Reducing risk and improving your decision-making process are important goals in using predictive analytics in construction. This article helps discover what predictive construction analytics are, their importance, and how to start using these tools for better business and project outcomes.

What is predictive construction analytics?

Predictive analytics for construction collect massive amounts of data to break down costs, labor, materials, performance, profits, and loss and helps contractors generate answers to complex questions before the next job begins.

Predictive analytics importance in construction

Construction teams continuously manage risk throughout a project. Projects are continually moving from stage to stage, with their impacts altering the work, budget, and schedule. The more complex a project, the more you need simple yet effective tools to make critical decisions that prevent costly mistakes.

Data analytics technology helps construction contractors unlock their ability to harness project data–organize it and interpret it to uncover patterns faster.

Data analytics software empowers you to make decisions that help lower costs, reduce issues and mitigate risk, making work more predictable on construction projects.

One example to consider is during preconstruction. Business intelligence and analytics software help design teams discover value and meet the client’s current budget by analyzing estimates, costs, and risks throughout design-build projects. As a result, the ongoing savings and avoidance of high-risk scenarios can be substantial.

Another example is during construction on the jobsite. The budgets project owners and field foreman are working towards are continually impacted by emerging scenarios during construction. Predictive analytics can help construction firms create budgets that account for all the potential factors that could emerge during a project, including material costs and regional labor issues, among other items.

3 tips for getting started with construction predictive analytics

Your ability to use current and historical data to forecast future outcomes is at the heart of predictive analytics. These data tools help you make educated predictions by leveraging data analytics, machine learning, and statistical models. Fortunately, there’s technology to make the calculations, but you still need accurate and factual data. So get started with predictive analytics for construction with these 3 tips.   

1. Determine a narrow scope and focus 

Before implementing predictive analytics technology for your next construction project, you should narrow the scope of your focus. Going too broad by asking too many questions can set your effort back, resulting in missed goals. Instead, determine one or two key focus areas to bring in more predictability to your project.

Questions to ask: 

  • How can we anticipate potential problems better and mitigate quality and safety issues?
  • Do we want greater visibility into project risk, like budget overruns, labor productivity, or distribution challenges?
  • Can we easily understand and interpret data on dashboards to help us make the critical project and budget decisions?

2. Standardize and centralize your data

Have a data strategy and eliminate paper-based and electronic (e.g., email requests, etc.) redundancies to get control of the data produced by your firm. Predictive analytics is only as accurate as your data, so you need to standardize and centralize your information and shore up inputs. Better “data in” equals better “data out.” One way to ensure your data is clean is by implementing a field-first data collecting solution like Rhumbix. Rhumbix’s Field Analytix, a construction insight platform, empowers construction contractors with better decision-making in the field.

Predictive analytics requires a central data platform for standardizing data inputs and structuring information for accelerated accuracy in software providing you intuitive dashboards to make informed decisions. Implementing a common data environment (CDE) can help quickly optimize and utilize data and provides the option to present it to the right stakeholder when they need it most. In addition, an excellent data strategy will empower future technologies that come to the market to increase profits, quality, and construction project delivery.

3. Finding the right predictive analytics technology 

Construction contractors need purpose-built predictive analytics software for risk management. Risks around the schedule, costs, quality, and safety are primary focus areas prior, during, and beyond project delivery. Predictive analytics can evaluate subcontractors’ performance on a single project and across multiple projects for general contractors. For large subcontractors, predictive analytics software can help them manage day-to-day risks as well as improve performance. Predictive analytics can also help safety managers discover leading indicators to avoid potential environmental and jobsite behavioral hazards and take proactive measures.  

Predict success today

Predictive analytics can help you organize your current and past project data to work toward future success, such as managing labor resources throughout a project. Finding the right predictive analytics solution for your next construction project begins with asking the right questions, determining the right solution, and implementing a field-first data collection strategy.