Data analytics in urban planning: What’s the future of the industry?

In recent years, we have seen a significant increase in the rate of population growth across the globe.

While it took more than 123 years for the global population to reach two billion from one billion, it only took another 94 years to grow by another five billion people. Experts estimate that we may see the global population reach eight billion as soon as 2022.

In addition, over the last few decades, more people are also moving to urban areas. It’s estimated that by 2050, about 66% of the global population will be dwelling in urban areas. 

This mass migration to urban environments has put a major strain on urban infrastructure, including living arrangements, public transport, and other community facilities.

What this means is that today, the urban planning sector is facing significant challenges in building cities that can support the surge in population. Data analytics has emerged as a crucial tool for urban planners to build safer, cleaner, and more productive urban environments in this scenario.

In this post, we explore how data analytics is transforming the present and future of urban development.

The role of data analytics in modern urban planning

• Data analytics helps urban planners build more efficient cities

Over the past decade, people have become very dependent on the Internet of Things (IoT) devices—smartphones and other similar technologies have become a part of daily life.

This has given urban planners access to an ocean of data, which they can use to gain crucial insights into the usage of city establishments, public transport, and urban living arrangements, allowing them to build better infrastructure.

In addition, urban planners can leverage predictive analytics and artificial intelligence to run simulations that give an accurate representation of how proposed urban developments will affect the lives of millions of city dwellers.

For instance, by using predictive analytics, urban planners can create virtual models of transportation infrastructure and simulate traffic conditions to gain insights into how the new system will affect traffic conditions across the city, allowing them to design public transport systems that minimise traffic congestions and make travelling more convenient.

• Improves communication between urban dwellers and developers

An age-old problem urban planners have faced is understanding the issues faced by city dwellers.

Fortunately, with the influx of new technology and IoT, urban planners can engage with the public more effectively and use data analytics to get better insight into their needs and biggest issues.

Data analytics also allows urban planners to share their insights with city dwellers and encourage them to participate in designing efficient cities by giving ideas on how to improve certain aspects of urban living, like public transport and waste disposal.

• Improves resource management

The growth of a city or any urban area depends on how resources are managed.

Through big data analytics, urban planners can get accurate insights on how city resources are being used and use these insights to allocate resources to areas where they are most needed.

What data analytics holds for the future of urban planning

Today, many developers across the world are developing smart cities that can support the needs of millions of city dwellers while delivering significantly better gains in many areas such as law enforcement and transportation.

In fact, data analytics has already helped urban planners to convert 280 cities into smart cities, and more may come in the coming decade.

Data analytics will also be a major driving force in the development of carbon-neutral urban environments in the future, as many developed and developing countries are trialling plans to reduce the carbon footprint of cities.

Leveraging data analytics is the best way forward for urban planning

With the boom in urban population, effective urban planning is key to ensuring urban areas are safe and sustainable. Leveraging the capabilities of data analytics will be critical to the creation of effective city development plans.

If you’re looking to find new ways to leverage data analytics in urban planning, try out the Selerity analytics desktops to optimise your SAS experience. Get in touch with our team for more information.

What data analytics can do for smart city development

Growing awareness on environmental sustainability, carbon emissions and a host of other factors is making governments realise the importance of building people-centred cities, i.e. cities built for the convenience of citizens, instead of vehicles and (dare I say), corporations. These ‘smart cities’ are said to be part of a future trend in urban design and are key to solving urban problems. However, a huge component of this new design trend is data analytics. Analytics is an integral part of smart city design and, in this blog, we are going to explain what data analytics does for intelligent city design.

Addressing the challenges of smart city development

Connect data from different sources

Smart city development is fraught with challenges. To make a city that is truly resource-efficient and livable for people, urban planners require data from different sources. They need geospatial data, crime statistics, traffic data, foot traffic on different streets and the number of registered vehicles. But how can one make sense of data from disparate sources? That’s what data analytics is built for. Using technology, like AI and machine learning, analytics can analyse data using complex algorithms to draw connections across disparate sources to reveal useful information for city planners.

Planning for the future

Smart city planning is not just about planning for the present, it is also about the future. City planning for the present population improves living standards, but an influx of people can put a strain on resources and disrupt the quality of life. Urban planners need to account for the future when recommending policies and programs for smarter city management. What data analytics can do is anticipate the future with predictive analytics algorithms. Using analytics algorithms, urban planners can get a pretty accurate picture of the number of people coming into the city, and plan accordingly.

Securing data

If smart city development is to evolve, then the relationship between the local government and its citizens must also change. This involves (though not limited to) actively shaping the virtual infrastructure of the city and securing data. What data analytics capability contributes to protecting data? With the hosting and administrative responsibilities that come with operating analytics, there is a better chance that data will be secure because the information is in the hands of an analytics specialist team. The importance of shaping the environment becomes even more crucial once AI starts to play a larger role in a city’s infrastructure.

