10 Examples of Data Analytics Sweeping Construction Project Management

RhumbixFebruary 16, 2023 • 5 min read

The construction industry has been constantly challenged for decades of poor planning, budgeting, miscalculations, management, cost overruns, low return on investment, insufficient financial means for completing a building. Data analytics can be used by construction project management firms to mitigate these issues, improve the entire project delivery cycle, and boost their bottom lines.

Below are 10 key examples of data analysis used to improve construction project management.

  1. Risk analysis for construction project management

Risk analysis and risk management are at the top of the list because these are critical elements for successful project deliveries and continued operation. Managing risk and processes involve planning, identification, monitoring, classification, response analysis, and several other factors. Risk analysis estimates the future assets, outcomes, and impacts that may present complications. Innovative field-first technology and tools for risk management and analysis.

Many factors related to construction projects can make the endeavor challenging. Some aspects include complexity, project type, site location, technical elements, number of stakeholders, and additional variables. Most of the digital tools for risk analysis are based on probability approaches.

  1. Predictive analytics

The challenge for contractors and their project managers are many, including paper-based workflows, data silos, misaligned processes, and ineffective solutions for collecting critical details from the field. Predictive analytics provides meaningful insights for stakeholders to take action on existing and future projects. However, it requires collecting massive amounts of data in real-time on the jobsite and across the organization. This is a game-changing solution in the construction industry. Multiple scenarios based on the insights can be applied to improve estimates, reduce costs and avoid failures on future projects helping produce better outcomes on the current work.

  1. Construction planning and modeling

One of the most popular examples of predictive analytics is the software development for construction Business Information Management (BIM) simulation. BIM helps all stakeholders view an entire project constructed (design, materials, costs data, etc.) prior to leveling the jobsite taking collaboration to new levels. Design issue prediction helps the constructors avoid possible problems in the erection and operation of the building. Designing large buildings and complexes involves a considerable number of calculations, matchings, and combination operations. BIM can bring it all together.

Save hours banner
  1. Warranty analysis

Warranty data analysis relies on the study of previous failures data and numerous external factors. A warranty analysis is the only way to keep track of further building operation and reliability. Warranty analysis helps avoid complications related to well-being, customer satisfaction, and safety, in construction. General and special conditions are developed to serve the purpose of the warranty provisions.

  1. Tracking equipment and assets in construction 

Asset management and tracking are essential for construction project management teams because they facilitate timely construction projects and operations. Equipment delays and failures can impact schedules that may have contractual obligations resulting in additional costs to contractors. Industry work relies on tools, vehicles, equipment, and mobile real-time tracking technology to prevent theft and equipment loss. Advanced asset tracking solutions help move from managing equipment and material on paper and spreadsheets to 24/7 monitoring. This technology also helps manage resources and staff assigned to projects and reassignments.

  1. Process optimization

For all construction project management teams, it is vital to maintain profit margins during construction project phases. Tracking time, money, and labor are crucial resources and aspects to optimize. Therefore, smart (specific, measurable, attainable, reasonable, time-based) and systematic processes require data analysis to improve business outcomes at every build stage.

Complex reporting banner
  1. Optimizing contractor performance

Measuring the performance of contractors during the project execution period allows general contractors to understand the possibilities for improvement and make more precise calculations. However, the optimization process might be challenging when you depend on these contractors for reports. Therefore, measuring contractor performance and optimizing efforts needs to be a joint effort using integrated management software. This software can track the contractor’s performance level and identify the areas for further improvements.

  1. Accurate budgeting and planning

The cost optimization process needs to be performed throughout the project lifecycle – from planning to execution to post-mortem. This has to be managed not only by your Enterprise Resource Planning (ERP) or “system of record” but by a tool that tracks real-time field-production data. It will provide stakeholders (Finance, PM, Foreman, etc.) real-time data to ensure budgeted costs meet actuals and enable these department leaders to take mitigating actions during the project build.

Accurate planning and budgeting are top priorities for all construction project management teams. The dynamic movements and unforeseen challenges that arise in projects and lack of preparation or tools can cause project leaders to fail. Innovative technology helps store the financial information, receipts, requirements, limitations, and documentation in one location, giving you the ability to analyze expenses and costs daily or weekly. Ensure that the technology you select includes risk assessment and auto alerts.

  1. Construction robotics

Automation is becoming a valuable source of labor productivity for the construction industry. Several types of construction robots have made their way into the construction industry. Among them are printing robots, construction robots, 3D printing for brick-laying, masonry, demolition robots, autonomous vehicles, and many others.

As construction companies seek to increase efficiency, the demand for construction automation is higher than ever. Due to the increased complexity of modern construction projects and the short time devoted to designing and building, robots are entering all stages of the construction process. AI-powered software, tools, and smart robots can continually help increase the speed and efficiency of the construction process because their activities are tracked, analyzed, and optimized for better quality and performance.

  1. Construction product development

Innovation and product development are rapidly shaping the construction industry to improve all aspects of the construction process. These cloud-based digital platforms, such as Rhumbix, empower contractors to better decision-making in the field, reduce costs, increase productivity and safety, and deliver better quality projects – on time and budget.


Data analytics and the technology supporting its application in the construction industry offer new opportunities for contractors to help them mitigate risks, improve project management, reduce costs and time spent working on a project. Construction technology and data analytics are continuing to revolutionize the industry.