Big Data: Opportunities and Challenges
In the construction industry there are huge amounts of information created on a daily basis. There's also a staggering amount of historical data that is sitting mostly unused and sitting in isolated silos. Big data is the catch all term for connecting, integrating, and extracting value from these oceans of information.
Think of all the plans and records of all the existing buildings in your city or town and then add to that the frenetic increase of additional inputs from sources as diverse as cranes, earth movers, and workers carrying mobile devices to material supply chains, sensors integrated into the building site, and security cameras. How can we extract value from this overwhelming flood of information?
Our traditional accounting systems excel at recording basic information about project schedules, designs, costs, invoices, and employees. But how well can they handle unstructured data? Things like video feeds or sensor readings or chains of text messages/emails. Just processing these kinds of inputs can be challenging let alone trying to use them to inform critical decisions.
To really harness the power of big data we need to be able to use huge, diverse pools of information to drive the decision making process and improve it. The data isn't useful on it's own but it is a sort of raw material that we can use to build bigger, more complex projects with maximum efficiency. This is critically important since this is an industry which is responsible for the biggest and most expensive projects on Earth and it is also an industry that's plagued by material waste, remedial work and time delays. The promise of Big Data is that it can help us to address all three of these issues.
Analytics have always played a big role for construction companies. Have you heard the one that goes, "construction companies are really just accounting companies that happen to build buildings." Despite the fact that analytics are a core competency of every construction firm the industry itself is starting to lag behind other industries. Retail and financing are well ahead of the curve in this area. Manufacturing and chemical processing--even oil refineries--are making big moves towards the kinds of advanced analytics made possible by big data.
Determined to not to fall too far behind the technology curve many construction companies have begun the move towards cloud based storage and incorporation of external data. One advantage that the construction industry has is that it already has huge pools of stored information to draw from the only problem is that most of that information is isolated. To really be in the big data game you need to be able to pull together information from every business department and division. While the cloud makes this possible it's still an arduous task. After you have your internal data in order the next step is to start incorporating external data sets into your models. Tracking historical meteorological reports and live weather conditions is a good start but advanced users are already including economic and political activity.
Even smaller companies can use some of these techniques and start to leverage their somewhat smaller data-sets. If industry trends hold their current course future proofing your data policy could yield huge savings in the coming years. It could also give you that critical edge the next time opportunity comes knocking.