Predictive Analytics for Smarter Project Planning in Construction

Authors: Deanna Welliver & Anja Whiteacre

Managing a construction project involves a wide range of responsibilities and challenges. From handling hundreds or even thousands of purchase orders and change orders, to overseeing labor costs and workforce hours, often with a diverse set of trade partners or union employees, to tracking every task in your project plan to certify timely completion. Add this to the unforeseen challenges that inevitably arise, the scope of responsibilities is endless. 

As a project manager, you must ensure that you deliver your projects on time and on budget. Some key metrics you would be reviewing daily might be:  

• Estimate at Complete (EAC) 
• Net Cash position  
• Labor Hours Performance Indicator (LHPI)  
• Percent Gross Margin  

This is where AI predictive analytics can help. 

Predictive analytics is used across most industries and is especially impactful in forecasting unforeseen twists and turns within large complex projects. 

According to Harvard Business School, predictive analytics is “the use of data to predict future trends and events. It uses historical data to forecast potential scenarios that can help drive strategic decisions. The predictions could be for the near future—for instance, predicting the malfunction of a piece of machinery later that day—or the more distant future, such as predicting your company’s cash flows for the upcoming year.”

To better understand the impact of predictive analytics, let’s explore a construction industry scenario to see how it can help forecast project outcomes with greater precision.  

Scenario: Cost-Code Level Spending  

As a project manager for a $2 billion solar energy field construction project, you are responsible for overseeing various costs. Effectively managing costs for your project involves accurate forecasting, procurement planning, and controlling waste to keep the project within budget and margin.  

In construction, some of the key cost types a project manager will oversee are 

• material, 
• equipment,  
• labor,
• suppliers, 
• general expenses, and 
• miscellaneous costs.  

Within each of those cost buckets, there can be thousands of cost codes, also known as project tracking expenses, charged to your project. These cost codes help you effectively manage your budget and what you have forecasted, allowing you to adjust as necessary and stay on track.  

Today, you may have a scheduled report that is sent to you showing what you’ve spent to-date. It provides you a snapshot of your spending for a given period in time to 

• review current budget,
• understand your job-to-date, 
• adjust your estimated timeline to project completion,
• analyze your physical and financial percent completion (how much is left and estimate what you think you must spend to be complete),
• predict labor needs and costs,
• review outstanding change orders, and 
• forecast further costs.

For an energy project, you may initially need to spend more money on essential equipment such as a generator. Due to manufacturing costs and time to ship, you will need to account for the time it takes for these tasks to be executed before labor costs hit your project. This will impact estimating your overall project time to completion as well as when to schedule labor to start to charge hours to the project.  

Predictive Analytics Solution

Here is where predictive analytics can be useful by providing insights for smarter estimates.  

How? 

The source system that houses your company’s data collects historical project data, integrates real-time updates from your current activities, and incorporates external factors like scheduled time off, market trends, and weather forecasts. Advanced algorithms then analyze the data to identify patterns.  

For instance, if subcontractor costs tend to spike mid-project, the model alerts you to the likelihood of a similar trend in your current project, giving you time to prepare. Instead of waiting for issues to arise, you receive information that better equips you to decide on what actions you can take immediately—such as renegotiating supplier contracts or reallocating resources to manage high-spending activities. 

Previously, you would have a standard Excel report sent with the variance of changes for material spending costs per specified timeframe. Now, you would be able to leverage AI to get further cost code level details that could then be rolled up, enabling greater insight into actual material costs. 

You can then dive further by leveraging historical data from similar projects (in size, contract value, and industry) to estimate future needs for understanding

• the ideal team to assemble (including things like productivity and team dynamics),
• material costs,
• equipment costs, 
• change orders,
• changes to estimates for completion based on weather forecasts, and  
• key holidays and scheduled time off throughout the year.

By leveraging predictive analytics in construction, you can enable smarter project planning that can result in better insights.  

Advantages of Predictive Analytics

• Better forecasting  
• Better and more realistic estimates for completion 
• Tighter margins  
• Auto filling of blank estimates for thorough completion 
• Various levels of aggregation with smarter estimates 
• Smarter predictions based on weather forecasts and scheduled time off   

At RevGen, we’ve helped several companies, some even in the Fortune 500, optimize their processes through AI-driven predictive analytics. If you’re interested in learning more about our data and AI offerings, you can visit our Analytics & Insights page or contact us today about our AI Workshop.

Deanna Welliver is a Manager at RevGen with a background in product ownership. She is committed to helping organizations develop impactful products that align with their vision and strategy, while fulfilling business objectives and addressing customer needs.

Anja Whiteacre is a Senior Consultant at RevGen and a certified Power BI Data Analyst Associate with a background in change management. She strives to help teams navigate complex transitions and achieve lasting results by empowering organizations with actionable insights that align data-driven solutions with business goals.