Posted by Ricardo J. Rodríguez - 03 June, 2022
About Ready for Next:
A series that explores the tech trends poised to disrupt the construction industry, culminating in an exclusive virtual event where Master Builders Solutions' Global Digital Insights Strategist, Ricardo J Rodríguez, and construction tech experts will discuss how these main trends will shape the construction businesses worldwide. Please follow the link below should you wish to learn more and confirm your attendance.
In this week's Ready for Next post, we provide a brief introduction to the well-established field of Big-Data. It generally refers to analyses of vast datasets that are so complex that traditional database software may not be able to handle them. It has become a focus area for construction because the industry deals with loads of data — videos, survey data, BIM models, etc. — that are getting larger every day. But beyond working with an increasing amount of data, there are many other reasons why predictive analytics are essential tools for contractors and business owners today. Although not all construction companies are unfamiliar with the concept of big data, many have only recently begun to grasp it effectively.
Recent technological advances, such as cloud computing and big data, have enabled businesses to process unprecedented amounts of data at scale, automatically organizing and interpreting it. As big data fuels Artificial Intelligence adoption, construction businesses will automate the most basic functions of construction work. This analysis will result in significant time savings for contractors who typically spend hours on such tasks.
What makes big data so unique?
Big data refers to large sets of information analyzed through various technologies, including Hadoop, NoSQL databases, and other analytical tools. It's used in almost every industry, from retailing and marketing to health care and finance. It's also been used in construction for years now; however, it wasn't until recently that these initiatives became more widespread across industries due to advances in technology. For example, many advancements have been made in machine learning over the last few years, making it possible for computers to learn independently without requiring human input.
Large amounts of data are collected through research and analysis at the core of big data. In construction, big data shows promise to address common industry problems, including reducing cost overruns, improving project management, and helping to reduce litigation by providing data that allows for better decision-making. Thus big data's use cases expand into scheduling, planning, and lean construction project delivery, allowing us to track progress in real-time. Data from various sources can be collected and fed into AI applications to determine which materials are required for each construction area. These materials will then be delivered at the precise time required. Data from sensors on construction equipment will also be used to accelerate project execution with minimal downtime and increasing profit margins. Platforms could then use this data to generate a schedule that optimizes workflow efficiency throughout the project lifecycle.
Big Data Laggards
The construction industry is a highly cyclical, capital-intensive business with high risk. Incorporating big data into the decision-making process can help construction companies manage this risk and improve overall performance. However, Big data is often poorly understood or implemented in a manner that lacks actionable insights. One of the biggest impediments to improvement is collecting the correct data in the right place at the right time.
The construction industry has been slow to adopt big data technology, despite its application in other industries such as manufacturing and healthcare. Several factors impede construction companies' ability to lead in this field. The workforce in the construction industry does not attract a lot of skilled data scientists and technologists. According to some 2020 estimates, there was a gap of 250,000 data scientists in the U.S., which means there is a significant shortage of qualified personnel for companies to hire on an ongoing basis1. In addition, many of those who do have skills in this area may be reluctant to enter the field because they expect their paychecks will be smaller than their counterparts in other industries.
Adopting emerging technology and various data tools can be difficult, especially for a company that lacks internal expertise and focuses solely on its core business/product. Embracing emerging technology and various data tools can be difficult, especially for a company that lacks internal expertise and concentrates exclusively on its core business (construction operations, professional services, or building material application). The construction industry is highly mixed, with many different stakeholders involved in every project, making it very difficult for any one player to have visibility into all aspects.
Construction is also one of the last industries to be digitized, even though much of what falls under its umbrella —building design, energy performance, and structural engineering — is based on technology. Big data should be a part of every construction company's toolbox, especially those with an eye on the future. Big data can help companies make better decisions about their operations, saving millions of dollars in costs.
How Construction Companies Can Compete With Tech Heavyweights
The construction industry is in the midst of a technological revolution. Nevertheless, One of the biggest challenges facing the construction industry today is finding ways to remain competitive in an increasingly tech-savvy world. As technology continues to advance, so too do the expectations of consumers and businesses.
Construction professionals are beginning to embrace new trends in increasing technology. Big Data can help construction companies compete with tech-heavyweights by allowing them to leverage data streams to make smarter business decisions. Construction organizations should pay close attention to several considerations needed to leverage big data effectively:
- Prioritize Tech - Big data can be overwhelming and intimidating if you don't know where to start. To make effective use of this resource, companies must prioritize technology. This means deciding what projects are worth putting money into and which ones can wait until later on down the road. Companies must also work with their vendors to ensure that any solutions they implement align with their overall goals and budgetary constraints.