What data analytics has done in real-life applications

Data analytics is already working in different fields relating to smart city development.

Crime prevention

How do cities tackle crime? While conventional solutions involve arming and expanding the police force, what data analytics does is bring more solutions to the table. With analytics, urban planners and criminologists can identify areas and times where crime is frequent. Police can be deployed to these areas to prevent crime before it even happens. The method is already being used in London, Chicago and Los Angeles with great success.

Transport

What data analytics can do in transport is make the entire network more efficient than before, reducing the degree of congestion, frequency of delays and increasing the efficiency of transport networks in smart cities. Data analytics can even make public transport more efficient from an operational standpoint. Predictive analytics can anticipate the demand for transport during weekends or special events. Public transport can then be ramped up or reduced, depending on expected demand.

More efficient spending

One of the biggest problems smart cities have is allocating financial resources. It is not unusual to see a lot of money allocated to vanity projects, and not enough in vital services. What data analytics does is track spending more efficiently, so urban planners and elected officials can make better use of resources.

Making use of an analytics environment

While we talk about what data analytics can do for specific industries, we rarely address the transformative impact it will have on our future. People who doubt that data is worth more than oil need only take a look at the transformative impact big data will have on urban development, and by extension entire nations. What data analytics can do is make cities more sustainable, efficient and healthier for citizens around the world. These are truly exciting times, especially for those working in data analytics because we have a chance to not only improve outcomes for organisations, but also for entire cities.

For innovative data analytics solutions, take a look at our Selerity analytics desktop. With this, you can access a SAS pro analytics software environment that can improve your organisation’s data analytics processes. Get in touch with our team if you need more details.

How data analytics in home renovation benefits the industry

Data analytics and AI is the ideal solution for the home renovation industry. The multi-billion dollar industry faces severe challenges that hamper home renovators. Along with the common pains of home renovation (like the design process), renovators are also facing higher costs, stiff regulation. The lack of transparency represents a huge challenge for many customers who want to renovate their homes, but don’t know where to begin. However, data analytics in home renovation can solve these problems, leading to a more transparent, efficient industry.

Planning and designing

The most challenging task in a home renovation project is the design and planning stage. For many home renovators, designing and planning are crucial but challenging because it is an iterative process that sees changes made to thousands of variables several times over. If homeowners want to make changes to a kitchen, renovators have to take into account furnishings, piping, heating, lighting, countertop material and more. If homeowners change their minds, then the design would have to be readjusted, and the variables have to change with it. Thus, designing and planning a home renovation project proves to be a big challenge.

Interconnectivity with different industries

Home renovation has a strong connection with the finance and retail industry. For example, homeowners might take out a loan for their home renovation or visit retailers to order equipment for the project. However, despite the strong connection between the three industries, there is a distinct lack of transparency and interconnectivity. Thus, homeowners have a hard time completing their projects because they are balancing the requirements of three different industries: home renovation, finance, and redesign.

Rising costs and regulations

Home renovators have to overcome tremendous challenges. The cost of labour, materials, and a stiff regulatory framework conspire to drive up the cost of a project and eat into profits. One reason for high costs is due to the demand for green, energy-efficient homes. Green homes have a heavier regulation framework and require non-standard materials for the project.

Another tremendous challenge is the reliance on external information. For example, when calculating estimates, builders need to get materials from a third-party – relying on an external contractor leads to costly delays in different processes, like calculating estimates. Furthermore, many builders do not use technology in their processes, small builders will calculate estimates manually, instead of using estimate software.

Thus, processes that can be completed in hours take days to finish and inefficient business processes represent a cost in the form of missed opportunities.

How problems are solved with data analytics in home renovation

More objective information

A significant benefit of data analytics in home renovation is its ability to absorb terabytes of data, clean, and analyse it to deliver helpful insights. These useful insights reveal trends based on facts and not opinions. Homeowners desperately need more objective information, when selecting their contractor. Most homeowners only have reviews to rely on, which is too subjective and therefore, not useful. However, homeowners can use objective, fact-based information to get the right contractor, due to data analytics. Thus, homeowners have far more information on their hands, allowing them to make more insightful decisions.

Democratisation of data

Data analytics in home renovation can bridge the gap between home renovation, finances, and retail. Powerful data analytics software can draw information from three vastly different industries to discover significant connections between the three. Furthermore, data analytics is accessible to non-technical people.

Many advanced data analytics programs, like SAS, come with several easy-to-use features, like virtual dashboards that make it easy to read data, meaning businesses with non-technical and analytics-savvy people, like home renovators, can now use data analytics. Information can be placed on open source platforms for almost anyone to access it. Therefore, home renovation, finance, and retail industries are more transparent, which makes it easier for renovators to deliver better services to customers through fair and accurate pricing methods.

