The advent and subsequent harnessing of big data has had myriad impacts on the construction industry. By nature, the business involves huge troves of data at every step, from pre-construction planning to contracts and materials ordering to site plans themselves. Before advanced data analytics capabilities hit the scene, much if not all of that data was unstructured and paper-based, requiring multiple tiers of back-and-forth communication to execute changes or ensure everything went according to plan.
But it’s a new day for the industry, and the power of data is giving companies all-new insights into every aspect of every project. Decision making has become easier than ever, with hard numbers to look at, requiring less guesswork. Scheduling issues, project delays and poor information sharing can now all be sussed out ahead of time with analytics, and construction sites themselves are operating more efficiently using data collected from sensor-equipped machinery, equipment and even workers.
Data-driven predictive modeling systems give owners a fuller picture of proposed structures from highly interactive models that enable changes to be made extemporaneously. This makes the design process faster, allowing designers to propose major changes to a plan to see how it would look and function within the building, as well as what impact it would have on their cost and timeline. This insight is invaluable in a business where time is money and every delay eats into the developer’s bottom line.
Building Information Modeling (BIM) is another data-driven modeling process that has changed the way construction gets done. Highly flexible and collaborative, BIM enables sharing of digital site plans across every stakeholder, creating a collaborative environment where all changes made and input provided by various subcontractors can be seen in real-time. It can root out discrepancies in the pre-construction phase, analyze potential issues from adding or removing structural elements, and reduce waste by identifying pre-fabrication opportunities and ensuring the right materials are delivered according to the plan’s exact specifications. All contributions made to the model can be later referenced and recalled to quickly identify the source of a problem.
Collaborative data-driven modeling also allows early identification of design conflicts or other errors that typically would only be discovered during the building process, necessitating everything to grind to a halt while the work can be redone. This reduces labor costs and ensures ever-tightening deadlines can be met.
External forces not necessarily directly related to construction but which can impact a job’s timetable are also an emerging key data source. Factors like weather, local economic or political activity on the ground can affect everything from labor to materials costs to job site accessibility, and must all be accounted for. Manually doing this process would be time- and cost-prohibitive, so digital solutions are being leaned on to crunch that data and pass results along to the teams.
Taking data sets out of their silos and making all information and insights they provide readily accessible across all stakeholders allows a new level of collaboration and efficiency. Keeping every architect, laborer, subcontractor and manager on the same page is critical for staying on schedule and reducing waste. The big data revolution is hitting the construction industry hard, and changing processes big and small every day.