10 Ways Commercial Construction Companies Can Use Big Data

Originally published by the Capterra’s Construction Management Blog

With big data now a hot item in many other industries, why should the commercial construction sector be left out?

Big data offers contractors many different possibilities. Some are general business improvements available to any company, while others are specifically linked to construction activities.

Unfortunately, the benefits of big data in commercial construction don’t just trickle down from early adopters. You can only get them by setting clear business goals, and having at least a basic understanding of what big data and big data analytics are in the first place.

What is Big Data in Commercial Construction?

Don’t underestimate the “big” in “big data.” The entire concept is all about volume–a volume of data so large that people cannot handle or interpret it on their own.

With that said, these huge swaths of data can be analyzed by computer programs to uncover relationships, patterns, and trends.

In the construction of an office block, for example, sensors might be fitted to the structure to capture readings on stress, temperature, humidity, and other factors. Readings could be made daily or hourly, and the data sent to a remote computer or a system running in the cloud. Data like this soon adds up to significant volumes, and becomes ‘big data.’ It can be examined to see if the building is performing over time as planned and if refurbishment should be done sooner or later.

Big data can exist in commercial construction in a number of other forms too. It could be in the quantities of CAD files and project scheduling data, amassed over the years, or in a customer relationship management (CRM) and bid management software applications holding historical data on sales leads and project bids.

How Much Big Data Can Contractors Start Using Today?

Before rolling out an ambitious list of possibilities, it’s a good idea to take further stock of the resources available.

The construction sector differs from many other sectors in its potential to use big data. While manufacturing, finance, government, and retail already have considerable amounts of their own big data, construction has relatively little. A report by McKinsey Global Institute indicates that only a few years ago (2009), total stored data for the construction industry was 51 petabytes, compared to 966 petabytes for manufacturing or 846 petabytes for government. A petabyte is one million gigabytes, but it’s the ratio (51 compared to 966, for instance) that concerns us here.

Why is there such a difference?

  • Fewer commercial transactions. Construction work, even in the commercial construction sector, by its nature has fewer direct digital transactions than other sectors like retail. While shops may log hundreds of credit card or other electronic transactions each day, construction project actions and deliveries are often far less frequent, even if each transaction is worth more money.
  • Difficulty in gathering other digital data. Recording data and events on construction sites has been a challenge in the past because most work is done remotely from a computer. With that said, mobile computing and on-site sensors connected to the Internet are beginning to change this situation.
  • High percentage of small companies. The commercial construction industry is composed of a few large firms and many small ones. There is higher turnover among the small firms and less incentive to spend time and effort (and money) on digitizing or improving the way they handle data.

Five General Business Uses of Big Data to Help Construction Companies

With big data, contractors should first know how to walk, before they start to run. Before diving into uses of big data that are specific to commercial construction, it makes sense to look at possibilities that are relevant to any business, big or small.

  1. Data availability. By collecting big data from software applications, instead of using manual methods to record such data, the data becomes easily and rapidly available afterwards. Using construction management software and construction estimating software, instead of pen and paper, are examples. CAD files and software for electronic construction project workflow management are others.
  2. Company performance evaluation. The more data you can access, the more accurately you can gauge your performance. This includes not only project profitability, but also return on construction assets, staff productivity/absences, and more.
  3. Better targeted marketing. Big data allows you to refine your marketing, more finely segment your client base, and better adapt your project bids.
  4. Improved decision-making. For example, with the corresponding big data available, you could see how construction machinery is being used, giving you insights into better choices between buying or renting such machines.
  5. Problem prevention. Data sent back to your enterprise by sensors in your assets on construction sites can warn you of failures before they happen. This lets you intervene or replace machines before unscheduled downtime starts to play havoc with your construction schedule.

Big Data Application Software that Won’t Break the Bank

Big data is only of any use if you have big data software to work with it. Applications range from the simple (the search function that comes as part of Microsoft Windows, for instance) to the sophisticated. However, neither type has to be expensive. In fact, free versions exist at both ends of the spectrum of complexity.

But don’t forget, time and effort required to use such software may represent an important cost as well.

Some IT vendors have been making remarkable progress in creating big data applications that are easy to use, an important point for smaller commercial construction companies with fewer IT specialists.

IBM’s Watson system gained fame worldwide when it won the American quiz show Jeopardy!. Watson offers “natural language” capabilities to make itself attractive to small companies as well as big ones. Free access is available with the possibility to upload your data to Watson over the Internet. You can then use the capabilities of the program to identify patterns and gain business insights into anything from the projects you are likely to win, to how to keep your employees happy at work.

