Using analytics in the construction industry

Imagine being a multi-dollar construction company creating a new state-of-the-art facility and finding itself late and over budget, accruing losses and delaying revenues by the day.

Or – maybe you don’t need to imagine — this may be a common occurrence.

As construction companies face increasing complexity, project leaders find themselves looking for new solutions to increase productivity and reach their end-of-year goals.

Enter the age of data analytics and artificial intelligence (AI).

According to recent reports, fifty-seven percent of construction companies want access to consistent financial and project data and 97.2% of organizations are investing in big data and AI.

What is data analytics?

Data analytics provides companies with possible outcomes and probabilities before they need it. Through software and data, companies can evaluate patterns and trends overtime and generate meaningful insight that optimize their decision-making and proactively identify delays.

Construction companies who deploy an effective data analysis strategy are able to confidently answer these questions:

• Can we realistically meet these milestones and target dates?
• What should our weekly progress goals be?
• Which subcontractors are the most productive?
• What are the material costs and contractor hours required for this specific project?
• What is an accurate price for procured contracts?
• Which activities have been delayed in the past?

Why use data analytics in construction?

Construction projects are highly complex. During this era of technology transformation, construction companies that remain content doing things the way they always have risk closing their doors permanently. On the other hand, companies that embrace data solutions like predictive analytics and business insights will build the foundation for a more ambitious future and generous bottom line. According a recent McKinsey report, construction firms could boost productivity by as much as 50 percent through real-time analysis of data.

Active intelligence produces insights that add value to nearly every aspect of construction project management. Here are some critical areas and benefits of using data analytics in construction:

Anticipate problems

By combining predictive maintenance with the Internet of Things (IoT) and machine learning, companies can see the likelihood of a cost overrun and identify which projects are most likely to have delays. Displaying project data and adding proactive alerts onto connected devices also allows field service professionals the opportunity to remotely monitor devices to address issues faster, identify at-risk project schedules and reduce downtime and maintenance costs. When armed with these insights, companies can be proactive in resolving issue areas before they even impact the project schedule.

Reduce costs

When companies can use data analytics in construction to predict how long a project will take to complete, they are able to better control costs and see which areas are likely to incur additional costs. Companies can also use real-time data to identify areas where they are leaving money on the table. Instead of relying on staff experience that are subject to inherent biases, project managers can track real-time financial data, monitor operational patterns and automatically generate reports for each job to see where they can break down costs.

Speed up operations

Whether it’s viewing machinery downtime or seeing which subcontractors are habitually off schedule, data analytics in construction can lead to actionable insights that impact operational efficiency. Power BI can display project data with easy-to-understand visuals that identify specific teams and tasks. This means that you are able to see where your company could be running more efficiently and identify areas that are consistently behind schedule.

Improve accuracy

When you are directing data from multiple operations into one central location, you can benchmark your team and better forecast future projects. Subcontractors and skilled labor are able to use data analytics to remove human error in data collection. For example, if your construction company is manually recording timesheets, construction daily or delivery receipts, it’s more susceptible to human error. Instead, companies can automate data collection from the field to produce higher-quality data and informed decision-making.

Advance safety in the field

Site safety is one of the most — if not the most important — priorities for any successful construction company. Workplace accidents can result in labor shortages, liability, and damaged reputation. Construction companies can turn to real-time data analytics to identify safety issues or behavior patterns before they occur. Monitoring machinery in the field can also minimize equipment malfunctions and mitigate risks.

Overall, construction companies can land more contracts by the variety of benefits that come from access to high quality data and data analysis. Companies that deploy a strategic data strategy in construction analyze opportunities, review KPIs and carry out what-ifs for different scenarios that lead to unbeatable proposals. With faster, safer and more profitable businesses, construction companies can get ahead of their competition.

How can CEM Business Solutions help?

In order to improve operations and achieve better results, CEM Business Solutions works with construction companies to produce and access quality data. Through an integrated construction management system that utilizes Power BI and data analytics, we enable construction companies to draw meaningful insights from their data.