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How big data population analytics will shape the way we build, plan and manage

By spring 2024 the United Nations estimates that the world population will reach 8 billion, more than four times what it was in 1924. It's also estimated that by 2030, 60 per cent of us will live in a city, that's compared to 20 per cent 100 years ago.

Unsurprisingly, this global population explosion and rural exodus is putting untold stress on our city infrastructures, particularly our transport networks, most of which were designed for a different era altogether.

Global leaders are increasingly looking to technological innovation to help measure and respond to the world's burgeoning people management issues.

Understanding global population pressure points is the very first step in the design of smarter cities that are better placed to cope with a far more people saturated millennia. Key to unlocking these crucial insights are mobile operators and an increasing number of devices connected through the "internet of things".

Introducing population analytics

Around 1 in 5 people in the world has a smartphone, and in the UK smartphone penetration has reached 70 per cent. These figures only scratch the surface with regards to the "internet of things", due to the proliferation of other connected devices such as wearables and connected cars.

These devices transmit anonymous location data that when aggregated can show accurately how whole populations flow – hence population analytics, a data-driven analytical technique for answering questions about large groups of people. Already, the sheer volume of mobile data available means that sample sizes correlate statistically with real-world population volumes.

Fuse this information with other accurate sources of location information, such as GPS data from connected cars (INRIX provides services to and collects data from eight of the top ten connected car manufacturers globally), and analysts can begin to understand the origins and routes taken by populations.

At INRIX, we collect billions of data points a day; combining and analysing anonymous data from more than 100 million connected cars, satellite navigation systems, fleet vehicles and road sensors to get a clearer picture of what's happening on roads around the world in real-time.

So how can population analytics help?

Population analytics is in its infancy, however the potential use cases are almost limitless. Its power comes from its ability to understand not just where anonymous groups of people are at a given time, but where they have been, how they got there and where they may be going next.

To understand the value of this in practice, consider a local authority planning a major event. Large scale events are likely to cause disruption to traditional population flow within an area, which in a best case scenario may result in minor delays and increased congestion on transport systems, but worst case could increase the security and safety risks in a highly populated area.

For authorities planning for these events, population analytics can be used to see where people typically travel from or to when visiting a venue. Using this information, organisers can identify patterns within the population and offer more tailored advice on the best times to travel, the most effective transport routes even set-up roadside alerts in areas that are identified as pressure points.

It's not just useful to event planners either. For city planners and transport consultancies in charge of planning buildings, roads, bridges and railways, for example, population analytics is a vital tool. For instance, it can be used to help determine the optimum location to build new transport infrastructure or to manage parking costs or to establish tolls roads based on population flow.

Population analytics can even be applied to the commercial retail environment, as big data allows retailers to identify what percentage of customers visiting their stores originate from which post codes, to better model customer demographics and create more tailored marketing offerings.

The challenges of population analytics

One of the biggest challenges of population analytics is that mobile operators don't necessarily have the expertise to accurately interpret large amounts of data from multiple sources. The intricacies of mobile technology can make it difficult to resolve to the level of detail needed to build accurate models of dynamic populations.

However, if you combine mobile data with other location-based data, such as mapping, routing and GPS data, the population picture becomes far clearer.

Ultimately population analytics is not a solution that operators need to tackle alone. Most operators lack the infrastructure and necessary algorithms needed to process and integrate large volumes of anonymised data. There's no question that the data they hold is incredibly valuable, but it must be applied and interpreted in a wider context to yield actionable information for potential purchasers.

To do this mobile operators would need to invest in invest in large, costly and time consuming technology infrastructure as well as source and process unfamiliar datasets and apply this insight in unfamiliar markets, which may leave them behind their competitors. Alternatively, mobile operators need to partner with big data companies, who have the data skills, algorithms, infrastructure and experience to generate accurate and meaningful results on national scales.

The future of population analytics

During the London Olympics, our company experienced first-hand how population analytics can be usefully applied to population management.

Working with Transport for London, we were able to analyse real time population flow across the capital and model the potential impact of various events so that organisers could better advise both spectators and Londoners on travel during the games. What was possible during the London Olympics is just the tip of the iceberg.

As connected things and devices proliferate, what we understand about human behaviour from the analysis of data will become infinitely more powerful. Ultimately as global populations expand at an ever increasing rate, the strain on existing infrastructures will be considerable.

Big data and population analytics, when effectively applied, will be an invaluable resource for city planners, transport consultancies, retailers, insurers and even financial services companies, and many more looking to navigate this change.

Danny Woolard is vice president of business development for EMEA at INRIX