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Data analytics in the construction industry

What is data analytics and how to use it in the construction industry

Data analytics can be a valuable tool in the construction industry, helping companies to make informed decisions by analyzing relevant project data. Find out more in this insight

Construction is a huge industry, and massive changes are happening. One of the most impactful is big data in construction.

There are numerous challenges that you might face today in the development of a project, whether large or small: poor planning, over budget and design mistakes are just some of the potential risks that can lead to not succeeding. However, professionals in the construction industry can leverage on a powerful tool to avoid all kinds of problems and improve design outcomes.

This tool is data analytics. Below you can find out all about its potential!

Before starting off, just remember that you can get the most out of your design processes only if you use a BIM Business Intelligence system for projects. You can immediately get hold of this solution for free and take full advantage of data analytics related to every aspect of your project. In this insight we’ll provide you with all the information you need to thoroughly understand your business and identify opportunities for improvement.

What is Data Analytics in Construction

Data analytics in the construction industry is the process of collecting, processing and monitoring data useful to design. It is extremely important for construction professionals in mitigating risks and achieving successful project objectives.

The data involved in the development of a construction project generally consist of: BIM Business Intelligence

  • BIM data: are data that architecture, design and construction teams generate while collaborating on the implementation of the project within a shared digital environment. More generally, we can understand by BIM data all the information related to the construction life cycle;
  • design data: integrate and extend BIM data and can include decisions, changes, drawings, contracts, budgets, timelines and much more;
  • management data: concern the management of assets and include planning documents, updates, maintenance, etc.;
  • financial data: are necessary to define the construction cost and to monitor expenses during a project’s life cycle;
  • supporting data: help getting a deeper understanding of a project and solve any related issues. They can result from RFI (Request For Information) investigations BIM issue tracking procedures, etc.
Understanding Construction Data Analytics

Construction data analytics and monitoring

Why use data analytics in construction

Data analytics uses artificial intelligence algorithms and business intelligence (BI) technologies to extract knowledge from the information above described. Its main objective is to leverage construction data to predict the future behaviour of a project in every aspect.

It goes without saying that, implementing an effective data analysis strategy enables you to identify relationships, links and trends in existing data. Consequently, it allows you to develop predictive models that help solving problems in advance and optimizing decision-making processes.

Data analytics can also be used in the construction industry to address a wide range of challenges. As the complexity of projects increases, design and construction teams will most likely face a growing number of issues (including costs, errors, changes, materials, equipment, subcontractors, contracts, etc.).

Obviously, generating a large amount of data, which must be filtered and analyzed in order to be effective to the project decision makers. Whether developing this procedure manually (with spreadsheets or paper reports) requires a considerable investment of time and resources, with no guarantee of results, on the contrary, information management with BIM Data Management, software, enables you to obtain surprising results, thanks to the benefits of using artificial intelligence.

Data analysis is therefore the most effective tool for successfully overcoming design challenges. In fact, it enables construction companies to improve processes productivity and efficiency. It also helps completing projects with fewer errors and to improve the quality and reliability of the final outcome.

What are the advantages of data analytics in the construction industry

Implementing a data analytics strategy during a project’s design process can be useful especially for the following reasons:

  • anticipating issues: Companies can predict the chances of cost overruns and identify which projects are most likely to be delayed;
  • reducing costs: Project managers can track financial data in real time, monitor operating models and generate automated reports that help understanding where costs can be reduced;
  • speeding up operations: project data can be viewed with easy-to-understand elements that identify specific teams and tasks and help increasing operational efficiency;
  • improving accuracy: Data analysis automates field data collection and removes human error, making each result much more accurate and reliable;
  • increasing safety: Construction companies can use data analytics to identify behavioural patterns and resolve safety issues before they occur.
How Data Can Help in Construction

Advantages of data analytics

8 ways to use Data Analytics in Construction

Data analytics has become popular in fields such as construction as it can help preventing risks and transforming project data into accurate information that can be used for a variety of purposes. Among the most significant applications we can find, for instance:

  • BIM models production: digital models that allow stakeholders to view the entire project. They contain all the information related to design, materials, costs, maintenance, etc. These models are essential to predict design problems and help manufacturers avoid interference during the construction phase. They also provide all the information necessary to ensure the correct functioning of the building during its life cycle;
  • risk management: it is an analysis that identifies adverse events already during the planning phase. It is based on a probabilistic approach that can be used to establish and manage different categories of risk (including safety, environment, time, costs, quality results, etc.). Data-driven decision making empowers companies with information that helps to choose the least “risky” alternatives;
  • predictive analytics: provides stakeholders with meaningful information to act on existing and future projects. It provides for the analysis of historical data and the collection of huge amounts of data in real time to evaluate different scenarios. It is used to improve cost estimates and cost reduction, it aligns processes and avoids failures on future projects;
  • resource monitoring: resources tracking solutions are essential especially during the building’s construction phase. In addition to ensuring greater efficiency, they help prevent theft and loss of equipment, and minimize delays that can have significant consequences on contractual obligations;
  • process optimisation: it is essential for all project management teams to maintain profit margins during all project phases. Crucial aspects to optimize include time, cost, labour, resources, etc. Data analytics is the only tool that can support processes enabling you to improve business results at every stage of the construction;
  • optimizing contractor performance: measuring contractor performance during project execution helps optimize efforts and identify opportunities for improvement. Data analytics supports this process by providing up-to-date and reliable information on the level of performance of each team involved in the project implementation;
  • budget forecasting and budget control: the cost optimization process covers the entire life cycle of the project, from planning, to execution until closing. This process is managed through tools that are able to track production data in real time. The main objective here is to check that the estimated costs correspond to the actual ones, so as to allow stakeholders to take any mitigation actions;
  • analytics of warranty data: it is an effective method to keep track of the operation and reliability of the building during the operation phase. It is based on the study of data relating to equipment failures and the influence of numerous external factors. This type of analysis helps to avoid complications related to well-being, customer satisfaction and construction safety.

The implementation of these processes is based on the use of advanced business intelligence systems. They are tools that collect and process large amounts of data in order to prepare them for different types of analysis. The results are provided to users in the form of reports, dashboards, charts, and easy-to-understand diagrams.

To discover all the advantages that these systems can offer, you can immediately test an effective BIM Business Intelligence solution.

With the help of this powerful tool, you can leverage your design data to make more informed decisions and achieve successful results. You can also access a cloud-based collaboration platform that will allow you to analyze and monitor every aspect related to project design, construction and maintenance.