Getting Started with Predictive Analytics in Construction

predictive analytics in construction

How current and historical data is bringing future insights to construction projects, and changing the course of the industry forever.

More and more, the industry is acknowledging that data plays an important role in construction. Still, projects produce massive quantities of data, and only a small portion of it is being used to inform decisions. One way of using data, however, is becoming more advanced and increasingly accessible for both small and large contractors: predictive construction analytics.

Using predictive analytics can help reduce risk and improve your decision making process. Read on to discover what predictive construction analytics are, why they’re important to the industry, and how you can start using these tools for better project outcomes.

Predictive Analytics 101

At the heart of predictive analytics is the ability to use current and historical data to forecast future outcomes. In other words, these tools make predictions about the future using techniques including statistical modeling and machine learning.

These techniques give the future insights generated by predictive analytics a significant degree of precision, especially with the use of machine learning. By generating algorithms based on current and historical data, machine learning is designed to solve business problems and streamline decision making, allowing you to choose the best path forward for your project.

Why Are Predictive Analytics Becoming More Important in Construction?

Each day, construction teams are managing a number of moving parts on site, from subcontractors to change orders, and beyond. The more complex construction projects become, especially in the era of social distancing and increased remote work, the more you need the kinds of tools that can take all available information into account and guide your next big decision. Enter, predictive construction analytics.

“What technology like data analytics, and even more specifically machine learning and artificial intelligence, is doing for us [construction] is unlocking our ability to harness the project data – organize it, interpret it to uncover patterns faster,” said Allison Scott, Director, Construction Thought Leadership & Customer Marketing at Autodesk, on a recent webinar

These tools can reduce issues, lower costs, and mitigate risk for construction projects by making the work more predictable. As an example, consider the preconstruction process. One of the biggest challenges for design teams during preconstruction is creating a realistic budget that can be applied to current and future project stages. On the construction side, teams frequently find it hard to manage the budget they receive from a project’s architecture or contractor teams. Predictive construction analytics allow preconstruction teams to create budgets that account for all possible factors that could emerge during a project, including regional labor and material costs, among other items.

Predictive analytics are poised to be a big part of the construction industry’s future. According to McKinsey & Company, solutions using predictive analytics, machine learning, and artificial intelligence will likely bring about major changes to how engineering and construction firms bid on and execute projects. Specifically, predictive analytics can help construction professionals answer questions around whether they should bid on a project, and if so, how much. These tools can also help determine if subcontractors’ bids are reasonable, and if a project is about to run into challenges. Predictive construction analytics can break down the costs and profitability of prior jobs, examine the accuracy of subcontractor bids received, and determine when and how past projects ran into trouble. All of this information can then generate the answers you’re looking for, before a new job has even begun.

Tips for Getting Started with Predictive Analytics in Construction

1. Hone in on our focus area

The best way to start implementing predictive analytics solutions for your next construction project is by first honing in on your area of focus. Going too broad in your adoption of predictive analytics can set you back, resulting in wasted time and disorganization. You should first determine one or two key focus areas where you want to bring in more predictability to your project. For example, do you want to better anticipate and mitigate safety and quality issues? Or perhaps you’d like more visibility into project risk, like budget overruns or labor challenges? Identify where you need more predictability and select a solution from there.

2. Find the right tools to measure

When it comes time to select the best predictive analytics tools, finding the right solutions based on your focus area can help you achieve your overall project goals. The right software for the construction industry can help with risk management around cost, schedule, quality, and safety. This solution can also help you evaluate subcontractor performance and mitigate day-to-day risks for future projects. Predictive analytics can also help safety managers understand the leading indicators to potential behavioral and environmental hazards, and take proactive measures before incidents arise. Moreover, a predictive analytics solution tailored to the construction industry can help executives identify risks across projects and take measures to improve project performance and set any job up for success.

3. Standardize and centralize

Finally, getting the most out of predictive analytics requires you to centralize and standardize your data. The higher quality your data input is, the higher quality, and thus better able to predict, your data output is. This is why it’s essential to establish a centralized data platform with standardized ways to input and structure information for accelerated accuracy in the predictive analytics solutions you use. Implementing a common data environment is one way to achieve this by allowing your team to optimize and utilize information when it’s needed most. Moreover, good data empowers future technologies, including machine learning and AI, to accelerate project delivery.

Predictive Analytics in Action

The use of predictive analytics tools in the construction industry has contributed to a number of successful project outcomes. Over the last few years, BAM Ireland, an operating company Royal BAM Group nv (BAM), has utilized BIM 360 Construction IQ, a predictive analytics software for the construction industry, to manage risk and streamline its workflows.

The software flagged a number of inconsistencies in BAM Ireland’s documents, including issues that were labeled as open despite being addressed and closed by project teams. Additionally, the system identified a number of critical issues that remained open, allowing the BAM Ireland team to address them before they became major challenges.

“A huge problem here for us is overdue issues,” Michael Murphy, digital construction operations manager at BAM Ireland, explained.

“If we fix these problems early, they’re cheaper to fix. If we start with a $25 issue that could be fixed in design, if that gets to construction, that increases to $250 to fix. If it’s spotted during snagging that will be $2,500. If it gets into operation it could cost $250,000. Knowing where the issues are early on is essential.

“If this system [Construction IQ] is taking a lot of heavy lifting away it’s giving us a laser sharp focus in terms of what the genuine health and safety issues are. We don’t have to explain how it works to the team; it just happens! Not only is it pointing at major issues, but it’s giving us more time.”

BAM Ireland has seen a 20% improvement in on-site quality and safety, and a 25% increase in staff time spent on high-risk issues since adopting Construction IQ as its predictive analytics solution. What’s more, as Construction IQ continues analyzing every BAM Ireland project, it is refining its prediction capabilities and improving the accuracy of its insights.

Predict Success Today

Predictive analytics can help you get organized and put your current and past project information to work toward success in the future. Finding the right predictive analytics solution for your next construction project starts with discovering how these tools can work for you. Learn more about available solutions and put predictive analytics to work for all of your future construction projects.

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Grace Ellis

As Manager of Content Marketing Strategy at Autodesk and Editor in Chief of the Digital Builder Blog, Grace has nearly 15 years of experience creating world-class content for technology firms. She has been working within the construction technology space for the last 6+ years and is passionate about empowering industry professionals with cutting-edge tools and leading strategies that improve the quality of their jobs and lives.