It’s no secret that construction software and technologies — and smart use of data — deliver a healthy ROI, leading companies to more productive, profitable and informed decisions. I recently re-read,“ 10 Innovations that Revolutionized Construction, ” and pondered how the article compares to today’s high-tech environment. While we use terms such as “predictive data technology,” “predic - tive analytics”, and “machine learning” to describe game-changing technology both in our work and personal lives, these technological concepts were only beginning to emerge when that article was written four years ago. And although they’ve progressed by leaps and bounds in just a few short years, this is a good time to take a deeper dive into how these technological advances can help contractors capture, share, manage and analyze data for safer work practices, better business deci - sions, higher profitability, and more. A Closer Look at Machine Learning Machine learning is already integrated into our everyday lives. It’s how Google Maps knows to warn drivers of an unexpected traffic jam. Machine learning is also howApple enables face recognition for login, and Facebook chooses the “people you may know.” It’s also how an email service provider filters junk mail and banks recognize suspicious account activity. Most people are aware of how machine learning is used but what is it, really? In short, machine learning absorbs large quantities of complex data, identifies patterns in the data and provides reliable, effective and repeatable results. It finds the nuggets of gold in a river of data. Computer algorithms then use grouped data to detect patterns and pre - dict outcomes, an act also known as Artificial Intelligence (AI). More than half of today’s mobile apps utilize AI to classify and group data. Businesses increasingly rely on technology that can help them go from data (i.e. a set of values) to information (i.e. data that’s given context and put into categories) to intelligence (information analyzed to un - cover patterns and better understand what’s actually going on). As I noted in a recent blog article on the topic, machine learning is commonly mistaken as simply using averages or statistics. Instead, it entails a complex process of understanding and preparing the data that is analyzed, developing algorithms that produce valuable predictions and outcomes, and testing and refining the algorithms to ensure accuracy. AI’s Role in Construction So, how can machine learning and AI support the construction industry Smart, Predictive Data is Driving the Future of the AEC Industry By Anne Hunt
as companies seek to grow their businesses and profits? First, contrac - tors can plan more effectively by analyzing data — also known as predictive analytics. Below are just some of the many ways contractors are using technology and predictive analytics to filter through terabytes of job data, assess patterns, and make informed decisions: • Closely tracking job costs, change orders, material and equipment usage, and worker productivity from previous projects for smarter bid - ding on future projects. • Identifying best practices and lessons learned, such as delivery time - line delays, weather patterns and staffing levels from previous projects that have similar criteria as current projects. • Utilizing factual data to deliver accurate bids and timely projects, which leads to strong customer and vendor relationships and positive project references. • Optimizing transportation routes and load sizes for a fleet of vehicles traveling to and from multiple job sites. • Providing real-time project updates, including up-to-the minute re - ports and dashboards, to quickly make smart decisions. • Improving emergency response mapping to enable faster response times. • Digitally tracking data on injuries and safety inspections to reduce risk by identifying high-risk tasks and dangerous conditions. • Analyzing data on employee movements (collected from wearables or smartphones) to understand how much extra movement takes place in the course of a day, and improve efficiency by relocating materials. • Pinpointing key employees, based on past jobsite performance, for general career or project-specific opportunities. • Identifying current customers for potential cross-selling opportunities. Contractors Increasingly Relying on Predictive Data Technologies Contractors are using predictive data technologies to cut through the clutter and gain the intelligence needed to reduce profit fade and boost productivity across every aspect of their business. In fact, Accenture estimates AI has the potential to increase the construction industry’s profits by 71 percent by 2035. Contractors are making smart use of the vast amount of data that’s collected on today’s projects. Consider these examples: Georgia-based Precision Concrete Construction, a full-service concrete contractor for industrial and manufacturing, as well as multi-family residential, sports, commercial and institutional projects, embraced cloud-based technologies to improve workflows. What was once a time-consuming combination of email communication, spreadsheets and double-handling of data through manual processes has been re - placed with connected data and workflows, powered by a cloud-based construction management suite of solutions from Trimble Viewpoint. By digitizing and modernizing, the company has streamlined its pro - cesses and become a much more efficient, data-driven contractor. As an example, payroll is entered into its back office Viewpoint Vista ERP through digitized timecards that are easily entered from a mobile application directly from the field. The data automatically populates into Vista regular payroll processes in real time, where it can be quickly reviewed for accuracy and approved.
51
september 2021
csengineermag.com
Made with FlippingBook Annual report