Reduce costs and improve efficiency

Data analytics and AI can improve efficiencies and cut costs for home renovators. Data analytics uncovers unexpected trends that provide unique insight into how renovators are spending their resources. Builders can discover new and innovative ways to conduct the same processes with data analytics in home renovation.

The processing power of data analytics models allows home renovators to complete work faster – especially work like calculating estimates. Data analytics even improves the design process. For example, Cowry Cabinets, a home renovation firm based in Canada, developed a Kitchen Designer App powered by AI technology. The app allows home renovators to design a kitchen with just a few clicks, saving time and money. Furthermore, renovators can choose from hundreds of suppliers to purchase their products, saving even more time. Thus, by incorporating AI and analytics into their work process, home renovators can cut costs and improve efficiency.

Main takeaways

There is a lot of potential for data analytics in home renovation to improve the home renovation industry. However, one significant roadblock for the implementation of data analytics models is the lack of information. Many home renovators, especially smaller builders do not collect data or information. If renovators want to solve the problems they face, it is important to start collecting data on their projects. Otherwise, they will not benefit from the technical innovations proliferating through the healthcare, automotive and other industries.

To find out how data analytics is changing aviation, public transport, and other industries, click here.

Tackling problems in construction with geospatial analytics

The construction industry has always lagged behind in innovation, compared to other industries but geospatial data analytics will transform construction, architectural design, and civil engineering.

Geospatial data analytics is location-based information, generated by billions of devices around the world. Thus, the additional insight provided to engineers and architectures helps the construction industry cut costs and improve efficiency.

Core problems with the construction industry

To understand the gains made from data analytics, it’s important to explain the problems the construction industry faces. According to a report, construction projects take 20% longer to complete and go over budget by 80%. Thus, we see an industry that’s prone to wasting resources and going significantly over budget.

One reason for the high costs of construction is the discrepancy between early estimates and reality. Early estimates form the backbone of construction projects, but failing to account for one variable throw off the entire estimate. When this happens, the project’s scope must be readjusted at the last minute, which is an additional cost to contractors. One reason why preliminary estimates go wrong is that they miss out on a single variable.

Certain variables are difficult to account for but, when encountered can throw off an entire plan. Therefore, the construction industry faces high costs due to differences between estimates and reality.

The high cost and waste of resources are compounded by a lack of innovation in the construction industry. For example, the automobile industry invests about 3.4% of resources into R’n’D, the aerospace industry invests about 4.5%, but the construction industry spends less than 1%. Thus the industry will lag behind on the technological front and miss out on innovations and improvements.

Here are a few ways geospatial analytics brings several positive changes that reduce costs and improve efficiency.

Accessing real-time information via geospatial data analytics

Conventional equipment reveals static information, which does not change until someone manually enters the new variables. Reliance on static information prompts many of the mistakes seen in estimates, as its impossible to record all changes manually. However, with geospatial data analytics, architects and engineers can access real-time information.
When architects and engineers are using real-time planning, it becomes easier to draw up accurate estimates because they are incorporating the latest information into their estimates, and not out-of-date data. Thus, the construction industry uses resources more efficiently due to accurate estimates. Hence, geospatial analytics brings efficiency in construction with real-time information.

3D-modeling in Building Information Models (BIM)

3D modelling in building information models (BIM) brings several benefits to the construction industry. With 3D modelling, architects can streamline the entire planning process. Architects will have an easier time identifying the shortcomings of a design when using a 3D model. Thus, the amount of work needed to adjust and finalise the design is reduced. Furthermore, architects can improve energy efficiency and building usability with a 3D model.

If geospatial analytics is incorporated into 3D modelling, architects and engineers will have more information on their hands. Thus, they can anticipate potential problems and plan around these obstacles, and reduce inefficiency and errors in design.

Incorporate cloud services

Companies in the construction industry face extensive capital expenses because they have to install machinery to provide services. However, with the advent of geospatial analytics, its possible to sidestep the high capital investment and instead, opt for a cloud-based service. For example, if a company is providing propane, they would normally have to install a machine to monitor their client’s use of propane.

However, with geospatial analytics, companies will know where their clients are, and data analytics can be used to assess their propane use. Thus, the company can monitor their client’s propane from afar, and deliver more, when propane levels reach a certain threshold. Companies can skip out on expensive capital costs by looking for cloud services.

The construction industry does not invest significantly in technological innovation. The end result is an industry that consumes more resources than it has to. However, geospatial analytics can change all that.

Geospatial data brings several innovations to the construction industry that cut costs and improve efficiency. As discussed, these innovations include incorporating cloud services, 3D modelling in BIM, and real-time geospatial information.

Don’t stop here! Learn more about the potential of data analytics by visiting our blog.