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5 Ways Big Data Improves Construction Company Operations

Complex issue planning is something every construction company should do for a project. However, even the most competent general contractors can encounter inevitable difficulties that hinder project planning.

The big questions are how can construction companies mitigate the impacts of problems that arise spontaneously? And how can general contractors predict when there might be problems?

If you’re a general contractor who wants to reduce problems before they happen, you can take advantage of analytics to ensure your projects run as smoothly as possible. To help you succeed, we’ve outlined five ways big data can make your construction business run better below. But first, let’s talk about what big data is and what it means in the construction industry.

What is big data in construction?

Big data in construction refers to the huge amounts of information stored in cloud-based systems that certain people can access from anywhere at any time, from general contractors and developers to subcontractors and individual tradespeople. . Big data can come from people, computers, other software, etc.

For example, a general contractor extracts data from the project schedule, materials used, and subcontractors on site. If any materials are out of stock, the analysis software will note the back order and suggest changes to the project schedule.

1. More accurate quotes and bids

Even before your crew lifts a single shovel of dirt on a job site, big data can help your construction company generate more accurate quotes, offers, and estimates. Analysis software can easily find information on past projects and take into account current material prices and subcontractor offers from your trading partner pool so you can understand a project’s size and schedule to provide an accurate quote and offer for a project. A complete platform can even fill out the standard forms needed to complete a full bid, saving your planning team time and money when competing for projects.

(Standard forms include application forms, contractual agreements with merchants and business partners, and logistics forms to be sent to transport companies for deliveries.)

Because big data helps you produce more accurate cost estimates, it will reduce your risk of going over budget and spending more time fixing issues in later stages of a construction project.

2. Reduces human error

Waste of materials and correction errors on construction sites account for 35% of construction costs, according to Forbes[1]. Not only will big data reduce your costs (which will make your offers more competitive), but it can also increase your profits by reducing these costly errors.

According to a market study on transparency[2]construction waste worldwide will total 2.2 billion tons by 2025. Digital tools, used early in the planning phase, combined with lean construction and manufacturing, can reduce waste by giving suppliers sufficient notice to have materials and equipment on site if needed. .

Big data can align architectural plans and technical drawings with site surveys and materials needed to mitigate potential problems before they arise. As a result, project managers and site superintendents can make decisions on potential issues earlier in the project schedule to reduce the impact of potential difficulties. It’s always easier to fix something before it happens than to have to redo something, causing even more delays.

3. Improve deadlines and meet deadlines

Meeting deadlines is the key to moving a construction project forward. When used by onsite and offsite teams, project management software can alert teams to potential delays, complications, and schedule changes along the way. Teams can automatically input or upload data that the software can use to assess the current situation.

For example, a truck delivering precast concrete beams could break down on its way to the site. Although the beams are undamaged, it will take crews 36 hours to safely bring another truck to the breakdown site, transfer the beams using a special crane, and then bring the new truck to the site. . A big data-powered project management platform will note this issue and adjust timelines and deadlines while notifying all parties of the change.

4. Mitigate risks to workers

Big data, when used right from the planning phase of construction projects, can help teams identify potential risks and issues on site.

For example, the platform analyzes labor and equipment productivity, then notifies project managers of potential delays, possible fatigue, or too much equipment on site. If teams are rushing to get projects done and there are too many people or too much equipment on site, it can lead to even more delays, slowdowns and worker fatigue when it comes to issues. security and overcrowding in relation to space for equipment, materials, and workers to move around the site efficiently. If injuries occur, the project bogs down even more.

5. Promotes predictability throughout a project

Big data systems in construction use advanced algorithms, artificial intelligence (AI) and machine learning (ML) to deliver crucial information and insights early in the planning phase.

Rigs can identify potential issues with the coordination of resources, manpower, equipment, potential site issues, and even seasonal weather changes that teams can address before issues arise. lead to delays and cost overruns.

Find the right construction software for your business

It’s hard to anticipate every problem that might arise during your construction project, but big data makes it easier to look at trends and predict supply costs, materials needed, and keep things running smoothly. profitable and efficient.

If you’re looking for software to help you do just that, Software Advice offers unbiased reviews of several types of big data platforms for your construction business to help you make your projects more efficient while mitigating problems before they happen. they do arise.


Sources

  1. How Big Data and Analytics are Transforming the Construction Industry, Forbes
  2. Construction Waste Market – Global Industry Analysis, Size, Share, Growth, Trends and Forecasts 2017-2025, Market Research Transparency