The Role of Data Analytics in Construction Management 2025

Data analytics in construction management utilizes information from corporate operations or industry activity to derive insights. Decision-makers might use these insights to guide their decisions or evaluate the efficacy of existing tactics.

Analytics programs in construction can evaluate performance, financial, and safety data. The article can help identify areas for improvement. It can also assess the efficacy of recent improvements in comparison to older processes. For example, a construction company could track work hours and quality for a new piece of equipment and compare it to data from earlier equipment.

Many construction firms have already adopted data analytics in construction management. According to KPMG research, 45% of construction organizations now utilize basic analytics, while the remaining 45% are in the process of implementing digital analytics technologies. Meanwhile, 68% have already implemented or intend to deploy sophisticated analytics solutions. Let’s take a closer look at this increasingly crucial part of construction.

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What is Data Analytics?

Data analytics in construction management is a technique for detecting patterns, trends, and relationships in existing data. Its purpose is to address an issue by analyzing construction data to acquire a better understanding of the situation and predict future behavior based on past behaviors.

Data analytics is currently being used in the construction industry to address a wide range of difficulties, some of which include a dizzying number of variables that are not always obvious. To make “informed” predictions, data analytics in construction management examines these variables to discover the relevant aspects in a data set.

 

The Importance of Data Analytics in Construction Management

Every day, construction project teams deal with a plethora of moving parts on the job site, including subcontractors, materials, and equipment, as well as unavoidable changes in scope and contract amendments. The more sophisticated construction projects become, particularly in an era of increasingly distant workers, the more technologies you’ll need to consider for improved communication and data collection to make informed judgments.

All of this generates a large volume of data that must be filtered and processed before it can be used by project decision-makers. This can take a large amount of time and resources to complete manually; enter machine learning and artificial intelligence. These are data analytics in construction management approaches that significantly improve the speed and accuracy of analysis and filtering; they organize data and detect patterns far more efficiently than a human could.

Preconstruction teams can use data analytics in construction management to create budgets that take into account all probable project variables, including regional labor and material prices. Data analytics, machine learning, and artificial intelligence solutions are likely to cause significant changes in how engineering and construction firms bid on and execute projects; for example, by combining tender information, current business status, and past performance, data analytics could support go/no go decisions.

 

 

4 Types of Data Analytics

As a construction leader, you should first comprehend the four forms of data analytics in construction management listed below.

1. Descriptive analytics: Crews use descriptive analytics to characterize the series of events that resulted in structural instability. For example, when a wall collapses, it answers the inquiry “What happened?”
2. Diagnostic analytics: This explains why something happened. In the above-mentioned wall scenario, teams may utilize data to determine whether the root cause was damaged lumber, poor fasteners, or improper assembly.
3. Predictive analytics: With undamaged boards and proper installation, a wall can withstand X pounds of pressure before collapsing. Predictive analytics identifies when this could happen.
4. Prescriptive analytics: Predictive analytics describes what should happen next. For example, if a wall is expected to collapse with a certain amount of pressure, how might crews reinforce it to withstand the load?

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How these Forms of Data Analytics May Help Construction Management?

This is how these forms of data analytics may help construction management:

 

1. Predictive Analytics

Predictive analytics uses previous data from your team or the experience of other businesses. It can assist crews:

• Accurately estimate job costs
• Develop a timeframe and schedule.
• Allocate resources

They frequently play an important role in project planning, with apparent benefits in generating estimates and submitting bids. Furthermore, they can anticipate aspects of a work that crew chiefs may overlook if they simply have a low-level view of operations.

For example, technology can forecast the potential negative consequences of a development project on adjacent rivers and whether they will necessitate additional permits near conservation areas. Knowing this from the outset of the process helps to avoid future delays that can cost time and materials.

 

2. Quality Control and Risk Management Examples

How do you know when quality control concerns occur? Historically, crews relied on consumer complaints, which always resulted in conflicts. However, data analytics in construction management enables you to evaluate construction quality management data from inspections, testing results, and defect reports in real-time to discover and correct patterns more rapidly.

For example, employing AI to analyze data can uncover the root cause of a reoccurring fault that requires final remedy. Identifying and addressing the source of the deficiency saves money and time spent repeating tasks.

