Building on data’s base

19 December 2017

As published in 'Fluid Futures'

The ability to analyse data from a range of sources in the existing built environment holds the key to creating flexible, future-proofed developments tailored to the requirements of occupiers and investors.

‘Big data’ is often misunderstood, being conflated with metadata and data mining. While there can be some connections with these processes, in property development, big data is distinct and is frequently becoming an essential part of the development process.

The ability of big data to help owners, investors and landlords respond to future trends – known as ‘future-proofing’ a building – has made such buildings “a flexible format with an integrated and robust digital provision that will deliver an authentic setting that can change, adapt and respond”, says Benoy director Robert Bentley.

Big data has always existed, just never as accessibly as it does now. Big data is the ability to gain useful insights and make decisions by collecting, storing and analysing a wide variety of diverse and seemingly unrelated data sources, says Kevin Kincaid, director of IT programme and development at developer Grosvenor Group in London.

Those sources are generally volume (the amount of data available), variety and velocity (time). “Big data has moved from ‘having data’ to ‘using data’,” says Kincaid.

Melanie Alshab, chief operating officer at NWP Retail in Jakarta, agrees. “To do this kind of thing 10 years ago you had to build very expensive systems. Now we have those tools.”

Data can be as basic as counting cars and analysing flight ticket prices.

As omnipresent as data may seem, its influence is still in its infancy. Learning to read it and use it effectively is the challenge.

Alshab says: “One of the key things about big data is that a lot of it is unstructured, or structured in a way that data used to be structured” – in static, columns and rows of information ready for extraction. But she adds: “It’s messy and there are globs of fluid information that change all the time.”

Adapting to future changes

Investors and developers use this data for what Alshab calls “rightsizing”: finding and evaluating the right location; building the right asset; and building it in a way that allows an asset to adapt to future changes and perform at peak capacity over time. 

“If we build an asset knowing it’s going to expand, we’ll build it to accommodate that expansion. That’s particularly important in emerging markets, or any market where you don’t have a significant volume of dominant retail players and they don’t have those kinds of analytics,” says Alshab.

Big data helps estimate when an asset might become attractive to those dominant retailers. Staying current and understanding shifting consumer needs is more crucial than ever in any business.

Increasing personalisation in most retail sectors is one example of such trends. “Big data can help retailers and operators stay relevant by understanding their customers’ habits and providing a more tailored response,” says Simon Poole, a divisional director in Benoy’s London studio.

Big data is synonymous with the internet, and though most of us think information comes from Facebook or Google, its origins are far broader than that. “You can’t talk about big data in physical locations without talking about the Internet of Things – IoT and big data go hand in hand,” says Alshab.

Retailing is indeed where big data shines, but shoppers, office workers and hotel guests are all connected, and all demand a great experience and value for money.

“Design is now bespoke and driven by customer experience,” says Benoy’s Bentley. “Shops are galleries, a window into a multi-channel offer, expressing brand and position. A building that respectfully sits in context has a brand ethos, which is clearly communicated both digitally and in its bricks and mortar.

“Being at the cutting edge of data collection allows owners to understand their customers’ habits and ensure that the building responds and remains a competitive destination.”

Grosvenor harvests big data

Grosvenor is investing in big data platforms in Hong Kong and London to improve customer experience and operational efficiency, and to achieve its ‘living cities’ objectives. These are to create buildings that are climate resilient, connected, economically resilient and show good governance; to create a healthy environment, high-quality places and strong communities; and to use sustainable resources.

Global advisory firm JLL, meanwhile, has just launched Command Centre, which provides owners and occupiers with advanced analytics for real time and remote building monitoring.

Peter Hilderson, head of engineering and operations solutions, JLL Asia Pacific, says: “This is a big data play. It is offered to both investors and occupiers, so can be applied to offices, industrial, retail, manufacturing and data centres.”

Buildings become smarter

Big data is making smart buildings more common and wi-fi-enabled hardware is helping operators improve efficiency. Logistics firm GLP is on board too, using optimisation tools based on customer demands and patterns.

“This technology analyses customers’ supply chains and warehouse requirements to optimise their distribution networks and helps them reduce transportation costs by around 20%,” notes GLP CEO Ming Z Mei.

The IoT makes big data investments cheaper; small devices, digital meters and temperature sensors are cheap; proprietary systems are no longer required; and systems  need not be incorporated at the building stage. At the design level, buildings are tailored to areas, function and occupiers, and architects are incorporating big data into modelling.

“This understanding can have an impact on numerous levels, from a single store layout, to the design of an entire building,” says Benoy’s Poole.

“The only real limit is the level of data you can draw relevant information from. This should be embraced as one more tool in the architect’s or designer’s toolkit.”

Poole underlines big data’s value as a design tool, with the architectural industry beginning to embrace it. “Big data gives us an unparalleled way to understand how people interact with buildings,” he says. “This, in turn, can give us great insight into designing and developing spaces and the experience within and around our buildings.

“In this context, big data is primarily about our ability to model human behaviour. Input about how people use an existing building, or might use a building that is still on the drawing board, can be a crucial part of the design process.”

Big data can be used to analyse and predict an existing or future asset’s performance, based on public transport, traffic and pedestrian flow, area crime rates, tourist numbers, demographics, and food and beverage options, while social media patterns can aid valuations and development plans.

This can answer questions such as whether a mixed-use building needs a hotel, and if so how big; or whether it needs offices. The ability to build or purchase the right mall in geographically diverse locations such as China, India and Indonesia is crucial.

As well as boosting operational efficiency, a product such as Command Centre uses predictive maintenance, with sensor analytics, to maximise usage, minimise disruptions and safeguard sensitive occupiers such as data centres. “This reduces operational downtime and overheads,” adds Grosvenor’s Kincaid.

If big data is in its infancy in the commercial property sector, it’s embryonic in others. But greater commoditisation of big data processes will ensure expansion.

“This can be applied to any building typology and there will always be something that can be learnt and made to improve a design,” says Poole.

The architect is applying big data processes to its work on London’s Heathrow, to ensure one of the world’s busiest airports functions seamlessly.

Data shapes residential projects

The patterns and trends shaping the design of immigration counters and office desks will eventually steer the size of swimming pools and clubhouse space in residential developments. For example, developer St James extracted data from surrounding projects to place the ground-floor pool at its White City Living project in London.

“For residential buildings, a better understanding of the target audience can be obtained from unstructured data sources such as Facebook, Twitter and restaurant reviews, combined with demographic data and historic property transactions, all leading to a more tailored building,” says Kincaid.

Similarly, hotels need to keep occupancy rates high, particularly as disruptors such as Airbnb gain traction, and big data is leading to personalised pricing based on reasons for travel, duration of stay, average spending, room preferences and so on. That understanding can lead to higher yields.

In logistics, GLP’s Mei sees tech and real estate converging and the IoT taking on a bigger role. GLP is implementing smart gates that track drivers and the goods being shipped and received simultaneously.

“Using these insights, we can help customers become more efficient and competitive. Logistics facilities have shifted from back-room functions to being part of the retail experience.

“Online retail has changed  the location and design requirements of logistics facilities and [we have] stayed at the forefront by anticipating and adapting to our customers’ changing needs and providing solutions instead of just properties.” 

 

Images:

1. Residential developer St James used big data – analysing surrounding projects’ layouts – to site elements of its White City Living development in west London

2. GLP says it can help logistics customers cut transportation costs by up to 20%, through use of technology at warehouses that helps analyse how supply chains function, allowing for the optimisation of distribution networks

 

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