5 Latest Advancements in Construction Analytics
The construction industry creates a large amount of data on a daily basis. This data ranges from cost estimates, designs, building models, and blueprints, which have a lot of field value. However, the plethora of data acquired by construction companies is not stored in a manner that allows insight to be gathered for future projects.
According to Forbes, the data market was expected to achieve a market value of 99.31 billion USD in 2021. Now, as we’re nearing the end of 2022, there’s a lot of talk about the use of big data in different industries and the value it can bring when coupled with advanced data analytics tools.
Big data comprises a complex set of information that needs advanced analysis to organize, comprehend, and garner valuable insights. Many industries are harnessing the power of big data to make informed predictions and smarter business decisions.
Construction analytics are yielding positive results for the industry, especially when paired with technological solutions that reveal critical insights to reduce risk and improve project outcomes. Data analytic tools have, overall, allowed construction companies to see marked improvements in efficiency, productivity, and cost controls.
Statistics regarding construction data
Construction companies that have used advanced data analytics have reported an 8% increase in revenue. Despite the construction industry’s overall slow adoption rate in technology, there’s been a rush to implement data analytics in particular, with 97.2% of construction companies expressing interest in investing in it.
It’s also been reported that 57% of construction companies in the U.S. want access to tools that can provide them with accurate project and financial data. Big data analytics have been shown, after all, to improve decision-making by 69%.
The latest advancements in construction analytics
Now let’s have a look at the latest advancements in construction data analytics relevant to different phases of construction projects.
1. Advanced simulations for planning
There are data analytics tools now available that can provide you with probable outcomes, allowing you to improve planning and budgeting for construction projects.
Big data analytics can be employed during the earliest stages of the construction project to create a solid framework for the next phases of the project.
Construction analytics can particularly help extract valuable information that can facilitate hassle-free project execution, resulting in timely project completion and cost-effective mechanisms.
Data from past and current construction projects can be extrapolated to map out project timelines and potential delays, with analytics presenting accurate estimates of costs regarding machinery, labor, and materials. The risk of cost overrun during the later stages of the project is, as a result, reduced to a minimum.
Overall, data analytics allow managers to make well-informed and timely decisions, reducing the risk of human error.
2. Digital modeling
Tools can be leveraged to create digital models, and data analytics can be employed to pinpoint any design issues before the construction process starts. In addition to previous design data, environmental data can also be fed into platforms to analyze the new designs and make predictions about design stability.
These tools keep a record of things in real-time, so any changes introduced into the design can be easily and timely shared with other stakeholders. Identifying potential structural errors before the design is materialized can save construction companies from a potentially disastrous situation.
Remedial work and material waste can incur hefty costs for construction businesses. By using advanced data analytic tools, construction companies can easily save themselves from cost overruns.
3. Data management tools
Advanced digital tools have been developed for data collection, organization, and analysis.
These digital tools have the ability to process data in real-time and notify managers about any anomalies that may cause project deviations. Some platforms also streamline communication, improving information exchange and sharing to create a more collaborative environment.
Various data-driven project management software specifically built for construction allow for the continuous input of construction data, which is continuously analyzed for discrepancies.
4. Data collection and analysis tools for maintenance
Data gathering and analysis sometimes continue even after the project has been completed, with sensors put in place on newly built structures to gather and analyze information.
This data can be utilized to devise improvements for future projects, giving maintenance teams access to structural patterns, energy usage, and temperature data that can prove to be handy for evaluating maintenance requirements in the long term.
5. Data tools for green construction
Many owners are now showing increasing concern for the environmental impact of their construction projects. They care about the compatibility of their processes and structures with regard to health and climate regulations, with a desire to lower their carbon footprint.
Embodied carbon in particular is a serious issue for environmentally-conscious owners, who desire access to information about the impact of design changes. Advanced data tools have been developed to inform owners about the environmental impact of their projects.
This development in tech simultaneously has an innovative effect, with more green construction projects expected in the future.
Conclusion
Advancements in data analytics technology can be leveraged to introduce progressive changes in the construction industry at all levels and phases. Insights gathered from advanced data analysis are dependable and can improve the construction industry’s performance as a whole.
Individual construction companies can develop better plans, designs, and project executions, which will ultimately result in better project delivery and increased revenues. Construction companies who are still thinking about investing in technology will likely be encouraged by the thought that incorporating it into their systems will achieve better business outcomes.