This Is How The Construction Business Is Using Data Analytics

“Bricks to me are like faces.” –Laurie Baker

The quest to reach the top is never-ending. What once started with ‘kaccha houses’ have now turned to bungalows and skyscrapers.

Banks, IT industry, HR, healthcare, financial services, sports; almost every signal industry has witnessed the breach of Data Science in one way or another and construction businesses are now the next in the list.

Yes, big data analytics is being used for construction as well.

Analytics is used to derive useful insights from chunks of data and tactfully optimize the future operations.

Let us see the primary use cases of Data Analytics in Construction.

Construction is a long process with multiple segments. With a myriad of tasks to carry out, dividing tasks effectively becomes essential- Analytics to our rescue.

Work Breakdown Structure (WBS) is one such method.

WBS helps to delegate work- first all the tasks are noted and then quantified depending upon the skills required. Once tasks are categorized, the next step is to identify the right set of manpower and assets required.

Business Analytics thus helps to understand the relevance and accuracy of the skills deployed for the work which was a time-consuming process before.

To err is human, Business intelligence helps with loop detection.

The primary requirement is that all the documents need to be digital to extract relevant information. A master sheet is created by using descriptive analysis which is a summary of all the previous failures, and the reason behind.

Big data technology helps to understand the possibility of the repetition of similar failures in ongoing and future projects.

Labourers are the backstage stars of the construction industry.

 Lack of labourers can disrupt entire construction, bring things to halt and can cost an arm and leg. Predictive and prescriptive analytics are helping to reduce on-site disasters. Using analytics, we can now point out the zones of disaster to an outright accuracy.

It gives insights on where to position heavy-duty equipment to reduce the probability of disasters.

Faulty machinery and outdated tools can also be tracked to avert any operating disasters in the future.

According to a survey, predictive analysis can reduce downtime by 36%.

Other than fault detection, Big data gives the companies the flexibility to operate and optimize the performance of their equipment.

With manual analysis, often some data goes unanalyzed. Analytics ensures every bit of data is analyzed and turned to valuable insights. Analytics makes the reporting highly detailed, accurate, and growth-oriented allowing the company to understand and estimate the quality and readiness of the project.

So to conclude, with the colossal volume of data comes data management. With sophisticated methods for real-time analysis; loss of life and revenue is all set to reduce in the future. This promises a better and safer construction industry in the future.

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