 

3. Safety and Risk Assessment

Construction is a dangerous profession, second only to transportation and materials handling in terms of overall risk. Reducing these catastrophes saves families a great deal of heartache while also saving money on lost work and legal bills.

Data analytics in construction management helps executives understand why accidents occur, which is critical for determining liability. It also enables them to make modifications to avoid similar situations in the future, potentially stopping trouble in real time. Drones in construction, for example, may scan locations for hazards and notify staff to dangers, allowing humans to be evacuated.

 

4. Supply Chain Optimization

Part of construction management is getting the necessary materials to the job site on time. Having plumbing subcontractors hang about waiting for a pipe delivery wastes time that could be used on other tasks. While variables such as rising gas prices owing to supply chain challenges or foreign wars influence all providers, data analytics can decide which provides the greatest job at the lowest cost, regardless of external pressures.

Data analytics in construction management allows you to better track existing inventory and predict when to order more. It can also help with contract negotiations by providing data to support mileage reimbursements and finding the optimal routes for items to reach your location.

 

5. Performance Monitoring and Benchmarking

How well does that new piece of equipment perform? data analytics in construction management demonstrates how a new forklift pays for itself over time and finally results in higher profitability. It also compares your usage to industry benchmarks to determine whether you’re making the most of your investment. If not, what areas can you improve?

You can also utilize data analytics in construction management to monitor employee performance against key performance indicators, recognizing top performers for a job well done. Providing bonuses and raises to individuals who exceed certain benchmarks boosts general morale and productivity, inspiring others to succeed.

 

6. Cost Estimation and Budgeting

How do you generate estimates? Many construction industry experts use data from previous works, subcontractor bids, and financial forecasts to predict material prices in the next months. Even the finest and brightest make mistakes that can be costly. However, the correct data analytics in construction management employs AI integration to do the majority of the job for you, merging data from numerous sources into comprehensive reports that drive decision-making.

The buck ultimately stops with you, therefore budgeting effectively guarantees that everyone is paid on time and that the task is finished to the required standard. No general or subcontractor wants to waste time and resources on litigation fights and unneeded liens, so use modern technology to create a meaningful project budget that covers all bases.

 

7. Resource Allocation and Optimization

Things change quickly on construction sites, so data analytics enables crews to make the most use of available equipment and workers, reducing downtime and waste. For example, real-time tracking informs supervisors about delays on one section of a building site, allowing them to dispatch otherwise idle bulldozers and backhoes to a waiting area.

Using data analytics in construction management to effectively distribute resources benefits more than just a crew’s bottom line; it also saves the environment. Currently, the construction industry accounts for 30% of total waste generation, significantly contributing to climate change. The same shifts that save you money also improve the environment.

 

Important Points About Big Data Analytics in the Construction Industry

Here are examples that will help you understand where and how big data analytics in construction management are altering the construction business.

 

1. Risk Assessment for Construction Project Management

Construction, regrettably, remains one of the most dangerous jobs. In the United States alone, about 1,000 construction workers died in 2022. Falls, struck-bys, caught-in-betweens, and electrocutions account for the vast majority of deaths. As a result, safety remains a top priority on-site in order to limit risk and the likelihood of injury or death.

Risk management include not only on-the-job safety, but also project management. Project management difficulties arise frequently in construction and field service. Big data analytics in construction management can predict whether a project is likely to run over budget, be delayed, or fail to reach its objectives. It can then notify project management, allowing any difficulties to be resolved before greater concerns occur.

 

2. Tracking Equipment and Assets in Construction

Prevent goods, equipment, and tools from becoming lost or misplaced. Tracking who is using what and on which site allows you to spot trends in often lost or stolen materials. Furthermore, keeping track of all of your equipment and tools allows you to more accurately assign where those supplies should be for your present jobs. This allows you to streamline travel and save the cost of shipping or transferring equipment to job sites that require it.

 

3. Process Optimization and Data-driven Process Enhancements

It’s reasonable to say that none of the hundreds or thousands of projects you’ve worked on in your career have gone exactly as planned. But where did each of these obstacles occur? What could you have done to prevent those difficulties in the future? It’s undoubtedly easier to say, “We’ll do better next time,” but big data has the potential to cut through the fog and pinpoint process improvements based on all of the jobs you’ve already completed.

From faster and more effective travel routes to staff assignments, leveraging data to drive choices and procedures can significantly improve your organization. This results in cheaper prices and more money in your pocket.

