The incorporation of technology and digitization has the potential to cause the construction industry to undergo massive change. With the use of technology, contractors can manage huge volumes of data with ease, giving them better insight into project aspects like design materials, weather patterns, and site conditions.
Using a data-driven strategy when managing construction projects can increase efficiency, save costs, and increase sustainability. In particular, analytics in generative construction can assist construction teams in improving quality, resulting in projects that are more likely to be completed.
For more on this method, check out ALICE’s article on generative construction. ALICE provides building solutions, as their pioneering platform allows you to assess multiple ways to build projects.
Using Analytics in Generative Construction Processes: What is data analytics?
Data analytics is a method that assesses raw data to draw insights and come to conclusions about it. By analyzing data, patterns that would otherwise go undetected can be identified for problem-solving.
Numerous industries, including business, healthcare, sports, and social sciences, benefit from data analytics. Construction is no exception, as it can be utilized in practically every construction element, from planning and scheduling to risk management.
How data analytics is used in generative construction
Throughout every phase of the construction project cycle, companies can save time, improve accuracy, and make better decisions using analytics in a generative structure. Businesses that use this technology can accomplish their objectives faster, benefiting from increased productivity and cost optimization.
Here are some ways that data analytics is used in generative construction.
Even if not much data is generated in the early stages of construction, planning can still benefit from data analytics. Schedules, budgets (including taxes), and resource usage information from earlier projects can be used by construction businesses in generative construction to identify what tactics are effective and what needs to be improved.
Project managers can use construction project analytics in generative construction to spot trends and patterns to increase productivity, optimize schedule and resource allocation, and lower overall building costs.
A thorough analysis of information in generative construction can assist in identifying and evaluating project risks, improving project planning.
Making resource management more effective
Data analytics in generative construction makes resource procurement and management much more effective in various ways. For instance, information like expected labor hours, materials needed, waste output, and equipment utilization, can be analyzed and used in generative construction processes to determine better and more ideal outcomes.
Construction project managers can optimize resource allocation to maximize their returns on material costs, utilization rates, inventory levels, and vendor pricing for each step of a building project.
Tips for using analytics in generative construction
Here are some tips for using analytics in generative construction.
Automate data collection
To properly execute data analytics, an immense amount of data must be available for analysis. Automating the collection of this massive amount of information enables teams to focus on decision-making rather than gathering and interpreting raw data. Consider using methods to automate the data collection process so more time can be spent on more important tasks.
Adhere to the 80/20 rule
The 80/20 rule states that 80% of the end result should come from 20% of the effort. This can also be applied to construction project analytics in generative construction, focusing on the most important 20% of the information, which will provide the most valuable insights and enhance decision-making processes.
Locate areas of improvement
Data-driven analyses in generative construction enable teams to pinpoint areas for improvement and increase their chances of completing projects. Use this method to identify risks and opportunities to adjust strategies accordingly.
Use the power of visualization
Data analytics is an integral component of generative construction, and visuals can help teams better comprehend their projects by making them easier to understand, assisting with spotting patterns, drawing conclusions, and making more informed decisions.
You may, for example, consider looking for generative construction platforms that integrate 3D modeling or BIM workflows.
Make sure the right people have access
The right people must have access to data and the platforms necessary for analysis. Teams should learn to utilize analytics tools efficiently while ensuring everyone has access when needed.
Data analytics in generative construction can offer teams significant advantages. By following the tips in this article, construction teams can complete projects on time, within budget, and with reduced risk of failure.