InsightSquared is another great big data software application for commercial builders. It looks at solutions you use in your commercial construction business today, such as your construction management software, accounting software, CRM applications, and project management software to present you with information you can act on.

Five Applications of Big Data Specifically for Commercial Construction

After the more general uses above, let’s look at examples of big data use that are more closely linked to commercial construction in particular:

  1. Tracking construction equipment and assets. No other industry spreads its assets out geographically like the construction industry. Losing a hammer may not be such a big deal, but knowing where an earth mover is and how fast it can be moved from one site to another can be of critical importance to bringing projects in on time.
  2. Reduction of construction project risk. Although commercial construction companies may have smaller numbers of transactions than other comparable enterprises, they often deal with a larger number of stakeholders and subcontractors. Big data can help choose partners and suppliers with better track records from the start.
  3. Simulation before construction. The bigger your data, the more potential you have to accurately predict remote construction site possibilities and limitations, and plan accordingly.
  4. Construct offsite. Big data can also help to precisely prefabricate larger modules of a building, in order to streamline construction on site afterwards.
  5. Construction site organization. Many construction sites must operate in tight spaces or with other physical constraints. Big data generated by combining vehicle data (GPS coordinates, for instance) and traffic information around the site can help optimize routing of supplies and machinery to maximize efficiency and minimize fuel costs.

Big Data Applications Especially for Commercial Construction

Big data applications that are purpose-built for the commercial construction industry don’t grow on trees — or at least, not yet. However, there are initiatives afoot that could lead to wider-spread utilization of big data for buildings and building sites. Larger contractors with in-house IT staff may choose to use commercially available software platforms to start developing their own big data applications.

General Electric, for example, offers a platform, called Predix, for developers to create apps to manage and collect big data for anything from locomotives to wind turbines. Backhoes, cranes, concrete trucks, and building structures could all be connected and integrated, too.

BIM (building information modeling) is also increasing the possibilities for using big data. According to the functionality in the software, a BIM application will let you create 3D models of structures to be visualized on a computer screen, store associated project data (CAD files, cost estimates, projects schedules, financial accounting, and so on), run automated checks to detect any design or structural inconsistencies, or even all of these things. Some BIM applications offer interfaces to let contractors add their own software applications. Some of those apps can be programs to analyze the large amount of data held or referenced by the BIM application, spot trends, predict future events, and offer solutions for optimizing construction projects and maintenance on existing structures.

An Example with GPS, Asset Management, and Earth Movers

While ideas and imagination are powerful resources, a real-life application of big data in commercial construction can also be inspiring. One such example comes from Nick Savko & Sons, Inc., a construction company based in Ohio, and offering earthmoving and road surfacing services. The company equipped its machines, including a scraper and articulated dump truck, with 36 global locator devices, so that the machines could be monitored at a distance. The initial installation of the first two devices was done for them by a dealer, and the company then installed the other 34 devices by themselves.

The devices gathered information on machine cycle time, idle time, productivity, and more. This information was then fed into an asset management software program. Idle time and location analysis allowed managers to know if too many or too few trucks were being used, or if an earthmover would be more gainfully used elsewhere. The same information was also analyzed to generate information on loads carried, cycle times, and cycle distances. Fuel consumption could be compared with benchmark figures to see if operators on site were using the machines efficiently, or if there were possible mechanical problems to be fixed.

The big benefits to the company included increasing productivity enough to finish the project a month ahead of schedule, and fixing potential problems before they became real ones. Because the data gathered also showed the company its real costs, it now uses this information to tune profitability and become even more competitive for following projects.

Conclusion

Commercial construction projects are increasingly suited to digital data gathering and analytics for optimization and improved profitability. Many of the big data applications to do this are still being built. However, the tools to do so are becoming easier to use, and the practical examples that can be followed are becoming more numerous.

At the same time, customers are likely to expect commercial construction companies to move towards big data, just like other industries are doing. One of the first applications may be to extract all the facilities management information digitally from a BIM application to hand it over to a new building owner as easy-to-use digital files, instead of a barrow-load of paper-based manuals and drawings. A “quick win” like this could then set the scene for continuing profitable and productive use of big data afterwards.

Have you used big data for your commercial company yet? Are you considering it? Let us know your thoughts in the comments below!