem like searching for a needle in a haystack, but the biggest hurdle is not technological challenges. Instead, it is often the lack of a cohesive IoT strategy.

Rather than dive in the deep end with grand multi-year deployments and embarking on a fishing expedition in terms of useful applications, each stage of an IoT rollout should focus on proven use cases that unlock business value and deliver a clear return on investment.

The low-hanging fruit could be as simple as monitoring office building temperature and humidity levels to optimise heating and cooling – extending the lifetime of the HVAC system while reducing energy bills and the organisation’s environmental footprint.

In factories there can be a misconception that embracing IoT requires replacing existing machinery, but it is often possible to tap into existing sensor outputs or retrofit sensors to older machinery. This allows organisations to take advantage of real-time performance monitoring and predictive maintenance to reduce costs, improve efficiency and increase uptime.

Many organisations fail to make the most of IoT, not because they are ignorant of the available opportunities but because they do not know how to capitalise on them, says Craig Adams, CEO of Australian-based global data analytics company Canopy Tools Group.

‘‘A staggering amount of data is collected by connected devices and there are vast data lakes across the world, overflowing with IoT sensor readings and other valuable information,’’ Adams says.

‘‘Despite this, very rarely is that data used to its full potential – analysing it, learning from it and turning it into actionable insight which can make a real difference to the business.’’

Canopy began life hosting data centres but has evolved into an IoT-focused data analytics company that allows businesses to securely host workloads, applications and IoT data. It closed a $21 million pre-IPO fundraising round in advance of a potential float in 2022.

Canopy’s customer base extends across healthcare, defence, education, facilities management, government, housing, tourism, biosecure cruises and mid-tier organisations.

While IoT use cases vary from industry to industry, one common theme is that evaluating the possibilities of IoT is often the catalyst that encourages organisations to take stock of all the data at their disposal.

‘‘Once they start to take inventory of their data sources and assets they can discover that it’s a lot more disparate and fragmented than they realised,’’ Adams says. ‘‘It’s a good opportunity to get their house in order.’’

The biggest challenge for most organisations is not deploying IoT infrastructure or ingesting data. Instead, the greater dilemma is determining which business challenge they want to solve and therefore deciding what insight they need to extract from that data.

Rather than gathering an overwhelming amount of data and then contemplating what to do with it, Adams says the best approach is to define outcomes and then work backwards to determine what kind of insight is needed, which data are required and how to gather and ingest that data.

This approach helps organisations address their most pressing issues and achieve rapid transformational results.

‘‘It’s important to remember that data itself is not the answer, data itself doesn’t provide an outcome,’’ Adams says.

‘‘Instead it’s all about what you do with the data – it’s the action based on insight that’s important. The data is just a mechanism to get you there.’’