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Using Data Analytics in the Construction Industry

The construction industry is still perceived by many to be one of the least digitized industries in the global economy. This mindset is currently changing. But, we still observe manual, repetitive data collection that is difficult to analyze and inconsistent. 

One of the most common ways of data entry today is manual monitoring by hand, followed by storing the records in filing cabinets in the depots, where it will not create any value. Information like precheck inspections, machine utilization, machine efficiency, or data about the construction project or site is recorded like this. 

The problem with gathering data in this manner is that it is difficult to analyze. Not only will the data not be used, but it doesn’t create any value. For data to become useful you need to use it. That is what makes it valuable. 

To make this process easier, it makes sense to collect data digitally. Construction analytics will enable you to make data-driven decisions that could help your business now and in the future.

 

What is data analytics?

Using construction analytics to make business decisions

Data analytics is a broad term that refers to analyzing data to answer questions, find patterns, and even predict potential outcomes. A successful data analytics initiative will combine several different components. 

Descriptive Analytics

This component seeks to answer what has happened. In a given situation, you would summarize large datasets of information to describe an outcome. Common measurements used in the business world to check performance (KPIs) or return on investment are considered descriptive analytics.

Diagnostic Analytics 

Diagnostic analytics is a step up from descriptive analytics. Instead of answering the question of what has happened, we explain why something happens. This type of analytics is a supplement to descriptive and can help businesses better understand why there may be outliers in the data. 

Predictive Analytics

When we talk about predictive, you should think about what will happen in the future. This component of analytics seeks to identify trends in the data and answer if they will happen again. This type of analytics requires more complex statistical and machine learning techniques. 

Prescriptive Analytics 

Prescriptive analytics can give insight into what action to take in a situation. Leveraging the data from predictive analytics, you can find patterns in large datasets that include past decisions and events that follow. Just like predictive analytics, this also requires techniques like machine learning. 

To leverage these different types of data, you need to, first of all, be able to collect the data.

 

The benefits of construction analytics

Construction site that can be optimized with the use of construction analytics

With access to data, you can start benefiting from data analytics in the construction industry. 

1. Make informed estimates on budget and timeline

As a contractor, you should utilize the data that you have available about project completion, machine utilization, construction site efficiency, etc. With that data, you can improve how you estimate project outcomes. As you’ll need data about past project completion and an understanding of what occurred during that project, it will require large datasets to start. But, with this information in hand, you’ll be able to give much better budget and timeline estimates. 

2. Right-size your equipment and fleet inventory

Analytics in construction is beneficial for many things. Outside of using it to understand your construction projects. Data can also help establish a better understanding of your tools, attachments, and machines. With access to machine data, you can use a construction data analytics solution to help you create valuable solutions. You might see that you are overutilizing tools or that you are underutilizing others. Data analytics will show you which equipment to either rent out or sell so you can improve your bottom line. 

3. Start building the capabilities for predictive and prescriptive analytics

Gathering project data to help you build descriptive and diagnostic analytics is the first step in building your analytics capabilities. By analyzing the data you’ve gathered, you can begin to use data to build predictive and prescriptive analytics models that will give you even more value.

 

How, you, in the construction industry can start collecting data

To move from manual data collection in the form of pen and paper checklists to digital automated data collection can be a challenging step for many to take. But it doesn’t have to be. 

Trackunit offers multiple different types of hardware for any machine type. Whether it be small handheld attachments for your equipment or large dumpers, you can use Trackunit’s hardware to gather data about your machine. The data you collect does not purely have to be about your equipment. You can use information about the utilization of your assets to check the efficiency of your operators on a construction site. Or you could use that same data to understand the environment your equipment is used in, so you can more accurately assess the potential risk of operating in the area. 

It does not matter what you want to do with the data. Trackunit can help you not only gather the data but will also present it in a manner that is easy to understand and provides you with value. Whether you want to integrate the data into your ERP system, or you want to use APIs to stream the data, Trackunit has a solution for you. 

Start collecting construction data with Trackunit today.

 

What does the future of construction data analytics entail?

The construction sector is changing rapidly. In recent years we have experienced the increased adoption of digital solutions, including the adoption of construction analytics. So far, we have seen customers save time and money and eliminate downtime due to this. Yet, there is much more value to be extracted from all the data that you collect. 

The opportunity to open up predictive analytics is an enticing possibility for the future. It will require much more data and processing, but it could result in more efficient construction industry. For this to truly work, the industry must also be open to sharing data. From manufacturer to end-user, sharing can unlock siloed information. 

If you are interested in learning more about data sharing in the industry. You can read the Blueprint for Data Sharing in Construction here.

 

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