 

4. Environmental Impact Assessment

Sustainability is the name of the game in industries other than building. As scientists and even the UN have warned, the globe is rapidly approaching the “point of no return” for climate change. Understanding the environmental impact of construction projects will become increasingly important.

Today’s construction must lower the danger of failure in the face of more severe weather circumstances such as wildfires, temperature extremes, and other natural disasters. Similarly, developments must offer possibilities to offset their carbon footprints and enable their customers to do the same. Big data analytics in construction management may gather prior endeavors’ information, analyze it, and reveal a road forward for a more sustainable future.

 

5. Predictive Analytics in Construction

If you’ve ever had a machine break down in the middle of a project — and who hasn’t? – predictive analytics is something you should take advantage of right away. Predictive maintenance may be the most effective application of predictive analytics. With AI in construction growing more common by the day, one immediate benefit is having your machines notify you when they require some TLC, allowing you to service them before they malfunction.

Other applications of predictive data analytics in construction management include the more paper-based aspects of the organization, such as reporting, financials, and forecasting. After all, big data is predicated on utilizing all of your company’s raw data, extracting insights from it, and forecasting the likely future status of your projects and business.

 

6. Accurate Budgeting and Planning to Prevent Overruns

If you’re like most business owners, you’re constantly thinking about keeping your firm profitable. Budgeting is an important aspect of making that venture a success. However, when supplier costs fluctuate and contractors come and go, as well as a slew of other external elements to consider, it’s a never-ending battle to maintain your profit margins.

However, big data analytics in construction management are revolutionizing the construction business and how it manages finances. Instead of having to pull out a calculator and manually total each payment to and from your firm to calculate your profit and loss, software like field service management platforms can not only do so for you, but also forecast your future numbers.

They can also forecast and demonstrate how your firm is trending during a project, rather than at the end of the month or quarter. So, at a look, you can see that your suburban apartment project is on track, while your commercial highrise is going to be somewhat over budget. This allows you to more easily course-correct and resolve issues before they become too massive to handle.

 

7. Construction Product Development

As building materials and methods evolve, whether to meet building requirements or just to increase efficiency or design, the construction industry adapts. We surely do not build things like we used to. Companies driving these improvements frequently employ technology, big data analytics in construction management to determine what those developments should be.

Consider the most inventive structures over the last few years. From dramatically altering how sustainability is integrated into the architecture to determining how effectively a construction can resist hurricanes and earthquakes. The level of advancement we can attain currently is entirely dependent on data from prior efforts.

 

8. Optimizing Contractor Performance

Contractor efficiency and performance are crucial, especially in smaller residential projects that may comprise single structures and a significant amount of travel from site to site. Even on larger projects, you don’t want your contractors losing time due to mismatched skill sets or bad planning. You can use operations management software to track individual contractors, the jobs they’re working on, success rates, timeframes, and other details.

You may then evaluate all data analytics in construction management to see what is and isn’t working well, and make changes to improve performance. Provide more training. Assign people to jobs that better match their skill set. Overall, your contractors perform better, which saves you money.

 

9. Construction Robotics in Modern Construction

If you’ve ever considered 3D printing a house, some are now officially available in the United States and other parts of the world. However, robots building houses one layer of cement at a time are not the only ones in the construction industry. Robotics is rapidly gaining traction in the business; for example, masonry robots can lay bricks and perform heavy lifting significantly faster than human counterparts.

Aside from housing, robotics can speed up operations like surveying and scanning building sites, removing the need for humans to navigate difficult terrain. The industry is also seeing the introduction of driverless trucks and vehicles, as well as AI-augmented forklifts and loaders.

While working, these robots may gather information on their building sites. Then you may evaluate information to constantly enhance not only the robots’ functionality but also site and employee efficiency and safety.

 

10. Construction Planning and Modeling

Being efficient and effective in construction is critical to success in the industry. Not only with your own operations, but also with the end product of your efforts: buildings and structures. Another benefit of incorporating big data analytics in construction management into construction is that it can aid in planning and modeling better buildings.

Engineers and architects can produce a building that is better adapted to the needs of customers and consumers by feeding a big data model information about the structure’s intended purpose, the site itself, and other essential planning and design factors. However, one structure is only the beginning. Building Information Modeling (BIM) is assisting in the development of better construction projects on a city-wide scale.

