One of the least digitised industries, construction companies struggle to change their way of doing things. However, many contractors are learning the real value of digitising their process and documentation – they are learning more about their business and how to improve operations in the process.
Thanks to data analytics, actionable insights are being provided to contractors who need to improve their processes, make more money and get more work. Data analytics plays a vital role in helping your construction firm.
What is construction data analytics
Construction data analytics refers to the process of using software and historical data to detect patterns and gain actionable insights into construction projects. The software is able to identify and predict when patterns will emerge, giving advance notice to the construction team to take corrective action. If implemented, this data analysis can lead to improved operations and higher quality work. Other advantages of construction data analysis includes more profit, improved safety, increased productivity and getting more work.
What tools do you need?
To tap into this powerful data science process, you’ll need four tools: data, software, hardware, and training.
- Data
While construction companies may have a lot of data, most of them don’t realise it because they’re still relying on analog systems to run their companies. Paper documents and analog communication processes make it tough to analyse data and find patterns. If communication is digitised, stored, and tracked in software, the power of data science begins to emerge.
- Software
If contractors want to take advantage of analytics, they need to invest in software that can collect, store and analyse construction data for trends. Don’t be taken in by systems designed for other industries. Construction is unique, and the software that you use has to be particularly developed for construction
- Hardware
Every employee, irrespective of their level, should be able to enter data into the system and read the data analysis results. Your construction team should have the hardware data collection, wherever they are. This hardware includes desktops or laptops, smartphones and tablets.
- Training
Finally, once you have the above pieces in place, you’ll need to train your employees on the system, including how to enter project data and interpret the results. The predictive power of analytics is based on getting accurate information from every level of a project. So, it pays to make sure everyone can properly enter the raw data and interpret the feedback the software provides.
- Construction data analytics examples
Finally, once you have the above pieces in place, you’ll need to train your employees on the system, including how to enter project data and interpret the results. The predictive power of analytics is based on getting accurate information from every level of a project. So, it pays to make sure everyone can properly enter the raw data and interpret the feedback the software provides.
- Make better bidding decisions
What is the mechanism for choosing which projects to bid on and which to pass on? Is it intuition about the project or have you analysed your bidding success over the years. One construction company took data from more than 100 projects including location, time and materials contract structure, and profit margin. Analysis of these factors revealed project characteristics that influenced their success on the project and the amount of profit they made. Using this information, they chose to bid on projects that they would be successful on and make more money.
- Forecast cost overruns
Instead of solely focusing on cost overruns that have already occurred, analytics helps contractors gauge where the project is vulnerable before it occurs. However if the entered project data includes productivity measures and manpower use, the software can monitor work progress and predict delays or added costs due to lack of production or other causes. It can also help in forecasting the number of skilled workers needed in a project before hiring construction workers. Events like weather delays and subcontractors who fail to show up on the project can be tied to direct cost increases.
- Predicting safety hazards
Upon tracking and analysing safety data, the software is able to find out dangerous work activities that have caused issues before and warn workers to take extra precautions. It may slo directly prevent potential issues like safety and job shutdown by tracking equipment maintenance requirements, and warning users about lagging maintenance, minimising project risk, breakdowns, or malfunctions.
All contractors can use data analytics to improve their construction firm’s performance, provide safer job sites, and make better decisions when finding new construction projects on construction bidding websites.
The construction business thus faces a major productivity challenge. The construction sector scores abysmal figures in terms of labour productivity increase. Engineering and construction firms drive changes that can help close this gap.
Most firms are turning to data-driven solutions that have revolutionised other sectors of the economy. Emerging as important tools for improving capital project outcomes and reducing risk, these techniques can be leveraged by E&C companies to collect, analyse and uncover important insights that improve the quality and speed of management decisions. They can help project teams assess market conditions, individual project performance and portfolio composition.
Using analytics tools may be challenging for project-driven businesses in the construction sector. Unlike manufacturers, which tend to go by predictable and repeatable processes, E&C firms face a high variability. Systems to track progress sometimes change mid-project, causing incompatibilities and inconsistencies in the collected data. Parameters like scale, materials, and subcontractors involved also vary significantly from project to project, making it difficult to establish benchmarks.
Within E&C firms, the cultures and processes can pose additional barriers. The industry trusts individual experience and expertise over empirics and few companies have data analysts on staff who can take ownership of advanced analytics initiatives.
Delivering projects on time and improved profit margins are a given when using construction data analytics. Depending on numbers and figures can help you set specific goals and objectives. Analytics can help you analyse your performance so you know which areas need improvement and where you are doing okay.
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