Mitigate Risk - Big data analytics has its risks and rewards; however, when used correctly, it can improve efficiency and reduce costs by identifying areas where waste occurs, or safety issues arise before any damage occurs. It also gives businesses insight into what products or services customers want to serve them better (and earn more money). If you aren't sure how much risk your business can tolerate
Setup for Machine Learning Cloud - To leverage the advantages of big data in this industry, companies must first establish a cloud environment that can support machine learning and AI services. A company should also have a system that allows them to identify opportunities for improvement within their organization by utilizing analytics tools such as Tableau or Microsoft Power BI.
Harness BIM - BIM (Building Information Modeling) implementation can increase efficiency and productivity within the organization by providing accurate information about materials used and equipment used during projects. This information can then be used by management to determine how best to utilize labor resources so that there is no unnecessary waste, resulting in additional costs for businesses.
Waste Reduction - Reducing waste is one of the most significant benefits of using big data in construction. It allows companies to track their resources and materials more efficiently by providing accurate information about where those products come from and how much they cost—helping them cut costs by eliminating unnecessary expenses and preventing them from wasting natural resources.
Equipment & Productivity Monitoring - Using real-time data analysis can help improve equipment productivity by allowing workers to make quick adjustments based on their workloads. It also helps companies identify areas where they need more equipment to optimize their resources effectively. With this information at hand, businesses can take proactive measures against possible bottlenecks that may affect their productivity levels - saving them time and money during busy seasons or sudden spikes in demand for their services.
Health, Safety, Welfare - The HSW system includes all the tools used by workers onsite at construction sites. These include personal protective equipment (PPE), life jackets, and fall protection systems. The HSW system also provides training programs for workers on safety issues like safe lifting techniques or how to handle hazardous materials safely. The HSW system is critical because it helps prevent injuries and accidents from happening on site, which would cost construction companies money in terms of lost productivity and legal fees dealing with lawsuits.
Customer Satisfaction - Construction leaders can use big data for customer satisfaction by collecting feedback about your product or service from customers and employees alike. This information can improve existing products or services and create new ones from scratch based on what your customers need most.
How Big Data Is Transforming the Construction Industry
The data transformation of the construction industry is coming faster than most people realize. Data is poised to become a significant part of every new construction project in the future. We predict that data will play an increasing role in construction projects worldwide over the next few years. This big data revolution will be unavoidable whether you are an architect or a builder. If your business isn't open to incorporating data into your work, you'll miss several opportunities to capitalize on assets. These are no longer tied to "counting and collecting" data but rather to understanding and analyzing it. In some instances, the value of the information itself would be greater than that of the physical asset.
Whether you are an architect or a builder, this big data revolution will be unavoidable if you want to remain competitive. In addition to our previous posts on AI and Field Robotics, some relevant use cases to start exploring are:
- Planning & Budgeting
- Generative Design
- Building Information Modeling (BIM)
- Smart Construction Management (SCM)
- Operations & Maintenance (O&M)
- Trends & Analytics
- Efficiency Improvements
- Environmental Impact Assessment (EIA)
- Improved Working Conditions on site.
A path forward
As the construction industry moves forward, we are witnessing a growing discontent with practices that prevent firms from realizing their full potential. There is a shift toward construction technology, and data analytics as more practitioners acknowledge their value in an increasingly competitive market. Thus, increasing maturity in data technology is vital to the survival of our construction businesses. Big data is an expansive field that can help companies capture value in many areas.
As more construction companies recognize the power of big data, architects and engineers are gradually incorporating digital technology into their firms. Businesses are slowly but surely beginning to capitalize on their ability to collect and process large amounts of data with the help of sensors, measuring tools, and cameras, and the ability to share those findings in real-time through the internet easily.
There are many ways to digitally transform an organization with big data. Still, the most important first steps are setting your strategy, developing a culture of innovation and digital maturity, and identifying actionable small wins. Though it may seem complex, there are numerous ways to begin integrating big data into your firm. It can dramatically impact the business—allow it to generate new revenue streams, improve customer engagement, find new efficiency opportunities, and more. Hopefully, this article has provided insights into the considerations needed to implement better data science, analytics, and systems into core business workflows. The future of our industry depends on it.