 

11. Warranty Analysis, Product Quality and Dependability

Not all products are created the same. To get the most out of the products your staff utilizes every day, your organization must continuously balance quality and cost. Understanding what your warranty covers, especially for more expensive equipment and machines like vehicles or specialist tools, is an important aspect of selecting the correct product for the job.

Alternatively, the materials you choose to build your projects may come with warranties and vary in quality and reliability. By collecting all of the data and conducting a cost-benefit analysis, you can help enhance work profitability, project success rates, and even customer satisfaction by matching the appropriate supplies and hardware to each job.

 

Selection of Data Technology for Construction

Three steps of successful selection of data technology for construction:

 

1. Choose the Correct Analytics Tool for Projects

With an expanding number of data analytics in construction management available, it’s critical to choose which one is best for your purposes. Standard standards for tools in construction include covering schedule, cost, and risks. Aside from that, technologies might help with on-site health and safety management, or they could focus on executive-level summary data for portfolio management.

 

2. Concentrate on Your Main Project Objective

Focusing on a particular area is the simplest method to begin employing data analytics in construction management tools for your next project. An oversupply of data analytics adoption may set you back, resulting in lost effort and disarray. Begin by focusing on one or two key areas where you wish to increase project predictability.

 

3. Organize and Standardize Your Data Collection procedures

To get the most out of data analytics in construction management, consolidate and standardize your data and procedures. The higher the quality of your data input, the higher the quality of your data output, and consequently the greater the value provided to the end user. This could need the establishment of a common data platform (or pool) with uniform data entry and organization methods in a shared environment. With such a massive volume of data being analyzed and entered, good input arrangement can significantly speed up the analysis.

 

The Future of Big Data in Building, Including Upcoming Trends

Aside from the previously highlighted benefits of big data analytics in construction management, a number of new trends are developing. For example, augmented reality (AR) and virtual reality are reducing the physical needs for some jobs and tasks in construction, while also breaking down barriers and facilitating communication between on- and off-site workers.

Natural language processing (NLP) is assisting in the discovery of all hidden data inside the construction business. For years, the industry has collected data in many sorts of files, making it impossible to understand all contained within them. NLP, which processes huge volumes of language and text data to assist computers in better understanding people’s natural ways of communicating with one another, excels at delivering useful insights.

Finally, artificial intelligence is gaining popularity daily, with far-reaching implications for the construction industry and beyond. From making big data analytics in construction management more accessible through AI-assisted graphing and charting to spotting construction project obstacles in real-time. AI provides huge development potential to organizations that use it.

 

FAQs 

What is Data Analytics in Construction Management and how is it used?

• Answer: Data analytics in construction management is a method of identifying patterns, trends, and linkages in existing data. Its goal is to handle a problem by studying construction data in order to gain a better knowledge of the situation and forecast future behavior based on previous behavior.

How can Data Analytics in Construction Management help with risk assessment?

• Answer: Data analytics in construction management enables executives to understand why accidents happen, which is crucial for assessing liability. It also allows them to make changes to avoid similar occurrences in the future, perhaps resolving problems in real time.

How does Data Analytics in Construction Management improve project performance?

• Answer: Data analytics in construction management demonstrates how a new forklift pays for itself over time, resulting in increased profitability. It also compares your consumption to industry standards to assess whether you’re getting the most out of your investment.

What are the key benefits of using Data Analytics in Construction Management for budgeting?

• Answer: Big data analytics in construction management are transforming the industry and how it handles finances. Software, such as field service management platforms, may estimate future numbers and show how your company is going during a project, allowing you to address problems before they grow too large.

 

Conclusion

Construction companies confront several problems, such as tight schedules, limited budgets, and complex regulatory requirements. However, it is obvious that data analytics in construction management can be a valuable tool for solving these challenges.

The construction business is one of the most data-intensive markets, so there is an increasing demand for improved construction analytics and big data management. Data analytics in construction management enables construction organizations to greatly improve project management and cost optimization, leading to widespread adoption of the technology.

 

Resources:

logikalprojects | rhumbix | kreo | autodesk | simprogroup | fieldwire | pixelplex | linarc | datumate | planradar | fmicorp | gminsights

For all the pictures: Freepik