he building and construction industry is becoming more tech-centric than ever. While the sector was resistant to new, cutting-edge technologies for much of its history, construction companies have started to embrace digital transformation. One of the most impactful of these new digital tools is building information modeling (BIM).
BIM provides a fast, accessible digital alternative to traditional physical building models and blueprints. This technology has become an industry standard and has enabled a 20% cost reduction in some areas. That’s a considerable improvement, but data analytics can take these benefits even further.
Many, if not all, BIM solutions today can integrate with data analytics. If more construction firms used these technologies in conjunction, they could experience more significant and sustainable benefits. Here’s a closer look.
How Does Building Information Modeling Work?
Building information modeling helps teams save time and money in a few distinct ways. First, it makes it easier to collaborate with different project stakeholders, as it uses cloud-based, shareable digital models. This accessibility reduces the time spent consulting other experts and prevents errors from miscommunication.
BIM tools also typically include a feature called clash detection, which automatically highlights potential errors. Whether it’s a design feature that won’t work in practice or a scheduling error, these clashes can be costly. They can cost large-scale construction projects as much as $34 million, but BIM lets teams find and fix them early, avoiding these expenses.
BIM models can also update in real-time as construction progresses. If any new problems emerge, teams can detect them in the digital model before having to rework them in the physical project. These updated models can continue to provide a valuable source of information to property managers after project completion, too.
Building information modeling presents significant potential benefits, but many teams fail to capitalize on them. Material waste and rework still account for 35% of industry costs, mostly because BIM use hasn’t evolved with the times. Integrating data analytics can unlock BIM’s full potential.
Advanced Clash Detection
The first and most significant way data analytics improves BIM is by enabling advanced clash detection. Traditional BIM software can highlight potential errors within a model or attached schedule, but the scope of this analysis is limited. If teams analyzed a broader range of data, they could find and fix more clashes.
The construction industry generates a vast amount of data that traditional BIM doesn’t consider. Errors from past projects, market trends, worker safety statistics, and equipment runtime can inform more accurate predictions. If firms took this information and fed it into analytics engines that work with their BIM, they could detect and prevent more clashes.
Rework accounts for a median of 9% of total project costs, and construction flaws aren’t the only clashes that cause delays or cost overruns. Time-consuming errors can come from anywhere, so broader data analysis is a necessary step in detecting and preventing them. Construction sites are also increasingly connected, providing more data points to analyze.
Faster Audits
The building and construction industry is a highly-regulated sector, and regulatory compliance is often time-consuming. Code violations can be costly and necessitate rework, so teams frequently audit their models before the construction phase. Data analytics can accelerate this process.
As of 2018, 68% of building departments can review electronic documents like BIM models, but these third-party checks aren’t always efficient. With data analytics, construction firms can perform their own audits, ensuring regulatory compliance much faster. As long as their analytics engine is up-to-date on relevant regulations, it can highlight potential violations.
Automating the auditing process saves a considerable amount of time. Teams can then address any potential issues without running behind schedule. Construction projects will become more efficient, more compliant, and safer as a result.
Optimized Supply Management
Issues with material supply are another common source of inefficiency in the construction industry. The sector generates billions of tons of waste each year, which comes with a monetary cost in addition to the environmental one. Data analytics in a BIM program can help construction companies manage their supply more efficiently.
Analytics engines can look at similar past projects to determine how much material a team needs. Similarly, these systems can scan for errors in equipment lists to find and correct redundancies or incorrect orders. With this improved accuracy, construction companies will only purchase as many materials as they need.
Supply management analytics can also find the most cost- and time-efficient way to order materials and equipment. Since large projects typically take 20% longer to finish than their original schedule, teams need to cut time wherever possible. With these analytics, they can find the suppliers that will provide the fastest deliveries.
Automated Reporting and Sharing
Finally, data analytics extends the accessibility benefits of building information modeling. Since construction involves so many different stakeholders, projects typically include writing and distributing many reports. These seemingly insignificant processes can consume a lot of time throughout the year, so streamlining them can bring considerable benefits.
BIM analytics tools can analyze models to determine what information a report needs and who needs to see it. They can then produce and share these documents automatically, saving workers time they can spend on other, more value-adding tasks. All stakeholders can stay informed without spending too much time filing and sharing reports.
This reporting automation continues to be helpful after the construction phase, too. BIM models can also help in operations and refurbishment, which also requires frequent reports and documentation. Analytics engines can tailor data reports to each stakeholder or project phase, ensuring everyone gets the information they need.
Data Analytics Makes the Most of Building Information Modeling
Building information modeling is a game-changing technology, but only if companies can take full advantage of it. Data analytics help construction firms extend BIM’s benefits past the constraints of older technology and to new processes. Without analytics, BIM isn’t as helpful as it could be.
Analytics engines help construction companies experience the full potential of BIM. As more companies use these technologies together, the industry can move past its persistent shortcomings. The sector could become as efficient and cost-effective as the digital age demands.
