In Big Data, Less Is More: What You Should Use Data For

January 20, 2021
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Big data is a buzzword that’s been circulating in Silicon Valley circles for a few years. It’s started to make its way into other industries and, once adopted, is quickly becoming an invaluable tool. Companies across the spectrum generate massive amounts of information every day, but they don’t necessarily need programs that will sort and organize every single thing. When it comes to this sort of data collection, less is definitely more. 

What should you be using it for in the construction industry?

Breaking Down Big Data Into Smaller Bites

According to data experts, in 2020, internet users generated 2.5 quintillion bytes of data every day. By 2025, that number will climb to more than 463 exabytes. The average construction project contributes to this massive number. Large projects can require upwards of 130 million emails, as well as documents and workflows that all need to be stored somewhere. 

More than 95% of that data doesn’t ever get used again. It’s stashed in a hard drive or a cloud storage system and forgotten, left to collect digital dust when it could instead have a dramatic impact on the construction industry. The trick with this information isn’t to try and make sense of all of it at once. It’s to break it down into smaller bites that are easier to swallow. 

Let’s take a closer look at the different types of uses for these small bites of big data in the construction industry. You’ll find there are many benefits to adopting it into all aspects of your business.

Data in the Design Phase

We start, as with any project, in the design phase. This stage generates a massive amount of data. You’ll collect historical and environmental information about the location, and you’ll launch social media campaigns and email chains a mile long. You’ll collect stakeholder and client input and gather all those stats in one place. Trying to look at it all at once is liable to be overwhelming. 

Instead of drowning in data, invest in a construction software program like one designed for building information modeling (BIM). This isn’t your traditional CAD program. This machine-learning system collects data from all the sources listed above — and more — and builds a digital model of the entire process, from breaking ground to the eventual ribbon cutting. 

The more data the program has, the more accurate its predictions become. Some studies show that a comprehensive BIM can cut expenses by up to 18% and even reduce the amount of time it takes to complete a project.

Data in the Construction Phase

Once we have a design in hand, the next step is to break ground and start construction, creating something from the ground up to the designer’s specifications. This phase also generates a massive amount of data, but it’s more than just emails and digital blueprints this time. This is where the Industrial Internet of Things (IIoT) comes into play. Networked devices and sensors can collect data on the ground on everything from vehicle fuel economy to how long it takes to complete a task. 

Sensors equipped with GPS tags can even submit geolocations to the database to help the system determine the best way to proceed. They can optimize efficiency and improve logistics while avoiding costly downtime that could put deadlines in jeopardy. Wearable technology for crew members is also growing in popularity because their information can contribute to the growing database. 

You don’t need to use every single bit of data this system collects. Instead, program it to make decisions based on the most important factors. This could mean targeting waste reduction or improving efficiency, but the exact details will vary depending on the precise needs of your job site.

Data in the Operational Phase

Finally, it’s time to move on to the operational phase. Grand openings are over, and the building is now open and functioning. Sensors are still a valuable tool here for collecting all sorts of data, depending on the project’s purpose. Roads and sidewalks can use sensors to collect information on traffic — both vehicular and pedestrian. They can also monitor the structure’s health to determine when it needs repairs and how much traffic it can withstand before upgrades are necessary. 

The exact sort of data will vary depending on the type of structure. In some cases — such as with homes or other private spaces — you may need to acquire permission to allow for collection. Doing so will be well worth the effort, though.

Under most circumstances, you’re not going to be using this data to correct problems with existing buildings. Instead, it becomes a pool of information to draw from so you can make changes to designs and procedures to prevent future problems. The more data you have, the more accurate and useful your predictions and alterations become. Machine learning and big data have the potential to become the closest thing we have to clairvoyance, at least when it comes to predicting what the future of construction projects might look like. 

The Future of Data in Construction

As its name suggests, big data can become overwhelming, especially for those who aren’t experts in the field. Consider dipping your toes in before diving in with both feet. It can be an invaluable tool, but if you go in with the mindset of needing to process and utilize every single byte, you’ll quickly become overwhelmed. Take your time getting used to the many benefits of this methodology.

Big data may have started as a Silicon Valley buzzword, but it has not stayed that way. Nearly every industry in the world can benefit from a way to organize and make use of the massive amounts of information they generate on a daily basis. Don’t try to tackle it all at once. You’ll likely find there are untold benefits waiting for you to uncover once you start excavating all the data you’ve collected over the years.

This article was written by a guest author. Rose Morrison is the managing editor for Renovated.

Rose Morrison

Rose Morrison is a freelance writer who covers construction management topics. She is also the managing editor of Renovated.

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