The insights gained from analyzing big data will have far-reaching impact on construction processes. Those insights will also affect company relationships and how people manage the built environment long after construction ends. Here are just a few ways that analyzing big data is poised to improve construction outcomes:
- Insights on jobsites, material availability factors, statistics on suppliers, and data on regional and local human resources will make budgets more accurate.
- Project decision makers will get new insights from analyzed data, and will also get those insights quicker during construction.
- People will see project risks reduced as big data analysis leads to deeper insights into the project schedule, causes of delays, and effects of poor information sharing.
- Construction sites will get more efficient and have better organization by using data from sensors in machines, and sensors that provide traffic information, locations of materials and equipment, and locations of personnel.
One of the first places construction companies found value in their big data was with schedule analysis. Back in 2012, reports detailed how companies were drilling into construction data to improve scheduling. Specialized software analyzed the schedule to find areas within it that would cause problems down the line. Today, these tools, some built into popular scheduling software, and some as standalone offerings, can find:
- Faulty logic in the schedule
- Areas with insufficient detail
As the tool databases gather more data from multiple projects, users can check the current schedule against benchmarks to assess the schedule’s quality. Once the software highlights the problems, it's possible to find new opportunities to fix and improve the schedule . With 4D BIM models, companies are now plugging in “what if” scenarios to the schedule to see the problems that spring up at each phase of construction.
Toward Project-Wide Big Data Analysis
Perhaps the greatest value for construction from big data comes from applying big data analysis and reporting on a project-wide basis. When all project participants provide information and data for all to use, everyone benefits from improved productivity. The potential advantages are enormous. Participants deliver quality the first time, changes drop, workers stay informed up-to-the-minute, and perhaps for the first time there’s the possibility of profitable outcomes for all participants. And, as the internet of things continues to grow, the data created and stored by sensors throughout a building will add volumes to the data created during construction. This sensor datum will go on to inform building owners and maintainers throughout the life cycle of the structure.
A Foundation of Improved Collaboration
But, for that to come to fruition, construction needs to become more collaborative at the project level. That means project participants need to stop competing once the owner awards the contract. One way that will happen is with wider adoption of collaborative delivery methods including:
- Design bid build
- Target value design
- Building information modeling
- Lean construction
- Integrated project delivery
Once collaboration is in place, big data tools and databases on the entire project can go to work to not only inform the next activity, but to also add value to all the data for the life cycle of the structure. There are also ways that analyzing vast swaths of data will alter traditional relationships.
Construction has always heavily relied on relationships. Because of that, many people in the industry assume quality performance from their project participants, without confirming it by looking at the data in the record. In many cases, relationships override good business decisions. As companies begin collecting and storing data that is easily accessed and analyzed, they will have the means to continually qualify partners as they move from project to project. Project records can reveal when consistency begins to become a problem, or when participants have difficulty keeping up with the schedule. By running the analysis regularly, managers can even find out about pending problems on the current project.
Factors Affecting Big Data Adoption and Use
There are construction industry realities that affect big data adoption, not the least of which is the fact that much of construction’s data inventory isn’t really that big yet, especially when compared to the data other industries are handling. Even BIM data pales in comparison with the data large retailers collect every hour. Besides that, there are other factors affecting the industry’s momentum with big data. Information in a 2011 McKinsey Global Institute analysis report showed construction:
- Would have an average level of difficulty in getting value from its data, when compared to other sectors
- That the industry has systemic barriers making it less likely to see gains from using big data
- Construction doesn’t have near the amount of stored data that other sectors have
- The industry has more unstructured data than text and number data, suggesting greater difficulty in analysis.
- Construction has the advantage of not having a lot of transaction-intensive data.
There are also demographic factors of the construction industry that will affect the benefits it receives from big data. The majority of U.S. construction companies have 10 or fewer employees, and most only have rudimentary data collection, storage and analysis. To date, when you read about big data getting used in construction, it's always about large construction firms like JE DUNN, and MWH Global. Even in those places, journeys into big data are for very specific purposes, and often done in concert with technology companies and universities. But, big data tools are becoming more useable and available thanks to the cloud and mobile devices.
Cloud computing, specifically cloud platforms, and mobile devices, are finally in position to deliver the kinds of technology solutions that construction needs. Whether or not those solutions incorporate big data analytics and reporting will determine how much, and how quickly the construction industry goes after big data and its advantages. Construction companies are probably not going to increase their technology spending until the technology itself gets out of their way and actually helps them build more efficiently, with less risk, and with better results. Construction’s uptake of technology tends to happen at construction’s pace, and not according to the desires of the tech companies marketing the solutions.
In much the same way that construction started using spreadsheets because they delivered more value than they cost, construction will increasingly harness the insights in the growing volumes of data it creates. Early adopters will find answers to questions they never thought about asking. They will become more competitive, but even those late to the table will share in the windfall of productivity offered by super smart processes and systems.