How can we improve living standards with Business Intelligence & analytics?

Much of the time, Business Intelligence (BI) and analytics are applied to business problems. They help address questions like: ‘How can I sell more product?’, ‘How can I increase the efficiency of my supply chain?’, or ‘How can I make better investment decisions on behalf of my clients?’.

These are important challenges to solve and questions to tackle. But think about the issues, features and aspects most important to you and your life. The factors that combine to give you the greatest satisfaction. The factors that are the most impactful upon your livelihood. For most of us, these factors will be based around social and community ideas which, when combined, improve our standard of living.

So what if BI and analytics could be applied to your community, to your life, in order to improve your livelihood? Would you be interested to find out more?

The SMART Infrastructure Facility: Improving livability through analytics

Well, that’s exactly what Pascal Perez is trying to achieve. Perez is the Director of Research at the SMART Infrastructure Facility at the University of Wollongong (UOW), based in New South Wales (NSW), Australia. The SMART Infrastructure Facility, a research arm of UOW, aims to help planners, designers and researchers better understand the complex interplay of infrastructure operations and uses across major utilities.

In the below video, Perez discusses how the SMART Infrastructure Facility is working to develop understandings and models to effectively collect, frame and analyze important data points that are considered to directly impact the perceived livability of an urban community.

It is hoped that developing a clearer understanding of – and being able to therefore analyze – the factors that underpin livability, the facility will be able to help urban planners, service providers and government authorities to act in a way that will most effectively improve living standards.

So, which city really is the most livable?

During his presentation, Perez used examples of the recently released World’s Most Livable City index – determined by the Economist Intelligence Unit’s (EIU) Global Livability Survey. He demonstrated how results could change dramatically if criteria was interpreted differently, or indeed if different sets of criteria were used to evaluate the livability of those same cities. As Perez explained, the problem with this variability is that the results become difficult for urban planners to harness.

Harnessing subjective and objective criteria

“Fact one: Better livability is a major objective of modern urban planning,” said Perez. “Fact two: You can use subjective or objective criteria to try to assess urban livability. Fact three: There’s a very poor correlation between objective and subjective criteria. So, where to from here?”

Developing a definition

Pascal said that the first step was for him and his research team to clearly define ‘livability’ in laypersons terms. They defined it like this: ‘To live in a place I like, where I have the ability to perform my tasks’. From there, they created a framework.

Developing factors and a framework

The framework they developed was based on six factors, which have been found to be almost unanimously important for people all over the world – regardless of their sex, race, stage of life or current living environment – for improving livability.

“These six factors are: My home, my neighborhood, my transport options, my entertainment opportunities, my available services, and access to my place of work or education,” said Perez. “We played with these factors again and again and again. But, depending on where we live, or at which stage in our lives we’re at, we will change how we [personally] rank these criteria.”

Collecting data

Perez and his team applied this framework when they interviewed five hundred people living in South Sydney (the capital city of New South Wales). They asked residents to rank these six criteria, and then explain why they were, or were not, satisfied with each of them. From there, they matched these responses with numeric data that fell into one of the six established factors. They counted everything they could in the neighborhood – from bus stops, to parks and coffee shops. They ended up with two types of information: Subjective perceptions from residents, and objective criteria.

“And from there, that’s where the magic starts to happen,” said Perez. “Then, you can start to ‘crack the code’ – understand what makes people tick.

“What the results told us was that young professionals are most interested in access to recreational activities and their place of work; and that retirees from our study area were mainly interested in services and access to transport.”

Developing a model

Based on their framework and preliminary research results, Pascal and his team developed a model to assist urban planners better understand the elements necessary to create high resident satisfaction – that is, to increase the ‘livability’ of a geographic area.

“This model was purpose built for the state department for transport in News South Wales,” said Perez. “The objective was to enable the transport planners and urban planners to have a better understanding of the consequences of a given scenario. For example, in South-west Sydney, which groups of people would be most interested in [utilizing] the light rail [system]? Mums and Dads with kids, young students, retirees, or a mix of all these people? Then, [once you’ve established] a particular patronage, [you can start asking questions like] what sort of housing facilities should you [as an urban planner] build to attract more of these types of people [in order to] align your transport planning with your other types of urban-related planning? And what are the other types of facilities you should build in the area to attract and retain these people? We hope that our model will help planners [to answer these sorts of questions].

“If you retain one lesson from this talk, it should be that when you talk about urban livability, peoples’ voice is everything.”

About UOW, SMART Infrastructure Facility and Yellowfin

UOW identified that regional and local authorities and planners in NSW were unable to access a comprehensive, reliable and interactive infrastructure data repository, in order to effectively and efficiently utilize current infrastructure assets and plan future infrastructure investment.

UOW’s SMART Infrastructure Facility has created an online regional dashboard – The SMART Infrastructure Dashboard, or (SID) – to address that gap. Underpinned by Yellowfin’s BI solution, SID integrates infrastructure, demographic and environmental data at various spatial and temporal levels – to assist planners, analysts and researchers understand the complex interplay of spatial, technical, social and economic issues and impacts associated with regional and urban development. Infrastructure data is provided by various public agencies and private operators.

Utilizing Yellowfin, SID offers reporting on three broad ‘infrastructure themes’:

• Regional usage of utility services (water, sewage, electricity, solid waste, transport)
• Operations on networks and assets (water, sewage, electricity, solid waste, transport)
• Vulnerability of infrastructure services (water, sewage, electricity, solid waste, transport) to different pressures (resource shortage, asset failure, climate event)

The project has national ambitions, with the potential to assist and guide infrastructure developments far beyond NSW.