Data-Driven Construction: Using Analytics to Optimize Operations and Improve Decision-Making

Construction is undergoing a digital transformation. Data analysis and business intelligence enable more informed decision-making and strategic planning, which can enhance efficiency and safety on the jobsite. Discover how analytics in construction are reshaping the industry. 

The Role of Data-Driven Construction

Data-driven decision-making prioritizes objective, real-time analytics over relying on experience or intuition. In construction, data analytics can streamline project timelines and optimize performance. With this data, a company is 69% more likely to formulate superior strategic decisions, increase profits by 8% and reduce costs by 10%.

Advantages of Construction Data Analysis

Data-Driven Construction

Effective data management in construction provides numerous benefits that support strong decision-making, from project design to execution and maintenance. 

Enhanced Accuracy

Construction business intelligence is a means of collecting and analyzing data to optimize performance. Many construction professionals use building information modeling (BIM) to save time and prevent miscalculations. These 3D models provide precise information to determine how much material a project will require. They can be refined and updated over time as the project comes to fruition, helping involved parties make better decisions. 

Risk Management

Hazards can slow task completion and decrease worker safety. Many modern construction technologies offer features for the operator’s safety and comfort, which can prevent accidents and injuries on the jobsite. The latest technology can be customized to help workers complete tasks safely and efficiently. 

Predictive analytics — such as weather patterns and equipment wear — can be used for further incident prevention. An Arizona State University study found that a cross-level data analysis of incidents, inspections and violations can reduce the likelihood of incidents by 17.3% in the construction industry. Construction analytic tools bring a much-needed level of predictability to the field. 

Innovative Technologies

Smart technology and integrations can give your construction company a leg up on the competition. In construction data management, they can be used individually or integrated for more in-depth insights. Along with BIM to enhance accuracy, construction workers can use:

  • Artificial intelligence (AI) to provide predictive analysis and recommendations.

  • Digital twins for simulation and performance optimization.

  • Internet of Things (IoT) sensors to collect and transmit real-time data.

  • Drones for site surveys and aerial data collection.

For instance, AI and machine learning can improve project cost estimations by analyzing information from previous projects, anticipating future costs, making real-time project adjustments, automating data processing and more. Together, these data-driven construction analytics benefit each stage of a project. 

Increased Sustainability

Modern construction professionals can use business intelligence to make processes more energy-efficient and eco-friendly. Construction analytics — using tools like BIM, predictive analytics, IoT devices and cloud-based systems — helps track and improve energy performance. 

Additionally, using sustainable materials in construction, like reclaimed wood or recycled rubber, can lower your workforce’s carbon footprint. This can help infrastructure meet LEED and other green certifications. 

Data for Improved Efficiency

Data-Driven Construction

Data analytics in construction can assist with project delivery and waste reduction. Historical and real-time project data can inform equipment usage and delivery schedules, helping reduce over-ordering or delays. 

Consider the expansion of U.S. Route 85 in North Dakota. The project used a predictive model to evaluate design elements —  particularly relating to safety and the environment — and accommodate stakeholder needs before the construction team physically began work on the road. 

Challenges of Implementing Analytics in Construction

While the advantages of construction business intelligence and analytics are evident, there are some barriers to overcome:

  • Data silos: Information may be scattered across teams, limiting a cohesive viewpoint.
  • Skills gap: Thorough training is required to integrate new systems and processes successfully. 
  • Resistance to change: Workers accustomed to traditional or manual methods may be less inclined to adapt to newer construction analytic tools. 
  • Data overload: Systems must be able to handle large data volumes generated by real-time monitoring. 
  • Implementation costs: Smaller construction companies may struggle with the financial investment in new systems. 

To overcome potential challenges, construction leaders must develop clear plans for implementing new data analytics tools and processes that align with overall business or project goals. They should also gather feedback from the workforce and adequately train them on new systems and meeting regulatory standards. 

Build Better With Data-Driven Construction

When construction companies adopt data-driven processes and systems, they can become more efficient, avoid jobsite hazards and gain a competitive advantage. Decision-makers in construction should embrace the many benefits of modern data-driven technology in workflows.