How Big Data is Changing Engineering & Construction

Big data has become a big deal in other industries. In architecture, engineering, and construction (AEC), big data is still in its infancy, yet it is already impacting how we design and construct buildings. At a time when everyone is looking for ways to do more with less, big data in construction offers a way to improve existing processes and make informed decisions about future projects. These are just four ways that big data in construction is changing the industry.

Data analysis has been present in health and safety for many years – there are many statistics available that demonstrate the link between the number of near misses received and the number of accidents that occur as a result, for example. But the increasingly advanced analytical techniques that are available can help identify and understand the risk factors that may lead to an incident. It’s also easier than ever to segment data and drill down into the information to identify potential risk groups that aren’t always apparent on the surface. With this level of insight, health and safety procedures can be updated to reflect what the data is highlighting and reduce the chance of an accident occurring.

Cost control has always been an area under intense scrutiny. While analyses of a company’s costs have been available for some time, big data in construction can help refine the information and identify patterns where wastage is occurring in the business. For projects, potential profitability has typically been determined by experienced staff. Big data takes this knowledge and puts it into an accessible format where factual analysis can be undertaken and robust predictions made before contracts are tendered for. Using past performance history, data analytics can also help improve contract control by identifying the conditions that have led to schedule or budget overruns and alert staff that preventative measures may be needed.

Technology such as wearables can gather data easily and efficiently in areas where information has typically been difficult to collect, such as site movements. Using big data in construction, sites can be optimized for efficient working by determining how much time is spent collecting materials and transporting them to the work zone, for instance. Rather than using anecdotal evidence, informed decisions can be made as to the most efficient layout for increased productivity. Similarly, logistics information can be analyzed to determine the best way to move goods and materials between sites and storage areas. Demand forecasting for resources – whether people, plant, materials, or money – can also help improve operations using predictive models.

Asset management is a key area where big data can provide invaluable insights. Being able to model asset behaviors and predict maintenance requirements before major work is needed is as useful to contractors managing their plant fleet as it is to clients who are responsible for buildings or infrastructure. Big data is helping drive the growth behind asset management, helping decision makers by providing factual information that allows them to invest their resources where they’re needed most. Asset management models can also help manage all the big data generated by a built asset.

Building Information Modeling (BIM), which provides a central place for all project information, is one of the first steps towards big data for construction. While a model isn’t big data on its own, there are thousands of documents, drawing, emails and records created for every project. BIM has made architects, engineers, and contractors information managers as well as constructors. Big data provides a way to structure and leverage this information in a way never before possible.

As big data within a construction context evolves, it’s use will develop as well. At the moment, cloud-based BIM platforms like ALLPLAN Bimplus offer a solution for central data management, allowing the project team to access and share information. But as artificial intelligence (AI) and machine learning develop, big data will change from a descriptive role (describing project details) to an analytical and even predictive role. Historic project data will be analyzed for performance management and improvement and forecasts and predictions will be made for future projects. If BIM is the future of construction, then so is big data.