Population Analytics: Making Sense Of Billions Of Data Points Daily

Population Analytics

It is estimated that around 90 percent of the world’s data has been generated over the last two years alone and every day we create 2.5 quintillion bytes more. There is no question that, if effectively applied, this data could prove invaluable to a huge number of public and private sector decision makers – from CEOs and CIOs of large businesses to transport consultants and city planners. The challenge is that data in isolation is like hidden treasure without a map – valuable, but ultimately inaccessible. Clearly interpretation is everything.

Unlocking The Potential Of Population Analytics

Essentially, population analytics is a data-driven analytical technique for answering questions about large groups of people – as its name suggests, whole populations rather than individuals. Its power comes from its ability to understand not just where anonymous groups of people are at a given time, but where they’ve been, how they got there and where they may be going next.

Still in its infancy, the application of population analytics to “big data” is already being heralded as a promising solution for businesses and governments looking to make more informed strategic decisions based on real time population data.

The Mobile Advantage

It’s worth remembering that although we produce quintillions of bytes of data a day, this data does not come as one easily digestible package. Data streams are often siloed and many organisations just have one piece of the big data puzzle.

Data from mobile networks opens up huge opportunities in population analytics. Today most of us routinely carry a handset, which means operators have access to a very large and evenly distributed number of sources. Although the sheer volume of mobile data available today means that sample sizes correlate statistically with real-world population volumes, the intricacies of mobile technology make it difficult to resolve to the level of detail needed to build accurate models of dynamic populations.

However, this data becomes infinitely more powerful when combined with other accurate sources of location information, such as GPS data from connected cars.

Population Analytics In Practice

The use cases for population analytics are virtually limitless. For example, for the London Olympics, Transport for London (TfL) combined mobile network data with connected car, road sensor and fleet vehicle data, to analyse real time population flow across the capital to model the potential impact of the various Olympic events. Using this information TfL could spot pinch points on the transport network in real-time to better advise organisers, spectators and Londoners on travel during the games.

The potential applications of population analytics extend beyond large scale events too. Below are just a few of the ways population analytics could be applied by different sectors:

  • Smart cities – existing city infrastructures are under strain, designed to suit an era when population numbers were far smaller. Now governments and public sector planners are tasked with extending and re-engineering our cities to cope with fast-growing urban populations. Using population analytics, smart city planners can determine how many people enter and leave a city, where they come from and where they return to. This is critical data for making informed decisions about everything from building new roads to implementing new bus routes and park and ride schemes.
  • Transport consultancies and urban planners – for those in charge of planning buildings, roads, bridges and railways, population analytics is a vital tool. For instance, it can help determine the most profitable location to build a store based on footfall, establish the optimum location and ideal access routes and parking based on typical and predicted population flow around the site.
  • Retail and marketing – population analytics can also provide unrivalled demographic insights to retailers and marketers. Although the “who” of course remains anonymous, “big data” can reveal what a store’s true catchment area is and the demographic and postal area of key markets. This in turn can be used as part of a location targeted marketing campaign. Furthermore, population journeys can be used by advertisers to make more informed decisions about which billboards to buy space on, based on precise volumes and demographics of passers-by.

Data In Context Key To Population Analytics

As more connected and trackable devices are added to global networks, the sheer scale of data we hold on population movements will continue to expand exponentially. However, big data only becomes truly useful in this context if large and multiple location-based datasets are combined and analysed in a wider context.

As populations expand and place an ever increasing strain on national infrastructures, those companies that can deliver true insight around population patterns will make themselves invaluable to governments, city planners, retailers, insurers and many more looking to manage finite landscapes and resources.

Danny Woollard

Vice President of Business Development, Danny Woolard leads efforts to develop and manage INRIX’s public sector business across EMEA. Danny brings to INRIX more than 20 years of technical, operational and business development expertise in the traffic information and driver services market. Most recently, Danny was General Manager of Operations for Australian traffic and telematics service provider Intelematics where he led efforts to scale the company’s infrastructure and improve quality to meet market needs. Previously, Danny was Technical Director at ITIS Holdings where he launched Europe’s first RDS-TMC based-traffic service in collaboration with Toyota, BMW, Ford and Daimler.