Data Analytics in Construction
Industry Changes Allow Jobsite Data to be Put to Work
The construction industry has been slow to adopt new technology. Regulatory uncertainty, data security concerns on temporary worksites, budget limitations and difficulty in estimating the return on investment are a few reasons the industry has lagged behind. Thin margins and issues such as labor shortages make getting work done more difficult. This is leading companies to begin to look more closely at technology for solutions.
While data analytics has recently gained popularity, analyzing data is not new. Many of the techniques that are currently being discussed have been around for a long time. Why have companies recently become more interested in analyzing data? Technological advances have allowed companies to overcome some of the struggles that have made doing detailed analysis difficult and time-consuming in the past.
Moving data from paper notebooks and rolls of documents to a digital format has enabled companies to take a closer look at the data they’re collecting. Technological advances such as mobile devices and cloud computing have made gathering and sharing information faster than ever before. The availability of timely information in a digital format makes it possible to move beyond reporting results and allows companies to proactively use data to make predictions.
Software integration and access to data
Software integration and access to raw data also make it easier for companies to analyze their data. Data has traditionally been stuck in silos. Even if you have been using technology for things like project management and accounting, it has traditionally been a very manual process to consolidate data across departments. Software available today allows companies to integrate and share data across software platforms within their companies and with subcontractors and other external stakeholders. Even if applications do not talk directly to each other it is often possible to access the data and compile information from several sources using analytics software.
Artificial intelligence and machine learning
Advances in artificial intelligence and machine learning have allowed companies to ensure the vast amounts of data they are collecting provide meaningful results when analyzed. These technologies provide data analysts assurance that the data they are using is free of errors. Verifying data manually is nearly impossible with vast amounts of data. Artificial intelligence and machine learning provide cut downtime and provide cost-effective solutions to provide assurance that the data is ready to be analyzed.
As technology continues to evolve and new technologies become available, construction companies will begin to use data analytics regularly to bid, manage jobs, and evaluate performance. Analytics will assist companies in identifying their core competencies so their limited resources can be allocated to the best work available.