How data can help check – and change – our habits
The precarious human-machine relationship has long been explored on film – think Blade Runner, 2001: A Space Odyssey and Westworld – but it was 2011’s Moneyball that cast the spotlight on data mining and predictive analytics. The film showed manager Billy Beane putting his faith in behavioural insights to dictate how he formed and ran a baseball team.
Ten years on and the Internet of Things (IoT) fulfils that role, but on a previously unimaginable scale. Statista reports tens of millions of people have consciously chosen to spend an average of $550 a year on devices that actively listen to and track their behaviour. According to DataProt, this year the number of IoT devices has exceeded 10bn and is on target to hit 25bn by 2030.
So if 10bn smart devices are talking among themselves, do they actually have anything interesting to say?
What is the Internet of Behaviours?
It turns out they have rather a lot to say. While IoT devices gather and exchange information about our activities, movements and habits, the Internet of Behaviours (IoB) puts that intelligence into the context of human behaviour. The result: machines know what we’ll do before us and can even steer us in a preferred direction.
“Over the long term, it is likely that almost everyone living in a modern society will be exposed to some form of IoB that melds with cultural and legal norms of our existing pre-digital societies,” says Daryl Plummer, managing vice-president and chief fellow at Gartner. And the stats back this up.
According to Gartner, within two years, the activities of 40% of the global population will be tracked digitally as a means of influencing behaviour and by the close of 2025, more than half of the world’s population will be exposed to at least one type of IoB programme.
How does it work?
In most instances, data is willingly supplied by users to a specific device or app they own, but some companies share across devices. Your smartphone holds your internet search and purchase history but it also communicates with other IoT devices you own, for instance, an in-car camera intended for security. The pair chat and suddenly you’ve got insurance quotes in your inbox and adverts for new cars on your browser.
But the IoB isn’t only about our data footprint. “People’s behaviours are monitored and incentives or disincentives are applied to influence them to perform towards a desired set of operational parameters. What is really relevant about the IoB is that it is not only descriptive but proactive – detecting which psychological variables to influence to bring about a certain outcome,” according to Softtek subsidiary Vector ITC.
Who’s using it?
The benefits are clear for sales and marketing. Customer experience firm Purple says: “By tracking purchases, facial recognition and more, businesses can begin to map and predict behaviours. With this information, they can make decisions to influence their customers based on solid data.” Purple uses the example of a coffee shop, where smart cameras focused on customers in the queue, with one person served at a time. Data from the cameras highlighted the number of customers who waited to be served against those who left after an amount of time. “With this information, the owner could change the shop floor plan and create additional queuing space,” says Purple.
The days of producing products with short shelf lives are also numbered. With sensors installed in smart devices, manufacturers are already able to use the data acquired to understand how people are using a product and which aspects do and don’t work. The result: the second-generation product will be a better match to customer requirements, cutting back on unnecessary elements in the design and manufacture.
Influencing consumer decisions
For supply chains, the technology is currently being used to understand and predict employee and customer actions, but even here is the creeping use of IoB for influence. During the pandemic, one factory collected data on employee bathroom breaks and hand washing to control the spread of the virus. Subsequently, this data was analysed to understand the efficiency of operations and to actually influence employee actions. So however we choose to use this information in the future, for now one thing is certain – the machines are listening.