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Harnessing big data to make precincts

“Just think of all the things that have come and gone in our own lifetimes, all the would-be futures we watched age into obsolescence – CD, DVD, answering machine, Walkman, mixtape, MTV, video store, mall. There were still some rotary phones around in our childhood – now it’s nothing but virtual buttons.” Rich Cohen, The Bestest Generation.

Just think what this means for the future of places. The age-old tradition of making buildings, places and cities by hand, by craft, by precedent, by discipline, by bespoke design, by mass production, by CAD, by BIM. It’s time to bring big data into the mix and get a handle on the power of data to shape the future of our precincts.

Big data and how it informs place
Big data surrounds us, it’s generated every minute of every day and is changing the way we live our lives. ‘Big’ refers to computational data that is too large and complex for traditional data processing to deal with. A step into the world of big data means a new language: data capture, data storage, data cleaning, analysis, search, share and transfer. It is also about visualisation to interpret, understand and apply information.

As a starting point, we are beginning to use data to understand when, how and why crowds form, and to predict their movements and actions.

In 2017, Transport for New South Wales released some of its Opal data, enabling research into the aggregated movement analytics of commuters based on real-time, real people data for the region. Granular and dense, the information maps origin, destination, time spent in location, customer preference and movement behaviours, to name only a few insights. Every tap of the Opal card allows us not only to better understand the customer, but also how to build destinations for them.

We’ve got it, but how to use it?
So now we have big data, what can we do with it?

The new precinct designer will be part creative, part scientist. New courses offered by institutions, such as the Urban Science offering at the University of NSW, tells us academia is ahead of practice in understanding the power of big data to the creation of place.

In 2016, I was part of the Urban Development Institute of Australia’s NSW City Life Labs program. The Value of Connectivity research set out to use big data to understand where best to locate infrastructure to facilitate growth in metropolitan Sydney. Taking part in the research were academics, data analysts, advocacy groups and industry practitioners. Very much a data/city-making mash-up and journey of discovery, the key lesson learnt was the power of data set correlation with respect to the key urban questions of our time. In other words, we asked the data analysts in which centres in Sydney people appeared to stay the longest and why? Using Opal data, could we see which public transport hubs had the longest diurnal stay and, using ABS data, could we correlate this tendency to linger to the types of retail, jobs, entertainment and living environments happening in those locations? With cautious, baby steps the resounding answer is ‘yes’. It also highlighted anecdotal evidence between what people say they do versus what they really do.

The research quantified that the people of the Northern Beaches, who say they live work and play in the Northern Beaches, do just that. But the people of the Sutherland Shire, who also say they live, work, and play in the Sutherland Shire, rely on Sydney’s central business district for employment and entertainment, providing a gap analysis between truth and desire.

What does this mean for creating retail precincts?
The COVID-19 pandemic world has seen laser focus on the behaviour of the customer. For the time being, our lives are centred around our homes and the distance to our local shops. While we settle into this emerging lifestyle, the artificial intelligence systems around us are busily mapping and analysing our new patterns of civic engagement and providing critical data around what we buy, where we buy it, where we exercise and for how long, and even if and when we need to attend a healthcare provider. Necessity is the mother of invention.

Smart tech providers, like Sydney start-up me&u, are revolutionising contactless ordering in restaurants and cafés. In doing so, the technology in our hands is rapidly shifting the long-known desire for mixed-use precincts to customer analysed abject need for collocated convenience retail and entertainment, work from or near home, recreation, exercise, health and wellbeing and more. The potential for big data to inform and confirm these property decisions is immense, and the potential for machine learning to anticipate the needs of a demographic, society and contextual place is even greater. We are living proof of this right now.

The way forward
The real value of the destination and place-creating professions of the future will be to apply the knowledge garnered through big data and its cousin, technology, to the real-world experience of the customer, of the people. We need to introduce to contemporary precinct-making the overlay of big data information to support, enable and shore up our desire for smarter, more resilient and deeply genuine places. But, we can’t rely on machines alone, at least at this stage, to understand the visceral, emotional and distinctive responses humans have to places. And for that reason, the place-creating industries are safe, for now.

This essay is an adopted extract from “Harnessing Big Data to Make Cities” in The Place Economy Volume 2.

About the author

Michelle Cramer

Michelle Cramer is a City Shaping Executive and Urban Precinct Specialist

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